WO2006015890A1

WO2006015890A1 - Mri method suitable for determining the condition of rheumatoid arthritis

Info

Publication number: WO2006015890A1
Application number: PCT/EP2005/051912
Authority: WO
Inventors: Eugenio Biglieri; Luigi Satragno
Original assignee: Esaote, S.P.A.
Priority date: 2004-08-12
Filing date: 2005-04-27
Publication date: 2006-02-16
Also published as: US7042219B2; EP1776598A1; US20060033493A1; US7660619B2; US20060183998A1

Abstract

A method for determining the condition of an object by MRI, comprising the following steps: a) acquiring at least one image by means of NRI along a slice or one section plane of an object under examination at different successive times within a predetermined time period; b) the said object being a sample object having known conditions; c) determining for the mean intensity of the MRI signal; d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image and the corresponding time of acquisition; e) graphically representing the function describing the said empiric time dependency method for determining the condition of an object by MRI, comprising the following steps: (a) acquiring at least one image by means of NRI along at least one slice or one section plane of an object under examination at different successive times within a predetermined time period; (b) the said object being a sample object having known conditions; (c) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample object under examination the mean intensity of the MRI signal; (d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; (e) graphically representing the function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair; (f) providing at least a second object to be examined having an unknown condition and carrying out the steps a) to e) using the said second object; (g) visually comparing the graphic representations of the functions approximating the empiric time dependency function relating to the sample object and to the second object in order to detect differences of the condition of the second object from the known conditions of the sample object.

Description

MRI METHOD SUITABLE FOR DETERMINING THE CONDITION OF RHEUMATOID ARTHRITIS

5 A method for determining the condition of an object by magnetic resonance imaging, MRI, particularly for determining the pathologic condition of arthritis rheumatoides and carrying out a patient follow up.

10 The invention relates to a method for determining the condition of an object by MRI.

The present invention particularly relates to a method for determining the conditions of an object which conditions can be evaluated by providing

15 information on time dependent effects either induced or spontaneous. For example in a solid body not of biologic kind, the perfusion of a gas or liquid which is fed under certain condition can be observed by MRI such as acquiring a sequence of images in which each

20 image is acquired at a different time within a certain time period. Structural modifications in relation of changing of physical or chemical parameters can be observed, such as for example temperature dependent structural changes in solid bodies which are subjected

25 to a time varying temperature by heating or cooling or structural changes induced by mechanical stress exercised on a body, or structural or chemical changes induced by the exposure to radiation which intensity or dosis changes with time, structural or chemical changes

30 occurring by means of applying chemical substances to the body interacting with the substance or material of which the body is made. Such time dependent effects may be observed by carrying out an MRI session of the body in which at predetermined time intervals an image is acquired, thus empirically determining the time dependent changes in parameters of the image for example the time dependent changes of the mean intensity of the image or of a partial area thereof.

In may cases, particularly in cases in which MRI is applied for diagnostic purposes, the pathologic condition of in vitro or living tissues is a time dependent one or can be best appreciated by means of induced mechanisms in the tissue which are time dependent. This means that in order to individuate the condition of the object it is necessary to carry out a sequence of images each acquired at certain different times within a certain time interval.

Particularly relevant is the case for individuating and evaluating pathologic conditions such as infections and/or tumors, or the like. It is known that vascularisation is enhanced in regions in which tumoral cells are present or in which there is an infection. Thus in this case in order to individuate such conditions it is known to evaluate the increase of vascularisation by means of contrast media perfusion measurements.

Perfusion measurements with MRI are usually carried out by acquiring a sequence of images of a selected anatomical region or tissue region after a contrast media has been injected into the region. Contrast media are transported by the blood and the speed of transport of diffusion of the contrast media in the tissue or anatomical region of interest is used for evaluating vascularisation. The mean intensity of the imaged region of interest is than determined form the image data of each image of the sequence and a so called perfusion curve is constructed by means of the data pairs, mean intensity of the region of interest of each one of the images of the sequence of images and time of acquisition of the images .

Comparing the perfusion curve with other perfusion curves which are univocally related to known clinic cases or tissue conditions it is then possible to determine some indications on the clinic condition of the imaged tissue or anatomical district.

This evaluation has been carried out until now in a non systematic way.

Thus there is the need for providing for a method of determining a condition of an object, particularly the pathologic condition of living or in vitro tissues which is much more reliable and which is integrated in a well defined manner and which automatically determines the indications about the probable pathologic condition of an object under examination which pathologic condition is unknown.

The invention therefore has the aim of providing a method for determining the condition of an object by MRI. The invention aims to the fact of providing a method enabling to have univoque criteria so that measurements carried out by different subjects and different apparati can be reliable and comparable, thus permitting a wide spread exchange of data between different subjects which carry out the examination and evaluate the results.

The invention aims also in reducing the uncertainties related to the skill in carrying out the examinations and visually comparing and interpreting the results.

The above mentioned aim is reached by the invention with a method for determining the condition of an object by MRI, comprising the following steps: a) acquiring at least one image by means of MRI along at least one slice or one section plane of an object under examination at different successive times within a predetermined time period; b) the said object being a sample object having known conditions c) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample object under examination the mean intensity of the MRI signal; d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; e) analytically determining the parameter of a function approximating the said empiric time dependency function. f) providing at least a second object to be examined having an unknown condition and carrying out the steps a) to e) using the said second object; g) comparing the parameters of the function approximating the empiric time dependency function relating to the sample object and to the second object in order to detect differences of the condition of the second object from the known conditions of the sample object. Objects under examination either of biologic or non biologic kind and/or unanimated or animated are often of the kind able to show at least two or more conditions or a continuously varying range of conditions. In this case the above mentioned steps are carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions; The unknown condition of a one or more further objects being determined by carrying out the steps described in the precedent paragraph for these one or more further objects and comparing the parameters of the function approximating the empiric time dependency function relating to the one or more further objects with the parameters of the function approximating the empiric time dependency function relating to the sample objects.

Different mathematic or statistic tools may be applied for carrying out the comparison of the parameters of the function approximating the empiric time dependency function relating to the one or more further objects with the parameters of the function approximating the empiric time dependency function, i.e. in order to determine the condition of the examined objects which condition is unknown.

Having a range of discrete range of conditions relating to the sample objects, the condition of the object under examination may be determined by interpolation.

A different approach may consist in generating a database comprising the sample objects time dependent functions relating to their condition and the corresponding known condition and using a predictive algorithm such as a neural network for determining the condition of the object under examination on the basis of the time dependent mean intensity function obtained by acquiring the sequence of MRI images.

When the objects does not show time varying effects which leads to time varying image parameter, particularly to time varying intensities of the images of the sequence of MRI images, the said time varying parameters can be induced or forced by applying to the sample objects and to the further objects of which the condition has to be determined a medium able to diffuse within the said objects and carrying out the acquisition steps of one or more images of the said objects along one or more selected slices or section planes within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the object. In order to select the slice or slices along which the sequence of images has to be acquired a first panoramic image a so called scout image is acquired along a first scout slice or section plane by means of which one or a series of selected section planes across the objects are determined along each of which an image has to be acquired.

Furthermore when only a limited and known region of the images along the selected slice or slices has to be examined or is relevant for determining the condition, a first image along a first section plane is acquired and the said limited region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, image acquired at later times along the same slice or section plane.

Determining the said region of interest is particularly relevant in the case the object to be examined is an anatomical district of a patient, human or animal.

The present invention can be further improved by further considering that instead of acquiring images along one or more section planes or slices a three dimensional image of the sample objects and of the objects having unknown conditions or of part thereof is acquired thus collecting a sequence of three dimensional images acquired each one at a different time and within a certain time period.

Acquiring a sequence of three dimensional images which volumetric image data can be stored allows to define and select section planes and region of interests at a later time, without running the risk of having to repeat the acquisition process due to a not precise or incorrect selection of the slices and/or of the regions of interest.

After having acquired the sequence of three dimensional MRI images or alternatively in the acquisition process in a first three dimensional image one or more three dimensional partial regions are selected being said regions so called three dimensional regions of interest and the position in space and boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated from the image data and used for constructing an empiric time dependency function of the mean intensity of the said region of interest by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

It is also possible not to limit examination to only one region of interest. In this case two or more selected regions of the sequence of two dimensional images along one or more selected slice or section planes of the objects or of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding two or three dimensional image of the sequence of two or three dimensional images and the corresponding time of acquisition.

A further alternative or improvement consist in the fact that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the objects or of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed in which for each two dimensional image along one selected plane or section plane of the sequence of section planes or for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

When limiting imaging to the two dimensional case, the images along one or more selected slices or section planes are acquired by acquiring a three dimensional image of the objects; defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

In order to have comparable data from different objects examined it is important that the region of interest chosen corresponds to the identical region of the real object, In the case of diagnostic images this means that the region of interest for each object correspond to the same anatomic district for each object and sample object examined. In order to ensure this the invention provides markers which markers are applied to the objects in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

Alternatively to external markers positioned in well defined points of the object, also markers can be used which markers are defined as selected zones or regions of the objects which are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images. For each slice image of the sequences of slice images or for each three dimensional image of the sequence of three dimensional images the selected region of interest or the selected regions of interest may be univoquely identified by means of their known geometrical form and the geometrical relation (distance and orientation) relatively to the markers. This operation can be carried out by means of simple mathematical algorithm such as for example so called registration algorithm which are well known in the art (see for example Hemmendorf, M.; Anderson, M.T.; Kronander, T.; Knutsson, H. Phase-based multidimensional volume registration. IEE Trans Med Imaging 2002, 21, 1536-43) . A particular field of use of the above mentioned invention is the field of diagnostic imaging. The above method can be used for determining if on the basis of MRI images of an anatomic region of a patient a pathologic condition is present in that region and if it is present the above mentioned method can provide as a further improvement also an evaluation of the level of the pathologic condition.

Particulalrly in the case of infections and or tumors, the invention consider to carry out the said method by acquiring a sequence of images of the anatomic district which images are taken at certain times during a certain period an that period lasting enough in order to consider a complete perfusion of the said anatomic district by means of contrast media injected in that anatomic region.

A particular kind of infection could be the arthritis rheumatoides. As an important region of interest to which imaging has to be carried out the sinovial can be used. It has been shown that this anatomic region is representative for individuating the level of activity of the disease.

Furthermore the invention can be used for carrying out a follow up thus helping to recognize the way the pathologic condition develops or the way the siad pathologic condition is regressing due for example to medical treatment.

Thus for above purposes the invention relates to a method for carrying out a follow up of the pathologic conditions of biologic tissues in isolated form or in or of an anatomic district of a body comprising the steps of a) acquiring at least one image by means of MRI along at least one slice or one section plane or a volume or a selected three dimensional region within the said volume of the biologic tissues having a known condition at different successive times within a predetermined time period; b) determining the mean intensity of the MRI signal for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample biologic tissues under examination; c) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; d) analytically determining the parameter of a function approximating the said empiric time dependency function. e) providing at least a second biologic tissues to be examined having an unknown condition and carrying out the steps a) to d) using the said second biologic tissues; f) comparing the parameters of the function approximating the empiric time dependency function relating to the sample biologic tissues and to the second biologic tissues having an unknown condition in order to detect differences of the condition of the second object from the known conditions of the sample object.

Considering the use of the present invention for a follow up of the disease the invention has following steps: repetition at several different times of the steps e) and f) for determining changes in the disease activity degree in time and during a therapeutic treatment.

When the above method is applied in combination with the presence of contrast media in the examined object or in the region of interest of the examined object, the follow up of the disease activity of a pathologic condition of the said object and within the said region of interest comprised the steps of a) generating a database of contrast media perfusion curves each one univoquely associated to a well defined degree of disease activity; b) the said database being generated by acquiring at least one image of an identical region of interest of the same anatomic district by means of MRI along at least one slice or one section plane of the said anatomic district in patients or a three dimensional MRI image of the anatomic district in more than one patient each patient having a known degree of disease activity; c) for each patient having a well defined degree of disease activity a sequence of MRI images is acquired which sequence comprises a certain number of MRI images taken at different times one from the other within a certain period of time; d) the said period starting immediately after or at the injection of a contrast medium in the anatomic district and terminating after a certain time determined as a typical duration of contrast media perfusion in the anatomic district; e) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged anatomical district under examination the mean intensity of the image data acquired; f) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; g) analytically determining the parameter of a function approximating the said empiric time dependency function. h) determining the disease activity in the same region of interest of the same anatomic district of a patient having an unknown level of disease activity by carrying out the steps of injecting the said contrast media in the anatomic district of the said patient and by acquiring the sequence of MRI images of the anatomic district for the predetermined period of time and finally constructing the empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition and analytically determining the parameter of a function approximating the said empiric time dependency function; i) comparing the parameters of the function approximating the empiric time dependency function relating to the database in order to detect the disease activity level. j) repeating at several different times the steps h) and i) for determining changes in the disease activity degree in time and/or during a therapeutic treatment.

The above mentioned method allows to estimate the health condition of a patient and the time development of disease with or without therapy.

It has been found that the above mentioned method allows to determine the level of disease activity and the health condition of rheumatoid arthritis in patients by MRI perfusion measurements of the wrist and particularly of the synovial membrane. In deed the synovial membrane is the anatomic site were early inflammation can be detected. The method allows to discriminate an active disease from an active disease and the level of activity.

In this case the anatomic district under examination is the wrist and the region of interest is the synovial membrane.

Since the measurements relate to determining a mean intensity of the image along a selected region which is the entire region of interest or a selected part thereof and since the follow up requires that imaging has to be carried out in different sessions at different times it is important and critical that at each session the same slice or region of interest is selected. This can be very difficult and can provide errors since the correct selection depends form the positioning of the wrist in the MRI scanner. Thus using a three dimensional MRI acquisition method and considering the mean intensity of an entire three dimensional region of interest or of a three dimensional part thereof can be helpful in avoiding errors due to wrong positioning and thus to the selection of a wrong section plane or a wrong region of interest. Further providing markers either of the external kind or consisting in precise anatomic or morphologic particulars of the anatomic district under examination, and combining the said markers with the above mentioned registration methods and algorithms allows to enhance the precision of the method also in combination with the three dimensional MRI acquisition.

Further improvements of the invention are described in the dependent claims.

The invention and the advantages deriving therefrom will appear more clearly form the following description of some non limitative examples and of the annexed drawings and tables, in which: Figure 1 sows a diagram explaining the basic steps of the method according to the present invention relatively to the sequence of MRI acquisitions carried out for a contrast media perfusion measurement and relatively to the three dimensional MRI case. Figure 2 shows an example of a typical perfusion curve obtained by reporting the mean intensity of the region of interest of images taken at different times with respect to the time of acquisition. Figure 3 is a table in the form of a flux diagram explaining the method steps of the invention according to a first embodiment.

Figure 4 is a variant of the embodiment according to figure b3 where a predictive algorithm is used for evaluating the condition of the examined object.

Figure 5 illustrate a table explaining the basic steps of a disease follow up according to the present invention. Figure 6 A to D illustrate an example of the use of markers in order to identify the same section plane along which the MRI image has to be acquired independently of the position of the object under examination in the MRI scanner which in this case is a hand.

It is to be stressed out that whilst the examples on which the following description is based relates to a biologic case in which the object under examination is the wrist of a living patient, the method is not limited to this example. Examinations of the same kind can be carried out also on not living bodies or on in vitro tissues. Furthermore the present method can be applied at least relatively to its basic steps on not biologic objects. For example on inanimated materials, where instead of the so called contrast media the perfusion or transition of waves or of fluids such as liquids or gas or particles modifying their structure are used unless obviously the modifications induced by the said media are visible by means of MRI. Relating to figure 1, an object 1 is represented by a cube. The object 1 is positioned in an MRI scanner and one or more panoramic images are acquired, the so called scout images. If needed these images are used by the operator to select a certain particular region of the object 1, a so called region of interest (ROI) indicated by a small cube 101 within the object 1.

Thus the apparatus is ready to carry out a sequence of images of the same region of interest 101 at different times.

Figure 1 illustrates the sequence of imaging acquisitions along time axis t by reproducing the image of the object 1 and of the region of interest 101 at each acquisition tine ti, where i=0,1,2,3, .. ,n.

The object 1 under examination can show spontaneous time varying states which are typical for a certain condition of the object. If this is not the case, a time varying state can be induced in the object under examination 1 and more precisely in the region of interest by subjecting the said object to a treatment. Such treatment can be for example the injection of a fluid such as a gas or a liquid which is able to permeate the body under examination or the injection of a mechanical wave or of am electric or electromagnetic wave or signal.

A typical case in the examination of biologic tissues is the injection of contrast media. This is indicated schematically by 2 in figure 1. Contrast media are transported by the vascular or lymphatic system and their concentration varies with time from the instant of injection. Contrast media are known and give a very high and identifiable MRI signal. By repeating the MRI image acquisition several time at different times from injection of the contrast media in the object under examination, the quantity of contrast media in the region of interest 101 first increases and then roughly reaches a maximum which is maintained for a certain time. In the MRI images of the sequence this can be detected by examining the mean intensity of each image of the sequence. Reporting this values in relation to the time of acquisition allows to draw a so called perfusion curve an example of which is illustrated on figure 2. The stars indicate the measured values of the mean intensity of each MRI image of the region of interest 101 at the time of their acquisition. The curve passing through the stars is an interpolation curve which represents a function of the mean intensity with respect to time.

This kind of measurements are known as perfusion measurements and are used in MRI diagnostic and in ultrasound diagnostic. In diagnostic perfusion curves gives a measure of vascularisation of a tissue or anatomic region which is a sign of the presence of an abnormal condition. Increased vascularisation can be observed in the presence of inflammations, infections and also tumors. Thus perfusion measurements can be of help in determining a pathologic condition of a patient.

If non biologic material is considered, such as for example permeable materials, then a fluid or a gas can be applied with a certain pressure to the permeable material and the perfusion curve of the said fluid can be determined in order to evaluate homogeneity of permeation within the entire cross section and length of the material and/or if the permeability has to follow a certain direction of flux deviations can be observed.

In order to be able to evaluate the condition of an object by means of the method according to the present invention a certain number of sample objects having known condition as to be submitted to the perfusion measurements as indicated by the diagram of figure 3. In this case perfusion measurements according to the above description are carried out for each of the n sample objects and the so determined empiric perfusion functions fl to fn are determined. This functions can be univoquely related to the known conditions Cl to Cn of each of the said n sample objects . Each empiric function fl to fn can then be approximated by a function as for example a polynomial expansion or series which parameters P(fl) to F(fn) are univoquely correlated to the conditions Cl to Cn of the said n sample objects. Algortihm capable of carrying out this step are known and widely used by the skilled persons, since they are common general knowledge.

Thus a database has been constructed which comprises data vectors consisting in the parameters P(fl) to P(fn) and the corresponding condition fo the sample object.

The database further has to comprise the definition of the region of interest 101 which has to be the same for each sample object and which has to correspond to the same part in each sample object. The method according to the invention further provides the steps of carrying out the perfusion measurement of the same region of interest 101 which is centered at the same part of an object to be examined which condition is unknown. This is shown at the left column of figure 3.

Imaging and the determination of the perfusion curve fE and therefrom of the parameters P(fE) is carried out in exactly the same manner as disclosed above for the sample objects and with reference to figures 1 and 2.

A comparison step of the parameters P(fE) with the database allows to indentify at least a condition Cl to Cn to which the condition CE of the object under examination of unknown condition is nearest. Different cases may be possible. If one considers that the objects may have only discrete conditions, then no interpolation is necessary. If the conditions of the objects may vary continuously then the condition of the examined object having unknown condition may be further determined by interpolation, obviously if the parameters P(fE) falls between two parameters of the sample objects. Also when carrying out MRI of the object under examination which condition is unknown it is important to determine the same region of interest 101 centered at the same part of the object as in the sample objects. Although the present invention can be carried out considering imaging along one or more selected slices, i.e. section planes of the objects, thus being limited to a so called two dimensional MRI case. Best results can be achieved by using three dimensional MRI . Three dimensional imaging technique is known and allows to acquire a three dimensional array of image data. (see for example "Magnetic Resonance Imaging, Physical Principles and Sequence Design" E. Mark Haacke, Robert W. Brown, Michael R. Thompson, Ramesh Venkatesan John Wiley & Sons Inc. Publication, ; "Practical NMR Imaging" M.A Foster & J.M.S. Hutchinson IRL Press) . In this case the uncertainity relating to the fact that for each object the same slice or slices or the same section plane or section planes are selected due to different positioning of the objects relatively to the MRI scanner are widely reduced.

Three dimensional MRI allows also to carry out the method by using slice images, since once a three dimensional image data array has been acquired a section plane or slice of the imaged volume can be defined and the image data falling on the said slice can be selected and retrieved form the image data memory.

Nevertheless as said above choosing to use a three dimensional region of interest 101 allows to improve precision.

In order to further enhance precision either in the case of two dimensional MRI and of three dimensional MRI markers can be provided on the objects under examination.

These markers can be external markers which are applied on the objects at the same places relatively to the shape of the objects. This can be done by identifying morphologically or anatomically univoque points on the objects surface.

Markers provide for univoquely identifiable MRI signals which can be used to bring into register the images acquired of each different object. Register algorithm capable of carrying out this tasks are known.

One of such algorithm and the corresponding method are disclosed in (Hemmendorf, M.; Anderson, M.T.;

Kronander, T.; Knutsson, H. Phase-based multidimensional volume registration. IEE Trans Med

Imaging 2002, 21, 1536-43) . Figures 6A to 6D try to explain with a simplified example the effects of such combination of markers and registration algorithms.

Figures 6A to 6D shows schematic views of different MRI sessions carried out at different times, each time positioning the object which in this case is a hand in the scanner and each time defining an imaging volume enclosing the hand, markers being provided at selected identical positions on the hand for carrying out a slice image registration in order to identify at each imaging session the same section plane across the hand along which a slice image has to acquired and displayed.

In Figures 6A to 6D the volume V defined by the user and in which the image data has to be acquired is represented by the rectangle. Considering for simplicity that this volume is always the same at each imaging session, the hand can be differently positioned at each session relatively to the volume with respect to all the other sessions. Thus section plane FlA defined in the session represented by figure 6A will correspond if referred to the hand as a body under examination to section plane PlB, PlC and PlD in the following imaging sessions represented by figures 6B to 6D.

In order to identify the correct section plane one, preferably at least two or more markers can be provided. The markers can be as illustrated in figure 6A to 6D MRI opaque elements 30 which can be positioned on the body under examination at univoquely and repeatedly identifiable points of the anatomy or shape of the said body. Alternatively the markers can be parts or zones of the anatomy of the body under examination which are univoquely recognizable as particularly evident zones and which are constant. This allows to use these zones as intrinsic markers.

Combination of these anatomic markers and of the opaque elements can also be used.

The example is referrend to the identification of a section plane within a volumetric image data but the same method apply also if a three dimensional region of interest 101 has to be identified and correctly oriented relatively to the object to be imaged.

The markers can be searched and identified within each of the volumetric image data acquired at each imaging session. The markers can be used to align spatially the volumetric image data of a predefined region of interest 101 by applying a so called Registering algorithm disclosed above.

The effect of the registration algorithm is that referring to the example of figures 6A to 6D the plane PlA can be correctly repositioned relatively to the imaged object (namely the hand) in the image data of the following imaging sessions giving to it the correct orientation as indicated by PlB, PlC, PlD in figure 6B, 6C, 6D. The same apply in the case of a volumetric region of interest 101.

The position of the object to be imaged, namely the hand can be identified and displacement vectors can be determined with reference to the position of the hand in figure 6A which displacement vectors can be used by calculating the new position and orientation parameters of the a section plane such as the section plane PlA of the illustrated example or of a volumetric region of interest 101 relatively to the different positions of the hand in each of the following imaging sessions.

Thus for each imaging session the same section plane or volumetric region of interest can be identified allowing to carry out reliable comparisons between the acquired image data.

Figure 4 illustrates a variation of the method according to figure 3. In this case the same database as in example 3 is used, namely a database comprising as input variables the parameters P (fl) to P(fn) of the functions fl to fn of the mean intensity of the sequence of MRI images as a function of time of each of the n sample objects. The output variables are the univoquely correlated conditions Cl to Cn of each one of the sample objects .

This database is used for training and testing a predictive algorithm such as an artificial neural network. The data of the examined object which condition CE is unknown, namely the parameters P(fE) of the function fE of the said examined object are fed to the trained and tested predictive algorithm and the said algorithm determines the condition of the said examined object. In this case the determination of the condition of the object is not carried out using a simple comparation, but the more sophisticated predictive algorithm.

The fact that the method according to the invention allows to determine a condition of an examined object basing on MRI image acquisitions of sample objects, and the combination of the said method with the marking and registering steps and with a three dimensional MRI image acquisition technique ensures that the results are highly independent form the variable positioning of the objects in the MRI scanner. This allows to use the said method to carry out follow up examinations which are reliable, particularly follow up examinations of the developments of a disease with or without therapeutic treatment.

In other words the present method allows to identify the developments for example of a disease with or without a therapy treatment which has occurred from one first imaging session to the successive ones or ones carried out at different later times.

Follow up examinations is a very important tool for analysing the developments of a disease or the response to a therapy. Generally today, MRI is considered not to be useful for follow up examinations due to the fact that it is not simple to position the body under examination exactly in the same position at each imaging session. This problem can be overcome by using the method according to the invention. Figure 5 illustrates the steps of a follow up carried out with the method according to the invention.

The object to be examined is subjected to an imaging session as previously described at different times at each time the condition of the examined body is determined with the method described above either by comparing the condition with a database of data relative to sample objects or also by simply comparing the data of the previous imaging sessions. This allows to reconstruct a development time table of the object conditions.

A particular application of the above disclosed method for determining the conditions of an object consist in determining the disease activity of rheumatisms and arthritis, particularly of rheumatoid arthritis. In this case the object to be examined is the anatomic district of the wrist and the region of interest is the synovial membrane. Indeed it is known that the synovial membrane is an anatomic site where inflammation can be detected at early stages. Thus the method according to the present invention can be used for determining the degree of rheumatoid arthritis activity and for carrying out a follow up of a patient which is affected from rheumatoid arthritis. The database is generated by carrying out the MRI acquisition steps as described above, particularly using a three dimensional MRI method. After one or more scout images are acquired a region of interest centered at the synovial membrane is defined and confirmed by the user. Anatomic and/or external markers can be identified and or defined and also or alternatively external markers are placed on the hand at univoquely identifiable points of the morphology of the hand. The contrast media perfusion measurements are carried out for each patient having a known degree of activity of rheumatoid arthritis. For each patient the same region of interest is selected by means of the markers and of the registration algorithm thus ensuring that the region of interest is always identical and centered at the synovial membrane.

After having generated the database a patient can be subjected to a perfusion measurement carried out in exactly the same manner as the perfusion measurements of the sample patients. The same region of interest is selected by means of the anatomic and/or external markers and the registration algorithm. The user can also confirm the region of interest by visualizing the image on a screen an visually recognizing -the synovial membrane. By means of a comparison method or a predictive algorithm the degree of disease activity can then be determined for the patient. The method allows to determine if the disease is present or not and if the disease is active or not.

Furthermore the patient can be submitted to a follow up observation. At each imaging session for contrast means perfusion measurement the same region of interest is selected by means of the markers as described above and for each perfusion measurement the degree of disease activity can be determined. In this way the development of the disease can be controlled and if the patient is submitted to a therapy the success of the therapy and the progress in the disease regression can be monitored, thus allowing to have a very strict and precise control of the disease development an/or of the effectiveness of the therapy.

Obviously the above method according to the invention either for determining the conditions - of disease activity or for a disease follow up can be applied to other kind of diseases, particularly to diseases which cause a variation in the vascularisation of the inflamed or attached tissue or tissues. As for the method for determining the conditions of an object also for the method of follow up according to the invention, the diagnostic filed is not the only one in which the said method can be used, but it can be applied also to in vitro biologic tissues or to non biologic material.

Referring to the example of a solid permeable body, variation of the condition relatively to the permeation of a fluid such as a liquid or a gas within the said solid body can be observed and determined for example depending on other parameters which may vary in time, such as temperatures, relative humidity, or induced by other physical or chemical treatments to which the body may be subjected.

Claims

1. A method for determining the condition of an object by MRI, comprising the following steps: a) acquiring at least one image by means of MRI along at least one slice or one section plane of an object under examination at different successive times within a predetermined time period; b) the said object being a sample object having known conditions c) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample object under examination the mean intensity of the MRI signal; d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; e) graphically representing the- function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said image; f) providing at least a second object to be examined having an unknown condition and carrying out the steps a) to e) using the said second object; g) visually comparing the graphic representations of the functions approximating the empiric time dependency function relating to the sample object and to the second object in order to detect differences of the condition of the second object from the known conditions of the sample object.

2. A Method according to claim 1, characterized in that the graphical representations of the functions approximating the empiric time dependency function relating to the sample object and to the second object, is carried out manually.

3. A Method according to claim 1, characterized in that the graphic representation of the functions approximating the empiric time dependency function relating to the sample object and to the second object is carried out by an approximation algorithm determining a path of a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said images.

4. A method according to one or more of the preceding claims, characterized in that the object under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions;

The unknown condition of a one or more further objects being determined by carrying out the steps a) to e) for these one or more further objects and comparing corresponding the graphical representations of the function approximating the empiric time dependency function relating to the one or more further objects with the graphical representations of the function approximating the empiric time dependency function relating to the sample objects.

5. A Method according to one or more of the preceding claims, characterized in that when in comparing the graphic representation of the function approximating the empiric time dependency function relating to the one or more further objects with the graphic representation of the function approximating the empiric time dependency function relating to the sample objects, the said graphic representation of the function approximating the empiric time dependency function relating to the one or more further objects falls at least partly or completely between the graphic representation of two different functions approximating the empiric time dependency function relating to the sample objects which functions are related to two different conditions of the sample objects, the condition of the further objects is determined by interpolation between the said two different graphic representation of the functions approximating the empiric time dependency function relating to the sample objects .

6. A method according to one or more of the preceding claims, providing the step of applying to the sample objects and to the further objects of which the condition has to be determined a medium able to diffuse within the said objects and carrying out the acquisition steps of one or more images of the said objects along one or more selected slices or section planes within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the object.

7. A method according to one or more of the preceding claims, characterized in that a first panoramic image a so called scout image is acquired along a first scout slice or section plane by means of which one or a series of selected section planes across the objects are determined along each of which an image has to be acquired.

8. A method according to one or more of the preceding claims, characterized in that a first image along a first section plane is acquired and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, image acquired at later times along the same slice or section plane.

9. A method according to one or more of the preceding claims, characterized in that instead of acquiring images along one or more section planes or slices a three dimensional image of the sample objects and of the objects having unknown conditions or of part thereof is acquired thus collecting a sequence of three dimensional images acquired each one at a different time and within a certain time period.

10. A method according to claim 9, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

11. A method according to one or more of the preceding claims, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slice or section planes of the objects or of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding two or three dimensional image of the sequence of two or three dimensional images and the corresponding time of acquisition.

12. A method according to one or more of the preceding claims, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the objects or of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed in which for each two dimensional image along one selected plane or section plane of the sequence of section planes or for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

13. A method according to one or more of the preceding claims characterized in that the images along one or more selected slices or section planes are acquired by acquiring a three dimensional image of the objects; defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

14. A method according to one or more of the preceding claims, characterized in that markers are applied to the objects in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

15. A method according to claim 14, characterized in that the markers are defined as selected zones or regions of the objects which are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

16. A method according to one or more of the preceding claims, characterized in that the object consist of a biologic tissue and/or of an ensamble of biologic tissues.

17. A method according to one or more of the preceding claims characterised in that the object is an anatomic district of a body under examination.

18. A method according to claim 17, characterized in that the medium applied to the object and permeating the object is a contrast agent supplied to the anatomic district of the body under examination.

19. A method for determining the condition of an object by MRI, comprising the following steps: a) acquiring at least one image by means of MRI along at least one slice or one section plane of an object under examination at different successive times within a predetermined time period; b) the said object being a sample object having known conditions c) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample object under examination the mean intensity of the MRI signal; d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; e) analytically determining the parameter of a function approximating the said empiric time dependency function. f) providing at least a second object to be examined having an unknown condition and carrying out the steps a) to e) using the said second object; g) comparing the parameters of the function approximating the empiric time dependency function relating to the sample object and to the second object in order to detect differences of the condition of the second object from the known conditions of the sample object.

20. A Method according to claim 19, characterized in that the object under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions;

The unknown condition of a one or more further objects being determined by carrying out the steps a) to e) for these one or more further objects and comparing the corresponding parameters of the function approximating the empiric time dependency function relating to the one or more further objects with the parameters of the function approximating the empiric time dependency function relating to the sample objects.

21. A Method according to claim 19 or 20, characterized in that when in comparing the set of parameters of the function approximating the empiric time dependency function relating to the one or more further objects with the set of parameters of the function approximating the empiric time dependency function relating to the sample objects, the said set of parameters of the function approximating the empiric time dependency function relating to the one or more further objects falls at least for some parameter or for all parameters of the set between two different values of at least some of the parameters or of all the parameters of the set of parameters of the functions approximating the empiric time dependency function relating to the sample objects which functions are related to two different conditions of the sample objects, the condition of the further objects is determined by interpolation between the said two different values of at least some of the parameters or of all the parameters of the set of parameters of the functions approximating the empiric time dependency function relating to the sample objects.

22 A method according to one or more of the preceding claims 19 to 21, providing the step of applying to the sample objects and to the further objects of which the condition has to be determined a medium able to diffuse within the said objects and carrying out the acquisition steps of one or more images of the said objects along one or more selected slices or section planes within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the object.

23. A method according to one or more of the preceding claims 19 to 22, characterized in that a first panoramic image a so called scout image is acquired along a first scout slice or section plane by means of which one or a series of selected section planes across the objects are determined along each of which an image has to be acquired.

24. A method according to one or more of the preceding claims 19 to 23, characterized in that a first image along a first section plane is acquired and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, image acquired at later times along the same slice or section plane.

25. A method according to one or more of the preceding claims 19 to 24, characterized in that instead of acquiring images along one or more section planes or slices a three dimensional image of the sample objects and of the objects having unknown conditions or of part thereof is acquired thus collecting a sequence of three dimensional images acquired each one at a different time and within a certain time period.

26. Λ method according to claim 25, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

27. A method according to one or more of the preceding claims 19 to 26, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slice or section planes of the objects or of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding two or three dimensional image of the sequence of two or three dimensional images and the corresponding time of acquisition.

28. A method according to one or more of the preceding claims 19 to 27, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the objects or of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed in which for each two dimensional image along one selected plane or section plane of the sequence of section planes or for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

29. A method according to one or more of the preceding claims 19 to 28 characterized in that the images along one or more selected slices or section planes are acquired by acquiring a three dimensional image of the objects; defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

30. A method according to one or more of the preceding claims 19 to 29, characterized in that markers are applied to the objects in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

31. A method according to claim 30, characterized in that the markers are defined as selected zones or regions of the objects which are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

32. A method according to one or more of the preceding claims 19 to 31, characterized in that the object consist of a biologic tissue and/or of an ensamble of biologic tissues.

33. A method according to one or- more of the preceding claims 19 to 32 characterised in that the object is an anatomic district of a body under examination.

34. A method according to claim 33, characterized in that the medium applied to the object and permeating the object is a contrast agent supplied to the anatomic district of the body under examination.

35. A method for determining the condition of an object by MRI, comprising the following steps: a) acquiring at least one three dimensional image by means of MRI of an object under examination at different successive times within a predetermined time period; b) the said object being a sample object having known conditions; c) determining for each image or for a selected region of each three dimensional image, which selected region is identical for each image or refers to an identical part of the imaged sample object under examination the mean intensity of the MRI signal; d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; e) graphically representing the function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said image; f) providing at least a second object to be examined having an unknown condition and carrying out the steps a) to e) using the said second object; g) visually comparing the graphic representations of the functions approximating the empiric time dependency function relating to the sample object and to the second object in order to detect differences of the condition of the second object from the known conditions of the sample object.

36. A method according to claim 35, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

37. Λ method according to claims 35 or 36, characterized in that two or more selected regions of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

38. A method according to one or more of the preceding claims 35 to 37, characterized in that two or more, selected regions of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed in which for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected regions of interests.

39. A method according to one or more of the preceding claims 35 to 38 characterized in that two dimensional images along one or more selected slices or section planes are retrieved from a three dimensional image of the objects acquired by MRI three dimensional imaging including the steps of defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

40. A method according to claim 39, characterized in that a first panoramic image a so called scout image is along a first scout slice or section plane is retrieved from the three dimensional images, by means of which scout image one or a series of two dimensional images along selected section planes across the objects are retrieved from the three dimensional images.

41. A method according to one or more of the preceding claims, characterized in that a first image along a first section plane is retrieved form the three dimensional image and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, two dimensional image retrieved at later times along the same slice or section plane.

42. A method according to one or more of the preceding claims 35 to 41, characterized in that markers are applied to the objects in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

43. A method according to claim 42, characterized in that the markers are defined as selected zones or regions of the objects which are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

44. A method according to one or more of the preceding claims 35 to 43, characterized in that the object consist of a biologic tissue and/or of an ensamble of biologic tissues.

45. A method according to one or more of the preceding claims 35 to 44 characterised in that the object is an anatomic district of a body under examination.

46. A Method according to claim 35, characterized in that the graphical representations of the functions approximating the empiric time dependency function relating to the sample object and to the second object, is carried out manually.

47. A Method according to claim 35, characterized in that the graphic representation of the functions approximating the empiric time dependency function relating to the sample object and to the second object is carried out by an approximation algorithm determining a path of a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said images.

48. A method according to one or more of the preceding claim 35 to 47, characterized in that the object under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions; The unknown condition of a one or more further objects being determined by carrying out the steps a) to e) for these one or more further objects and comparing corresponding the graphical representations of the function approximating the empiric time dependency function relating to the one or more further objects with the graphical representations of the function approximating the empiric time dependency function relating to the sample objects.

49. A Method according to one or more of the preceding claims 35 to 48, characterized in that when in comparing the graphic representation of the function approximating the empiric time dependency function relating to the one or more further objects with the graphic representation of the function approximating the empiric time dependency function relating to the sample objects, the said graphic representation of the function approximating the empiric time dependency function relating to the one or more further objects falls at least partly or completely between the graphic representation of two different functions approximating the empiric time dependency function relating to the sample objects which functions are related to two different conditions of the sample objects, the condition of the further objects is determined by interpolation between the said two different graphic representation of the functions approximating the empiric time dependency function relating to the sample objects .

50. A method according to one or more of the preceding claims 35 to 49, providing the step of applying to the sample objects and to the further objects of which the condition has to be determined a medium able to diffuse within the said objects and carrying out the acquisition steps of one or more images of the said objects within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the object.

51 A method for determining the condition of an object by MRI, comprising the following steps: a) acquiring at least one three dimensional image by means of MRI of an object under examination at different successive times within a predetermined time period; b) the said object being a sample object having known conditions; c) determining for each image or for a selected region of each three dimensional image, which selected region is identical for each image or refers to an identical part of the imaged sample object under examination the mean intensity of the MRI signal; d) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; e) analytically determining the parameter of a function approximating the said empiric time dependency function. f) providing at least a second object to be examined having an unknown condition and carrying out the steps a) to e) using the said second object; g) comparing the parameters of the function approximating the empiric time dependency function relating to the sample object and to the second object in order to detect differences of the condition of the second object from the known conditions of the sample object.

52. A method according to claim 51, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

53. A method according to claims 51 or 52, characterized in that two or more selected regions of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

54. A method according to one or more of the preceding claims 51 to 53, characterized in that two or more selected regions of the sequence of three dimensional images of the objects are defined and an empiric time dependency function of the mean intensity is constructed in which for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected regions of interests.

55. A method according to one or more of the preceding claims 51 to 54 characterized in that two dimensional images along one or more selected slices or section planes are retrieved from a three dimensional image of the objects acquired by MRI three dimensional imaging including the steps of defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

56. A method according to claim 55, characterized in that a first panoramic image a so called scout image is along a first scout slice or section plane is retrieved from the three dimensional images, by means of which scout image one or a series of two dimensional images along selected section planes across the objects are retrieved from the three dimensional images.

57. A method according to one or more of the preceding claims 51 to 56, characterized in that a first image along a first section plane is retrieved form the three dimensional image and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, two dimensional image retrieved at later times along the same slice or section plane.

58. A method according to one or more of the preceding claims 51 to 57, characterized in that markers are applied to the objects in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

59. A method according to claim 58, characterized in that the markers are defined as selected zones or regions of the objects which are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

60. A method according to one or more of the preceding claims 51 to 59, characterized in that the object consist of a biologic tissue and/or of an ensamble of biologic tissues.

61. A method according to one or more of the preceding claims 35 to 44 characterised in that the object is an anatomic district of a body under examination.

62. A method according to one or more of the preceding claim 51 to 61, characterized in that the object under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions;

The unknown condition of a one or more further objects being determined by carrying out the steps a) to e) for these one or more further objects and comparing the parameters of the function approximating the empiric time dependency function relating to the one or more further objects with the parameters of the function approximating the empiric time dependency function relating to the sample objects.

63. A Method according to claim 51 or 62, characterized in that when in comparing the set of parameters of the function approximating the empiric time dependency function relating to the one or more further objects with the set of parameters of the function approximating the empiric time dependency function relating to the sample objects, the said set of parameters of the function approximating the empiric time dependency function relating to the one or more further objects falls at least for some parameter or for all parameters of the set between two different values of at least some of the parameters or of all the parameters of the set of parameters of the functions approximating the empiric time dependency function relating to the sample objects which functions are related to two different conditions of the sample objects, the condition of the further objects is determined by interpolation between the said two different values of at least some of the parameters or of all the parameters of the set of parameters of the functions approximating the empiric time dependency function relating to the sample objects.

64. A method according to one or more of the preceding claims 51 to 63, providing the step of applying to the sample objects and to the further objects of which the condition has to be determined a medium able to diffuse within the said objects and carrying out the acquisition steps of one or more images of the said objects within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the object.

65. A method for carrying out a follow up of the pathologic conditions of biologic tissues in isolated form or in or of an anatomic district of a body comprising the steps of a) acquiring at least one image by means of MRI along at least one slice or one section plane of the biologic tissues having a known condition at different successive times within a predetermined time period; b) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample biologic tissues under examination the mean intensity of the MRI signal; c) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; d) analytically determining the parameter of a function approximating the said empiric time dependency function. e) providing at least a second biologic tissues to be examined having an unknown condition and carrying out the steps a) to d) using the said second biologic tissues; f) comparing the parameters of the function approximating the empiric time dependency function relating to the sample biologic tissues and to the second biologic tissues having an unknown condition in order to detect differences of the condition of the second object from the known conditions of the sample object.

66. A method according to claim 65, characterized in that the condition of the biologic tissue is a pathologic condition.

67. A method according to claim 65 or 66, characterized in that the biologic tissue or the biologic tissues under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions;

The unknown condition of a one or more further biologic tissues being determined by carrying out the steps a) to e) for these one or more further biologic tissues and comparing the parameters of the function approximating the empiric time dependency function relating to the one or more further biologic tissues with the parameters of the function approximating the empiric time dependency function relating to the sample biologic tissues.

68. A method according to one or more of the preceding claims 65 to 67, providing the step of applying to the sample biologic tissues of known conditions and to the further biologic tissues of unknown condition and of which the condition has to be determined a medium able to diffuse within the said biologic tissues and carrying out the acquisition steps of one or more images of the said biologic tissues along one or more selected slices or section planes within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the biologic tissue.

69. A method according to one or more of the preceding claims 65 to 68, characterized in that a first panoramic image a so called scout image is acquired along a first scout slice or section plane by means of which one or a series of selected section planes across the biologic tissues are determined along each of which an image has to be acquired.

70. A method according to one or more of the preceding claims 65 to 69, characterized in that a first image along a first section plane is acquired and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, image acquired at later times along the same slice or section plane.

71. A method according to one or more of the preceding claims 65 to 70, characterized in that instead of acquiring images along one or more section planes or slices a three dimensional image of the sample biologic tissues having known conditions and of the one or more further biologic tissues having an unknown condition or of part thereof is acquired thus collecting a sequence of three dimensional images acquired each one at a different time and within a certain time period.

72. A method according to claim 71, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and the boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

73. A method according to one or more of the preceding claims 65 to 72, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the biologic tissues or of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding two or three dimensional image of the sequence of two or three dimensional images and the corresponding time of acquisition.

74. A method according to one or more of the preceding claims 65 to 73, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the biologic tissues or of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed in which for each two dimensional image along one selected plane or section plane of the sequence of section planes or for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

75. A method according to one or more of the preceding claims 65 to 74 characterized in that the images along one or more selected slices or section planes are acquired by acquiring a three dimensional image of the biologic tissues; defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

76. A method according to one or more of the preceding claims 65 to 75, characterized in that markers are applied to the biologic tissues in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

77. A method according to claim 76, characterized in that the markers are defined as selected zones or regions of the biologic tissues and/or of an anatomical district wherein these tissues resides, which selected zones are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

78. A method according to claim 77, characterized in that the medium applied to the biologic tissues and permeating the biologic tissues is a contrast agent supplied to the anatomic district of the body under examination.

79. A method according to one or more of the preceding claims 65 to 78, characterized in that the pathologic condition is rheumatoid arthritis.

80. A method for carrying out a follow up of the pathologic conditions of biologic tissues in isolated form or in or of an anatomic district of a body comprising the steps of a) acquiring at least one image by means of MRI along at least one slice or one section plane of the biologic tissues having a known condition at different successive times within a predetermined time period; b) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged sample biologic tissues under examination the mean intensity of the MRI signal; c) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; d) graphically representing the function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said image; e) providing at least a second biologic tissues to be examined having an unknown condition and carrying out the steps a) to d) using the said second biologic tissues; f) visually comparing the graphic representations of the functions approximating the empiric time dependency function relating to the sample biologic tissues and to the second biologic tissues having an unknown condition in order to detect differences of the condition of the second object from the known conditions of the sample object.

81. A method according to claim 80, characterized in that the condition of the biologic tissue is a pathologic condition.

82. A method according to claim 80 or 81, characterized in that the biologic tissue or the biologic tissues under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions;

The unknown condition of a one or more further biologic tissues being determined by carrying out the steps a) to e) for these one or more further biologic tissues and comparing the graphic representation of the function approximating the empiric time dependency function relating to the one or more further biologic tissues with the graphic representation of the function approximating the empiric time dependency function relating to the sample biologic tissues.

83. A method according to one or more of the preceding claims 80 to 82, providing the step of applying to the sample biologic tissues of known conditions and to the further biologic tissues of unknown condition and of which the condition has to be determined a medium able to diffuse within the said biologic tissues and carrying out the acquisition steps of one or more images of the said biologic tissues along one or more selected slices or section planes within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the biologic tissue.

84. Λ method according to one or more of the preceding claims 80 to 83, characterized in that a first panoramic image a so called scout image is acquired along a first scout slice or section plane by means of which one or a series of selected section planes across the biologic tissues are determined along each of which an image has to be acquired.

85. A method according to one or more of the preceding claims 80 to 84, characterized in that a first image along a first section plane is acquired and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, image acquired at later times along the same slice or section plane.

86. A method according to one or more of the preceding claims 80 to 85, characterized in that instead of acquiring images along one or more section planes or slices a three dimensional image of the sample biologic tissues having known conditions and of the one or more further biologic tissues having an unknown condition or of part thereof is acquired thus collecting a sequence of three dimensional images acquired each one at a different time and within a certain time period.

87. A method according to claim 86, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and the boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

88. A method according to one or more of the preceding claims 80 to 87, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the biologic tissues or of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding two or three dimensional image of the sequence of two or three dimensional images and the corresponding time of acquisition.

89. A method according to one or more of the preceding claims 80 to 88, characterized in that two or more selected regions of the sequence of two dimensional images along one or more selected slices or section planes of the biologic tissues or of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed in which for each two dimensional image along one selected plane or section plane of the sequence of section planes or for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

90. A method according to one or more of the preceding claims 80 to 89 characterized in that the images along one or more selected slices or section planes are acquired by acquiring a three dimensional image of the biologic tissues; defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

91. A method according to one or more of the preceding claims 80 to 90, characterized in that markers are applied to the biologic tissues in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

92. A method according to claim 91, characterized in that the markers are defined as selected zones or regions of the biologic tissues and/or of an anatomical district wherein these tissues resides, which selected zones are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

93. A method according to claim 92, characterized in that the medium applied to the biologic tissues and permeating the biologic tissues is a contrast agent supplied to the anatomic district of the body under examination.

94. A method according to one or more of the preceding claims 80 to 93, characterized in that the pathologic condition is rheumatoid arthritis.

95. A method for carrying out a follow up of the pathologic conditions of biologic tissues in isolated form or in or of an anatomic district of a body comprising the steps of a) acquiring at least one three dimensional image by means of MRI of the biologic tissues having a known condition at different successive times within a predetermined time period; b) determining for each image or for a selected region of each -three dimensional image, which selected region is identical for each image or refers to an identical part of the imaged sample biologic tissues under examination the mean intensity of the MRI signal; c) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional image or of the part of each three dimensional image and the corresponding time of acquisition; d) analytically determining the parameter of a function approximating the said empiric time dependency function. e) providing at least a second biologic tissues to be examined having an unknown condition and carrying out the steps a) to d) using the said second biologic tissues; f) comparing the parameters of the function approximating the empiric time dependency function relating to the sample biologic tissues and to the second biologic tissues having an unknown condition in order to detect differences of the condition of the second object from the known conditions of the sample object.

96. A method according to claim 95, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and the boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

97. A method according to claims 95 or 96, characterized in that two or more selected regions of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

98. A method according to one or more of the preceding claims 95 to 97, characterized in that two or more selected regions of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed in which for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

99. A method according to one or more of the preceding claims 95 to 98 characterized in that the images along one or more selected slices or section planes are retrieved from a three dimensional image of the biologic tissues including the steps of: defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

100. A method according to one or more of the preceding claims 95 to 99, characterized in that a first panoramic image a so called scout image is along a first scout slice or section plane is retrieved from the three dimensional images, by means of which scout image one or a series of two dimensional images along selected section planes across the biologic tissues are retrieved from the three dimensional images.

101. A method according to one or more of the preceding claims 95 to 100, characterized in that a first image along a first section plane is retrieved form the three dimensional image and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, two dimensional image retrieved at later times along the same slice or section plane.

102. A method according to claim 95, characterized in that the condition of the biologic tissue is a pathologic condition.

103. A method according to claim 95 or 96, characterized in that the biologic tissue or the biologic tissues under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a)^r to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions; The unknown condition of a one or more further biologic tissues being determined by carrying out the steps a) to e) for these one or more further biologic tissues and comparing the parameters of the function approximating the empiric time dependency function relating to the one or more further biologic tissues with the parameters of the function approximating the empiric time dependency function relating to the sample biologic tissues.

104. A method according to one or more of the preceding claims 95 to 103, providing the step of applying to the sample biologic tissues of known conditions and to the further biologic tissues of unknown condition and of which the condition has to be determined a medium able to diffuse within the said biologic tissues and carrying out the acquisition steps of one or more three dimensional images of the said biologic tissues within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of said media in the biologic tissue.

105. A method according to one or more of the preceding claims 95 to 104, characterized in that markers are applied to the biologic tissues in univoquely defined positions thereof, the markers generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

106. A method according to claim 105, characterized in that the markers are defined as selected zones or regions of the biologic tissues and/or of an anatomical district wherein these tissues resides, which selected zones are univoquely identifiable in the images of the selected slices or section planes or in the three dimensional images.

107. A method according to claim 106, characterized in that the medium applied to the biologic tissues and permeating the biologic tissues is a contrast agent supplied to the anatomic district of the body under examination.

108. A method according to one or more of the preceding claims 95 to 107, characterized in that the pathologic condition is rheumatoid arthritis.

109. A method for carrying out a follow up of the pathologic conditions of biologic tissues in isolated form or in or of an anatomic district of a body comprising the steps of a) acquiring at least one three dimensional image by means of MRI of the biologic tissues having a known condition at different successive times within a predetermined time period; b) determining for each image or for a selected region of each three dimensional image, which selected region is identical for each image or refers to an identical part of the imaged sample biologic tissues under examination the mean intensity of the MRI signal; c) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional image or of the part of each three dimensional image and the corresponding time of acquisition; d) graphically representing the function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said image; e) providing at least a second biologic tissues to be examined having an unknown condition and carrying out the steps a) to d) using the said second biologic tissues; f) visually comparing the graphic representations of the functions approximating the empiric time dependency function relating to the sample biologic tissues and to the second biologic tissues having an unknown condition in order to detect differences of the condition of the second object from the known conditions of the sample object.

110. A method according to claim 109, characterized in that in the first three dimensional image one or more three dimensional partial regions are selected being said regions so called regions of interest and the position in space and the boundaries of the said regions of interest being determined, while the said regions of interest are automatically selected for each following three dimensional image being acquired at every later times, the mean intensity of the image data of each three dimensional region of interest being calculated and applied for constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each three dimensional region of interest of each three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

111 A method according to claims 109 or 110, characterized in that two or more selected regions of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed separately for each different selected region by means of the data pairs consisting of the mean intensity of the corresponding selected region of each corresponding three dimensional image of the sequence of three dimensional images and the corresponding time of acquisition.

112. A method according to one or more of the preceding claims 109 to 111, characterized in that two or more selected regions of the sequence of three dimensional images of the biologic tissues are defined and an empiric time dependency function of the mean intensity is constructed in which for each three dimensional image of the sequence of three dimensional images the mean intensity is determined by the sum of the mean intensities of the different selected region of interests.

113. A method according to one or more of the preceding claims 109 to 112 characterized in that the images along one or more selected slices or section planes are retrieved from a three dimensional image of the biologic tissues including the steps of: defining within the said three dimensional image one or more planes crossing the volume represented by the said three dimensional image and reconstructing the image along the said one or more planes from the three dimensional image data by selecting the image data falling on each selected plane crossing the volume.

114. A method according to one or more of the preceding claims 109 to 113, characterized in that a first panoramic image a so called scout image is along a first scout slice or section plane is retrieved from the three dimensional images, by means of which scout image one or a series of two dimensional images along selected section planes across the biologic tissues are retrieved from the three dimensional images.

115. A method according to one or more of the preceding claims 109 to 114, characterized in that a first image along a first section plane is retrieved form the three dimensional image and a partial region of the said image is determined which region is a so called region of interest (ROI) , the geometric shape and position of the said region of interest being determined and selected on each further, two dimensional image retrieved at later times along the same slice or section plane.

116. A method according to claim 115, characterized in that the condition of the biologic tissue is a pathologic condition.

117. A method according to claim 109 or 116, characterized in that the biologic tissue or the biologic tissues under examination is of the kind able to show at least two or more conditions or a continuously varying condition, the step a) to e) being carried out for every discrete possible condition of the body under examination or for a certain number of different selected conditions of the continuously varying conditions;

118. A method according to one or more of the preceding claims 109 to 117, providing the step of applying to the sample biologic tissues of known conditions and to the further biologic tissues of unknown condition and of which the condition has to be determined a medium able to diffuse within the said 5 biologic tissues and carrying out the acquisition steps of one or more three dimensional images of the said biologic tissues within a time period starting before or at or immediately after the application of the said diffusion media and ending after complete diffusion of

10 said media in the biologic tissue.

119. A method according to one or more of the preceding claims 109 to 118, characterized in that markers are applied to the biologic tissues in univoquely defined positions thereof, the markers

15 generating univoquely recognizable image data in the images acquired and the selected region or regions being defined by means of the geometric relation of the said markers with the position and boundaries of the selected regions.

-20 120. A method according to claim 119, characterized in that the markers are defined as selected zones or regions of the biologic tissues and/or of an anatomical district wherein these tissues resides, which selected zones are univoquely

25 identifiable in the images of the selected slices or section planes or in the three dimensional images.

121. A method according to claim 120, characterized in that the medium applied to the biologic tissues and permeating the biologic tissues is

30 a contrast agent supplied to the anatomic district of the body under examination.

122. A method according to one or more of the preceding claims 109 to 121, characterized in that the pathologic condition is rheumatoid arthritis.

123. A method for carrying out a follow up of the disease activity of the pathologic conditions of an anatomic district of a body by means of contrast media perfusion measurements in the said anatomic district comprising the steps of a) generating a database of perfusion curves each one univoquely associated to a well defined degree of disease activity; b) the said database being generated by acquiring at least one image of the anatomic district by means of MRI along at least one slice or one section plane of the anatomic district in patients or a three dimensional MRI image of the anatomical district in patients having a known degree of disease activity; c) for each patient having a well defined degree of disease activity a sequence of MRI images is acquired which sequence comprises a certain number of MRI images taken at different times one of the other within a certain period of time; d) the said period starting immediately after or at the injection of a contrast medium in the anatomic district and terminating after a certain time determined as a typical duration of contrast media perfusion in the anatomic district; e) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged anatomical district under examination the mean intensity of the image data acquired; f) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; g) analytically determining the parameter of a function approximating the said empiric time dependency function. h) determining the disease activity in the same anatomic district of a patient having an unknown level of disease activity by carrying out the steps of injecting the said contrast media in the anatomic district of the said patient and by acquiring the sequence of MRI images of the anatomic district for the predetermined period of time and finally constructing the empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition and analytically determining the parameter of a function approximating the said empiric time dependency function; i) comparing the parameters of the function approximating the empiric time dependency function relating to the database in order to detect the disease activity level.

124. A method according to claim 123 characterized in that a follow up of the disease activity comprises the repetition at several different times of the steps h) and i) for determining changes in the disease activity degree in time and during a therapeutic treatment.

125. A method according to claims 123 or 124, characterized in that a first MRI scout image of the anatomic district is acquired before injection the contrast media; a Region of Interest is defined on said image comprising or containing the image of an anatomic relevant object; the position and boundaries parameters of the said region of interest are determined relatively to the image acquired or relatively to anatomic markers or to external markers previously defined; the said region of interest being automatically determined for each MRI image of the sequence of MRI images and in each following image acquisition of the follow up method; the mean intensity of the image data within the said Region of interest being used as a time dependent perfusion measure at the time of acquisition of the corresponding image used to construct the time dependent perfusion function.

126. A method for carrying out a follow up of the disease activity of the pathologic conditions of an anatomic district of a body by means of contrast media perfusion measurements in the said anatomic district comprising the steps of a) generating a database of perfusion curves each one univoquely associated to a well defined degree of disease activity; b) the said database being generated by acquiring at least one image of the anatomic district by means of MRI along at least one slice or one section plane of the anatomic district in patients or a three dimensional MRI image of the anatomical district in patients having a known degree of disease activity; c) for each patient having a well defined degree of disease activity a sequence of MRI images is acquired which sequence comprises a certain number of MRI images taken at different times one of the other within a certain period of time; d) the said period starting immediately after or at the injection of a contrast medium in the anatomic district and terminating after a certain time determined as a typical duration of contrast media perfusion in the anatomic district; e) determining for each image or for a selected region of each image, which selected region is identical for each image or refers to an identical part of the imaged anatomical district under examination the mean intensity of the image data acquired; f) constructing an empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition; g) graphically representing the function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said image; h) determining the disease activity in the same anatomic district of a patient having an unknown level of disease activity by carrying out the steps of injecting the said contrast media in the anatomic district of the said patient and by acquiring the sequence of MRI images of the anatomic district for the predetermined period of time and finally constructing the empiric time dependency function of the mean intensity by means of the data pairs consisting of the mean intensity of each image or of the part of each image and the corresponding time of acquisition and graphically representing the function describing the said empiric time dependency by drawing a curve passing through the points represented by each data pair consisting of the time of acquisition of the corresponding image and the mean intensity of the said image; i) visually comparing the graphic representations of the functions approximating the empiric time dependency function relating to the database in order to detect the disease activity level.

127. A method according to claim 126 characterized in that a follow up of the disease activity comprises the repetition at several different times of the steps h) and i) for determining changes in ^* the disease activity degree in time and during a therapeutic treatment.

128. A method according to claims 126 or 127, characterized in that a first MRI scout image of the anatomic district is acquired before injection the contrast media; a Region of Interest is defined on said image comprising or containing the image of an anatomic relevant object; the position and boundaries parameters of the said region of interest are determined relatively to the image acquired or relatively to anatomic markers or to external markers previously defined; the said region of interest being automatically determined for each MRI image of the sequence of MRI images and in each following image acquisition of the follow up method; the mean intensity of the image data within the said Region of interest being used as a time dependent perfusion measure at the time of acquisition of the corresponding image used to construct the time dependent perfusion function.