Device for diagnosing neurodegenerative diseases

FIELD: medicine.

SUBSTANCE: invention relates to means for diagnosing neurodegenerative diseases. Device contains module of obtaining images which receives visual data about patient's brain state, and image analyser, made with possibility of determining quantitative index, which shows degree of development of neurodegenerative disease of patient's brain on the basis of visual data with application of probability mask for determination of studied areas on the image, specified by visual data. Method of clinical assessment includes stages of obtaining visual data and their analysis for determination of quantitative index, which makes it possible to assess degree of development of neurodegenerative diseases of patient's brain with application of probability mask. Software carrier contains computer programme, settings of data processing device for its performance of at least one of method stages.

EFFECT: invention facilitates early diagnostics and control of neurodegenerative diseases, for instance, Alzheimer's disease.

25 cl, 8 dwg

 

The SCOPE of the INVENTION

This invention relates to diagnostics of neurodegenerative diseases. In particular, this invention relates to a device and methods for visual analysis of data on the condition of the brain for the diagnosis of neurodegenerative diseases such as Alzheimer's disease (AD).

BACKGROUND of the INVENTION

It is known that neurodegenerative diseases such as Alzheimer's disease, is difficult to accurate diagnosis in vivo. For example, despite the ability to identify people who have a genetic predisposition to develop Alzheimer's disease [1, 2], often the only possible one is the formulation of a preliminary diagnosis based on the data obtained in the laboratory, clinical data and more recent studies of the brain image, when some characteristic symptoms become obvious to experienced clinical specialists.

To facilitate setting the preliminary diagnosis of Alzheimer's disease has been used in various ways. These methods include detecting various tests, such as, for example, optical test, developed by Newman [3]in which to detect the reduction in the number of ganglion cells in the patient's eye due to the development of Alzheimer's disease using optical is reamy.

Such methods preliminary diagnosis are very useful. Recently, however, there is increasing evidence that the pathological process of Alzheimer's disease may begin long before the possibility of carrying out any of these diagnostics, the so-called pre-clinical stage of the disease. The specified pre-clinical stage can be divided into two main phases: an initial latent phase", in which there are no visible symptoms, and the subsequent "prodromal phase", in which there are some symptoms which are insufficient for setting the preliminary clinical diagnosis.

Have been made various attempts to provide diagnosis at an early stage of the disease by identifying the various symptoms of pathological processes during the course of these two pre-clinical phases. To date, we used two main methods of detection of abnormalities that may be associated with early stage Alzheimer's disease, namely: a) magnetic resonance imaging (MRI) and functional magnetic resonance imaging (FMRI) of the brain [4, 7], and b) assessment of metabolic changes in the brain by controlling the absorption of radioactive18F-2-fluoro-2-deoxy-D-glucose (FDG) using scanner positron emission tomography (PE who) [2, 5, 6].

Although such methods facilitate the diagnosis of Alzheimer's disease, they only detect the secondary symptoms of the disease, and therefore there is a need to create an improved method for rapid and accurate evaluation of patients with ensuring the detection of Alzheimer's disease in all three stages: pre-clinical phase, at a stage of preliminary diagnosis and final diagnosis. The use of such a method is especially important in the preclinical phase, when early diagnosis and treatment can help prevent or slow its progression. In addition, there is also a need for a more qualitative assessment of the development of Alzheimer's disease, including response to treatment, on all three phases of the disease.

The INVENTION

In various aspects and versions of the present invention proposed tools for the diagnosis and monitoring of neurodegenerative diseases of the brain (such as Alzheimer's disease)which do not have the above disadvantages of the prior art.

In accordance with the first aspect of the present invention has been proposed to install for the clinical assessment of the current state of a neurodegenerative disease of the patient. This system includes a module for retrieving images, which is performed in the possibility of obtaining the image data of the brain state of the patient, and the Image analyzer, which is designed with the ability to determine on the basis of the image data of the quantitative index indicating the degree of development of neurodegenerative diseases of the brain of the patient.

In accordance with the second aspect of the present invention, a method of clinical assessment of the current state of a neurodegenerative disease of the patient. This method includes obtaining image data of the brain state of the patient and their analysis to determine them on the basis of some measure. This parameter allows you to assess the current state of neurodegenerative diseases of the brain of the patient.

In accordance with a third aspect of the present invention proposed a computer program product containing a computer program that is executed with a possibility of setting processing unit with the capability of performing at least one stage of different ways in accordance with aspects and variants of execution of this invention.

The advantage of the facilities, methods and computer program products in accordance with these aspects of the present invention is the fact that this metric is an exact value (e.g., numerical value)that can use the change health workers to facilitate diagnosis. Thus, this quantitative indicator can be used to detect the presence of various symptoms of neurodegenerative disease, but also to indicate its severity. In addition, because the specified indicator is quantitative, it can also facilitate the tracking of clinical specialists any changes in the condition of the patient at various time intervals, resulting in similar installations, methods and computer program products can be used to monitor the development of any disease (for example, deterioration/remission), effectiveness of treatment, etc.

BRIEF DESCRIPTION of DRAWINGS

Below is a description of the various aspects and embodiments of the present invention with reference to the accompanying drawings, in which:

figure 1 depicts the setup for the clinical assessment of the current state of a neurodegenerative disease of the patient in accordance with one embodiment of the invention,

figure 2 illustrates the method for the clinical evaluation of the current state of a neurodegenerative disease of the patient in accordance with different variants of carrying out the invention

figure 3 illustrates the sequence of actions, including the various ways in accordance with aspects of the invention,

figure 4 illustrates the standardization of the data positron emission tomography (PET) using a sample of magnetic resonance imaging (MRI) of the patient, smoothed with the use of the anisotropic filter

figure 5 illustrates the identification of diagnostic features using the ratio of gray and white substance of the brain in accordance with one embodiment of the invention,

figa illustrates the use of the intensity profile of an image taken from a patient suffering from Alzheimer's disease, as a diagnostic characteristic in accordance with one aspect of the invention,

fig.6b illustrates the use of the intensity profile of the image, taken from a healthy patient as a diagnostic characteristic in accordance with one aspect of the invention,

figa shows a three-dimensional image of the results of the survey of the study area brain and measuring the ratio of gray and white substance of the brain, obtained in accordance with one aspect of the invention,

fig.7b shows the graphical representation of the results of the analysis of the intensity profile of the brain, obtained in accordance with one aspect of the invention,

figs shows the graphical representation of the results of the analysis on the basis of the elements of three-dimensional images obtained in accordance with one aspect of the invention,

figa shows a three-dimensional image analysis profile intensives who and the brain of the patient, Alzheimer's received in accordance with one aspect of the invention, and

fig.8b shows a three-dimensional image analysis of the intensity profile brain healthy patient who is not suffering from Alzheimer's disease, obtained in accordance with one aspect of the invention.

DETAILED description of the INVENTION

Figure 1 shows the installation of 100 for the clinical assessment of the current state of a neurodegenerative disease of the patient in accordance with one embodiment of the invention. This facility contains 100 device 120 data with interfaces 123, 126, module 122 imaging and analyzer 124 images. These interfaces 123, 126, module 122 imaging and analyzer 124 images can be logically combined using a bus 125 data and controlled by a Central processor (not shown).

The device 120 data provided the first universal interface 126, intended for communication specified device 120 with external components. In this embodiment, the external components include: channel 127 transmission input connected to the device 128 user input (e.g. mouse/keyboard etc), channel 143 transmission of network data connection is connected to the Internet 142, and channel 129 data on a display connected to the display 130. In addition, the universal interface 126 also includes a graphical interface 123 user (GUI)through which the user installation 100 may enter data, commands, etc. and to receive visual information, watching the display 130.

The ISU 123 can be used to create two - and/or three-dimensional images of at least part of the brain of the patient. In such images the brain areas can be highlighted in different colors depending on the degree of absorption of their nutrients. This facilitates visual perception of the data users install 100. In addition, in various embodiments, the execution, the user can also rotate the flat image and/or slices of volumetric images by controlling the ISU 123 using device 128 input.

The ISU 123 can also be used to convert data from a tabular form in a three-dimensional image. For example, the user can mouse-click on the data values displayed in the table to highlight the corresponding area of the image to the brain, or Vice versa. This allows for fast access to the quantitative indicators of the displayed image.

In various embodiments, the execution unit 120 of the data processing which may be equipped with a universal computer, for example, a personal computer (PC). The specified computer can use the software modules providing module 122 imaging and analyzer 124 images, and therefore, can be accomplished by upgrading existing equipment with a software update. For example, the software product 144 containing a computer program may be transferred from a remote server (not shown) via the Internet 142 to the device 120 data channel 143 data.

Install 100 also contains an additional scanner 140 positron emission tomography (PET), connected to the device 120 data using channel 131 data. The scanner 140 and/or database data 132 may be accomplished by transmitting the image data module 122 retrieving images. For example, in the absence of a PET scanner, the image data can be transmitted from the database 132, which can store image data obtained previously. These data can be generated remotely from the installation of 100 (for example, in a remote medical facility, etc. where the device forming the image data) and then move into the base 132 of the data, where they can be re-extracted by the module 122 retrieving images. The specified module 12 can optionally be used to transfer the image data, obtained by the scanner 140, the base 132 of the data for backup.

The specified analyzer 124 images can be used for determining on the basis of the image data of the quantitative index indicating the degree of development of neurodegenerative diseases of the patient. This quantitative indicator can represent a numerical Value that is determined from a set of image data, the normal state on the basis of the presence of anatomical and/or chemical changes. In a preferred mode of operation the analyzer 124 image uses image data obtained from the PET scanner 140, to determine on the basis of their quantitative metric by determining the concentration of amyloid plaques in the brain of the patient. Graphic display of concentration of amyloid plaques in human brain represents one of the promising ways to determine the parameters that are directly associated with the pathological process of Alzheimer's disease, resulting in methods of quantitative evaluation of the image data for the presence of amyloid is very important.

Determination of amyloid, such as β-amyloid, is especially important for the diagnosis of Alzheimer's disease and monitor treatment effectiveness. Currently developed p the radioactive label to display the presence of amyloid using positron emission tomography or single photon positron emission tomography, and one aspect of this invention relates to automated data analysis of these surveys. In addition, this aspect of the method may also simplify the process of obtaining data with the possibility of using a simpler Protocol for transmission and, thus, reduce the time required to obtain a quantitative measure indicating the degree of development of neurodegenerative diseases by reducing the time of obtaining the data required for different ways of providing multiple images.

Despite the fact that the installation of 100 preferably operates using at least one mode in which revealed the presence of amyloids for analysis of their content in the brain, it should be understood that the unit 100 is not limited to this mode. For example, to different modes of operation of the plant 100 may include the following modes and their combinations: PET visualization of the content of amyloids, FDG visualization of metabolic changes in the brain, MRI and FMRI of the brain, etc. Such regimes and, in particular, their combinations can be used to provide more accurate visualization and, therefore, more accurate quantification, for example, due to the time required for obtaining the image data, processing itd, when any necessary clinical application installation 100.

Figure 2 illustrates the embodiment of the method 200 clinical assessment of the current state of a neurodegenerative disease of the patient. The method 200 may be implemented using various embodiments of the proposed device, such as, for example, installation of 100, depicted in figure 1.

Method 200 includes step 220 receiving the image data on the state of the brain. The specified step can include receiving image data, for example, from the storage device, or may include performing positron emission tomography at least part of the brain of the patient. In the latter case, the patient can be entered the substance representing radioactive label. For example, a radioactive label may contain chemical structural element that selectively bind to the amyloid protein, such as radioactive drug from the family of radioactive labels GE® Pittsburgh compound B (PiB), described in international publications WO 02/16333 and WO 2004/083195, or radioactive label FDDNP (2-(1-{6-[(2-[18F]fluoroethyl)(methyl)amino]-naphtyl}ethyliden)malononitrile) and its analogs, are described in international publication WO 00/10614. Thus, quantitative indicators can be defined on the basis of the concentration of AMI is oidov in the brain of the patient, that facilitates the diagnosis of neurodegenerative diseases.

The method 200 includes the step 240 analysis of visual data, and step 260 to determine the quantitative indicator. The combination of steps 240 and 260 can be performed using various methods, some of which are described in more detail below. For example, at step 240 the analysis of visual data can perform at least one of the following: the definition of control areas of the image based on the image data, determining a quantitative measure based on the absorption of a substance as the relationship of the degree of absorption in the gray matter of the brain to the degree of absorption in the white matter of the brain, determining a quantitative measure as to the degree of change of the amount of visual parameter in the selected projection brain etc.

In various embodiments of method 200 for maximum utilization of the obtained graphic data used in the analysis of scanning by positron emission tomography, put the preliminary diagnosis. For example, if the PET scanner with it can be performed anatomical standardization. If data are available positron emission tomography/computed tomography can be used a device for computer tomography. This scheme helps to ensure the highest cost is Y. the accuracy obtained in the survey information. The following is a more detailed description of this method.

Figure 3 illustrates the sequence 300 that includes various methods 320, 350, 380 in accordance with aspects of the present invention. For example, at least one of the methods 320, 350, 380 can be performed by setting 100, depicted in figure 1, or may be a step of the method 200 illustrated in figure 2.

In the first aspect of the sequence of method 300 320 receiving the base of the normal image data (BNVD). Such BNVD used to specify the number of control data, which can then be used to identify physiological, chemical or anatomical abnormalities that may indicate the presence of neurodegenerative diseases. Specified BNVD can be created once, for example, in the Central medical facility and then distributed or can be created for at least one installation on the basis of testing healthy patients.

In various embodiments, the execution of the invention BNVD can constantly replenished by scanning a specific area of healthy patients to improve the accuracy of the data in the specified database. Such data can be directed to several plants located in different places, to enhance the overall accuracy of the data in BNVD. Uh what about the particularly important if, for example, in a small hospital there is a setting made in accordance with one of the embodiments, but there is a large number of patients and, therefore, the possibility of creating local statistically useful BLVD.

Scanning a large number of patients, and making the received data in BNVD can be performed on the stages 322 and 322'. For clarity, shows only two stages 322 and 322' scan, but it is clear that N can be any positive integer and preferably is the maximum possible number required to obtain optimized BLVD.

Processing the image data received from the scanners at the stages 322 and 322', perform on stage 324. Processing the image data includes the following three stages: 1) anatomical standardization, 2) normalization of the intensity and 3) identification sign. Below in the relevant sections describe the different ways of performing the above three steps.

Anatomical standardization

The purpose of anatomical standardization (sometimes also called spatial normalization is to transform the data of different patients in the standard anatomical space, such as, for example, stereotaxic (Talairach) space or space Tits (Montreal Neurological Institute). Anatomical standardises the Yu is performed by a spatial transformation of the first set of images (which may be referred to as a free image), ensuring its alignment with the second set of images (which may be referred to as reference image). In most cases, the conversion is performed by an iterative matching for maximum gain some similar characteristics convert free image and a corresponding reference image. The search for a suitable transformation typically involves the use of an optimization algorithm. The conversion type and the number of parameters determine the accuracy of anatomical standardization. In the General case, the execution of anatomical standardization using anatomical images with high resolution (for example, the received magnetic resonance imaging (MRI) can be performed with higher accuracy than when using the functional images obtained using positron emission tomography or single photon positron emission tomography.

Anatomical standardization allows for direct comparison of data of different patients, as each individual anatomical structure is located in a standardized space in the same place. Anatomical standardization also provides the ability to create the normal image data and use pattern of the study area brain for automatic quantitative assessment of the degree of Pogos is of different areas, for example, with the introduction of the patient radioactive labels.

Precise anatomical standardization is important, and in General the process can be made more accurately when combined anatomical image and the PET image data. However, because of the anatomical images are not always available, it is important to have a method that provides the ability to perform precise anatomical standardization with the direct use of PET data. Therefore, it may apply the method of automatic selection of image analysis depending on the class/classes of image data, as described above. This choice can include the following steps:

a) When data are available, magnetic resonance imaging of the patient they are registered together with the data from positron emission tomography. MRI image of spatial normalize by applying fuzzy reception, which maximally increases similar characteristics between these PET patient and sample data PET in a standardized space. The result is a transformation in which PET data are displayed in a standardized space. The specified transformation performed in the previous step is then used to transfer the PET scan in standardized space.

b) In the absence of data magnetic resonance imaging of a patient PET data obtained by the joint use of positron emission tomography and computed tomography, as a rule, be ready for registration. However, this assumption is checked, and if the image data is not standardized, the visual data of computer tomography register together with the visual data PAT. The acquired image data of computer tomography spatial normalize by applying fuzzy reception, which maximally increases the similar characteristics between the data computed tomography of the patient and the sample data in a standardized space. The result is a transformation in which data of computer tomography are displayed in a standardized space. The specified transformation, carried out in the previous step is then used to transfer the image data of PET scanning in standardized space.

(C) if the only available visual data in positron emission tomography, their spatial normalize by applying fuzzy reception, which maximally increases the similar characteristics between the PET data and the sample data in a standardized space. In the case of analysis of data on amyloid is m (for example, using Pittsburgh compound B (PiB)) there is a characteristic contrast of the sample image data when comparing brain images of a patient affected by Alzheimer's disease, with images of the brain of a healthy patient. This can lead to systematic errors when using standard methods anatomical data standardization PET. In addition, analysis of the data on amyloid particularly important to accurately allocate space around the control area (see below). To overcome these difficulties, use the following method. As a sample use data magnetic resonance imaging of the brain of the patient is transferred into the space of Tits (see, for example, figure 4). To reduce the risk of obtaining local minima of a function of comparing the reference sample was treated with an anisotropic filter, which smoothes the sample by maintaining the boundaries of the tissues.

For data logging PET data regarding the specified pattern using the comparison function based on normalized mutual information. The specified registration is performed in two stages. At the first stage of PET data generally recorded on the sample using a polynomial transformation with 18 settings. At the second stage performs a local registration data control around the area. The bounding rectangle formed by the inner and outer surround contours (parallelepiped, sphere, or body of irregular shape), have around the control area, and then perform local registration data within the internal volume of the circuit using a simple transformation. The data in the area between the outer and inner surround interpolate contours to ensure a smooth transition from data within the bounding rectangle to the data outside of this rectangle. This method provides in General a qualitative examination of the brain of the patient at increased data accuracy near the control area (i.e. inside the bounding rectangle). Figure 4 shows the bounding box 410 to control the area around Valieva bridge should be understood, however, that can be used in other areas (e.g., the cerebellum).

It should be noted that the sample used in step (b)may be built on the basis of data from magnetic resonance or computed tomography, while the sample used in step (C), based on data of magnetic resonance imaging. Used registration methods can be based on maximum gain similar characteristics, including the use of correlation, General information, n is melisovonos General information and transformation for the spatial normalization of the data, including, for example, affine, polynomial, discrete cosine transform (DCT), etc.

Normalization intensity (control area)

To enable visual comparison of data from different patients, to assess the validity of the entered medications, weight changes patients and so the data may be normalized in intensity. One possible way is the normalized data according to the degree of absorption in the region, presumably not affected identify neurodegenerative disease.

In different versions of the present invention in the image, a given visual data, allocate control the area over which it is necessary to determine the degree of development of neurodegenerative diseases of the patient. The control region may, for example, correspond to a small area of the brain, such as, for example, varolii bridge, thalamus, cerebellum, and so on, the Use of such a relatively small control areas increases the need for clear definitions.

For example, when analyzing for the presence of amyloid (e.g., using compounds C11-PIB) as a control area can be selected area of the gray matter of the cerebellum. As a rule, the specified area note manually on the image obtained by magnetic resonance tomogra the AI. However, in the case of an automated method to control the area must be defined in a standardized space. To accurately perform this step can also be used to mask the maximum probability. The following is a description of examples: a) obtaining a mask and (b) the use of the mask.

a) creating a probabilistic mask for the control field.

The mask of maximum probability of gray matter brain perform in accordance with the following method: 1) image data of a magnetic resonance tomography and positron emission tomography N patients jointly register, 2) the specialist selects the control region of the cerebellum in co-registered MRI data, 3) all data is transferred in a standardized space using the above-described method, and 4) for each element of the three-dimensional images are probabilistic graph showing the probability of the presence of this element in all control areas of these N patients. Thus, the volume element of the image, which is part of the control area for all patients assigned a numerical value of 1.0; the volume element of the image, which is part of the control area for all patients except for one, assign a numerical value (N-1)/N, and d A similar approach is used in relation to other control areas to ensure the creation of the standard probabilistic masks control areas, such as, for example, varolii bridge and subcortical white matter of the brain.

b) Use a probabilistic mask inspection area to ensure the normalization of the data by intensity: this mask is used in the following way: 1) the mask used to anatomically standardized visual data, positron emission tomography, 2) calculate the average value of the volumetric image element of all such elements is limited to the specified mask, and the relative weight of the volume element of the image set on the corresponding probability value in the mask, and 3) the overall image is divided in accordance with the calculated average value. Thus have a comparative image, resulting in the absorption of radioactive labels are normalized relative to the control area.

It should be noted that the use of such probabilistic masks in combination with anatomic standardization, which is done with high accuracy in the area around the control, allows accurate determination of the control values and, therefore, increases the accuracy of the comparison on the basis of the scan data.

Vyyavleny the characteristic

In order to identify characteristic is the identification information specific to the diagnosed neurodegenerative diseases. Different dimensions (or features) are optional and may be used to provide diagnostic information, accurate measurements for continuous analysis, as well as to improve the visual interpretation of visual data.

To determine the required characteristics may be used various ways, four examples of which are described in more detail below:

a) To determine the relationship of the analyzed brain areas to the control data area can be divided into the study area. For example, using a method that includes the following steps: 1) application of Atlas investigated the brain regions for comparative image (i.e. the scan result, anatomically standardized and normalized intensity), and specified the Atlas displays such anatomical region as the frontal lobe of the brain, the field Brodmann, etc. and 2) evaluation statistics for the different studied areas identified using the Atlas. Atlas of the studied areas of the brain can be saved in various formats, for example, as noted in the volume or shape. Between the C specified satin and data in a standardized space must be compliance. In the simplest case, such a correspondence is single-valued, so that each volume element of the image in the marked volume corresponds to the volume element image in a standardized space. Any part of the Atlas study area can then be reflected in the image quality in a standardized space, and various parameters of all elements of the volumetric image can be computed as average, probable and standard deviation values of the volumetric image elements that are limited to a specified study area.

b) it Should be noted that PET data on amyloids are usually different depending on whether the patient suffers Alzheimer's disease or not. Positron emission tomography amyloid plaques of a patient suffering from Alzheimer's disease, shows high signal in the region of the cerebral cortex, while in healthy patients, a high signal is evident in the area of the white matter, and low in cortical areas. In this regard, the most suitable criterion for data analysis for amyloid in the study area is the ratio of gray and white substance of the brain. This can be done by: 1) using satin investigated the brain regions for comparative image (i.e. the scan result, anatomically with ondertiteling and normalized intensity), moreover, the specified Atlas displays such anatomical region as the frontal lobe of the brain, the field Brodmann, etc. and, in addition, displays the gray matter of the brain and white matter of the brain, 2) determine the extent of absorption of gray matter for such regions as the frontal lobe of the brain, taking into account only the volumetric image elements, the limited study area and the mask of the gray matter of the brain, 3) determine the degree of absorption of the white matter for the same regions taking into account only the volumetric image elements, the limited study area and the mask of the white matter, and 4) calculated as the ratio of gray and white substance brain for each study area.

In different versions of the numerical value is defined as the ratio of the amount of substance absorbed gray matter of the brain, to the amount of the substance absorbed by the white substance of the brain. Absorbed by the substance may be any substance, the content of which is changed with the appearance of neurodegenerative diseases, for example, radioactive18F-2-fluoro-2-deoxy-D-glucose (FDG) for PET imaging of amyloid radioactive labels for PET imaging, etc. One advantage of this method is the lack of red is the necessity to normalize the control field.

One way to use such a ratio of gray and white substance of the brain the brain is described in more detail below with reference to figure 5.

c) Can be signs of intensity profile that is carried out, for example, as follows: 1) determine the number of surface points and axes passing through the normal to the surface in a standardized space, and indicate which of the areas under study Atlas (i.e. to which anatomical region) relates each specified point, 2) use a comparative image (i.e. the scan result, anatomically standardized and normalized intensity) to calculate the intensity profiles for the pre-specified study area along lines perpendicular to the surface of the brain (see, for example, figa and 5b), 3) calculate the characteristic describing the intensity distribution along each axis (one of these characteristics is a gradient indicating the degree of change of intensity on each axis), and 4) average calculated characteristics (for example, gradient values) for all axes within each study area with obtaining an average value that can be used to determine a quantitative measure indicating the degree of development of neurodegenerative b is Lesni patient.

In different versions of the specified metric is defined as the rate of change of the magnitude of the visual parameter in the selected projection brain. This provides the ability to detect the presence of neurodegenerative diseases, as well as its quantitative analysis for follow-up studies/tests/ scans of the patient.

One way of using such characteristics of the intensity profile is described in more detail below with reference to figa and 6b.

d) Can be used in signs, based on the properties of the elements of the volumetric image. One such method is based on the use of values as a diagnostic indication of the intensity of the elements of three-dimensional images of the whole brain or items that are restricted anatomical areas, specified by the Atlas regions.

e) In the case of data on amyloid preferable to combine the derived characteristics in one "amyloid index. This can be done by calculating the weighted average values of the studied areas calculated in the analysis of these areas and/or the analysis of the intensity profile, and dividing these values by the corresponding value of one or more of the control areas.

After determining the image data for the normal image data (NVD), performed using at least one of the above methods, the normal image data remain in the database 326 data with various statistical information such as, for example, average values and variances of calculated parameters for patients from different age groups.

Figure 3 also illustrates the second aspect of the sequence 300 of action, in which the method 350 clinical evaluation of neurodegenerative disease patient by calculating on the basis of the image data of the quantitative index indicating the degree of development of any neurodegenerative diseases of the brain of the patient.

The method 350 includes the step 352 scan of the patient. This scan can be one or more of the following: positron emission tomography, magnetic resonance imaging, computed tomography, etc. In one of the preferred modes of this scan includes positron emission tomography for determination of amyloid in the brain of the patient. Visual information obtained by scanning (scans), the process at step 354, ensuring detection of clinically important information. For example, at step 354 on the basis of the image data can be calculated metric. On this the e 356 result, obtained in step 354, compared to the indicator of a healthy patient to identify deviations, indicating that the patient has a neurodegenerative disease. The result of this comparison are at the stage 358, then at step 360 a report is made.

In the illustrated example, at step 354 may be used in any of the ways described above in connection with step 324 create BLVD. However, to a person skilled in the art it is obvious that the aspects and embodiments of the present invention that is not limited.

For comparison of the detected signs of scanning 352 data BLVD at step 356 may be used various ways. One such method is performed by comparing the various diagnostic features, such as: a) the average value of the characteristics of the studied areas compared with normal range, defined BNVD, and calculates deviations, including Z-indexes, b) the ratio of gray and white substance brain for each study area compared with the normal range defined BNVD, and calculates deviations, including Z-indicators) the characteristic values of the intensity profile corresponding to the properties of the intensity along each axis (the maximum intensity, maximum gradient and other signs), compared with the norm inim range, defined BNVD, and calculates deviations, including Z-scores and/or g) the data on signs, based on the properties of the elements of the three-dimensional image is compared with the mean and standard deviation, defined BNVD, and build image for the Z-score, and then make a group analysis of these data, and then groups that are smaller than the specified size are excluded.

The result of the comparison data of the scan data BLVD obtained in step 356, can be presented in step 358. Below figa-7C, 8A and 8b in two-dimensional and three-dimensional space illustrated examples of such comparison. Of course, for additional identification of any deviations identified in the scan result, indicators of a healthy patient, such results can be presented in color.

In one of the embodiments using characteristics of the studied areas, or the ratio of gray and white substance brain data are in tabular and graphical form with the rendered image the brain in a standardized space and designation of the boundaries of the areas under study. Study area and/or gray/white matter of the brain highlighted in accordance with their value. In case of signs of the intensity profile of the decree of the data can be projected onto a plane, and their values are deferred on axis (maximum intensity, maximum gradient and other signs) (Figa and 8b), and/or data of the Z-indices of the characteristics of the intensity profile compared to normal data, projected onto a two-dimensional plane and three-dimensional image of the brain in a standardized space (figa-7C). In the case of signs, based on the properties of the volumetric image elements, image variance and charts Z-indices can also be reflected by overlaying data on magnetic resonance imaging.

In this embodiment also performs the step 360 report that can be saved for later use and/or transmitted to a remote facility (hospital etc) to study the workers concerned. The report may contain the following information: a) patient data, date, etc. b) the original image of the scanning of the patient, b) processed image showing the result, g) table dimensions (for example, the results for the studied areas) and the report, which stated, lie if the results are within the range of data for a healthy patient.

Figure 3 also illustrates the third aspect of the sequence 300 of action, in which the method 380 observations developed the eating of any neurodegenerative disease in a patient.

This method 380 further includes scanning 384 patient performed after a previous baseline scan 382. These scans can include one or more of the following: positron emission tomography, magnetic resonance imaging, computed tomography, etc., In one of preferred modes of this scan includes positron emission tomography for determination of amyloid in the brain of the patient.

As in step 350 diagnostic scan, visual information obtained by scanning (scans), the process at step 386, ensuring detection of clinically important information. For example, at step 386 on the basis of the image data can be calculated metric. At step 388, the result obtained at step 386, compared to the preceding baseline scan 382 to quantify the development of neurodegenerative diseases of the brain of the patient. The results of this comparison are at the stage 390, then at step 392 constitute the report. Method step 390 bringing results and stage 392 report can be similar to, respectively, the above steps 358 and 360 action sequences in the diagnosis.

In produced Luterana example, at step 386 can be used any way, described above in connection with step 324 create BLVD. However, to a person skilled in the art it is obvious that the aspects and embodiments of the present invention that is not limited.

At step 388 comparing the average value, obtained by scanning different regions, compared with the corresponding values obtained for basic scanning. Can then be calculated difference that compare with normal range, defined BLVD. When comparing relations, obtained by scanning different regions, and the corresponding values obtained for basic scanning, you can also use the ratio of gray and white substance of the brain. Can then be calculated difference that compare with normal range, defined BLVD. When comparing the values on each axis (the maximum intensity, maximum gradient and other signs), obtained by scanning different regions, and the corresponding values obtained for basic scanning, may also be used the characteristics of the intensity profile. Can then be calculated difference that compare with normal range, defined BLVD. When composing a differential image and statistical parametric maps, which provide increasing and decreasing values, can be used in signs, based on the properties of the elements of the volumetric image.

Figure 4 illustrates the registration data of positron emission tomography for the presence of amyloid. Reference image (the bottom number) represents the image magnetic resonance imaging brain of one patient, defined in the space of Tits. The results of magnetic resonance imaging darken with use of an anisotropic filter, which smoothes the results within tissue with preservation of boundaries between tissues. Figure 4 also shows the data of positron emission tomography before (upper row) and after (middle row) anatomical standardization, and also illustrates the use of the bounding rectangle 410 with a two-stage registration.

Figure 5 illustrates the identification of diagnostic features using the ratio of gray and white substance of the brain in accordance with one embodiment of the present invention. Anatomical regions used in standardized space (e.g. space Tits) define the study area, and the mask 530 white matter of the brain and the mask 530 gray matter of the brain. A separate study area, shown in figure 5, corresponds to the anterior frontal lobe 520 brain.

<> Quantitative analysis performed as follows: the study area 520 of the anterior frontal lobe and the mask 530 white matter brain combined with the logical "And" to ensure that the study area, covering only the area of the white matter of the frontal lobe 535. New study area included in the image data 550 and is used to identify values for white matter in the frontal lobe. Similarly the study area 520 of the frontal lobe and the mask 540 grey matter of the brain combined with the logical "And" to ensure that the study area, covering only the area of the gray matter of the frontal lobe 535. This study area included in the image data 550 and is used to identify values for gray matter in the frontal lobe. These two values are then brought together to see the ratio of gray matter to white matter brain in the frontal lobe, and a rectangular chart 560 illustrates the distribution of these relations between patients suffering from Alzheimer's disease (ad)and healthy patients (RFP). To a person skilled in the art it is obvious that the area of white and gray substances the brain is not necessarily calculated in accordance with the above method, for example, the study area gray veshestva white matter well can be imposed using the interactive method of obtaining the study area grey and white matter.

Figa illustrates the use of the intensity profile of an image taken from a patient suffering from Alzheimer's disease, as a diagnostic characteristic in accordance with one aspect of the invention.

Fig.6b illustrates the use of the intensity profile of the image, taken from a healthy patient as a diagnostic characteristic in accordance with one aspect of the invention.

In this embodiment of the proposed method using the image of a healthy brain in a standardized space (e.g., imagine) and all elements of the volumetric image facing to the rear background, consider superficial. Coordinates (x, y, z) of all surface elements and surfaces, held normally in a specified location, is recorded in the list of surface points. In addition, comprise a sheet of labels, consistent with the list of surface points and identifying a specific point of the surface one way or another anatomical region. Thus, each row of the list of surface points corresponds to a row in the list of labels, which indicates the identity of this point one way or another anatomical region. A compilation of several lists provides the ability to track multiple facilities (dot surface may, for example, belong to both left isvi the ine brain and the left frontal lobe).

When the image analysis, it must first spatial normalization to the point on the surface, the coordinates of which are defined in the list of surface points correspond to points on the surface of the brain in the analyzed image. Then this list of points on the surface of the step by step process and for each point in the negative direction normal to the surface of the build intersecting the axis 620, 640. This axis runs in the transverse direction from the point on the surface (or even a little beyond the boundaries of the surface to improve the accuracy of the method), and the values along the specified axis, record and save in the array when moving along the axis to the brain. These data along the axis of the re-selected, the distance between the points along the axis, and the maximum distance of implementation in the brain, are editable parameters. The above procedure is performed for each point to obtain the intensity profile 625, 645 along the axis recorded in the form of a data array. Then make an analysis of the intensity profile and the identification of diagnostic features. In one embodiment of the invention as a diagnostic sign of use maximum gradient, computed as the deviation between two points located at a given distance is I. In another embodiment, the invention calculates the maximum intensity along the axis. In yet another embodiment, the invention calculates the relationship between two points located at a given distance along the axis. For specialists in the art it is obvious that can be calculated and other parameters of the intensity profile.

Figa shows a three-dimensional image of the results of the survey of the study area brain and measuring the ratio of gray and white substance of the brain, obtained in accordance with one aspect of the invention.

Three-dimensional image of the brain labeled by color in accordance with the results obtained when the selected operation mode. In accordance with one aspect of the invention, the characteristics of the intensity profile, such as the maximum gradient, average across selected brain areas (e.g., frontal lobe), then the calculated average is compared to a database of normal image data to determine a Z-score. Z-scores for different areas of the brain can then be used for marking color three-dimensional images of the brain. To do this, use the appropriate color scale, providing the selection of areas with significant deviations from the norm, certain BLVD.

Figs shows the graphical representation of the results of the analysis on the basis of the elements of three-dimensional images obtained in accordance with one aspect of the invention. On the specified drawing shows the results of the analysis on the basis of the volumetric image elements.

Figa shows a three-dimensional image analysis of the intensity profile of a brain of a patient suffering more than the new Alzheimer's, received in accordance with one aspect of the invention. The intensity profiles calculated, as described above, i.e. a list of points on the surface of the step by step process and for each point in the negative direction normal to the surface of the build intersecting its axis. Data along the specified axis re-select and calculate the intensity profile. On the basis of the intensity profile to determine various characteristics such as the maximum value and the maximum gradient profile. The value at each point of the surface is then used for labeling the color of the corresponding points of the three-dimensional images of the brain using the preset color scale, which can be changed by the user. On figa shows the brain of a patient affected by Alzheimer's disease, studied by the method of maximum gradient.

Fig.8b shows a three-dimensional image analysis of the intensity profile brain healthy patient who is not suffering from Alzheimer's disease, obtained in accordance with one aspect of the invention. Principles of construction of such images is similar to the principles described with reference to figa.

Various embodiments of the invention can be implemented using at least one of the following is rest: hardware, software and/or firmware. In one embodiment of the invention, the native code can be represented in the form of software that can be used for improvements to the existing traditional installation with providing new functionality in accordance with various aspects and/or variants of execution of the present invention. The specified native machine code, or alternatively, may be made in the form of a computer software product, which may, for example, be provided through the media. Such media may, for example, to represent the signals transmitted via different transmission channels, for example, the Internet, wireless channel, an optical channel, line radio, e-channel, dedicated telephone channel/data channel, local/global network, etc. may be used for improvements to the existing installation and/or may, for example, be a computer program on traditional media, such as magnetic disk, magnetic tape, optical disk, semiconductor device, etc.

To a person skilled in the art it is obvious that some embodiments of the present invention can be used to improve existing facilities; special is the aliste in the art will also obviously some embodiments of the present invention can be implemented using the distribution system, in which various data processing units perform different functions. For example, in various embodiments, the execution module retrieving images can be embedded in the PET scanner and/or the processing unit may be part of a PET scanner.

Although the present invention is described in terms of several embodiments, those skilled in the art it is obvious that it is not limited to these options perform and there are various changes in the redistribution of descriptions and claims.

Links

1. Publication of the U.S. 2003/0233197, Carlos E. Padilla and Valeri I. Karlov.

2. Publication of the U.S. 2005/0283054, Eric M. Reiman.

3. Publication of the U.S. 2005/0094099, Richard W. Newman and Corinn C. Fahrenkrug.

4. Publication of the U.S. 2005/0197560, Stephen M. Rao and Catherine L. Elsinger.

5. Publication of the U.S. 2005/0215889, James C. Patterson II.

6. Publication of the U.S. 2005/0273007, Ziad Burbar.

7. International publication WO 02/101407, Nicholas Fox and Ilya Charles.

8. International publication WO 2006/083378, Vladimir Kepe, etc.

These sources if possible in full included in the description of this invention by reference.

1. Installation (100) for clinical evaluation of the current state of neurodegenerative disease patient that contains the module (122) received the I images, which is configured to receive visual data about the brain state of the patient, and the analyzer (124) images, which is designed with the ability to determine on the basis of visual data using a probabilistic mask to define regions in the image, given the visual data, a quantitative index indicating the degree of development of neurodegenerative diseases of the brain of the patient.

2. Unit (100) according to claim 1, containing the device (120) data, which provides the specified module (122) imaging and analyzer (124) images.

3. Unit (100) according to claim 1, additionally containing a scanner (140) positron-emission tomography, which is arranged to transmit the image data to the module (122) acquiring images.

4. Unit (100) according to claim 1, in which the analyzer (124) images is additionally configured to determine based on the image data of the specified measure by determining the concentration of amyloid plaques in the brain of the patient.

5. Unit (100) according to claim 1, in which the analyzer (124) images is additionally configured to determine the study area image, which is specified visual data and for determining the degree of development neurodegen is exploring the patient's disease.

6. Unit (100) according to claim 1, in which the analyzer (124) images is additionally configured to determine the specified measure as the ratio of amount of substance absorbed gray matter of the brain, to the amount of the substance absorbed by the white substance of the brain.

7. Unit (100) according to claim 1, in which the analyzer (124) images is additionally configured to determine the specified quantitative indication as to the rate of change of intensity of the image data in the selected projection brain.

8. Unit (100) according to claim 1, in which the analyzer (124) images is additionally configured to automatically select anatomical standardization and/or method of image analysis, depending on the class/classes of visual data.

9. Unit (100) according to any one of claims 1 to 8, containing a graphical user interface (123) of the user who performed with the possibility of creating three-dimensional images of the brain of the patient on which brain areas are marked by different color depending on the degree of absorption of their substance.

10. Unit (100) according to claim 9, in which the graphical user interface (123) of the user is further configured to convert the data from a tabular form in a three-dimensional image.

11. The method (200) clinical assessment of the current state of a neurodegenerative disease of the patient, includes step (220) receiving visual data about the brain state of the patient and the stage (240) analysis of the visual data to determine on the basis of these data measure (260), which allows us to estimate the degree of development of neurodegenerative diseases of the brain of a patient with this step (240) of the analysis of visual data includes the use of probabilistic mask to define regions in the image, the set of visual data.

12. The method (200) according to claim 11, in which step (220) receiving image data additionally perform positron emission tomography at least part of the brain of the patient.

13. The method (200) according to item 12, in which the patient is additionally administered the substance, which represents a radioactive tag, which may contain chemical structural element that selectively bind to the amyloid protein.

14. The method (200) according to claim 11, in which the metric is defined as the concentration of amyloid in the brain of the patient.

15. The method (200) according to claim 11, in which step (240) of the analysis of visual data to determine the specified metric as the ratio of the amount of substance absorbed gray matter of the brain, to the amount of the substance absorbed by the white substance of the brain.

16. The method (200) according to claim 11, in which step (240) and the aleesa visual data to determine the specified quantity as a rate of change of intensity of the image data in the selected projection brain.

17. The method (200) according to claim 11, which further automatically choose the anatomic standardization and/or method of image analysis, depending on the class/classes of visual data.

18. The method (200) according to claim 11, in which perform anatomical standardization in two stages, namely: registration of data in a shared database and specify the specified registration by applying fuzzy data recording in the field, limited internal and external volumetric circuits, while the final registration data are a combination of data obtained during the registration data in a shared database and fuzzy reception, and data between the external and the internal volume interpolate contours to ensure a smooth transition from data within locally refined the field to data in a shared database.

19. The method (200) according to claim 11, in which the anatomical standardization of data positron emission tomography for amyloid, and the results of the scan by magnetic resonance imaging brain of one patient receive the reference sample in a standardized space, and to optimize the use of mutual information or normalized mutual information.

20. The method (200) according to claim 19, in which the reference sample, the resulting scan is of by magnetic resonance imaging brain of one patient, process using anisotropic filter, which smoothes the specified pattern with maintaining the boundaries of the tissues.

21. The method (200) according to claim 11, which further calculates amyloid index by dividing the weighted average of values calculated for a number of anatomical areas, the corresponding value of at least one control area, and the specified value for each region are estimated using analysis of the study area and/or analysis of the intensity profile.

22. The method (200) according to any one of § § 11-21, which further creates a three-dimensional image of the brain of the patient on which brain areas are marked by different color depending on the degree of absorption of their substance.

23. The method (200) according to claim 11, which further comprise a report containing at least one of the following: an indication of the presence or absence of a neurodegenerative disease in a patient, this quantitative measure, a quantitative indication of the presence or absence of a neurodegenerative disease in a patient, patient data, date, time, images of the initial scan of the patient, the processed image of the results obtained using the method according to any of § § 11-21, table of measurements, the results for the study area is her amyloid index and report, which stated, lie if the results are within the range of data for a healthy patient.

24. Media (142) computer software product (144), containing a computer program that is configured to configure the device (120) data for one of the stages of the method (200) according to any one of § § 11-23.

25. Media (142) according to paragraph 24, wherein said carrier (142) represents at least one of the following: magnetic disk, magnetic tape, optical disk, an electronic signal, optical signal, a radio signal, and a semiconductor device.



 

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11 cl, 3 dwg

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