JP5061150B2 - Data processing method, image data processing apparatus, and computer program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method for solving the problems of a region method or a standard brain coordinate system statistical analysis method and displaying the image of the condition of each region in an organ such as the brain and heart of each person objectively and precisely. <P>SOLUTION: The method of image-related data processing is used for displaying a target part of an organ distinctively from other parts by an imaging processing device. The method includes the following steps. (1) The region to be distinguished from others in the organ is determined based on a standard organ atlas, and (2) the order of the region to be distinguished, determined by the process (1), is determined according to a condition for the imaging processing and the region border data is obtained. Next, (3) the organ to be observed is imaged and the observation data are obtained, and (4) the observation data are converted to standardized data by the anatomical standardization. Then, (5) the standardized data and the region border data obtained in the process (2) are combined and processed so that the condition of the target part in the organ is displayed. <P>COPYRIGHT: (C)2009,JPO&amp;INPIT

Description

  The present invention relates to an image-related data processing method using a medical image obtained by photographing an organ in a body, and more specifically, image-related data that is divided into a plurality of regions of an organ and performs imaging to display the status of each region. It relates to the processing method.

  In recent years, with the advance of medicine, there has been a remarkable progress in diagnostic imaging. An imaging diagnostic machine (X-ray CT, magnetic resonance imaging device (MRI), ultrasound diagnostic machine, radiological diagnostic machine) to capture the state of the body as an image without imposing a heavy burden on patients etc. Is indispensable in the current medical field. Image diagnosis using them is widely used as providing functional information such as early diagnosis of diseases, selection of treatment methods, prediction and determination of treatment effects, and the like.

  In the clinical field of nuclear medicine, single photon emission computed tomography (SPECT) and positron using a radioisotope (RI) into the patient's body and using gamma rays emitted therefrom Emission tomography (PET) is used by using each apparatus.

  In such a medical image processing apparatus, various programs are prepared so that various image processing such as image reconstruction and image analysis can be performed from collected data.

  In addition, a region of interest (ROI) is set in an image, and a statistic for the region of interest is calculated. For example, each part of the brain is set as a region of interest in a SPECT image obtained by photographing the head, and an average value or standard deviation of pixel values in each part of the brain is calculated and used for brain diagnosis. It has been broken. In addition, a left ventricular region is set as a region of interest in a SPECT image obtained by imaging the heart, and an average value or standard deviation value of pixel values in the left ventricular region is calculated and used for diagnosis of the heart. . In addition, a renal function test is performed in which an image taken using the kidney as a region of interest is analyzed using the renogram method.

  More recently, the brain image data of each patient is converted to the standard brain coordinate system standard brain chart, and then compared with the brain image database of normal subjects to more accurately and objectively identify the site of blood flow or metabolic decline. At present, it is being applied to clinical practice as a standard brain coordinate system statistical analysis method.

  Specifically, by matching each patient's brain image to the shape of a standard brain that can “identify anatomical positions by coordinates”, multiple brain images of different shapes are treated the same, and Comparison between each patient can be performed between the same pixels (three-dimensional voxels). Furthermore, it has become possible to objectively extract abnormal sites using a statistical analysis method by comparing the images of each patient with a normal database.

  As such a method, SPM method (Statistical Parametric Mapping) and 3D-SSP method (Three-Dimensional Stereotactic Surface Projections) are known, and these are active regions on PET images and functional magnetic resonance imaging (fMRI) images. Has been developed for the purpose of detecting cerebral blood flow, and has since been applied to the analysis of regional cerebral blood flow in SPECT images.

  The above technique is described in detail in the following documents, for example.

Friston KJ, Holmes AP, Worsely KJ, et al: Statistical parametricmaps in functional imaging; A general linear approach.Human Brain Mapping 2: 189-210 (1995) Minoshima S, Koeppe RA, Frey KA, et al: Stereotactic PET atlas of the human brain; Aid for visual interpretation of functional brain images.J Nucl Med 35: 949-954 (1994) Minoshima S, Frey KA, Koeppe RA, et al: A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET.J Nucl Med 36: 1238-1248 (1995) Clinical Psychiatry Course S10 Image diagnosis in psychiatric clinics (Nakayama Shoten)

  By the way, in the region-of-interest method, since the shape of each part differs depending on the patient, it is difficult to set the region of interest at exactly the same location when comparing the degree of accumulation at a certain part between different patients. There was a possibility of comparing different sites. Therefore, even the same analyst has a problem that the result is different by reanalyzing. That is, since the analyst subjectively sets the region of interest, it is difficult to set the anatomically correct position, and there is a risk of erroneous diagnosis only by different image analysts. This made it difficult to directly compare changes over time in a series of diagnosis / treatment flows of the same patient. Furthermore, since it is necessary to set a region of interest for each patient, it is practically impossible to set a detailed region of interest for the entire brain. There was a problem that it was not possible to evaluate.

  In addition, the standard brain coordinate system statistical analysis method analyzes all pixels (or voxels) of the image compared to the region of interest method, so that the entire brain can be targeted, and the difference in the results of the analysts There is an advantage that is not. However, when considering application in clinical diagnosis, there is a problem that this method is an n-to-1 statistical analysis using a plurality of normal data and one patient data. That is, in the case of the above method, it is necessary to collect a plurality of normal data and construct a standard brain database, which is the most important factor. However, it is ethically difficult to collect brain function image data of normal persons with unified diagnostic imaging equipment, collection conditions, and processing methods for each age and gender, and it is very difficult because it has an economic burden. There was a problem that it was impossible in ordinary facilities and general clinical hospitals.

  Therefore, it solves the problems of the above-mentioned region method and standard brain coordinate system statistical analysis method, and displays the state of each region in the organ objectively and accurately even for different individual organs (brain, heart, etc.) There was a need to develop possible methods.

  As a result of earnest research to solve the above problems, the present inventor determined a region to be distinguished in the organ based on the standard organ atlas, and the region was subjected to a certain imaging process. It is possible to display the state of the target site in the organ without individual differences by combining and processing the image data in the range predicted to be shown as the boundary and the image data standardized after imaging. The present invention has been completed.

That is, the present invention is an image-related data processing method for distinguishing and displaying a target region in an organ by an imaging processing device,
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The observation data is converted into data by anatomical standardization to obtain standardized data.
(5) Provided is an image-related data processing method characterized in that the standardized data and the region boundary data acquired in (2) are processed in combination to display the state of the target site in the organ. is there.

The present invention also provides an image-related data processing method for distinguishing and displaying a target site in an organ by an imaging processing apparatus,
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The region boundary data obtained in (2) is converted into corrected region boundary data by using the inverse operation for the operation used to convert the observation data into standard data by anatomical standardization (5) The present invention provides an image-related data processing method characterized in that the observation data and the correction area boundary data acquired in (4) are processed in combination to display the state of the target site in the organ.

  Furthermore, the present invention provides a program for causing a computer to execute the image-related data processing.

  As described above, according to the 3DSRT method of the present invention, the setting of the region of interest related to the organ, which has been performed manually in the past, is objectively performed three-dimensionally and automatically, and the region of interest with high accuracy is obtained. Detection became possible. In addition to the quantitative and easy visual evaluation of the cerebral circulatory state using numerical data, this method objectively evaluates pre- and post-operative circulatory reserves. It is possible to eliminate fluctuations between observers, between subjects and within subjects that could not be solved by the conventional ROI setting, which not only contributes to the convenience of diagnosis but also relates to the detected region of interest. Accurate diagnosis can be performed.

The drawing showing the origin and X, Y coordinates and slice number directions for obtaining imaging data from an anatomical standard brain. It is drawing which shows 3DSRT. In the figure, each number indicates a distinguished area. Eight areas 1 to 8 are cortical perfusion areas that are perfused from the same branch of the cerebral artery (1 is the corpus callosal marginal artery of the anterior cerebral artery, 2 is the central anterior artery of the middle cerebral artery (MCA), 3 is the central artery of MCA, 4 is the parietal artery of MCA, 5 is the angular artery of MCA, 6 is the temporal artery of MCA, 7 is the posterior cerebral artery, and 8 is the periapical artery of the anterior cerebral artery. Reference numeral 9 denotes a lens nucleus, 10 a thalamus, 11 a hippocampus, and 12 a cerebellar hemisphere. It is drawing which shows the protocol of RVR method. It is an anatomically standardized rCBF SPECT quantitative image at rest by 3DSRT of a patient with Alzheimer's disease (53-year-old woman). Drawing which contrasted (A) which is not combining 3DSRT, and (B) which was combined about a part (12 pieces of upper right sides) of a SPECT quantitative image of Drawing 4. It is a anatomically standardized rCBF SPECT quantitative image at rest by 3DSRT of a patient with Alzheimer's disease (73 year old female). It is a anatomically standardized rCBF SPECT quantitative image at rest by 3DSRT of an Alzheimer's disease patient (51-year-old female). As described above, in FIGS. 4, 6, and 7, the characteristic that the blood flow of the primary sensory motor area is maintained is recognized on both sides. It is a resting anatomically standardized rCBF SPECT quantitative image by 3DSRT of an 82-year-old woman (left putamen infarction) having a lesion limited to deep gray matter. It is a anatomically standardized rCBF SPECT quantitative image at rest by 3DSRT of a 63-year-old male (right thalamic infarction) having a lesion limited to deep gray matter. FIG. 3 is a resting anatomically standardized rCBF SPECT quantitative image by 3DSRT of a 51 year old male (CO poisoning) with a lesion limited to deep gray matter. In FIGS. 3A and 3B, the areas of reduced blood flow in the left putamen, right thalamus, and bilateral pallidus are in good agreement with the 3DSRT outline. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the patient 1 of Table 1 at the time of the rest before surgery which overlap | superposed 3DSRT. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the patient 1 of Table 1 before surgery and after Acz administration on which 3DSRT was superimposed. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the rest of the patient 1 of Table 1 after the operation of overlaying 3DSRT. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the patient 1 of Table 1 after the operation of superimposing 3DSRT and after Acz administration. From FIG. 4 above, a decrease in circulatory reserve before surgery and a significant improvement after surgery in slices 11 to 16 in the right primary sensorimotor area were observed. It is an anatomically standardized cerebral blood flow quantitative SPECT image of the patient 4 of Table 1 before and at rest, in which 3DSRT is superimposed. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the patient 4 of Table 1 before the operation on which 3DSRT was superimposed and after Acz administration. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the rest of the patient 4 in Table 1 after the operation of overlaying 3DSRT. It is the anatomically standardized cerebral blood flow quantitative SPECT image of the patient 4 in Table 1 after the operation of superimposing 3DSRT and after the Acz administration. From the above 4 figures, preoperative wide hypoperfusion and decreased circulatory reserve (Figures 14 and 15) and improvement after left carotid endarterectomy (Figures 16 and 17) in the left cerebral hemisphere were observed. .

  The method of the present invention is an image-related data processing method for distinguishing and displaying a target site in an organ from others using an imaging processing device. As an imaging processing device used in the present invention, In addition to single photon emission computed tomography (SPECT) and positron emission tomography (PET) using radiation, X-ray CT, magnetic resonance imaging (MRI), ultrasound diagnosis and the like are included.

  As a method for distinguishing and displaying a target site in an organ by using these imaging processing devices, for example, an organ having a three-dimensional structure is represented as a plurality of images such as a tomographic image, and the plurality of images are displayed. In general, there is a method that can grasp the internal state of an organ from the image of the image, that is, a method of expressing one organ two-dimensionally with a plurality of images, but is not limited to this, for example, numerical information before imaging or You may display by processing this.

  In addition, to display the target part separately from others, for example, the target part is surrounded by a line in the captured image, or the image of an unnecessary part is deleted from the captured image. This means that a part to be displayed is displayed or only a specific part is emphasized.

The method of the present invention includes the following steps:
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The observation data is converted into data by anatomical standardization to obtain standardized data.
(5) An image-related data processing method (hereinafter referred to as “first mode method”) including processing that combines the standardized data and the region boundary data acquired in (2) and displays the state of the target site in the organ. ") And the next step,
(1) Based on the standard organ atlas, determine the areas to be distinguished in the organ,
(2) Determine the boundary of the region to be distinguished determined in (1) so as to synchronize with the imaging processing conditions, obtain region boundary data,
(3) Imaging the organ to be observed to obtain observation data,
(4) The region boundary data obtained in (2) is converted into corrected region boundary data by using the inverse operation for the operation used to convert the observation data into standard data by anatomical standardization (5) An image-related data processing method (hereinafter referred to as “second mode method”) including processing the observation data and the corrected region boundary data acquired in (4) in combination to display the state of the target site in the organ. ) Is included.

  Since the first aspect method and the second aspect method differ only in (4) stroke and (5) stroke, the first aspect method will be described first, and then the second aspect method will be different from the first aspect method. Will be explained.

  In carrying out the method according to the first aspect of the present invention, it is first necessary to determine a region to be distinguished in an organ based on a standard organ atlas.

  Generally, organs are dominated by several arteries, and defects in these arteries cause troubles in each organ part. Therefore, the areas to be distinguished are generally distinguished according to the flow of the arteries. Although it is preferable to select a region, the present invention is not necessarily limited to this.

  For example, taking the brain as an example, it is preferable to use the standard brain atlas of the brain's stereotaxic coordinate system, Talairach, as the standard organ atlas, and the corpus callosum of the anterior cerebral artery supplying blood to the brain 8 of the peripheral artery, central anterior artery of the middle cerebral artery (MCA), central artery of the MCA, parietal artery of the MCA, angular artery of the MCA, temporal artery of the MCA, posterior cerebral artery, anterior corpus callosum artery It is desirable to set a region to be distinguished for each of the two dominant arteries. Further, if necessary, the lens nucleus, thalamus, hippocampus, bilateral cerebellar hemisphere, etc. in the deep gray matter can be set as regions to be distinguished.

  In addition to the standard brain atlas of Tarailach, the standard brain atlas includes MNI templates developed at the Montreal Neurological Institute and three-dimensional brain MRI images such as HBA (human brain atlas). It is also possible to use the one created based on. In addition to the arterial control area, the areas to be distinguished include the nerve distribution area distinguished according to the classification of cranial nerves, the anatomical area distinguished by anatomical structure, and the brodmann's area distinguished by cytostructuring (brodmann's area ) Etc. can also be used.

  Next, for the region to be distinguished in the standard organ atlas set as described above, the boundary of the determined region to be distinguished is determined so as to synchronize with the imaging processing conditions, and region boundary data is acquired.

  Here, determining the boundary region so as to synchronize with the imaging processing conditions means that each of three-dimensional regions assumed in the organ from a plurality of standard organ atlas displayed on the plane (generally included in the region). This means that the boundary of each region that each region will show will be determined if it is assumed that the actual organ was imaged under the imaging conditions. To do.

  Specifically, based on a large number of objective regions of interest (ROI) in an organ, the boundaries of each region may be created. For example, in the brain, many ROIs in the cortex and deep gray matter Originally, the boundary of each region is shown by showing these positions on a plurality of images on the assumption that they are imaged under the same conditions (slice thickness, slice angle, pixel size, etc.) as later described imaging. Region boundary data is obtained.

  On the other hand, an organ to be actually observed is imaged by a conventional method to obtain observation data, and the data is converted into data by anatomical standardization to obtain standardized data.

  As described above, an apparatus for imaging can use SPECT, PET, X-ray CT, MRI, ultrasonic diagnosis and the like. In addition, data conversion by anatomical standardization of this data is performed in order to eliminate individual differences in organ shapes for each subject. For example, anatomical standardization obtained from known statistical parametric mapping (SPM) It may be performed by.

  The standardized data obtained in this way is processed in combination with region boundary data created in synchronization with the imaging process, and displays the state of the target site in the organ.

  As this processing, image processing is generally used. Specifically, the region boundary data is superimposed on the standardized image data and the belonging region in the standardized image is displayed, and the standardized image data other than the predetermined region boundary data is used. For example, a process of displaying only a region including a target part, a process of emphasizing predetermined region boundary data in standardized image data, and the like. These processes can generally be performed using a computer, but more simply, an image showing a plurality of region boundaries is created from the region boundary data in a manner corresponding to the plurality of images from the standardized image data. It is also possible to create and use this as a template after printing on a plastic sheet, for example, and visually observe the correspondence between the target site on the standardized image and the region boundary. In addition, using standardized data and region boundary data, numerical data before imaging can be used to numerically display the state of the target portion.

  As a display method as an image, normal transaxial (TRANS AXIAL) display (displayed by a transaxial surface perpendicular to the human body axis), sagittal (SAGITAL) display (perpendicular to the human forehead surface, Formats are displayed in a sagittal plane that is parallel to the body axis), and coronal (CORONAL) display (also referred to as a coronal plane, indicated by a coronal plane that is parallel to both the forehead and body axes). It can be used, and may be displayed not only in two dimensions but also in three dimensions.

  On the other hand, the implementation of the method of the second aspect may be performed according to the method of the first aspect, but the region boundary data obtained as described above is used to convert observation data into standard data by anatomical standardization. Therefore, it is necessary to display the region of the target region in the organ by processing it in combination with the observation data by using the inverse operation expression for the operation expression.

  Here, the inverse arithmetic expression with respect to the arithmetic expression refers to an expression where x = 1 / a · X−b / a when the expression for converting observation data into standard data is X = ax + b. Using this inverse operation expression means that the region boundary data derived from the standard organ atlas that has been anatomically standardized is converted into corrected region boundary data corresponding to the subject, and imaging from the subject is performed. This means that it is possible to display the state of the target part in combination with the region boundary data without modifying the image.

  According to the method of the present invention described above, once the region boundary data corresponding to the standardized image data is acquired, the state of the target part in the organ can be displayed in an arbitrary manner, and the There are no individual differences between subjects in the display.

  Therefore, the method of the present invention can be conveniently used as an organ imaging method in the field of treatment.

  In order to easily implement the method of the present invention, a program for executing these procedures on a computer can be used.

That is, as a program for preferably carrying out the first aspect method, a program for sequentially executing the following procedures (1) to (4) is preferable.
(1) Create and store region boundary data of regions to be distinguished in a predetermined organ based on the standard organ atlas so as to synchronize with the imaging processing.
(2) Obtain and store observation data by imaging an organ to be observed.
(3) The observation data is converted into data by anatomical standardization and stored as standardized data.
(4) The standardized data and the region boundary data acquired in (1) are processed in combination, and the state of the target part in the organ is displayed as data.

Moreover, as a program for preferably implementing the second aspect method, a program for sequentially executing the following procedures (1) to (4) is preferable.
(1) Create and store region boundary data of regions to be distinguished in a predetermined organ based on the standard organ atlas so as to synchronize with the imaging processing.
(2) Obtain and store observation data by imaging an organ to be observed.
(3) The region boundary data obtained in (1) is converted and stored as corrected region boundary data using an inverse operation to the operation used to convert the observation data into standard data by anatomical standardization.
(4) The observation data and the modified region boundary data acquired in (3) are processed in combination to display the state of the target part in the organ.

  These programs may be recorded on a computer-readable recording medium, or may be incorporated in an imaging processing apparatus such as SPECT, PET, or MRI.

  EXAMPLES Next, although an Example is given and this invention is demonstrated in more detail, this invention is not restrict | limited at all by these Examples.

Get region boundary data:
First, the structure of the human brain was classified into the following eight anatomical sites based on the perfused artery according to the standard brain atlas of Tarailach, which is a stereotaxic coordinate system. (1) Anterior corpus callosum artery of the anterior cerebral artery, (2) Central anterior artery of the middle cerebral artery (MCA), (3) The central artery of the MCA, (4) The parietal artery of the MCA, (5) The MCA 8 segments of the coronary artery of the angular gyrus, (6) MCA temporal artery, (7) posterior cerebral artery, and (8) anterior cerebral artery.

  Next, based on the above classification, the blood vessel dominating area was set with reference to the Brodmann area classification, and area boundary coordinates were created in the cortical area on the standard brain atlas of Tarailach.

  In addition to the cortical region coordinates created in this way, for the deep gray matter, the branched arteries are intricately distributed, so it is defined in the standard brain atlas of Tarailach (9) lens nucleus, (10) thalamus and (11) Based on each part of the hippocampus, three zones were set in the deep gray matter, and each region coordinate was created.

  In addition, (12) 22 ROIs were set on both sides of the cerebellar hemisphere, but visually corrected on the anatomical standardized brain. The reason is that it was determined by visual inspection that the conversion formula described later cannot be applied correctly.

  These region coordinates were created on the Taira Lach standard brain atlas from 1-2 (65 mm) to 11-12 (-36 mm). The conversion formula between the coordinates of Taira Lach standard brain atlas and anatomical standard brain coordinates,

X = 0.45Yt + 53.75 (7)
Y = 0.49Xt + 39.84 (8)
Z = 1.14Zt−0.056Yt + 0.071 (9)
[In the above formula, (Xt, Yt, Zt) represents the coordinates of the Tarailach standard brain atlas, and (X, Y, Z) represents the anatomical standard brain coordinates].

  By using these equations, the cortical perfusion area of the cerebral artery defined in the Tarailach Standard Brain Atlas and the coordinates of the boundary points that make up each area and cerebellar hemisphere defined in the deep gray matter are obtained. Converted into continuous three-dimensional position coordinates. The three-dimensional position coordinates obtained here were reconstructed equally with respect to the Z axis so as to form 59 two-dimensional slices.

  Next, in order to actually perform image processing analysis, the obtained coordinates on the anatomical standard brain are converted to coordinates on image software (IPLab: Scanalytic) having a pixel size of 95 × 79 with the origin as shown in FIG. Converted and set 270 ROIs with symmetry on one side.

  When converting the coordinates on the converted anatomical standard brain into pixels as image data, taking into account that it can be quantified and analyzed with high precision, use rounded approximations, etc., make integers without decimal points, and Z coordinates Was imaged as slice numbers 1 to 59 from the parietal lobe to the cerebellum. This includes (1) the corpus callosum arterial artery of the anterior cerebral artery, (2) the central anterior artery of the middle cerebral artery (MCA), (3) the central artery of the MCA, (4) the parietal artery of the MCA, (5) the MCA The coronal region of the ROI based on each vascular control region of the coronary artery of (6) the temporal artery of the MCA, (6) the temporal artery of the MCA, (7) the posterior cerebral artery, (8) the periapical artery of the anterior cerebral artery, (9) lens ROI based on each region of nucleus, (10) thalamus and (11) hippocampus in deep gray matter, (12) ROI of bilateral cerebellar hemispheres in each region boundary data (X pixel number, Y pixel number, Z slice number) ). One side of the obtained area boundary data is described below. FIG. 2 shows an image of this region boundary data (hereinafter abbreviated as “3DSRT”).

(1) Callosal marginal artery of the anterior cerebral artery
(68,42, 1), (68,39, 1), (19,39, 1), (18,42, 1), (68,42, 2), (68,39, 2), (19 , 39, 2), (18, 42, 2), (71, 43, 3), (71, 39, 3), (17, 39, 3), (15, 43, 3), (71, 43 , 4), (71, 39, 4), (17, 39, 4), (15, 43, 4), (71, 43, 5), (71, 39, 5), (17, 39, 5 ), (15, 43, 5), (74, 43, 6), (74, 39, 6), (15, 39, 6), (13, 43, 6), (74, 43, 7), (74,39, 7), (15,39, 7), (13,43, 7), (74,43, 8), (74,39, 8), (15,39, 8), (13 , 43, 8), (76, 46, 9), (76, 39, 9), (14, 39, 9), (13, 46, 9), (76, 46, 10), (76, 39 , 10), (14,39,10), (13,46,10), (78,47,11), (80,39,11), (13,39,11), (12,47,11 ), (78,47,12), (80,39,12), (13,39,12), (12,47,12), (79,47,13), (80,39,13), (12,39,13), (12,47,13), (79,47,14), (80,39,14), (12,39,14), (12,47,14), (81 , 47,15), (82,39,15), (12,39,15), (11,47,15), (81,47,16), (82,39,16), (12,39 , 16), (11,47,16), (80,53,17), (84,45,17), (78,39,17), (66,39,17), (66,47,17 ), (80,53,18), (84,45,18), (78,39,18), (66,39,18), (66,47,18), (79,53,19), (85,46,19), (80,39,19) (66,39,19), (66,47,19), (81,53,20), (85,46,20), (80,39,20), (68,39,20), (68 , 47,20), (83,55,21), (71,47,21), (71,39,21), (83,39,21), (87,46,21), (83,55 , 22), (71,47,22), (71,39,22), (83,39,22), (87,46,22), (82,56,23), (71,47,23 ), (58,39,23), (83,39,23), (89,46,23), (82,56,24), (71,47,24), (58,39,24), (83,39,24), (89,46,24), (81,59,25), (74,52,25), (60,39,25), (83,39,25), (90 , 48,25), (81,59,26), (74,52,26), (62,39,26), (83,39,26), (90,48,26), (82,60 , 27), (73,52,27), (65,39,27), (86,39,27), (90,48,27), (82,60,28), (73,52,28 ), (65,39,28), (86,39,28), (90,48,28), (86,55,29), (73,52,29), (65,39,29), (86,39,29), (90,45,29), (86,55,30), (74,52,30), (67,39,30), (86,39,30), (90 , 46,30), (88,56,31), (75,53,31), (69,39,31), (87,39,31), (91,48,31), (88,56 , 32), (75,53,32), (71,39,32), (87,39,32), (91,48,32), (91,48,33), (79,47,33 ), (71, 39, 33), (89, 39, 33), (91, 48, 34), (79, 47, 34), (71, 39, 34), (89, 39, 34), (89,54,35), (78,53,35) , (68,39,35), (89,39,35), (89,54,36), (78,53,36), (68,39,36), (89,39,36), ( 88,53,37), (72,54,37), (79,47,37), (68,39,37), (89,39,37), (88,53,38), (72, 54,38), (79,47,38), (68,39,38), (89,39,38), (86,57,39), (74,53,39), (77,47, 39), (66, 39, 39), (89, 39, 39), (86, 57, 40), (74, 53, 40), (77, 47, 40), (66, 39, 40) , (89, 39, 40), (86, 55, 41), (74, 49, 41), (62, 39, 41), (89, 39, 41), (86, 55, 42), ( 74, 49, 42), (62, 39, 42), (89, 39, 42), (88, 49, 43), (89, 39, 43), (62, 39, 43), (62, 45,43), (88,49,44), (89,39,44), (62,39,44), (62,45,44), (87,48,45), (88,39, 45), (61, 39, 45), (61, 45, 45), (87, 48, 46), (88, 39, 46), (61, 39, 46), (61, 45, 46) , (85,48,47), (85,39,47), (63,39,47), (63,45,47), (85,48,48), (85,39,48), ( 63,39,48), (63,45,48)

(2) Central anterior artery of middle cerebral artery (MCA)
(68,43, 1), (46,43, 1), (47,58, 1), (58,54, 1), (64,51, 1), (68,43, 2), (46 , 43,2), (47,58,2), (58,54,2), (64,51,2), (71,44,3), (46,44,3), (51,59 , 3), (60, 56, 3), (66, 53, 3), (71, 44, 4), (46, 44, 4), (51, 59, 4), (60, 56, 4 ), (66, 53, 4), (71, 44, 5), (46, 44, 5), (51, 59, 5), (60, 56, 5), (66, 53, 5), (74,44, 6), (46,44, 6), (54,61, 6), (62,57, 6), (68,53, 6), (74,44, 7), (46 , 44,7), (54,61,7), (62,57,7), (68,53,7), (74,44,8), (46,44,8), (54,61 , 8), (62, 57, 8), (68, 53, 8), (76, 47, 9), (50, 48, 9), (57, 63, 9), (72, 55, 9 ), (76, 47, 10), (50, 48, 10), (57, 63, 10), (72, 55, 10), (77, 50, 11), (49, 50, 11), (57,64,11), (72,56,11), (77,50,12), (49,50,12), (57,64,12), (72,56,12), (77 , 50,13), (49,50,13), (57,64,13), (72,56,13), (79,52,14), (48,52,14), (52,68 , 14), (62,64,14), (72,60,14), (79,52,15), (48,52,15), (52,68,15), (62,64,15 ), (72,60,15), (79,52,16), (48,52,16), (52,68,16), (62,64,16), (72,60,16), (79,54,17), (49,54,17) (49,71,17), (64,66,17), (73,60,17), (79,54,18), (49,54,18), (49,71,18), (64 , 66,18), (73,60,18), (80,54,19), (50,54,19), (50,70,19), (65,66,19), (73,61 , 19), (80,54,20), (50,54,20), (50,70,20), (65,66,20), (73,61,20), (83,56,21 ), (63, 56, 21), (47, 60, 21), (50, 71, 21), (67, 66, 21), (83, 56, 22), (63, 56, 22), (47,60,22), (50,71,22), (67,66,22), (82,57,23), (64,57,23), (50,59,23), (53 , 71,23), (72,66,23), (82,57,24), (64,57,24), (50,59,24), (53,71,24), (72,66 , 24), (81,60,25), (74,53,25), (53,59,25), (54,72,25), (73,66,25), (81,60,26 ), (74,53,26), (53,59,26), (54,72,26), (73,66,26), (82,61,27), (73,53,27), (54,59,27), (55,72,27), (73,66,27), (82,61,28), (73,53,28), (54,59,28), (55 , 72,28), (73,66,28), (86,56,29), (73,53,29), (47,63,29), (49,73,29), (66,68 , 29), (79,63,29), (86,56,30), (73,53,30), (47,63,30), (49,73,30), (66,68,30 ), (79,63,30), (88,57,31), (75,54,31), (51,63,31), (51,73,31), (80,64,31), (88,57,32), (75,54,32) (51,63,32), (51,73,32), (80,64,32), (91,49,33), (79,48,33), (76,56,33), (60 , 60,33), (60,69,33), (75,67,33), (86,60,33), (91,49,34), (79,48,34), (76,56 , 34), (60,60,34), (60,69,34), (75,67,34), (86,60,34), (89,55,35), (78,54,35 ), (74,56,35), (60,60,35), (62,69,35), (76,67,35), (84,60,35), (89,55,36), (78,54,36), (74,56,36), (60,60,36), (62,69,36), (76,67,36), (84,60,36), (88 , 54,37), (76,51,37), (72,55,37), (62,58,37), (64,67,37), (77,67,37), (82,62 , 37), (88,54,38), (76,51,38), (72,55,38), (62,58,38), (64,67,38), (77,67,38 ), (82,62,38), (86,58,39), (74,54,39), (61,59,39), (64,67,39), (77,68,39), (82,62,39), (86,58,40), (74,54,40), (61,59,40), (64,67,40), (77,68,40), (82 , 62,40), (86,56,41), (77,66,41), (64,60,41), (74,50,41), (86,56,42), (77,66 , 42), (64,60,42), (74,50,42), (85,56,43), (77,65,43), (67,62,43), (64,53,43 ), (85,56,44), (77,65,44), (67,62,44), (64,53,44), (85,56,45), (76,63,45), (66,62,45), (62,53,45)

(3) Central artery of middle cerebral artery (MCA)
(46,58, 1), (45,43, 1), (36,43, 1), (36,58, 1), (46,58, 2), (45,43, 2), (36 , 43, 2), (36, 58, 2), (37, 61, 3), (36, 44, 3), (45, 44, 3), (50, 59, 3), (44, 61 , 3), (37, 61, 4), (36, 44, 4), (45, 44, 4), (50, 59, 4), (44, 61, 4), (37, 61, 5 ), (36,44, 5), (45,44, 5), (50,59, 5), (44,61, 5), (41,65, 6), (36,44, 6), (45,44, 6), (53,61, 6), (48,64, 6), (41,65, 7), (36,44, 7), (45,44, 7), (53 , 61,7), (48,64,7), (41,65,8), (36,44,8), (45,44,8), (53,61,8), (48,64 , 8), (42, 66, 9), (37, 51, 9), (42, 48, 9), (49, 48, 9), (56, 64, 9), (50, 66, 9 ), (42,66,10), (37,51,10), (42,48,10), (49,48,10), (56,64,10), (50,66,10), (42,69,11), (40,50,11), (48,50,11), (56,66,11), (42,69,12), (40,50,12), (48 , 50,12), (56,66,12), (42,69,13), (40,50,13), (48,50,13), (56,66,13), (41,70 , 14), (41,52,14), (47,52,14), (51,68,14), (41,70,15), (41,52,15), (47,52,15 ), (51,68,15), (41,70,16), (41,52,16), (47,52,16), (51,68,16), (41,71,17), (41,54,17), (48,54,17) (48,71,17), (41,71,18), (41,54,18), (48,54,18), (48,71,18), (43,73,19), (43 , 54,19), (49,54,19), (49,70,19), (43,73,20), (43,54,20), (49,54,20), (49,70 , 20), (43,57,21), (46,57,21), (49,72,21), (43,73,21), (43,57,22), (46,57,22 ), (49,72,22), (43,73,22), (44,57,23), (49,57,23), (52,72,23), (43,73,23), (44,57,24), (49,57,24), (52,72,24), (43,73,24), (47,74,25), (45,58,25), (52 , 58,25), (53,72,25), (47,74,26), (45,58,26), (52,58,26), (53,72,26), (49,74 , 27), (47,61,27), (53,58,27), (54,72,27), (49,74,28), (47,61,28), (53,58,28 ), (54,72,28)

(4) Parietal artery of middle cerebral artery (MCA)
(34,58, 1), (37,43, 1), (18,43, 1), (24,55, 1), (34,58, 2), (37,43, 2), (18 , 43, 2), (24, 55, 2), (36, 61, 3), (35, 44, 3), (15, 44, 3), (26, 57, 3), (36, 61 , 4), (35,44, 4), (15,44, 4), (26,57, 4), (36,61, 5), (35,44, 5), (15,44, 5 ), (26, 57, 5), (40, 65, 6), (35, 44, 6), (13, 44, 6), (24, 59, 6), (40, 65, 7), (35,44, 7), (13,44, 7), (24,59, 7), (40,65, 8), (35,44, 8), (13,44, 8), (24 , 59,8), (41,66,9), (36,51,9), (41,48,9), (13,48,9), (19,58,9), (30,64 , 9), (41, 66, 10), (36, 51, 10), (41, 48, 10), (13, 48, 10), (19, 58, 10), (30, 64, 10 ), (41,69,11), (39,50,11), (12,50,11), (20,59,11), (29,65,11), (41,69,12), (39,50,12), (12,50,12), (20,59,12), (29,65,12), (41,69,13), (39,50,13), (12 , 50,13), (20,59,13), (29,65,13), (40,70,14), (40,52,14), (12,52,14), (20,63 , 14), (29,67,14)

(5) Angular artery of the middle cerebral artery (MCA)
(40,70,15), (40,52,15), (12,52,15), (20,63,15), (29,68,15), (40,70,16), (40 , 52,16), (12,52,16), (20,63,16), (29,68,16), (40,71,17), (40,57,17), (27,54 , 17), (20,63,17), (29,70,17), (40,71,18), (40,57,18), (27,54,18), (20,63,18 ), (29,70,18), (42,73,19), (42,59,19), (26,56,19), (20,64,19), (29,70,19), (42,73,20), (42,59,20), (26,56,20), (20,64,20), (29,70,20), (42,73,21), (42 , 59,21), (26,56,21), (18,64,21), (29,70,21), (42,73,22), (42,59,22), (26,56 , 22), (18,64,22), (29,70,22)

(6) Temporal artery of middle cerebral artery (MCA)
(42,73,23), (43,63,23), (26,55,23), (19,65,23), (29,71,23), (42,73,24), (43 , 63,24), (26,55,24), (19,65,24), (29,71,24), (46,74,25), (44,63,25), (26,56 , 25), (20,65,25), (29,71,25), (46,74,26), (44,63,26), (26,56,26), (20,65,26 ), (29, 71, 26), (48, 74, 27), (46, 63, 27), (26, 56, 27), (20, 65, 27), (29, 71, 27), (48,74,28), (46,63,28), (26,56,28), (20,65,28), (29,71,28), (48,74,29), (46 , 63,29), (27,59,29), (20,67,29), (31,72,29), (48,74,30), (46,63,30), (27,59 , 30), (20,67,30), (31,72,30), (50,73,31), (50,63,31), (36,64,31), (27,59,31 ), (20,67,31), (31,73,31), (50,73,32), (50,63,32), (36,64,32), (27,59,32), (20,67,32), (31,73,32), (59,72,33), (59,61,33), (43,63,33), (27,59,33), (20 , 67,33), (35,75,33), (59,72,34), (59,61,34), (43,63,34), (27,59,34), (20,67 , 34), (35,75,34), (57,72,35), (54,61,35), (43,63,35), (27,59,35), (20,67,35 ), (35,74,35), (57,72,36), (54,61,36), (43,63,36), (27,59,36), (20,67,36), (35,74,36), (57,70,37) (55,58,37), (43,63,37), (29,60,37), (25,71,37), (40,74,37), (57,70,38), (55 , 58,38), (43,63,38), (29,60,38), (25,71,38), (40,74,38), (59,70,39), (53,59 , 39), (43,63,39), (29,60,39), (25,71,39), (40,75,39), (59,70,40), (53,59,40 ), (43,63,40), (29,60,40), (25,71,40), (40,75,40), (55,72,41), (58,61,41), (46,62,41), (37,64,41), (26,60,41), (23,70,41), (33,75,41), (55,72,42), (58 , 61,42), (46,60,42), (37,62,42), (26,60,42), (23,70,42), (33,75,42), (55,72 , 43), (58,61,43), (46,60,43), (37,62,43), (26,60,43), (23,70,43), (33,75,43 ), (64,65,44), (57,57,44), (49,58,44), (41,60,44), (26,72,44), (42,74,44), (52,71,44), (64,65,45), (57,57,45), (49,58,45), (41,60,45), (26,72,45), (42 , 74,45), (52,71,45), (63,62,46), (56,57,46), (50,59,46), (43,60,46), (33,73 , 46), (45,73,46), (58,71,46), (63,62,47), (56,57,47), (50,59,47), (43,60,47 ), (33,73,47), (45,73,47), (58,71,47), (64,61,48), (57,55,48), (51,55,48), (34,73,48), (48,73,48) (59,70,48), (64,61,49), (57,55,49), (51,55,49), (34,73,49), (48,73,49), (59 , 70,49)

(7) Posterior cerebral artery
(26,54,17), (19,48,17), (10,48,17), (13,57,17), (19,63,17), (9,39,18), (9 , 47,18), (12,56,18), (19,63,18), (26,54,18), (19,47,18), (22,39,18), (9,39 , 19), (9,48,19), (12,56,19), (19,64,19), (25,56,19), (19,47,19), (22,39,19 ), (9,39,20), (9,48,20), (12,56,20), (19,64,20), (25,56,20), (19,47,20), (22,39,20), (9,39,21), (9,48,21), (12,57,21), (17,64,21), (25,56,21), (20 , 47,21), (22,39,21), (9,39,22), (9,48,22), (12,57,22), (17,64,22), (25,56 , 22), (20,47,22), (22,39,22), (8,39,23), (8,48,23), (12,58,23), (18,65,23 ), (25,55,23), (21,47,23), (23,39,23), (8,39,24), (8,48,24), (12,58,24), (18,65,24), (25,55,24), (21,47,24), (23,39,24), (7,39,25), (7,49,25), (12 , 59,25), (19,65,25), (25,55,25), (22,47,25), (24,39,25), (7,39,26), (7,49 , 26), (12,59,26), (19,65,26), (25,55,26), (22,47,26), (24,39,26), (6,39,27 ), (6,49,27), (12,59,27), (19,65,27), (25,56,27), (22,47,27), (24,39,27), (6,39,28), (6,49,28) (12,59,28), (19,65,28), (25,56,28), (22,47,28), (24,39,28), (5,39,29), (5 , 50,29), (11,59,29), (19,67,29), (26,59,29), (22,47,29), (24,39,29), (23,39 , 30), (5,39,30), (5,50,30), (11,59,30), (19,67,30), (26,59,30), (22,47,30 ), (5,39,31), (5,51,31), (11,59,31), (19,67,31), (26,59,31), (22,47,31), (23,39,31), (5,39,32), (5,51,32), (11,59,32), (19,67,32), (26,59,32), (22 , 47,32), (23,39,32), (5,39,33), (4,41,33), (4,50,33), (10,60,33), (19,67 , 33), (26,59,33), (18,48,33), (29,53,33), (38,53,33), (38,44,33), (31,44,33 ), (20,41,33), (5,39,34), (4,41,34), (4,50,34), (10,60,34), (19,67,34), (26,59,34), (18,48,34), (29,53,34), (38,53,34), (38,44,34), (31,44,34), (20 , 41,34), (5,39,35), (4,41,35), (4,52,35), (10,60,35), (19,67,35), (26,59 , 35), (18,48,35), (34,55,35), (39,55,35), (39,44,35), (34,45,35), (20,44,35 ), (5,39,36), (4,41,36), (4,52,36), (10,60,36), (19,67,36), (26,59,36), (18,48,36), (34,55,36) (39,55,36), (39,44,36), (34,45,36), (20,44,36), (2,41,37), (2,52,37), (11 , 62,37), (24,71,37), (28,60,37), (20,50,37), (35,55,37), (40,55,37), (40,46 , 37), (35,46,37), (20,44,37), (5,39,37), (2,41,38), (2,52,38), (11,62,38 ), (24,71,38), (28,60,38), (20,50,38), (35,55,38), (40,55,38), (40,46,38), (35,46,38), (20,44,38), (6,39,38), (2,41,39), (2,52,39), (11,62,39), (24 , 71,39), (28,60,39), (37,56,39), (42,57,39), (41,47,39), (37,47,39), (29,48 , 39), (23,45,39), (5,39,39), (2,41,40), (2,52,40), (11,62,40), (24,71,40 ), (28,60,40), (37,56,40), (42,57,40), (41,47,40), (37,47,40), (29,48,40), (23,45,40), (5,39,40), (2,41,41), (2,52,41), (11,63,41), (22,70,41), (25 , 60,41), (46,58,41), (46,50,41), (40,47,41), (32,49,41), (23,50,41), (18,39 , 41), (5,39,41), (2,41,42), (2,52,42), (11,63,42), (22,70,42), (25,60,42 ), (46,58,42), (46,50,42), (40,47,42), (32,49,42), (23,50,42), (18,39,42), (5,39,42), (2,41,43) , (2,52,43), (11,63,43), (22,70,43), (25,60,43), (46,58,43), (46,50,43), ( 40,47,43), (32,49,43), (23,50,43), (18,39,43), (5,39,43), (2,41,44), (2, 52,44), (11,63,44), (25,72,44), (41,59,44), (49,57,44), (49,47,44), (41,48, 44), (39,52,44), (26,57,44), (19,39,44), (5,39,44), (2,41,45), (2,52,45) , (11,63,45), (25,72,45), (41,59,45), (49,57,45), (49,47,45), (41,48,45), ( 39,52,45), (26,57,45), (19,39,45), (5,39,45), (50,46,46), (38,53,46), (24, 60,46), (29,71,46), (32,73,46), (43,59,46), (50,58,46), (50,46,47), (38,53, 47), (24,60,47), (29,71,47), (32,73,47), (43,59,47), (50,58,47), (50,46,48) , (34,72,48), (51,54,48), (50,46,49), (34,72,49), (51,54,49)

(8) Artery around the corpus callosum of the anterior cerebral artery
(65,47,17), (65,39,17), (11,39,17), (10,47,17), (20,47,18), (23,39,18), (65 , 39,18), (65,47,18), (20,47,19), (23,39,19), (65,39,19), (65,47,19), (20,47 , 20), (23,39,20), (67,39,20), (67,47,20), (21,47,21), (23,39,21), (70,39,21 ), (70, 47, 21), (21, 47, 22), (23, 39, 22), (70, 39, 22), (70, 47, 22), (22, 47, 23), (24,39,23), (42,39,23), (42,47,23), (22,47,24), (24,39,24), (42,39,24), (42 , 47,24), (23,47,25), (25,39,25), (36,39,25), (36,47,25), (23,47,26), (25,39 , 26), (36,39,26), (36,47,26), (23,47,27), (25,39,27), (35,39,27), (35,47,27 ), (23,47,28), (25,39,28), (35,39,28), (35,47,28), (23,47,29), (25,39,29), (35,39,29), (35,47,29), (23,47,30), (24,39,30), (35,39,30), (35,47,30), (23 , 47,31), (24,39,31), (35,39,31), (35,47,31), (35,39,32), (24,39,32), (23,47 , 32), (35,47,32)

(9) Lens core
(53,47,30), (45,52,30), (49,53,30), (58,50,30), (53,47,31), (45,52,31), (49 , 53,31), (58,50,31), (55,46,32), (45,53,32), (50,54,32), (57,52,32), (61,49 , 32), (55,46,33), (45,53,33), (50,54,33), (57,52,33), (61,49,33), (54,43,34 ), (44,53,34), (47,54,34), (50,54,34), (55,53,34), (59,51,34), (62,49,34), (54,43,35), (44,53,35), (47,54,35), (50,54,35), (55,53,35), (59,51,35), (62 , 49,35), (54,43,36), (44,53,36), (47,54,36), (50,54,36), (55,53,36), (59,51 , 36), (62,49,36), (54,43,37), (44,53,37), (47,54,37), (50,54,37), (55,53,37 ), (59,51,37), (62,49,37), (54,43,38), (48,50,38), (44,54,38), (47,54,38), (52,53,38), (56,52,38), (59,51,38), (62,49,38), (54,43,39), (48,50,39), (44 , 54,39), (47,54,39), (52,53,39), (56,52,39), (59,51,39), (62,49,39), (54,44 , 40), (51,47,40), (48,50,40), (45,54,40), (49,54,40), (52,53,40), (55,52,40 ), (59,51,40), (62,49,40), (60,45,40), (57,44,40), (54,44,41), (51,47,41), (48,50,41), (45,54,41) (49,54,41), (52,53,41), (55,52,41), (59,51,41), (62,49,41), (60,45,41), (57 , 44,41)

(10) Thalamus
(43,43,27), (43,49,27), (50,47,27), (51,44,27), (43,43,28), (43,49,28), (50 , 47,28), (51,44,28), (40,45,29), (40,49,29), (43,51,29), (53,45,29), (53,43 , 29), (51,41,29), (43,41,29), (40,45,30), (40,49,30), (43,51,30), (53,45,30 ), (53,43,30), (51,41,30), (43,41,30), (40,44,31), (40,49,31), (43,51,31), (53,45,31), (54,42,31), (51,40,31), (43,41,31), (40,44,32), (40,49,32), (43 , 51,32), (53,45,32), (54,42,32), (51,40,32), (43,41,32), (40,42,33), (40,50 , 33), (43,50,33), (49,46,33), (52,41,33), (50,40,33), (43,41,33), (40,42,34 ), (40,50,34), (43,50,34), (49,46,34), (52,41,34), (50,40,34), (43,41,34), (41,45,35), (41,50,35), (44,50,35), (51,44,35), (51,41,35), (44,42,35), (41 , 45,36), (41,50,36), (44,50,36), (51,44,36), (51,41,36), (44,42,36), (41,45 , 37), (41,50,37), (44,50,37), (51,44,37), (51,41,37), (44,42,37)

(11) Hippocampus
(38,44,33), (38,53,33), (29,53,33), (31,44,33), (38,44,34), (38,53,34), (29 , 53,34), (31,44,34), (39,44,35), (39,55,35), (34,55,35), (34,45,35), (39,44 , 36), (39,55,36), (34,55,36), (34,45,36), (40,46,37), (40,55,37), (35,55,37 ), (35,46,37), (40,46,38), (40,55,38), (35,55,38), (35,46,38), (41,47,39), (42,57,39), (37,56,39), (37,47,39), (41,47,40), (42,57,40), (37,56,40), (37 , 47,40), (46,50,41), (40,47,41), (32,49,41), (37,58,41), (46,58,41), (46,50 , 42), (40,47,42), (32,49,42), (37,58,42), (46,58,42), (46,50,43), (40,47,43 ), (32,49,43), (37,58,43), (46,58,43), (49,47,44), (49,57,44), (41,59,44), (39,52,44), (41,48,44), (49,47,45), (49,57,45), (41,59,45), (39,52,45), (41 , 48,45), (50,46,46), (50,58,46), (43,59,46), (38,53,46), (50,46,47), (50,58 , 47), (43,59,47), (38,53,47), (51,54,48), (50,46,48), (34,72,48), (51,54,49 ), (50,46,49), (34,72,49)

(12) Cerebellar hemisphere
(39,51,49), (28,50,49), (19,40,49), (9,39,49), (4,45,49), (15,54,49), (24 , 60,49), (34,62,49), (39,51,50), (28,50,50), (19,40,50), (9,39,50), (4,45 , 50), (15,54,50), (24,60,50), (34,62,50), (39,51,51), (28,50,51), (19,40,51 ), (9,39,51), (4,45,51), (15,54,51), (24,60,51), (34,62,51), (39,51,52), (28,49,52), (19,40,52), (12,40,52), (8,47,52), (15,55,52), (24,60,52), (34 , 64,52), (39,51,53), (28,49,53), (19,40,53), (12,40,53), (8,47,53), (15,55 , 53), (24,60,53), (34,64,53), (40,51,54), (27,53,54), (22,48,54), (22,39,54 ), (15,39,54), (8,46,54), (16,61,54), (28,67,54), (37,68,54), (40,51,55), (27,53,55), (22,48,55), (22,39,55), (15,39,55), (8,46,55), (16,61,55), (28 , 67,55), (37,68,55), (40,51,56), (27,53,56), (22,48,56), (22,39,56), (15,39 , 56), (8,46,56), (16,61,56), (28,67,56), (34,68,56), (40,51,57), (27,53,57 ), (22,48,57), (22,39,57), (15,39,57), (8,46,57), (16,61,57), (28,67,57), (34,68,57), (40,51,58) (27,53,58), (22,48,58), (22,39,58), (15,39,58), (8,46,58), (16,61,58), (28 , 67,58), (34,68,58), (40,51,59), (27,53,59), (22,48,59), (22,39,59), (15,39 , 59), (8,46,59), (16,61,59), (28,67,59), (34,68,59)

(1) Imaging by SPECT:
According to the method collectively shown in FIG. 3 (RVR method), half the amount of labeled technetium-99m-L, L-ethylcysteinate dimer (99mTc-ECD) (600 MBq / 3 mL) supplied in 3 mL per syringe (1. 5 mL) was intravenously injected as a bolus and RI angio was performed. Using a dual-head SPECT system (Prism 2000XP, Marconi, Ohio, USA) equipped with a high-resolution parallel-hole collimator, 99mTc-ECD flowing from the aortic arch to the brain for 120 seconds immediately after administration Monitoring was performed at 1 second intervals (magnification 1.0).

  The ROI was manually set on the aortic arch and both cerebral hemispheres, and brain perfusion was performed from the time activity curve by the method of Matsuda et al. (Eur. J. Nucl. Med. 1992; 19: 195-200). The index (BPI) was calculated. Then, BPI was converted and the CBF average value (mCBF) at rest was calculated.

  Seven minutes after the completion of RI angio, SPECT imaging was performed in a 64 × 64 format (magnification 1.33) using Prism 2000XP high-resolution fan beam collimator for 20 seconds for each angle in 30 ° steps. . Collection time was 12 minutes.

Ten minutes before the completion of the first SPECT imaging, 1 g of acetazolamide (Acz) was intravenously administered to the patient, and the remaining amount of 99mTc-ECD (1.5 mL) was administered simultaneously with completion of imaging. Nine minutes later, the second SPECT imaging was performed under the same collection conditions as at rest without changing the position of the subject's head and the camera at all. In order to obtain projection data after Acz administration, the first SPECT data is subtracted from the second SPECT data obtained by multiplying 1.041 which is a correction coefficient for attenuation of 99mTc between the first and second SPECT data. Data after time and Acz loading were obtained and reconstructed by backprojection using a Ramp filter, followed by a Butter-worth filter (order 8, cut-off 0.26). Furthermore, after performing absorption correction using the Chang method (correction coefficient: μ = 0.09), the body axis cross-sectional image was reconstructed so as to be parallel to the orbital ear canal line. The pixel size and slice thickness were 4.5 mm ² and 4.5 mm, respectively.

  In order to calculate mCBF after Acz administration, two consecutive slices including the basal ganglia were added to create a reference slice (slice thickness: 9.0 mm). The average SPECT count of the reference slice at rest and after Acz loading is calculated from the ROI including all gray matter, white matter, and ventricles, and Lassen's linearization correction algorithm (α = 2.59) was used to calculate mCBF after Acz loading.

99mTc-ECD at rest and after Acz loading
Using a SPECT qualitative image and each mCBF, a ^99m Tc-ECD SPECT quantitative image at rest and after Acz loading was created by Lassen's linearization correction algorithm (α = 2.59).

(2) Anatomical standardization:
For the calculation of rCBF (local cerebral blood flow), we used MATLAB® (MathWorks, Massachusetts) based SPM99 running on Windows® 98 for cerebral blood flow SPECT quantitative images at rest and after Az administration. On the other hand, anatomical standardization was performed using a standardization algorithm of 12 parameters (rigid body, zoom and affine) set in the cerebral blood flow SPECT qualitative image at rest.

  For proper color display of anatomically standardized quantitative images, pixels that have more than 90 values of cerebral blood flow SPECT quantitative images at rest and after Acz administration before applying standardization Pretreatment to replace all 90 was added. Thereafter, anatomical standardization was performed in exactly the same manner as described above.

(3) Quantitative display of anatomical standardized SPECT images:
After applying the pre-processing, by adding several pixels having a value of 90 to the corners of each slice of these images, the maximum value of each slice is made all the same as 90, and then 10 to 90 are performed in 8 steps. The same color table divided evenly was applied to all of these to perform color display.

Verification of anatomical accuracy of 3DSRT (1) Examination in Alzheimer's disease patients:
In order to examine the accuracy of 3DSRT set for the superficial cortex, eight resting SPECT quantitative images (five women, three men, age range 51-85 years) were evaluated. Subjects were patients diagnosed with “probable Alzheimer's disease” according to the diagnostic criteria of NINCDS / ARDRA (Neurology 1984; 34; 939-944). As a result of superimposing 3DSRT on the anatomically standardized resting SPECT quantitative image, the position where the blood flow in the MCA central artery perfusion region, which is the region corresponding to the primary sensorimotor region, is retained, and the region 3 in FIG. It was confirmed that the positions of the ROIs coincided exactly. FIG. 4, FIG. 6 and FIG. 7 show a part of the results (three persons). Moreover, about the part of FIG. 4, the case where 3DSRT is not used and the case where it uses is compared (FIG. 5). Since the drawings attached to the present specification are monochrome and difficult to see, the SPECT images (colors) shown in FIGS. 4 and 6 to 18 are submitted separately as reference drawings.

(2) Examination in patients with local lesions in gray matter:
In order to examine the accuracy of 3DSRT set for deep tissue, 7 resting SPECT quantitative images (3 women, 4 men, age range 54-80 years) were evaluated. Subjects were patients with lesions limited to the lens nucleus or thalamus (3 putamen infarcts, 3 thalamic infarcts, 1 CO poisoning). As a result of superimposing 3DSRT on the anatomically standardized resting SPECT quantitative image, it was confirmed that the low blood flow site, which is a lesion, and the position of the corresponding ROI of 3DSRT exactly matched. FIGS. 8 to 10 show a part of the results (three persons).

(3) Conclusion The most important perfusion site for examining whether or not anatomical standardization is appropriately performed is the central arterial perfusion region of the middle cerebral artery. Although this region exists on many slices, it is all small and even if there is a slight misalignment, it becomes fatal to the quantitative result of rCBF. From this point of view, this time, the position of the primary sensorimotor region in the anatomically standardized SPECT image of the Alzheimer's disease patient was evaluated. This site is widely known to maintain blood flow regardless of the stage of Alzheimer's disease (J. Nucl. Med. 1995; 36: 690-696, J. Nucl. Med. 1996; 37: 1159-1165, Brain imaging in Alzheimer's disease. Lippincott Williams &Wilkins; 1999: 67-93). Since the ROI position of the primary sensorimotor area in 3DSRT and the region where perfusion is characteristically maintained on the standardized cerebral blood flow SPECT images (FIGS. 4, 6 and 7) are well matched, The accuracy of 3DSRT was confirmed. Even in patients with a lesion site limited to the deep gray matter region, the ROI position and the blood flow reduction site on the standardized cerebral blood flow SPECT image (FIGS. 8 to 10) show the same good agreement as the superficial site. The blood flow value of each ROI at rest by 3DSRT, the reliability of “Regional CBF (rCBF)” was confirmed for both deep and superficial sites.

Evaluation of cerebrovascular reserve ability before and after surgery using 3DSRT method To analyze reactivity to Acz, “CBF after Acz administration / CBF at rest” is defined as “Increment Ratio (IR)” and corresponds to mCBF IR corresponding to rCBF was defined as mIR, IR corresponding to rCBF was defined as rIR, and IR corresponding to segmental CBF calculated from the weighted average of rCBF of each ROI constituting the segment was defined as segmental IR (sIR). The IR threshold for normal response to Acz was 1.20.

  Revascularization (13 superficial temporal arteries (STA) -MCA anastomosis, 4 carotid endarterectomy, 3 carotid stenting) (2 women, 11 men, age) Followed up (range 51-70 years).

  In Table 1 below, in addition to clinical symptoms, MRI findings, magnetic resonance angiography (MRA) findings, the area-weighted average of mCBF and mIR values of the entire cortex region (2-6 sites in FIG. 2) perfused from MCA Show about.

  Transient cerebral ischemic attack (TIA) or reversible cerebral ischemic neuropathy (RIND) was the subject of analysis, and those with clear infarct were excluded, but the pit state (lacuna) was the subject of analysis. Local unilateral stenosis was observed in 10 (1 female, 9 males, age range 51-70 years) (unilateral stenosis group). The remaining three (1 female, 2 males, age range 63-70 years) had stenosis on both sides (bilateral stenosis group). In this case, the diseased side was determined from MRA findings.

  For each of the above patients, sCBF and sIR at rest before surgery and after Acz administration were compared with postoperative data. The data of the unilateral stenosis group (patient 1-10) and the bilateral stenosis group (patient 11-13) are shown in Table 2 to Table 5, respectively. In the table below, Ant is the site 1 in FIG. 2, PreC is the site 2, Cent is the site 3, Pari is the site 4, Ang is the site 5, PoTe is the site 6, and Post is the site 7. Respectively.

Patient example 1. 70 year old male patient (patient 1 in Tables 1 and 2):
A stenosis with a degree of stenosis of 90% was accidentally found in the right internal carotid artery (ICA), and a right carotid artery stenting was performed. 11 to 14 show standardized SPECT quantitative images at rest and after Acz administration of the patient under pre- and post-operative conditions. Table 6 summarizes the rCBF data at rest and after Acz administration in 28 consecutive ROIs in the region (site 3 in FIG. 2) perfused from the central artery of the patient under pre- and post-operative conditions. It was.

2. 69 year old male patient (patient 4 in Tables 1 and 2):
Due to 99% stenosis of the left ICA, the left eye had transient cataract symptoms and underwent left carotid endarterectomy. After surgery, the above symptoms were ameliorated. 15 to 18 show standardized SPECT quantitative images at rest and after Acz administration of the patient under pre- and post-operative conditions.

  Compared with the mIR of the entire MCA region (Table 1), Acz reactivity decreased (IR <1.20) preoperatively, 8 out of 10 (patient 3-10) in the unilateral stenosis group (patient 1-10) ) On the diseased side, 5 (patients 4, 6, 8-10) on the healthy side, and only the diseased side of 2 patients (patients 8 and 9) with ICA occlusion continued to have decreased responsiveness after surgery Met. In the bilateral stenosis group (patients 11-13), the bilateral decreased responsiveness observed before surgery was all normalized after surgery.

  On the other hand, when compared by sIR, in the unilateral stenosis group, some of 9 patients excluding patient 1 out of 10 patients on the disease side and 7 patients (patients 3, 4, 6-10) on the healthy side before surgery. Decreased Acz responsiveness was observed in these segments, and the reduced Acz responsiveness persisted in several segments on the diseased side of 3 (patients 8-10) and 2 (8, 10) on the healthy side (Table). 2 to Table 4). In the bilateral stenosis group (Table 5), Acz responsiveness decline was observed preoperatively in all 3 sites, and Acz responsiveness persisted in several segments of 2 subjects (patients 12 and 13).

  Compared with rCBF and rIR, for example, in Patient 1, a more detailed study of impaired circulatory reserve in the right central arterial perfusion zone was possible (Table 6). Before the operation, the Az reactivity decreased in the 11th to 16th slices. However, the rCBF at rest was slightly lower on the healthy side than on the affected side. After the operation, Az reactivity was remarkably improved on both sides, but the rCBF at rest was still lower on the healthy side than on the affected side. These findings could be confirmed visually and clearly with the SPECT quantitative image superimposed with 3DSRT (FIGS. 11 to 14).

  By combining visual evaluation and quantitative analysis using SPECT quantitative images superimposed with 3DSRT, objective evaluation of circulatory reserve became easy. For example, as shown in patient 4 (Tables 1 and 3a), preoperative wide hypoperfusion and reduced circulatory reserve in the left cerebral hemisphere (FIGS. 14 and 15) and significant post-carotid endarterectomy The improvement (FIGS. 16-17) is shown very clearly.

  To assess the effectiveness of revascularization, sCBF calculated from the weighted average of rCBF at hemodynamically related sites sharing the same perfused artery was mainly used. It is known that the perfusion region of the cerebral artery is different in its extent and position, and it was initially thought that the examination by sCBF was inappropriate in the evaluation of the circulatory reserve. However, the standardization of the position of the blood vessel dominating region and the reference plane is extremely important for an accurate comparison of the cerebral circulation state, and sCBF is also found from the pre- and post-operative follow-up data shown in Tables 3 to 5. Useful for objective assessment of cerebral circulation disorders. It is possible to evaluate the circulatory reserve capacity in a limited area that cannot be determined from the mCBF value based on the sCBF and sIR, but if necessary, it is shown to the patient 1 by adding the analysis of the rCBF and rIR values. Thus, it is possible to more accurately evaluate early localized cerebral ischemia. Because cerebral vasodilation, which increases cerebral blood volume, is the earliest response of autoregulatory capacity to cerebral perfusion pressure drop, resting blood flow is normal, but the area where dilatation ability is reduced is drug loaded It is very important to detect by. Therefore, it is not appropriate to consider evaluating early cerebral ischemia using only rCBF at rest, which is prone to mistakes and inappropriate. On the other hand, if an anatomically standardized image, which was previously considered only as a preliminary step for statistical analysis by SPM, is analyzed by the 3DSRT method, useful and direct quantitative information on local cerebral circulation reserve is obtained. It became possible to obtain objectively.

  Conventionally, if the RVR method is performed, it is possible to non-invasively obtain rCBF SPECT images at rest and after Acz loading. However, since the IR values obtained with subtle changes in the shape, size and position of the ROI vary, it is more difficult to examine the circulation reserve based on the IR values than initially expected. In addition, comparison of the same subject before and after revascularization is even more difficult because it is impossible to set the same ROI for SPECT images obtained at different dates even for a single subject.

  In the RVR method, the position of the head at the time of SPECT imaging is unchanged, and the SPECT image after Acz loading also has the same anatomical position coordinates as at rest. Focusing on the fact that anatomical standardization can be performed with the same movement parameters as those applied to the anatomical standardized image at rest and after Acz loading, the 3DSRT method is applied to Postoperative circulatory reserve was objectively evaluated, and fluctuations between observers, subjects, and subjects that could not be solved by conventional ROI settings were eliminated.

Claims (9)

  In order to cause a computer having a storage unit storing region boundary data of a plurality of three-dimensional arterial control regions in the brain determined in advance based on the standard brain atlas to execute the following steps (1) to (3) Computer program.
(1) Save observation data obtained by imaging the brain.
(2) The observation data is converted by anatomical standardization and stored as standardized data.
(3) The standardized data and the ROI determined based on the region boundary data are processed in combination, and the state of each arterial dominant region is numerically displayed using numerical data before imaging.   In (3),
  Using the plurality of ROIs determined based on the region boundary data respectively corresponding to the plurality of slices of the standardized data, the state of each arterial region is numerically displayed using numerical data before imaging The computer program according to claim 1.   In order to cause a computer having a storage unit storing region boundary data of a plurality of three-dimensional arterial control regions in the brain determined in advance based on the standard brain atlas to execute the following steps (1) to (3) Computer program.
(1) Save observation data obtained by imaging the brain.
(2) The region boundary data is converted by using an inverse operation with respect to an operation used for converting the observation data into standard data by anatomical standardization to generate corrected region boundary data.
(3) The observation data and the ROI determined based on the corrected region boundary data generated in (2) are processed in combination, and the state of each arterial region is numerically expressed using numerical data before imaging. indicate.   The observation data is data generated by X-ray CT, single photon emission computed tomography (SPECT), positron emission tomography (PET), or magnetic resonance imaging (MRI). A computer program according to any one of the above.   The recording medium which stored the computer program in any one of Claims 1-4.   A computer having a storage unit in which region boundary data of a plurality of three-dimensional arterial control regions in a brain determined in advance based on a standard brain atlas is stored,
(1) Save observation data obtained by imaging the brain,
(2) The observation data is converted by anatomical standardization and stored as standardized data.
(3) A data processing method for processing by combining the standardized data and the ROI determined based on the region boundary data, and numerically displaying the state of each arterial dominant region using numerical data before imaging .   A computer having a storage unit in which region boundary data of a plurality of three-dimensional arterial control regions in a brain determined in advance based on a standard brain atlas is stored,
(1) Save observation data obtained by imaging the brain,
(2) Using the inverse operation to the operation used to convert the observation data into standard data by anatomical standardization, transform the region boundary data to generate corrected region boundary data;
(3) The observation data and the ROI determined based on the corrected region boundary data generated in (2) are processed in combination, and the state of each arterial region is numerically expressed using numerical data before imaging. The data processing method to display.   A first storage unit for storing region boundary data of a plurality of three-dimensional arterial dominating regions in the brain determined in advance based on the standard brain atlas;
  A second storage unit for storing observation data obtained by imaging the brain;
  Means for converting the observation data stored in the second storage unit by anatomical standardization and generating standardized data;
  The generated standardized data and the ROI determined based on the region boundary data stored in the first storage unit are processed in combination, and the state of each arterial dominant region is used as numerical data before imaging. An image data processing device.   A first storage unit for storing region boundary data of a plurality of three-dimensional arterial dominating regions in the brain determined in advance based on the standard brain atlas;
  A second storage unit for storing observation data obtained by imaging the brain;
  Area boundary data stored in the first storage unit by using an inverse operation for an operation used to convert the observation data stored in the second storage unit into standard data by anatomical standardization To generate corrected region boundary data,
  The observation data stored in the second storage unit and the ROI determined based on the generated corrected region boundary data are processed in combination, and the state of each arterial control region is expressed using numerical data before imaging. An image data processing device.

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