JP2005328933A - Transcranial brain function measuring apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To easily perform significant data comparison without performing the complicated three-dimensional arithmetic processing of the entire brain in a transcranial brain function measuring apparatus. <P>SOLUTION: This brain function measuring apparatus comprises: a transcranial brain activity data acquisition part 11 for determining the detection position of brain activity data with the shape of the cranial surface 21 of a patient as a reference and acquiring the brain activity data at the detection position; a brain image data acquisition part 12 for attaining the correspondence of the position relation of the cranial surface and a brain surface at the time of sampling the brain activity data by the transcranial brain activity data acquisition part 11 and acquiring brain image data; and a synthetic image display part 13 for forming a brain surface image on the basis of the brain image data, forming a brain activity image on the basis of the brain activity data, and forming and displaying synthetic images for which the brain surface image and the brain activity image are superimposed. The synthetic image display part 13 is provided with an image conversion processing part 14 for performing image conversion to enlarge and reduce the synthetic image with a feature point on the brain surface determined on the basis of the brain image data as a reference, the synthetic image is enlarged and reduced with the feature point as the reference, and the significant comparison of the brains with each other is made possible. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

The present invention relates to a transcranial brain function measuring apparatus that measures brain function by non-invasively measuring brain activity data of a living body, and more specifically, determines a measurement position based on a reference point provided on the surface of the skull. The present invention relates to a transcranial brain function measuring device that measures brain activity data.
Specifically, the present invention relates to a brain function measuring device such as a near-infrared spectrometer (NIRS) and a magnetoencephalograph (MEG).

In recent years, a transcranial measurement of brain activity, that is, a near-infrared spectrometer (hereinafter abbreviated as NIRS) and a magnetoencephalometer (hereinafter abbreviated as MEG) capable of non-invasively measuring brain activity from the outside of the head. ) Is used.
For example, in the NIRS, a light transmission fiber is arranged on the surface of the subject's skull, irradiated with near infrared rays, and the near infrared ray reflected from the brain is detected by a light receiving fiber also arranged on the surface of the skull. Near-infrared light is optically transmitted through skin tissue and bone tissue, and is optically absorbed by oxyhemoglobin and deoxyhemoglobin in blood. In NIRS, using such properties of near-infrared light, oxyhemoglobin concentration, deoxyhemoglobin concentration at the measurement site of the brain, and total hemoglobin concentration calculated from these are obtained. NIRS measures the activity state of the brain from the temporal change in the hemoglobin concentration, and performs image processing such as averaging processing and mapping on the acquired brain activity data to form an image.

  In NIRS, despite the fact that the measurement site is the brain (brain surface), there is actually a skull outside the brain, so that the position of the channel (sending position) is detected while confirming the position of the brain itself. It is impossible to position a position with high detection sensitivity determined by the position of the optical fiber and the light receiving fiber, specifically, an intermediate point between the light transmitting fiber position and the light receiving fiber position.

Therefore, instead of positioning the channel based on the brain position, the position of the channel is determined based on a reference point provided on the surface of the skull, thereby obtaining measurement reproducibility. In other words, the data at each channel position obtained by NIRS can only estimate the positional relationship with the brain (brain surface), although the position of the data corresponds to the skull surface.
Therefore, in order to associate the data of each NIRS channel position with the brain position, it is necessary to associate the skull surface with the brain surface. In the measurement, the skull surface and the brain are measured by MRI together with the NIRS data. Three-dimensional image data of the head including the surface is acquired, and the correspondence between the channel position and the brain surface is attached.

  By the way, regarding brain activity data acquired by NIRS, when comparing data between subjects, it is necessary to compare the same anatomical brain structures (for example, sensory areas and motor areas). However, there are individual differences in the anatomy of the brain. That is, the actual brain and skull shapes vary greatly from person to person. Therefore, the signal at each channel position of NIRS (or mapping data obtained by image processing thereof) is a signal obtained by detecting a signal at a different brain position for each individual, and even if NIRS data for each subject is simply compared. There is no meaning, and until now, there has been no comparison of individual brain activity data obtained by NIRS.

On the other hand, in recent years, in order to be able to compare NIRS data between individuals, standardization (standard brainization) by three-dimensional processing of the entire brain has been performed, and accurate statistical correspondence between the skull surface and the brain surface Attempts have been made to perform the attachment (see Non-Patent Document 1).
According to this, the association between the skull surface and the brain surface based on the International 10-20 method, which is the reference of the measurement position when measuring based on the skull shape, has been announced.
“Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping” (NeuroImage 21 (2004) 99-111)

  As in the prior art (Non-patent Document 1) described above, it is possible in principle to compare individual data by converting to a standard brain obtained by standardization of the brain by three-dimensional processing. Regarding the processing of the correspondence between the skull surface and the brain surface by standardization, it has not been completely established yet.

Therefore, the present invention is easy and significant in a transcranial brain function measuring apparatus such as NIRS or MEG without being converted into a standard brain, that is, without performing complicated three-dimensional arithmetic processing of the entire brain. An object of the present invention is to provide a brain function measuring apparatus capable of comparing various data.
Also provided is a transcranial brain function measuring device that can easily perform data comparison in a short time by shortening the data collection time and calculation time without performing complicated three-dimensional calculation processing of the entire brain. The purpose is to do.

  The transcranial brain function measuring device of the present invention made to solve the above-mentioned problem determines the detection position of brain activity data based on the shape of the skull surface of the subject, and acquires the brain activity data from this detection position Brain image data is acquired so that the positional relationship between the surface of the skull and the brain surface is matched when the brain activity data is collected by the transcranial brain activity data acquisition unit and the transcranial brain activity data acquisition unit. A brain image data acquisition unit and a brain surface image are formed based on the brain image data, a brain activity image is formed based on the brain activity data, and a composite image is formed by superimposing the brain surface image and the brain activity image. A transcranial brain function measuring device including a composite image display unit for displaying the composite image, wherein the composite image display unit displays a composite image based on feature points on the brain surface determined based on the brain image data. Image to scale So that an image conversion processing unit that performs conversion.

According to this invention, first, the transcranial brain activity data collection unit determines the detection position of brain activity data based on the shape of the head of each subject, and acquires brain activity data from this detection position. . As the transcranial brain activity data collection unit, NIRS, MEG, or the like can be used.
For example, when NIRS is used in the transcranial brain activity data collection unit, the detection position (channel position) of brain activity is determined by the attachment position of the NIRS transmission fiber and light reception fiber. When the MEG is used for the transcranial brain activity data collection unit, the pickup position of the detection signal based on the SQUID is determined based on the head shape of each subject.

  The brain image data acquisition unit acquires brain image data in such a manner that the collection position on the skull surface of the brain activity data by the transcranial brain activity data acquisition unit can correspond to the brain surface structure. As the brain image data acquisition unit, for example, a nuclear magnetic resonance diagnostic imaging apparatus (hereinafter referred to as MRI) can be used. The correspondence of the positional relationship between the skull surface and the brain surface is made to include a position specifying marker when acquiring brain image data.

The composite image display unit forms a brain surface image based on the brain image data, forms a brain activity image based on the brain activity data, and associates the brain surface image and the brain activity image (with the positions corresponding to the markers). ) A superimposed composite image is formed and displayed.
The brain surface image is preferably a brain rendered image, and the brain activity image is preferably a color-mapped topography image, but the image format is not limited thereto. By displaying a composite image obtained by superimposing the brain surface image and the brain activity image, the display is performed so that the correspondence between the brain activity information and the position on the brain surface is attached.

  Then, the image conversion processing unit performs image conversion for enlarging / reducing the synthesized image displayed by the synthesized image display unit with reference to the feature point on the brain surface determined based on the brain image data. The displayed image is displayed again.

Here, as a feature point on the brain surface, a boundary point between the motor cortex and the somatosensory cortex, which can be obtained on the basis of the intersection of the central groove and the midline, can be selected. In addition, the boundary point between the frontal cortex (also called prefrontal cortex) and the motor cortex (premotor cortex and motor cortex) that can be obtained geometrically with reference to the line connecting the front and rear commissures (premotor cortex) Can be selected. In addition, the front and rear end points and the left and right end points of the brain rendered image can be selected.
Based on these feature points, by performing image conversion to enlarge / reduce the composite image, the composite image is combined with another subject's composite image (composite image to be compared) and feature points with different brain structures. Adjust the length of the composite image to match.

  As a result, it is possible to display a composite image standardized with reference to feature points, and to compare data of brain activity information between different subjects.

  Further, if the image conversion processing unit is configured to be able to divide a composite image into a plurality of feature points on the brain surface and perform image conversion to enlarge / reduce each of the divided composite images, an anatomy By selecting a point that is a boundary of the brain structure as a feature point, it is possible to divide and normalize the brain for each identical anatomical structure and compare the data.

  In addition, as a feature point on the brain surface, a feature point that divides at least one of the frontal association cortex and motor cortex (premotor cortex and motor cortex) and motor cortex and somatosensory cortex is included. By doing so, it is possible to make a comparison for each brain function (thinking, movement, sense) localized in each brain structure part.

  In addition, by using a near-infrared spectrometer (NIRS) or a magnetoencephalograph (MEG) for the transcranial brain activity data acquisition unit, in NIRS and MEG measurement, data comparison between subjects has not been easy so far. In addition, it is possible to easily compare brain function data.

Hereinafter, an embodiment of a transcranial brain function measuring apparatus according to the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing a configuration of a transcranial brain function measuring apparatus according to an embodiment of the present invention. The transcranial brain function measuring device 10 includes a transcranial brain activity data acquisition unit 11, a brain image data acquisition unit 12, a composite image display unit 13, and an image conversion processing unit 14.

The NIRS is used for the transcranial brain activity data acquisition unit 11 that collects transcranial brain activity data. The transcranial brain function measurement by NIRS will be described. As shown in FIG. 2, channels (# 1, # 2,...) Serving as detection positions are defined on the skull surface (scalp) 21 of the subject. For example, the channels may be arranged in a grid pattern (or may be arranged according to the international 10-20 system). At this time, the channels are arranged based on the appearance feature points of the subject's ear, nose, and the like. Determine the position. And the attachment position of the light transmission fiber S and the light reception fiber D is defined so that the detection sensitivity in each channel position may become the highest. Specifically, the light transmitting fiber S and the light receiving fiber D are arranged so that the midpoint between the light transmitting fiber S and the light receiving fiber D is at the channel position.
In this way, NIRS acquires data with reference to the position relative to the skull surface.

  On the other hand, MRI is used for the brain image data acquisition unit 12 that acquires brain image data. When acquiring brain image data by MRI, by including a marker in the channel position, the brain and the skull surface in the brain activity data are associated with each other using the marker as a clue. As a result, the NIRS data acquired with reference to the position relative to the skull surface and the MRI data are associated with each other.

The composite image display unit 13 and the image conversion processing unit 14 are configured by a data processing computer. However, this computer may be provided independently as a data processing computer, or a computer used for NIRS or MRI control. May be used.
Data acquired by NIRS or MRI is sent to the composite image display unit 13 for image processing and image processing such as averaging processing and colorization.
At this time, as described above, the composite image in the composite image processing unit 13 is matched with the positional relationship between the images with reference to the marker included in the brain image data. As a result, the brain activity data by NIRS and the corresponding brain image data can be displayed correctly aligned.

The image conversion processing unit 14 performs image conversion processing for data comparison between data of different subjects, and is based on feature points on the brain surface determined based on brain image data acquired by MRI. Then, image conversion for enlarging or reducing the composite image is performed.
The feature points on the surface of the brain can be obtained here as the intersection of the central groove and the midline (shown as feature point X in FIG. 3), the boundary point between the motor cortex and the somatosensory cortex, and the anterior commissure The boundary point between the motor cortex and the frontal association area that can be obtained geometrically by setting a perpendicular to the brain surface with reference to the line connecting the posterior commissure (shown as a feature point Y in FIG. 2) And are used. In addition to these feature points X and Y, the front and rear end points and the left and right end points of the brain rendering image are used as feature points.

Based on these feature points, the image conversion processing unit 14 determines that the shape and size of the brain image match between the brain composite image to be compared and the reference brain composite image. Convert.
If the overall size is adjusted by this image conversion, correspondence between the two composite images can be easily achieved, and data comparison can be made by itself.

At this time, the brain image is divided based on the anatomical feature points X and Y, not just by matching the whole size, and the shape of the brain image is determined for each divided partial brain image. , Convert the size into an image and normalize it. That is, image conversion of brain images is performed for each frontal association area, motor cortex, and somatosensory cortex. As a result, the brain activity information contained in the composite image is also standardized for each frontal association area, motor cortex, and somatosensory cortex, and various statistical processes such as averaging and variance are performed for each anatomy. Can be carried out in a structural unit.
Next, image conversion processing by the transcranial brain function measuring apparatus of the present invention will be described by taking as an example a case where two synthesized images by different subjects are compared.

(Example)
FIGS. 3 to 7 are diagrams for explaining image conversion processing procedures by the transcranial brain function measuring apparatus according to an embodiment of the present invention. Each of them is acquired by NIRS on a brain surface render image acquired by MRI. The brain activity data is superimposed and displayed by color mapping to form a composite image (so-called brain function map). In the figure, the brain activity data is color-mapped according to the amount of activity in the area surrounded by the broken line.
3 to 7, columns A and B are images of different subjects A and B, respectively. Here, “A” indicates a reference-side composite image when performing data comparison, and “B” indicates a composite image on the side to be compared.

  Composite images A and B (b) shown in FIG. 3 are both original composite images before image conversion processing for subjects A and B is performed. The composite image A and the composite image B are greatly different in anatomical structure, and no meaningful comparison can be made even if the two composite images (function maps) are simply compared.

  As one improvement method for performing data comparison, image conversion processing is performed so that the front and rear and left and right lengths of the synthesized image are the same. That is, the front and rear, left and right end points are selected as the feature points of the image conversion process, and the two composite images are compared to have the same size. This method is also effective because some standardization is made, but it is not sufficient because it does not necessarily take into account the anatomical structure of the brain.

In the anatomical structure of the brain, areas such as motor areas and sensory areas are largely divided according to function. Therefore, it is effective to divide the brain for each region and compare the activity data of two brains in each unit.
Therefore, when dividing brain structures for each function and comparing brain activity data, the feature points for dividing the frontal association area and motor cortex, motor cortex and somatosensory cortex, are used as feature points. Feature points to be divided are defined, the brain is divided based on these feature points, and the synthesized image is normalized for each divided region.

  The VAC line 31 in FIG. 3B (a) is a line defined for dividing the frontal association area and the motor cortex. As shown in FIG. 2, this line has a feature point Y that is an intersection point with the brain surface when a perpendicular is established from the front commissure a with respect to a straight line connecting the front commissure a and the rear commissure b. Defined as a line drawn through and perpendicular to the midline.

  3B (a) is a point defined for dividing the motor cortex and the somatosensory cortex. This feature point X is defined as the intersection of the midline and the central groove. Then, the motor cortex and the somatosensory cortex are divided by the CS line 32 (see FIG. 3B (b)) drawn along the feature point X and perpendicular to the median line.

FIG. 4 and FIG. 5 are explanatory diagrams when normalizing the composite image B divided based on the VAC line 31 and the CS line 32.
First, as shown in FIG. 4A, the front part of the composite image B is enlarged (reduced) in the front-rear direction so as to match the composite image A, and partially normalized.
Subsequently, as shown in FIG. 4B, the center portion of the composite image B is enlarged (reduced) in the front-rear direction so as to match the composite image A, and partially normalized.
Further, as shown in FIG. 4C, the rear part of the composite image B is enlarged (reduced) in the front-rear direction so as to match the composite image A, and partially normalized.
Then, as shown in FIG. 5, the front, center, and rear portions of the composite image B standardized in FIGS. 4A to 4C are integrated and integrated. In the composite image B in FIG. 5, the front-rear direction of the composite image B is normalized with reference to the feature points.

  Next, as shown in FIG. 6, the length of the composite image B in the left-right direction is enlarged (reduced) according to the composite image A. In the normalization in the left-right direction, the left and right end points are simply determined so that the left and right lengths of the composite image A and the composite image B are the same.

FIG. 7 is a diagram summarizing the first and last changes of the composite image B by the image conversion processing described in FIGS. 4 to 6, and FIG. 7B (a) shows the composite image B before the image conversion processing. FIG. 7B (b) shows a final composite image B standardized by image conversion processing using feature points X and Y.
As a result of the image conversion processing using the feature points X and Y, the brain activity data included in the composite image B is also standardized separately for each feature point X and Y. Based on the data, significant data comparisons regarding brain function can be made.

  In the above embodiment, the feature point X for dividing the association area and the motor area and the feature point Y for dividing the motor area and the sensory area have been described. However, the selection of the feature points is not limited to these. Other feature points may be used as long as they are effective in measuring brain activity. In addition, two feature points X and Y are selected as feature points for dividing the brain. However, the feature points may be one, or may be increased to three or more.

  Furthermore, in this embodiment, NIRS is used as the transcranial brain activity data acquisition unit. However, the same applies when MEG is used instead of NIRS, and these are merely examples, and other than NIRS and MEG. A measuring instrument that performs transcranial measurement may be used.

  The present invention can be used for a transcranial brain function measuring apparatus that measures brain function transcranially.

The block diagram which shows the structure of the transcranial brain function measuring apparatus which is one Embodiment of this invention. The figure explaining the relationship between the position of the light transmission fiber in NIRS, a light reception fiber, the skull surface, and the brain surface. The figure explaining the synthesized image in the transcranial brain function measuring apparatus which is one Embodiment of this invention. The figure explaining the image conversion process in the transcranial brain function measuring apparatus which is one Embodiment of this invention. The figure explaining the image conversion process in the transcranial brain function measuring apparatus which is one Embodiment of this invention. The figure explaining the image conversion process in the transcranial brain function measuring apparatus which is one Embodiment of this invention. The figure explaining the image conversion process in the transcranial brain function measuring apparatus which is one Embodiment of this invention.

Explanation of symbols

10: Transcranial brain function measuring device 11: Transcranial brain activity data acquisition unit (NIRS)
12: Brain image data acquisition unit (MRI)
13: Composite image display unit 14: Image conversion processing unit 21: Skull surface 22: Brain 31: VAC line 32: CS line

Claims (4)

Determine the detection position of brain activity data on the basis of the shape of the skull surface of the subject, and acquire a brain activity data at this detection position, a transcranial brain activity data acquisition unit,
A brain image data acquisition unit for acquiring brain image data so that the correspondence of the positional relationship between the skull surface and the brain surface at the time of collecting brain activity data by the transcranial brain activity data acquisition unit;
A composite image display that forms a brain surface image based on brain image data, forms a brain activity image based on brain activity data, and forms and displays a composite image in which the brain surface image and brain activity image are superimposed A transcranial cerebral function measuring device comprising:
The composite image display unit has an image conversion processing unit that performs image conversion for enlarging or reducing the composite image with reference to feature points on the brain surface determined based on the brain image data. measuring device. The image conversion processing unit is configured to divide a composite image into a plurality of features based on feature points on the brain surface, and to perform image conversion for enlarging or reducing each of the divided composite images. The transcranial brain function measuring device according to claim 1. The feature point on the brain surface includes a feature point that divides at least one of the frontal association area and the motor cortex and the motor cortex and the somatosensory cortex. Transcranial brain function measuring device. The transcranial brain function measuring device according to claim 1, wherein a near-infrared spectrometer (NIRS) or a magnetoencephalograph (MEG) is used for the transcranial brain activity data acquisition unit.