JP2013144068A - Treatment support apparatus and control program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To generate display data that are effective to the treatment planning and treatment of a nerve endoscopic surgery.SOLUTION: A treatment support apparatus 100 includes: a region division part 4 in which volume data collected from a patient head region are region-divided, and that thereby extracts a cerebral ventricle bottom region, a vascular territory, and a nerve bundle region; a bottom wall thickness measuring part that measures the wall thickness of the cerebral ventricle bottom region; a distance measuring part 7 that measures the distances from the predetermined position of the cerebral ventricle bottom region to the vascular territory and to the nerve bundle region; a fenestration candidate region setting part 8 that sets a fenestration candidate region to the cerebral ventricle bottom region based on the measurement result of the wall thickness and the distance; a PVR image data generation part 10 that generates perspective projection image data based on the volume data; a display data generation part 12 that generates display data for supporting a treatment planning by superimposing the position information of the fenestration candidate region to the perspective projection image data; and a display part 13 that displays the display data for supporting the treatment planning.

Description

  Embodiments described herein relate generally to a treatment support apparatus and a control program for the purpose of assisting treatment planning and treatment of neuroendoscopic surgery.

  Medical image diagnosis has made rapid progress with an MRI apparatus, an X-ray CT apparatus, and the like that have been put into practical use with the recent development of computer technology, and is indispensable in today's medical care. In particular, MRI and X-ray CT systems enable real-time display of image data by increasing the speed and performance of the biological information detection unit and arithmetic processing unit, and further collecting three-dimensional image information (volume data). Since the generation / display of the three-dimensional image data using the volume data is facilitated, it is possible to provide medical information effective not only for detecting the diseased part but also for formulating a treatment plan for the diseased part.

  In particular, in recent years, treatment plans and treatments for various types of neuroendoscopic surgery including third ventricular fenestration have been performed based on image information of the patient's head collected by the above-described medical diagnostic imaging apparatus. It became as to be.

  Third ventricular fenestration is used to prevent headaches, vomiting, disturbances of consciousness, etc. that occur with increasing brain pressure when there is an obstruction site in the patient's brain that prevents cerebrospinal fluid circulation for some reason. And an outflow hole (a fenestration) for draining the cerebrospinal fluid stored in the third ventricle to the outside of the ventricle. This is performed under observation of endoscopic image data collected by the endoscope apparatus. In addition, a treatment plan for the third ventricular fenestration based on volume data or three-dimensional image data collected by MRI imaging or X-ray CT imaging of the patient's head has been developed.

JP 2005-323793 A

   As described above, the treatment efficiency is improved by formulating a treatment plan based on volume data or three-dimensional image data collected by MRI imaging or X-ray CT imaging of the head region, or treatment under observation of endoscopic image data. Greatly improved.

   On the other hand, in the third ventricular fenestration, etc., when performing the fenestration on the treatment target site (hereinafter referred to as fenestration candidate region) of the ventricular bottom region, it was used for the fenestration. Serious complications caused by damage to blood vessels and nerve bundles caused by the treatment device must be prevented. However, in the above-described conventional methods, fenestration candidate regions to be subjected to fenestration and the opening of the fenestration region are considered. Since it was impossible to accurately grasp the blood vessel region and the nerve bundle region located in the vicinity of the window candidate region, there was a problem that a highly safe fenestration operation could not be performed.

  The present disclosure has been made in view of the above-described problems, and its purpose is to damage peripheral blood vessels and nerve bundles when performing neuroendoscopic surgery on a patient's head region. It is an object of the present invention to provide a treatment support apparatus and a control program capable of presenting position information of a suitable fenestration candidate region not given to a medical staff such as an operator.

  In order to solve the above-described problem, the treatment support apparatus according to the present embodiment generates display data for treatment plan support effective for a treatment plan for neuroendoscopic surgery based on volume data collected from a patient's head region. In the treatment support apparatus that performs display, region classification means for extracting at least one of a blood vessel region or a nerve bundle region and a ventricular bottom region by segmenting the volume data, and measuring a wall thickness of the ventricular bottom region Base wall thickness measuring means, distance measuring means for measuring a distance from a predetermined position of the ventricular bottom region to the blood vessel region or the nerve bundle region, a measurement result of the wall thickness, and a measurement result of the distance A fenestration candidate region setting means for setting a fenestration candidate region for the ventricle bottom region, and image data for generating image data based on the volume data. Generating means, display data generating means for generating treatment plan support display data by superimposing position information of the fenestration candidate region on the image data, and display means for displaying the treatment plan support display data. It is characterized by having prepared.

The block diagram which shows the whole structure of the treatment assistance apparatus in this embodiment. The block diagram which shows the specific structure of the volume data memory | storage part with which the treatment assistance apparatus of this embodiment is provided. The figure for demonstrating the wall thickness distribution data produced | generated by the measuring method of the bottom wall thickness in this embodiment, and a wall thickness distribution data production | generation part. The block diagram which shows the specific structure of the PVR image data generation part with which the treatment assistance apparatus of this embodiment is provided. The figure which shows the specific example of the display data for treatment plan assistance produced | generated / displayed in this embodiment. The figure which shows the specific example of the display data for treatment assistance produced | generated / displayed in this embodiment. The flowchart which shows the production | generation / display procedure of the display data for treatment plan assistance in this embodiment. The flowchart which shows the production | generation / display procedure of the display data for treatment assistance in this embodiment.

  Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

  The treatment support apparatus of the present embodiment divides the volume data collected in advance by MRI imaging of the patient's head region into regions, thereby dividing the bottom region of the third ventricle (hereinafter referred to as the ventricle bottom region) and blood vessels. Based on the distance between the blood vessel region or nerve bundle region and each of a plurality of measurement points set in the ventricle bottom region and the wall thickness of the ventricle bottom region at these measurement points A fenestration candidate region suitable for neuroendoscopic surgery is set. Next, the information on the fenestration region, the blood vessel region, and the nerve bundle region is superimposed on the virtual endoscopic perspective projection image data generated using the volume data and the MPR image data of a predetermined cross section, and the blood vessel region Alternatively, the treatment plan support display data is generated by adding the measurement result of the shortest distance between the nerve bundle region and the fenestration candidate region.

  Furthermore, the treatment support apparatus according to the present embodiment converts the MPR image data generated by using the endoscopic image data collected by endoscopic imaging of the head region and the above-described volume data at the time of neuroendoscopic surgery. The display data for treatment support is generated by superimposing the information on the fenestration candidate region, the blood vessel region, and the nerve bundle region and adding the measurement result of the shortest distance.

  In the embodiment described below, a case will be described in which display data for treatment plan support and display data for treatment support effective for neuroendoscopic surgery (a fenestration) for the third ventricle of the patient's head is generated. The application site of neuroendoscopic surgery is not limited to the third ventricle. In addition, a case where a ventricle bottom region and a blood vessel region and a nerve bundle region close to the ventricle bottom region are extracted based on volume data collected by an MRI apparatus will be described. However, other medical images such as an X-ray CT apparatus are described. The above-described extraction may be performed based on image information collected by the diagnostic apparatus.

(Device configuration)
The overall configuration of the treatment support apparatus in this embodiment will be described with reference to the block diagram of FIG.

  The treatment support apparatus 100 of the present embodiment shown in FIG. 1 uses an MRI apparatus installed separately, and is collected by T1-weighted or T2-weighted MRI imaging of the head region when the contrast medium is not administered and when the contrast medium is administered. A volume data acquisition unit 2 that receives volume data and volume data collected by diffusion-weighted MRI imaging for the head region together with imaging position information; a volume data storage unit 3 that stores the obtained volume data; By segmenting these volume data based on a predetermined standard brain model (segmentation), a segmentation unit 4 for extracting a cerebral ventricular bottom region, a blood vessel region and a nerve bundle region located in the vicinity thereof, and a ventricular bottom region Bottom wall that measures the wall thickness (bottom wall thickness) at each of a plurality of measurement points set inside A measurement unit 5; a wall thickness distribution data generation unit 6 that generates wall thickness distribution data of the ventricular bottom region based on the obtained measurement result of the bottom wall thickness; and a blood vessel region or a nerve bundle region and a ventricular bottom region A distance measurement unit 7 that measures the distance to the above-described measurement point set to 1, a measurement result of the bottom wall thickness in the ventricular bottom region, and a measurement result of the distance from the measurement point to the blood vessel region or nerve bundle region Based on the volume data read from the volume data storage unit 3, a window-pane candidate region setting unit 8 that sets a window-opening candidate region suitable for the neuroendoscopic operation based on the MPR (multi planar reconstruction) image MPR image data generation unit 9 that generates data, and PV that generates virtual endoscopic perspective image data in the third ventricle based on the volume data described above An endoscopic image data acquisition unit 11 that includes an image data generation unit 10 and that receives endoscopic image data in the third ventricle supplied from a separately installed endoscopic device together with imaging position information; Region data (hereinafter referred to as fenestration candidate region data, blood vessel region data, nerve bundle region data), wall thickness distribution data, MPR image data, PVR image data A display data generator for generating treatment plan support display data effective for the treatment plan of the neuroendoscopic surgery and treatment support display data effective for the neuroendoscopic surgery based on the endoscopic image data and the like 12, a display unit 13 for displaying the obtained treatment plan support display data and treatment support display data, an input unit 14 for inputting patient information and various instruction signals, and the treatment support apparatus 100. And a system control unit 15 which collectively controls the respective units described above.

  Next, the configuration and function of each of the units included in the treatment support apparatus 100 will be described in more detail with reference to FIGS.

  As shown in FIG. 2, the volume data storage unit 3 includes an intracerebral tissue image information storage unit 31, a blood vessel emphasized image information storage unit 32, and a nerve bundle emphasized image information storage unit 33, and volume data from a separately installed MRI apparatus. It has a function of storing various volume data supplied via the acquisition unit 2.

  That is, the brain tissue image information storage unit 31 stores, for example, volume data collected by T1-weighted or T2-weighted MRI imaging of the head region as brain tissue volume data, and the blood vessel emphasized image information storage unit 32. The difference value of the volume data collected by the similar MRI imaging with respect to the head region at the time of contrast medium administration and when the contrast medium is not administered is stored as blood vessel enhancement volume data. Further, the nerve bundle emphasized image information storage unit 33 stores, for example, volume data collected by diffusion tensor imaging (DTI) MRI imaging as nerve bundle emphasized volume data. Note that imaging position information for a patient is added as supplementary information to each of the brain tissue volume data, blood vessel enhancement volume data, and nerve bundle enhancement volume data described above.

  Then, the intracerebral tissue volume data stored in the intracerebral tissue image information storage unit 31 includes a ventricular bottom region extraction unit 41, an MPR image data generation unit 9, and a PVR image data generation unit 10 described later included in the region classification unit 4. Supplied to. The blood vessel enhancement volume data stored in the blood vessel enhancement image information storage unit 32 is supplied to a blood vessel region extraction unit 42 (to be described later) included in the region segmentation unit 4 and is stored in the nerve bundle enhancement image information storage unit 33. The emphasized volume data is supplied to a later-described nerve bundle region extracting unit 43 provided in the region dividing unit 4.

  Returning to FIG. 1, the region segmentation unit 4 performs region segmentation based on a standard brain model in which tissue volume data, blood vessel enhancement volume data, and nerve bundle enhancement volume data read from the volume data storage unit 3 are created or collected in advance. (Segmentation) has a function of extracting the ventricle bottom region, blood vessel region, and nerve bundle region, and the ventricle bottom region extraction unit 41, blood vessel region extraction unit 42, nerve bundle region extraction unit 43, and standard brain model storage A portion 44 is provided.

  The ventricle bottom region extraction unit 41 expands / reduces the brain tissue volume data read from the brain tissue image information storage unit 31 of the volume data storage unit 3 based on the standard brain model read from the standard brain model storage unit 44. A plurality of ventricles including the third ventricle are detected by performing the processing and the rotation processing, and the ventricle bottom region is extracted based on the detection results.

  Similarly, the blood vessel region extracting unit 42 performs predetermined processing on the blood vessel emphasized volume data read from the blood vessel emphasized image information storage unit 32 of the volume data storage unit 3 based on the above-described standard brain model, thereby causing the ventricle bottom portion. A blood vessel region located in the vicinity of the region is extracted, and the nerve bundle region extracting unit 43 performs the same processing on the nerve bundle emphasized volume data read from the nerve bundle emphasized image information storage unit 33 of the volume data storage unit 3. To extract a nerve bundle region located in the vicinity of the ventricle bottom region.

  A specific method of segmentation using the volume data collected by the MRI apparatus and the standard brain model is described in JP-T-2011-514190 and the like, and detailed description thereof is omitted.

  Next, the bottom wall thickness measurement unit 5 is based on the MPR image data generated by the MPR image data generation unit 9 using the brain tissue volume data read from the brain tissue image information storage unit 31 of the volume data storage unit 3. The bottom wall thickness at a plurality of measurement points set at a predetermined interval with respect to the ventricle bottom region is measured. In this case, the MPR image data generation unit 9 includes, for example, a plurality of crossings that are perpendicular to the ventricle bottom region extracted by the ventricle bottom region extraction unit 41 of the region sorting unit 4 and intersect at the center of the ventricle bottom region. A plurality of MPR image data indicating a longitudinal section of the ventricular bottom region is generated by forming MPR sections and setting these MPR sections with respect to the intracerebral tissue volume data described above.

  Then, the bottom wall thickness measurement unit 5 measures the bottom wall thickness at the measurement points set at predetermined intervals in the ventricle bottom region using the longitudinal image of the ventricle bottom region indicated in each MPR image data. The wall thickness distribution data generation unit 6 generates wall thickness distribution data based on the measurement result of the bottom wall thickness measured by the bottom wall thickness measurement unit 5.

  FIG. 3 is a diagram for explaining the measurement method of the bottom wall thickness in the bottom wall thickness measurement unit 5 and the wall thickness distribution data generated by the wall thickness distribution data generation unit 6. That is, FIG. 3A shows a plurality of MPR cross sections Mp-n (n = 1 to N) formed by an MPR cross section forming section described later provided in the MPR image data generation section 9. The cross section Mp-n is formed so as to intersect with the ventricle bottom region Ra extracted by the ventricle bottom region extraction unit 41 of the region segmentation unit 4 and intersect at the center of the ventricle bottom region Ra. In the MPR cross section Mp-n, measurement points P-nm (n = 1 to N, m = 1 to M) are set at predetermined intervals. However, in FIG. 3A, only the measurement points P-11 to P-1M set in the MPR section Mp-1 are shown.

  FIG. 3B shows, for example, MPR image data Im-1 generated by the MPR image data generation unit 9 in the MPR section Mp-1, and MPR image data indicating a longitudinal section of the ventricle bottom region Ra. Based on Im-1, the bottom wall thickness of the third ventricle at the measurement points P-11 to P-1M is measured.

  On the other hand, FIG. 3C shows the bottom wall thickness measured by the bottom wall thickness measurement unit 5 at the measurement points P-nm (n = 1 to N, m = 1 to M) of the MPR sections Mp-1 to Mp-N. A specific example of the wall thickness distribution data Dt generated by the wall thickness distribution data generation unit 6 based on the measurement result is shown. This wall thickness distribution data Dt connects measurement points having substantially the same wall thickness. This is indicated by a plurality of curves (iso-thick lines) formed by.

  Returning to FIG. 1 again, the distance measuring unit 7 is configured to extract the blood vessel region and the nerve bundle region extracted by the blood vessel region extracting unit 42 of the region dividing unit 4 from each of the above-described measurement points set in the ventricular bottom region, for example. The distance to the nerve bundle region extracted by the extraction unit 43 is measured, and further, the shortest distance between the fenestration candidate region set by the later-described fenestration candidate region setting unit 8 and the above-described blood vessel region or nerve bundle region is determined. measure.

  On the other hand, the fenestration candidate region setting unit 8 measures the measurement result of the bottom wall thickness supplied from the bottom wall thickness measurement unit 5 and the distance between the measurement point supplied from the distance measurement unit 7 and the blood vessel region or nerve bundle region. Based on the results, a safe fenestration candidate region that does not damage the blood vessels and nerve bundles is set for the ventricle bottom region. Specifically, the shortest distance from the measurement point set in the ventricle bottom region to the blood vessel region and nerve bundle region existing in the vicinity of the ventricle bottom region is measured, and the distance to the blood vessel region and nerve bundle region is measured. A fenestration candidate region suitable for the neuroendoscopic surgery is set based on the position information of the measurement point whose distance is longer than the predetermined distance threshold value α and whose bottom wall thickness is thinner than the predetermined wall thickness threshold value β.

  The MPR image data generation unit 9 includes an MPR cross-section forming unit and a voxel extraction unit (not shown). The MPR cross-section forming unit is, for example, a plurality of crossing units perpendicular to the ventricular bottom region and in the center of the ventricular bottom region. The MPR cross section (see FIG. 3A) is formed. On the other hand, the voxel extraction unit sets the above-described MPR sections for the brain tissue volume data read from the brain tissue image information storage unit 31 of the volume data storage unit 3, and the brain tissue existing in these MPR sections. By extracting the voxels of the volume data, a plurality of MPR image data showing a longitudinal section of the ventricular bottom region is generated.

  The PVR image data generation unit 10 renders the intracerebral tissue volume data read from the intracerebral tissue image information storage unit 31 of the volume data storage unit 3 to perform virtual endoscopic perspective projection image data (PVR image data). ), And includes a viewpoint / line-of-sight direction setting unit 101, a volume data correction unit 102, an opacity / tone setting unit 103, and a rendering processing unit 104, as shown in FIG.

  The viewpoint / line-of-sight direction setting unit 101 sets a viewpoint inside the third ventricle detected by the ventricle bottom region extraction unit 41 of the region segmentation unit 4, and further uses this viewpoint as a starting point for the ventricle bottom region extraction unit A line-of-sight direction perpendicular to the ventricle bottom region extracted by 41 is set. On the other hand, the volume data correction unit 102 uses the line-of-sight direction and the brain set by the viewpoint / line-of-sight direction setting unit 101 for the voxel value of the brain tissue volume data read from the brain tissue image information storage unit 31 of the volume data storage unit 3. The opacity / color tone setting unit 103 sets opacity and color tone based on the corrected voxel value. The rendering processing unit 104 performs perspective projection on the ventricular bottom region and its peripheral region by rendering the above-described brain tissue volume data based on the opacity and color tone set by the opacity / color tone setting unit 103. Generate image data.

  Next, the display data generation unit 12 illustrated in FIG. 1 is supplied from the perspective projection image data and the MPR image data generation unit 9 supplied from the PVR image data generation unit 10 when formulating a treatment plan for neuroendoscopic surgery. Mating window candidate area data supplied from the window opening candidate area setting unit 8 to the MPR image data, blood vessel area data supplied from the blood vessel area extracting unit 42, nerve bundle area data supplied from the nerve bundle extracting unit 43, and wall thickness By superimposing the wall thickness distribution data supplied from the distribution data generation unit 6 and adding the measurement result of the shortest distance between the fenestration candidate region supplied from the distance measurement unit 7 and the blood vessel region or nerve bundle region The treatment plan support display data effective for the treatment plan of the neuroendoscopic surgery is generated.

  Further, the display data generation unit 12 obtains the endoscope image data acquisition unit 11 from the endoscope apparatus separately installed in the case of neuroendoscopic surgery for the fenestration candidate region based on the above-described treatment plan support display data. The fenestration window candidate area data, blood vessel area data, nerve bundle area data, and wall thickness distribution data described above are superimposed on the endoscope image data supplied through the shortest distance between the fenestration candidate area and the blood vessel area or nerve bundle area. By adding the distance measurement result, display data for treatment support effective for the neuroendoscopic surgery is generated.

  The display data generation unit 12 includes a data storage unit that stores the aforementioned fenestration candidate region data, blood vessel region data, nerve bundle region data, and wall thickness distribution data used for generating treatment plan support display data. The above-mentioned various data stored in the data storage unit are used again in the generation of display data for treatment support.

  Next, specific examples of the treatment plan support display data and the treatment support display data generated by the display data generation unit 12 are shown in FIGS.

  The treatment plan support display data shown in FIG. 5 shows the display data Ba based on the perspective projection image data Ip obtained when the viewpoint is set inside the third ventricle and the longitudinal section of the ventricle bottom region. Display data Bb based on the MPR image data Ima, and the display data Ba is supplied from the fenestration window candidate region setting unit 8 to the above-described perspective projection image data Ip supplied from the PVR image data generation unit 10. Fenestration candidate region data Rx, blood vessel region data Rv supplied from the blood vessel region extraction unit 42, nerve bundle region data Rn supplied from the nerve bundle extraction unit 43, and wall thickness supplied from the wall thickness distribution data generation unit 6 It is generated by superimposing the distribution data Dt.

  On the other hand, the display data Bb is, for example, described in the MPR image data Ima generated by the MPR image data generation unit 9 in the MPR cross section Mpa substantially perpendicular to the ventricle bottom region indicated by the one-dot chain line position marker in the display data Ba. The window candidate region data Rx, the blood vessel region data Rv, and the nerve bundle region data Rn (not shown) are superimposed, and the measurement result Lmin of the shortest distance between the fenestration candidate region and the blood vessel region or the nerve bundle region is added. Generated by.

  The display data for treatment support shown in FIG. 6 includes display data Ca based on endoscope image data Ie obtained by inserting the distal end portion of the endoscope into the third ventricle and the brain. Display data Cb based on MPR image data Imb showing a longitudinal section of the room bottom region is provided, and display data Ca is supplied from an endoscope apparatus separately installed via the endoscope image data acquisition unit 11. Is generated by superimposing the aforementioned fenestration region data Rx, blood vessel region data Rv, nerve bundle region data Rn, and wall thickness distribution data Dt on the above-described endoscope image data Ie.

  In this case, the endoscopic image data Ie of the display data Ca indicates the treatment device Fo that treats the fenestration candidate region inserted through a forceps channel of an endoscope scope (not shown), and the display data Ca By locating the distal end portion of the treatment device Fo at a suitable position of the fenestration candidate region under the observation, it becomes possible to perform an accurate and safe neuroendoscopic operation.

  On the other hand, the display data Cb includes, for example, the above described fenestrations in the MPR image data Imb generated by the MPR image data generation unit 9 in the MPR cross section Mpb substantially perpendicular to the ventricle bottom indicated by the one-dot chain line position marker in the display data Ca. The candidate area data Rx, the vascular area data Rv, and the nerve bundle area data Rn (not shown) are superimposed, and the measurement result of the shortest distance Lmin between the fenestration candidate area and the blood vessel area or the nerve bundle area is determined. It is generated by adding position information.

  The registration of the fenestration candidate region data Rx, the vascular region data Rv, the nerve bundle region data Rn, the wall thickness distribution data Dt, and the endoscope image data Ie based on the volume data collected by the MRI apparatus is performed using the volume data. This is performed based on the photographing position information added to and the photographing position information added to the endoscope image data.

  Further, the position of the MPR cross section Mpb indicated by the alternate long and short dash line in the display data Ca is set by the detection result of a position detector (not shown) provided at the distal end portion of the treatment device Fo, for example, the distal end portion of the treatment device Fo and its It is set based on position information obtained from a plurality of position detectors provided in the vicinity and center position information of the fenestration window candidate region Rx. Further, the position and direction of the treatment device Fo shown in the display data Cb can be set by a plurality of pieces of position information supplied from the position detector described above.

  Next, the display unit 13 in FIG. 1 displays the treatment plan support display data (see FIG. 5) generated by the display data generation unit 12 when formulating a treatment plan for neuroendoscopic surgery and the treatment support display data generated during treatment. (See FIG. 6), and a conversion processing unit that performs conversion processing such as D / A conversion and television format conversion on the treatment plan support display data and the treatment support display data and the conversion processing described above A monitor (none of which is shown) for displaying the display data is provided.

  The input unit 14 includes various input devices such as a keyboard, a switch, a selection button, and a mouse (not shown) and a display panel, and inputs patient information, selection of a treatment plan support mode and a treatment support mode, selection of a standard brain model, and perspective projection. Setting of image data generation condition and MPR image data generation condition, setting of display data generation condition, setting of MPR cross section and measurement point arrangement interval for ventricular bottom region, distance threshold value α and wall thickness necessary for setting fenestration candidate region The threshold value β is set and various instruction signals are input.

  The system control unit 15 includes a CPU (not shown) and an input information storage unit, and the input information storage unit stores the above-described various information input / selected / set in the input unit 14. Then, the CPU comprehensively controls each unit of the treatment support apparatus 100 based on these pieces of information, and generates / displays treatment plan support display data at the time of formulation of a treatment plan for neuroendoscopic surgery and neuroendoscopy. Generation / display of treatment support display data during mirror surgery is executed.

(Generation / display procedure of display data for treatment plan support)
Next, a procedure for generating / displaying treatment plan support display data according to the present embodiment will be described with reference to the flowchart of FIG.

  Prior to the generation of the treatment plan support display data, a medical worker (hereinafter referred to as an operator) who operates the treatment support apparatus 100 inputs patient information, selects a standard brain model, and a perspective projection image at the input unit 14. After setting the data generation conditions and MPR image data generation conditions, setting the display data generation conditions, setting the MPR cross section and measurement point array interval for the ventricular bottom region, setting the distance threshold α and the wall thickness threshold β, etc. Select the treatment plan support mode. The above-described information initially set in the input unit 14 is stored in the input information storage unit of the system control unit 15. (Step S1 and Step S2 in FIG. 7).

  When the above initial setting is completed, the operator inputs a display data generation start instruction signal for treatment plan support at the input unit 14 and receives the above display data generation start instruction signal via the system control unit 15. The volume data acquisition unit 2 acquires intracerebral tissue volume data, blood vessel enhancement volume data, and nerve bundle enhancement volume data using imaging position information supplied from a separately installed MRI apparatus as supplementary information to obtain a volume data storage unit 3 is stored in the intracerebral tissue image information storage unit 31, the blood vessel emphasized image information storage unit 32, and the nerve bundle emphasized image information storage unit 33 (step S <b> 3 in FIG. 7).

  On the other hand, the ventricle bottom region extraction unit 41 of the region classification unit 4 reads the brain tissue volume data read from the brain tissue image information storage unit 31 of the volume data storage unit 3 from the standard brain model storage unit 44. A plurality of ventricles including the third ventricle are detected by performing expansion / reduction processing and rotation processing based on the model, and a ventricle bottom region is extracted based on these detection results.

  Similarly, the blood vessel region extraction unit 42 performs a predetermined process on the blood vessel enhancement volume data read from the blood vessel enhancement image information storage unit 32 to extract a blood vessel region located in the vicinity of the ventricle bottom region, and The bundle region extraction unit 43 performs a similar process on the nerve bundle enhancement volume data read from the nerve bundle enhancement image information storage unit 33, thereby extracting a nerve bundle region located near the ventricle bottom region (FIG. 7). Step S4).

  Next, the MPR image data generation unit 9 applies the ventricle bottom region extracted by the ventricle bottom region extraction unit 41 of the region sorting unit 4 based on the MPR cross-section setting information supplied from the system control unit 15. A plurality of MPR cross-sections that intersect perpendicularly at the center of the ventricular bottom region are formed. Then, the above MPR sections are set for the brain tissue volume data read from the brain tissue image information storage section 31 of the volume data storage section 3, and the voxels of the brain tissue volume data existing in these MPR sections are set. By extracting, a plurality of MPR image data showing a longitudinal section of the ventricle bottom region is generated.

  Next, the bottom wall thickness measurement unit 5 measures the wall thickness at the measurement point on the MPR cross section using the longitudinal image of the ventricle bottom region shown in each MPR image data, and the wall thickness distribution data generation unit 6 Then, wall thickness distribution data is generated based on the bottom wall thickness at the measurement point of the ventricle bottom region measured by the bottom wall thickness measurement unit 5 using a plurality of MPR image data (step S5 in FIG. 7).

  The distance measurement unit 7 is extracted by the blood vessel region and nerve bundle region extraction unit 43 extracted by the blood vessel region extraction unit 42 of the region segmentation unit 4 from each of a plurality of measurement points set in the ventricle bottom region. The distance to the nerve bundle region is measured (step S6 in FIG. 7), and the fenestration window region setting unit 8 supplies the measurement result of the bottom wall thickness supplied from the bottom wall thickness measurement unit 5 and the distance measurement unit 7. A fenestration candidate region that does not damage the blood vessel or nerve bundle is set for the ventricle bottom region based on the measurement result of the distance between the measurement point described above and the blood vessel region or nerve bundle region (FIG. 7). Step S7).

  On the other hand, the PVR image data generation unit 10 generates virtual endoscopic perspective projection image data by rendering the brain tissue volume data read from the brain tissue image information storage unit 31 of the volume data storage unit 3. (Step S8 in FIG. 7).

  Next, the display data generation unit 12 generates the perspective projection image data supplied from the PVR image data generation unit 10 and a predetermined section supplied from the MPR image data generation unit 9 (for example, the MPR section Mpa in FIG. 5). Mating window candidate area data supplied from the window opening candidate area setting unit 8 to the MPR image data, blood vessel area data supplied from the blood vessel area extracting unit 42, nerve bundle area data supplied from the nerve bundle extracting unit 43, and wall thickness The wall thickness distribution data supplied from the distribution data generation unit 6 is superimposed, and further, the fenestration candidate region supplied from the distance measurement unit 7 (that is, the fenestration closest to the blood vessel region or nerve bundle region). By adding the measurement result of the shortest distance between the measurement point in the candidate area) and the blood vessel area or nerve bundle area, display data for treatment plan support effective for the treatment plan is generated. 7 is displayed on the monitor of the display unit 13 (step S9 in FIG. 7), and the above-mentioned fenestration region data, blood vessel region data, nerve bundle region data, and wall thickness distribution data used for generating treatment plan support display data. The shortest distance measurement result is stored in its own data storage unit (step S10 in FIG. 7).

(Procedure for generating / displaying treatment support display data)
Next, a procedure for generating / displaying treatment support display data in the present embodiment will be described with reference to the flowchart of FIG.

  When the formulation of the treatment plan based on the treatment plan support display data is completed, the operator selects the treatment support mode at the input unit 14 and further inputs a display data generation start instruction signal for treatment support. After that, the distal end portion of the endoscope scope and the distal end portion of the treatment device are inserted into the third ventricle of the patient's head through the introduction catheter (Step S21 and Step S22 in FIG. 8).

  The endoscope image data acquisition unit 11 that has received the above-described display data generation start instruction signal via the system control unit 15 is an imaging that is separately provided and supplied from an endoscope apparatus that includes the above-described endoscope scope. Endoscopic image data in the third ventricle using the position information as supplementary information and the position information of the treatment device tip and its vicinity supplied from the position detector of the treatment device are acquired (step S23 in FIG. 8).

  Next, the MPR image data generation unit 9 forms an MPR cross section including the treatment device based on the position information of the treatment device tip and its vicinity and the center position information of the fenestration candidate region, and the volume data storage unit 3 The above MPR cross section is set for the intracerebral tissue volume data read from the intracerebral tissue image information storage unit 31. Then, by extracting the voxels of the intracerebral tissue volume data existing in the MPR cross section, MPR image data showing the vertical cross section of the ventricle bottom region is generated (step S24 in FIG. 8).

  On the other hand, the display data generation unit 12 reads the endoscope image data supplied from the endoscope image data acquisition unit 11 and the MPR image data supplied from the MPR image data generation unit 9 from its own data storage unit. The fenestration area data, blood vessel area data, nerve bundle area data, and wall thickness distribution data are superimposed, and the result of the shortest distance measurement between the fenestration candidate area and the blood vessel area or nerve bundle area is added to the treatment. Effective treatment support display data is generated and displayed on the monitor of the display unit 13 (steps S25 and S26 in FIG. 8).

  According to the embodiments of the present disclosure described above, when performing a neuroendoscopic operation on the patient's head region, suitable fenestration candidate positions that do not damage surrounding blood vessels and nerve bundles are obtained. It can be presented to medical personnel such as surgeons.

  In particular, a fenestration candidate region suitable for neuroendoscopic surgery based on the position information of the ventricle bottom region and the bottom wall thickness information extracted by segmenting the volume data and the position information of the blood vessel region and nerve bundle region Therefore, it is possible to set a fenestration candidate region that does not damage blood vessels and nerve bundles located in the vicinity of the ventricular bottom region.

  In addition, the treatment plan support display data in the present embodiment is the perspective projection image data and MPR image data generated by rendering the volume data, the fenestration candidate region data, the blood vessel region data, the nerve bundle region data, and the brain. It is generated by superimposing the wall thickness distribution data of the room bottom region and adding the measurement result of the shortest distance between the fenestration candidate region and the blood vessel region or the fenestration candidate region and the nerve bundle region. It is possible to easily determine whether or not the window candidate region has been set. Therefore, it is possible to perform a treatment plan for neuroendoscopic surgery accurately and in a short time.

  Furthermore, the display data for treatment support in the present embodiment includes the above-mentioned fenestration region region data, blood vessel region data, and nerve bundle region data in the endoscope image data collected by the endoscope scope inserted into the ventricle. Since it is generated by superimposing the wall thickness distribution data of the ventricular bottom region, the positional relationship between the distal end portion of the treatment device inserted into the ventricle together with the endoscope scope and the fenestration candidate region can be easily grasped Therefore, safe and accurate neuroendoscopic surgery can be performed.

  As mentioned above, although embodiment of this indication has been described, this indication is not limited to the above-mentioned embodiment, and it can change and carry out. For example, in the above-described embodiment, the case of generating treatment plan support display data and treatment support display data effective for neuroendoscopic surgery on the third ventricle of the patient's head has been described. The application site of the operation is not limited to the third ventricle.

  In addition, the case where the ventricle bottom region and the blood vessel region and nerve bundle region adjacent to the ventricle bottom region are extracted based on the volume data collected by the MRI apparatus has been described. The above-described extraction may be performed based on image information collected by the image diagnostic apparatus. Further, although the case where the blood vessel region and the nerve bundle region are extracted based on the volume data has been described, only one of the blood vessel region or the nerve bundle region may be extracted.

  Furthermore, the case of adding the shortest distance measurement result between the blood vessel region or nerve bundle region and the fenestration candidate region measured in the process of the treatment plan support display data to the MPR image data of the treatment support display data has been described. A distance measurement result between the blood vessel region or nerve bundle region newly measured based on the MPR image data and the fenestration candidate region may be added to the MPR image data.

  In addition, the blood vessel region extraction unit 42 and the nerve bundle region extraction unit 43 in the above-described embodiment are based on the standard brain model based on the brain tissue volume data, blood vessel enhancement volume data, and nerve bundle enhancement volume data collected by the MRI apparatus. Although the case where the ventricle bottom region, blood vessel region, and nerve bundle region are extracted by dividing the region has been described, the ventricle bottom region, blood vessel region, and nerve bundle region are compared by comparing the above volume data with a predetermined threshold value. May be extracted.

  Further, the bottom wall thickness measuring unit 5 is based on the MPR image data generated in a plurality of MPR cross sections perpendicular to the ventricular bottom region and intersecting at the center of the ventricular bottom region. As described above, the position and direction of the MPR cross section can be arbitrarily set. In addition, the case where the distance to the blood vessel region or nerve bundle region and the bottom wall thickness are measured at the common measurement points set at predetermined intervals together with the above-described MPR cross section for the ventricular bottom region has been described. The above-described measurement may be performed at a set dedicated measurement point.

  Each unit included in the treatment support apparatus 100 of the present embodiment can also be realized by using, for example, a computer including a CPU, a RAM, a magnetic storage device, an input device, a display device, and the like as hardware. . For example, the system control unit 15 of the treatment support apparatus 100 can realize various functions by causing a processor such as a CPU mounted on the computer to execute a predetermined control program. In this case, the above-described control program may be installed in advance in the computer, or may be stored in a computer-readable storage medium or installed in the computer of the control program distributed via the network. .

  Although several embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

2 ... Volume data acquisition unit 3 ... Volume data storage unit 4 ... Region segmentation unit 41 ... Ventricular bottom region extraction unit 42 ... Blood vessel region extraction unit 43 ... Nerve bundle region extraction unit 44 ... Standard brain model storage unit 5 ... Bottom wall thickness Measurement unit 6 ... Wall thickness distribution data generation unit 7 ... Distance measurement unit 8 ... Opening window candidate region setting unit 9 ... MPR image data generation unit 10 ... PVR image data generation unit 11 ... Endoscope image data acquisition unit 12 ... Display data Generation unit 13 ... display unit 14 ... input unit 15 ... system control unit 100 ... treatment support device

Claims (11)

In a treatment support apparatus for generating and displaying display data for treatment plan support effective for treatment plan of neuroendoscopic surgery based on volume data collected from a patient's head region,
Region segmentation means for extracting at least one of a blood vessel region or a nerve bundle region and a ventricle bottom region by segmenting the volume data;
Bottom wall thickness measuring means for measuring the wall thickness of the ventricular bottom region;
Distance measuring means for measuring a distance from the predetermined position of the ventricular bottom region to the blood vessel region or the nerve bundle region;
A fenestration candidate region setting means for setting a fenestration candidate region for the ventricle bottom region based on the measurement result of the wall thickness and the measurement result of the distance;
Image data generating means for generating image data based on the volume data;
Display data generating means for generating display data for treatment plan support by superimposing position information of the fenestration candidate region on the image data;
A treatment support apparatus, comprising: display means for displaying the treatment plan support display data.   The image data generating means generates at least one of virtual endoscopic perspective projection image data or MPR (multi planar reconstruction) image data of the ventricular bottom region based on the volume data. The treatment support apparatus according to claim 1.   The treatment support apparatus according to claim 2, wherein the bottom wall thickness measuring unit measures the wall thickness of the ventricular bottom region based on the MPR image data generated by the image data generating unit. In a treatment support apparatus for generating and displaying display data for treatment support effective for neuroendoscopic surgery based on volume data collected from a patient's head region,
Region segmentation means for extracting at least one of a blood vessel region or a nerve bundle region and a ventricle bottom region by segmenting the volume data;
Bottom wall thickness measuring means for measuring the wall thickness of the ventricular bottom region;
Distance measuring means for measuring a distance from the predetermined position of the ventricular bottom region to the blood vessel region or the nerve bundle region;
A fenestration candidate region setting means for setting a fenestration candidate region for the ventricle bottom region based on the measurement result of the wall thickness and the measurement result of the distance;
Display data generating means for generating treatment support display data by superimposing position information of the fenestration candidate region on endoscopic image data of the ventricle bottom region collected by an endoscopic device;
A treatment support apparatus comprising display means for displaying the treatment support display data.   An image data generating means for generating MPR (multi planar reconstruction) image data is provided, and the bottom wall thickness measuring means measures the wall thickness of the ventricular bottom region based on the MPR image data. Item 5. The treatment support apparatus according to Item 4.   The display data generating means adds the treatment plan support display data or the treatment support display data to the position information of the blood vessel region, the position information of the nerve bundle region, the measurement result of the distance, and the wall thickness. The treatment support apparatus according to claim 1 or 4, wherein at least one of wall thickness distribution data generated based on the measurement result is added.   The display data generation means includes the MPR image data in which at least one of the position information of the blood vessel region, the position information of the nerve bundle region, and the measurement result of the distance is added to the treatment support display data. The treatment support apparatus according to claim 6, wherein   The region segmentation means extracts the ventricle bottom region, the blood vessel region, and the nerve bundle region by comparing the volume data with a standard brain model collected in advance. Item 5. The treatment support apparatus according to Item 4.   The fenestration candidate region setting means is based on the positional information in the ventricle bottom region where the distance to the blood vessel region or the nerve bundle region is longer than a predetermined distance threshold and the wall thickness is thinner than a predetermined wall thickness threshold. The treatment support apparatus according to claim 1, wherein a fenestration candidate region is set. A treatment support device that generates and displays treatment plan support display data effective for treatment planning for neuroendoscopic surgery based on volume data collected from the patient's head region.
A region segmentation function for extracting at least one of a blood vessel region or a nerve bundle region and a ventricle bottom region by segmenting the volume data;
A bottom wall thickness measurement function for measuring the wall thickness of the ventricle bottom region;
A distance measuring function for measuring a distance from the predetermined position of the ventricular bottom region to the blood vessel region or the nerve bundle region;
A fenestration candidate region setting function for setting a fenestration candidate region for the ventricular bottom region based on the measurement result of the wall thickness and the measurement result of the distance;
An image data generation function for generating image data based on the volume data;
A display data generation function for generating treatment plan support display data by superimposing position information of the fenestration candidate region on the image data;
A control program for executing a display function for displaying the treatment plan support display data. For a treatment support device that generates and displays treatment support display data effective for neuroendoscopic surgery based on volume data collected from the patient's head region,
A region segmentation function for extracting at least one of a blood vessel region or a nerve bundle region and a ventricle bottom region by segmenting the volume data;
A bottom wall thickness measurement function for measuring the wall thickness of the ventricle bottom region;
A distance measuring function for measuring a distance from the predetermined position of the ventricular bottom region to the blood vessel region or the nerve bundle region;
A fenestration candidate region setting function for setting a fenestration candidate region for the ventricular bottom region based on the measurement result of the wall thickness and the measurement result of the distance;
A display data generation function for generating treatment support display data by superimposing position information of the fenestration candidate region on endoscopic image data of the ventricle bottom region collected by an endoscopic device;
A control program for executing a display function for displaying the display data for treatment support.

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