JP6411072B2 - Medical image processing apparatus, medical image processing method, and program - Google Patents

Description

  Embodiments described herein relate generally to a medical image processing apparatus, a medical image processing method, and a program.

  Medical diagnostic imaging has evolved rapidly with advances in modalities and has become indispensable in today's medicine. Displaying image data in real time is also possible with recent X-ray CT (Computed Tomography) apparatuses and MRI apparatuses. Furthermore, it has become common to collect three-dimensional image information (volume data) and to generate / display three-dimensional image data using volume data. For example, it is possible to precisely observe a stenosis or an aneurysm that has occurred in a blood vessel wall.

  According to such a technique, it is possible to visually capture important information when selecting a treatment method for an aneurysm, such as aneurysm size, shape, neck size, and relationship with surrounding blood vessels. In particular, more information about the relationship with surrounding bones and blood vessels can be obtained than with cerebral angiography.

  Assessing the risk of aneurysm rupture is very important to prevent serious diseases such as subarachnoid hemorrhage and abdominal (thoracic) aortic aneurysm rupture, and research and development are underway. For example, a plurality of contrast volume (Volume) data for one heartbeat obtained by electrocardiographic synchronization reconstruction of a CT dynamic volume scan can be reproduced by cine reproduction, and a change in aneurysm dynamics within one heartbeat can be observed. Based on the result, the presence of Bleb with pulsation can be confirmed. Then, by performing a follow-up test of CTA (CT Angiography), for example, every six months, the growth of an aneurysm can be confirmed, and the risk of aneurysm rupture can be evaluated.

JP 2012-110444 PR Special table 2008-523877 Special table 2003-502723

As an index that can evaluate the risk of aneurysm rupture, the magnitude of pulsation and the amount of growth can be considered. That is, it can be said that the aneurysm with a large pulsation has a high risk of rupture, and the aneurysm with a high degree of growth has a high risk of rupture. However, conventionally, there is no known technique capable of evaluating the aneurysm pulsation magnitude in association with the growth amount.
An object is to provide a medical image processing apparatus, a medical image processing method, and a program capable of quantitatively evaluating the risk of aneurysm rupture.

  According to the embodiment, the medical image processing apparatus includes a storage unit, a calculation unit, and a display unit. The storage unit stores the first medical image data of the subject acquired in the first examination and the second medical image data of the subject obtained in the second examination performed after the first examination. . The calculation unit calculates an index value related to a change in the lesion part included in the first medical image data and the second medical image data for each pixel on the surface of the lesion part based on the first medical image data and the second medical image data. calculate. The display unit displays each pixel with a hue corresponding to the calculated index value.

FIG. 1 is a functional block diagram illustrating an example of a medical image processing apparatus according to an embodiment. FIG. 2 is a diagram illustrating an example of the growth of an aneurysm between examinations that change in time. FIG. 3 is a diagram illustrating an example of the relationship between the extracted pulsation amount and growth amount of the aneurysm and the display color. FIG. 4 is a schematic diagram showing the relationship between pulsation and growth of an aneurysm. FIG. 5 is a schematic diagram showing the relationship between the pulsation amount and the growth amount, and the color value. FIG. 6 is a diagram illustrating an example of a GUI (Graphical User Interface) window on the display unit 5. FIG. 7 is a schematic diagram showing an example of processing for selecting a hue with the color scale bar shown in FIG. FIG. 8 is a flowchart illustrating an example of a processing procedure in the medical image processing apparatus according to the embodiment.

  FIG. 1 is a functional block diagram illustrating an example of a medical image processing apparatus according to an embodiment. Hereinafter, the medical image processing apparatus is indicated by reference numeral 100. A medical image processing apparatus 100 shown in FIG. 1 is a computer including a CPU (Central Processing Unit) and a memory (not shown). The medical image processing apparatus 100 includes a storage unit 1, a calculation unit 2, a display control unit 3, a risk level setting unit 4, a display unit 5, an input unit 6, and a system control unit 7.

  The input unit 6 is a human machine interface including input devices such as a display panel, a keyboard, a trackball, a mouse, a selection button, and an input button. The input unit 6 includes a patient information input unit 61 and a test result input unit 62. The patient information input unit 61 is used for inputting patient information. The test result input unit 62 is used to input past image diagnosis results (test results) for each patient's cerebral aneurysm.

  Further, the input unit 6 is used for inputting various instruction signals, setting a burst risk region detection condition, and display data generation conditions. These input data are stored in the memory of the computer.

  The risk level setting unit 4 sets a rupture risk level for the detected cerebral aneurysm based on patient information of the patient, past image diagnosis results, and the like. The display unit 5 displays the display data generated by the display control unit 3. The system control unit 7 comprehensively controls each functional block of the medical image processing apparatus 100. For example, the system control unit 7 realizes various functions according to the embodiment by the calculation function of the CPU using software and various data stored in the memory.

  The storage unit 1 is, for example, a semiconductor memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory), or a storage medium such as a hard disk drive (HDD). In addition to magnetic disks such as HDDs, optical disks such as magneto-optical disks, CDs (Compact Discs), DVDs (Digital Versatile Discs), and Blu-ray (registered trademark) disks can also be used.

  The storage unit 1 stores volume data in a head region of a patient (subject) to be examined. The volume data is acquired by a medical image diagnostic apparatus such as an X-ray CT apparatus or an MRI apparatus, and is given via a hospital communication network (not shown) or a storage medium such as a CD-ROM. The volume data stored in the storage unit 1 is collected by, for example, X-ray CT imaging of a patient's head region to which a contrast medium has been administered using a multi-slice method. In addition, volume data acquired by a modality such as a helical cas scan X-ray CT or MRI apparatus may be used.

  In order to diagnose a cerebral aneurysm or the like generated on a vascular wall of a cerebral artery, generally, a method of observing the shape of a blood vessel by imaging blood flowing through the blood vessel is used. For example, in MRI imaging, contrast MRA imaging that collects MR signals from blood with a high contrast ratio by injecting a contrast agent such as Gd-DTPA, or a pulse sequence such as TOF (time of flight) method Applied non-contrast MRA (magnetic resonance angiography) imaging is known. In addition, PC (phase contrast) imaging is also known in which the phase change amount of MR signals generated from blood flowing in blood vessels is measured to visualize blood velocity information. Through these imaging operations, volume data (medical image data) for observing cerebral aneurysms can be collected.

  In the embodiment, it is assumed that the same patient is subjected to the same kind of examination multiple times. Volume data obtained by temporally preceding inspection among a plurality of inspections is referred to as inspection 1 data (reference 11), and volume data obtained by temporally subsequent inspection (follow-up inspection) is inspected 2 The following description will be made by referring to the data (denoted by reference numeral 12).

  The calculation unit 2 includes an aneurysm extraction unit 21, a pulsation amount calculation unit 22, a growth amount calculation unit 23, and a risk evaluation unit 24. The aneurysm extraction unit 21 performs image processing on each of the examination 1 data 11 and the examination 2 data 12 to extract a cerebral artery region, and further examines the cerebral aneurysm generated in the cerebral artery region with the examination 1 data 11 and the examination 2 data 12. Extract every.

  The pulsation amount calculator 22 measures the pulsation magnitude of the extracted aneurysm. For example, as shown in FIG. 2, it is assumed that four image data corresponding to different cardiac phases (phases) are obtained for each heartbeat of the patient. The pulsation amount calculation unit 22 measures the magnitude of pulsation for each point constituting the surface of the aneurysm, for example, for each pixel at a predetermined resolution.

  The amount of pulsation is measured for each of examination 1 and examination 2, and is quantified as an index value. That is, the examination data 11 is image-processed to obtain the pulsation amount in the examination 1, and the examination data 12 is image-treated to obtain the pulsation quantity in the examination 2.

  The growth amount calculation unit 23 calculates an index value indicating the growth amount of the aneurysm between the examination 1 and the examination 2. That is, as shown in FIG. 2, image data corresponding to the cardiac time phase is obtained for each of examination 1 and examination 2. The growth amount calculation unit 23 compares the inspection data 11 and the inspection data 12 for each time phase, for example, and quantifies the degree of growth of the aneurysm (growth amount) as an index value. For the growth amount, the magnitude of pulsation is measured for each point constituting the surface of the aneurysm, for example, for each pixel at a predetermined resolution. Note that both the pulsation amount and the growth amount can be understood as index values related to the size change of the aneurysm.

  The risk evaluation unit 24 evaluates the rupture risk for each pixel on the aneurysm surface based on the calculated index value indicating the pulsation amount and the index value indicating the growth amount.

  The display control unit 3 displays three-dimensional image data of a head region including a cerebral artery and a cerebral aneurysm obtained by rendering the volume data. Further, the display control unit 3 generates display data by color-mapping the three-dimensional image data with a color corresponding to the burst risk level. That is, the display control unit 3 generates display data for displaying a color map on the surface of the aneurysm by associating the explosion risk for each pixel calculated by the risk evaluation unit 24 with a color. The generated display data is transferred to the display unit 5 and displayed visually.

  FIG. 3 is a diagram illustrating an example of the relationship between the extracted pulsation amount and growth amount of the aneurysm and the display color. For example, the display control unit 3 sets the pulsation amount in the examination 1 to the first primary color (for example, R: Red), the pulsation amount in the examination 2 to the second primary color (for example, G: Green), and the growth amount to the third primary color. The display color for each pixel is determined by associating it with (for example, B: Blue).

  FIG. 4 is a schematic diagram showing the relationship between pulsation and growth of an aneurysm. The amount of pulsation is an index indicating changes in the size of the aneurysm at different time phases in the same examination (lateral direction in the figure). The size of the knob can be expressed, for example, based on the distance from the center of the neck surface of the knob to the surface of the knob. For the amount of pulsation, the distance from the center of the neck surface (arrow in the figure) for each point on the surface of the aneurysm indicated in the volume data for each time phase is obtained, and the difference in the same direction between different volumes (maximum distance-minimum distance) ) Can be calculated.

  The growth amount is an index indicating a change in the size of the aneurysm at the same time phase in different examinations (vertical direction in the figure). The amount of growth can be calculated by calculating the distance from the center of the neck surface (arrow in the figure) between the volumes of the same phase (distance of inspection 2 -distance of inspection 1) for each point on the surface of the aneurysm.

FIG. 5 is a schematic diagram showing the relationship between the pulsation amount and the growth amount, and the color value. A region where there is no movement on the aneurysm surface, that is, a pixel that has not grown and has no pulsation corresponds to a three-dimensional origin, that is, a region where RGB is close to zero. Therefore, for example, the lightest color is displayed.
In addition, since the color values of R and B are high in the portion where the pulsation amount of the examination 1 is large and the growth amount is large, it is displayed in dark purple. Thus, the pulsation amount in the first examination and the second examination and the growth amount of the aneurysm are uniquely associated with the display color. That is, for each point on the aneurysm surface, RGB element values are determined based on the magnitude of the values, with the amount of pulsation in examination 1 = R, the amount of pulsation in examination 2 = G, and the amount of growth = B. Note that the maximum value of the growth amount may be the maximum value of all surface points of the growth amount. Further, the maximum value of the pulsation amount may be the maximum value of the values of all the surface points of the inspection 1 and the inspection 2.

FIG. 6 is a diagram illustrating an example of a GUI (Graphical User Interface) window on the display unit 5. When any pixel on the aneurysm surface displayed in the color map on the display unit 5 is designated by a click operation using the mouse of the input unit 6, for example, the matrix shown in FIG. 6 is displayed as an indicator in the window. The
In FIG. 6, a two-dimensional gradation map is shown in which the value of the amount of pulsation of examination 1 is on the horizontal axis, and the value of the amount of pulsation of examination 2 is on the vertical axis. The color indicating the pulsation amount corresponding to the clicked location is graphically shown on the matrix by a crossing point (circle symbol). In addition, a color indicating the growth amount is graphically displayed as a one-dimensional bar graph beside the matrix (left in the figure). Such an interface allows the medical staff to understand at a glance the meaning of the color of the clicked location.

  In the procedure of the present application, the matrix in FIG. 6 must be displayed in monochrome, but the matrix is displayed in color in the actual apparatus. In comparison with FIG. 5, the matrix of FIG. 6 is drawn with a gradation having G as the vertical axis and R as the horizontal axis. The bar graph of FIG. 6 corresponds to B of FIG. The matrix in FIG. 6 is a color scale bar related to hue, with 0 as the lower limit and the maximum value of pulsation amount and growth amount as the upper limit.

  FIG. 7 is a schematic diagram showing an example of processing for selecting a hue with the color scale bar shown in FIG. For example, the hue range can be arbitrarily designated by placing the mouse pointer on the color scale bar and dragging the boundary line on the matrix. Based on the designation by the user, the display control unit 3 displays only the pixels of the hue included in the selected range on the display unit 5. Thereby, only the range of the desired change amount can be highlighted and displayed on the display unit 5. FIG. 7 shows an example in which only the region where the pulsation is significantly increased and the pulsation is large is displayed in color.

  FIG. 8 is a flowchart illustrating an example of a processing procedure in the medical image processing apparatus according to the embodiment. In FIG. 8, the calculation unit 2 reads out time series data of the examination 1 (first examination data 11) and time series data of the examination 2 (second examination data 12) from the storage unit 1 (Steps S1 and S6). ).

  Next, the calculation unit 2 manually or automatically extracts the aneurysm region from the entire volume data for each of the examination 1 and the examination 2 (steps S2 and S7). Next, the calculation unit 2 manually or automatically sets the neck surface of the extracted aneurysm region (steps S3 and S8).

  Next, the calculation unit 2 calculates the distance from the center of the neck surface of the extracted aneurysm region for all points on the surface of all volumes for each of the examinations 1 and 2 (steps S4 and S9). Next, the calculation unit 2 calculates a change in the distance between different time phases in the examination 1, and calculates the amount of pulsation in the examination 1 (step S5). Further, the calculation unit 2 calculates a change in distance between different time phases in the examination 2, and calculates a pulsation amount in the examination 2 (step S10).

  Further, the calculation unit 2 compares the volume data in the first phase of the examination 1 with the volume data in the first phase of the examination 2 and calculates the change in distance for each point on the surface of the aneurysm. The amount of growth between inspections is calculated (step S11). The pulsation amount and the growth amount calculated in this way may be stored in the storage unit 1.

  When the above procedure is completed, the display control unit 3 calculates the display colors of all the pixels on the surface of the aneurysm based on the pulsation amount and the growth amount (step S12). In parallel with this, the matrix of FIG. 6 may be displayed (step S13).

  When the color of the aneurysm surface is determined through the above procedure, the display control unit 3 displays the aneurysm volume in the first time phase of the examination 1 on the display unit 5 in a color map, for example. Thereby, the color map on volume rendering display according to the embodiment is realized (step S14). That is, a quantitative value that correlates the growth amount of the aneurysm and the change in the magnitude of pulsation accompanying the growth is displayed on the aneurysm surface in a color map (ColorMap).

  As described above, in this embodiment, the storage unit 1 stores time-series volume data that captures the pulsation of a plurality of cerebral aneurysms by the follow-up examination. The calculation unit 2 extracts a cerebral aneurysm of each volume, and calculates the change amount of the pulsation of the aneurysm in the time phase direction of the volume data of each time series and the growth amount of the aneurysm between the follow-up examination data. Then, an index value obtained by combining the pulsation amount (or change amount) for each examination and the growth amount between examinations is evaluated for each point on the aneurysm surface, and is displayed in a color map.

  Thereby, the growth amount of the aneurysm and the change in the magnitude of pulsation accompanying the growth are displayed in a color map on the aneurysm surface in association with the color. Therefore, the medical staff can easily confirm a location where both the pulsation amount and the growth amount are high, a low location, a location where either one is high, and a location where it is low. The amount of growth of the aneurysm and the amount of change in pulsation accompanying the growth are indices that directly represent the risk of rupture.

  That is, according to the embodiment, it is possible to grasp at a glance the risk of rupture based on the relationship between the growth of the aneurysm and the pulsation change in association with the color. Therefore, according to the embodiment, it is possible to quantitatively evaluate the change in the shape of the aneurysm, and it is possible to provide a medical image processing apparatus that can easily determine the risk of rupture of the aneurysm. .

  The present invention is not limited to the above embodiment. For example, in the embodiment, a color map is displayed on the surface of a three-dimensional volume image showing an aneurysm. Alternatively, each pixel on the polygon surface that models the shape of the aneurysm may be displayed in a three-dimensional color map. Alternatively, each pixel on the polar map in which the surface of the aneurysm is developed in a circular shape may be displayed in a three-dimensional color map. In the volume display, the part that becomes the back side can be seen by displaying it on the polar map.

  In the embodiment, the lesion is described as an aneurysm. However, this is an example, and it will be easily understood by those skilled in the art that the same description can be applied to a varicose vein, for example. In general, the technique of the embodiment can be applied to a tissue (anatomical site) whose size and shape can change, and a similar color map display can be performed. For example, the heart and lungs are representative examples of such tissues.

  In particular, the heart is particularly useful in a test comparing a state where no load is applied (rest phase) and a state where stress is applied by drugs or exercise (stress phase). For example, the wall motion tracking inspection can be used to evaluate the amount of change in the thickness of the inner and outer walls of the heart (may be divided into end diastole and end systole), and the change amount can be color-coded using the technology of the embodiment. Can be displayed.

  In addition, the medical image processing apparatus according to the embodiment can also be used to evaluate the growth and shrinkage of a tumor generated in the body. Thus, the technique of the embodiment can be applied to a target that can acquire a plurality of image data by a plurality of inspections.

  Further, not only RGB but also CYMK (cyan, yellow, magenta, black) four-dimensional hues can be used to display more information.

  In the embodiment, the amount of pulsation and the amount of growth of the lesion (aneurysm) are calculated. Any of these index values can be understood as an index value related to a change in the shape or size of a lesion. Instead of this, a qualitative change in the lesion, for example, in the case of the liver, a change in hardness accompanying the progression of cirrhosis may be calculated as an index value and displayed in a color map.

  Although an embodiment of the present invention has been described, this embodiment is presented as an example and is not intended to limit the scope of the invention. The novel embodiment can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. This embodiment and its modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

  DESCRIPTION OF SYMBOLS 1 ... Memory | storage part, 2 ... Calculation part, 3 ... Display control part, 4 ... Risk level setting part, 5 ... Display part, 6 ... Input part, 7 ... System control part, 11 ... Examination data, 12 ... Examination data, 21 ... aneurysm extraction unit, 22 ... pulsation amount calculation unit, 23 ... growth amount calculation unit, 24 ... risk evaluation unit, 61 ... patient information input unit, 62 ... examination result input unit, 100 ... medical image processing apparatus.

Claims (13)

A storage unit that stores first medical image data of the subject acquired in the first examination and second medical image data of the subject obtained in the second examination performed after the first examination. When,
An index value related to a change in a lesion part included in the first medical image data and the second medical image data is determined for each pixel on the surface of the lesion part based on the first medical image data and the second medical image data. A calculation unit for calculating
A display unit that displays each of the pixels in a hue corresponding to the calculated index value ;
The calculator is
Calculating the amount of pulsation, which is the amount of change in shape due to pulsation, of the lesion in the first medical image data;
Calculating the amount of pulsation, which is the amount of change in shape due to pulsation, of the lesioned part in the second medical image data;
Calculating the amount of growth of the lesion between the first medical image data and the second medical image data;
The medical image processing apparatus which calculates the said index value which combined the amount of pulsations and the growth amount of the said lesion part in said 1st medical image data and said 2nd medical image data for every pixel in the surface of the said lesion part . The lesion is an aneurysm;
The calculation unit includes a first index value indicating the pulsation amount of the aneurysm in the first examination, a second index value indicating the pulsation quantity of the aneurysm in the second examination, and the first A third index value indicating the amount of growth of the aneurysm between the examination and the second examination,
The display unit sets the first index value as a color value of a first primary color, the second index value as a color value of a second primary color, and the third index value as a color value of a third primary color, respectively. association with respectively the 3-dimensional color map representation of the pixels, the medical image processing apparatus according to claim 1. The display unit, the to each pixel of the 3-dimensional color map displayed on the shape modeled polygon surfaces of the aneurysm, the medical image processing apparatus according to claim 2. The display unit, the to each pixel of the 3-dimensional color map displayed on the polar map obtained by developing the surface of the aneurysm in a circle, the medical image processing apparatus according to claim 2. And a user interface for designating pixels on the surface of the lesion.
The display unit displays the color at the designated pixel on the color scale bar using the user interface, the medical image processing apparatus according to any one of claims 1 to 4.   The medical image processing apparatus according to claim 5, wherein the display unit displays pixels having a hue included in a range selected on the color scale bar. A storage unit that stores first medical image data of the subject acquired in the first examination and second medical image data of the subject obtained in the second examination performed after the first examination. A medical image processing method applicable to a medical image processing apparatus comprising:
An index value related to a change in a lesion part included in the first medical image data and the second medical image data is determined for each pixel on the surface of the lesion part based on the first medical image data and the second medical image data. To calculate
Displaying each of the pixels in a hue corresponding to the calculated index value ;
Said calculating is
Calculating the amount of pulsation, which is the amount of change in shape due to pulsation, of the lesion in the first medical image data;
Calculating the amount of pulsation, which is the amount of change in shape due to pulsation, of the lesioned part in the second medical image data;
Calculating the amount of growth of the lesion between the first medical image data and the second medical image data;
A medical image processing method , wherein the index value obtained by combining the pulsation amount and the growth amount of the lesion in the first medical image data and the second medical image data is calculated for each pixel on the surface of the lesion . The lesion is an aneurysm;
The calculating includes: a first index value indicating a pulsation amount of the aneurysm in the first examination; a second index value indicating a pulsation quantity of the aneurysm in the second examination; Calculating a third index value indicating the amount of growth of the aneurysm between the first examination and the second examination;
The displaying means that the first index value is a color value of a first primary color, the second index value is a color value of a second primary color, and the third index value is a color value of a third primary color. each three-dimensional color map display of said pixels by associating each medical image processing method according to claim 7. It is said that each of the pixels 3-dimensional color map display on shape modeled polygon surfaces of the aneurysm, a medical image processing method according to claim 8, wherein the display. It is said that each of the pixels of the 3-dimensional color map displayed on the polar map obtained by developing the surface of the aneurysm in a circle, a medical image processing method according to claim 8, wherein the display. That said display displays the color at the designated pixel on the color scale bar using the user interface for specifying the pixels of the surface of the lesion, according to any one of claims 7 to 10 Medical image processing method.   The medical image processing method according to claim 11, wherein the displaying displays pixels of a hue included in a range selected on the color scale bar. A storage unit that stores first medical image data of the subject acquired in the first examination and second medical image data of the subject obtained in the second examination performed after the first examination. A computer comprising:
An index value related to a change in a lesion part included in the first medical image data and the second medical image data is determined for each pixel on the surface of the lesion part based on the first medical image data and the second medical image data. Function as a calculation unit that calculates
Causing each of the pixels to function as a display unit that displays a hue corresponding to the calculated index value ;
The calculation unit,
Calculating the amount of pulsation that is the amount of change in shape due to pulsation of the lesioned part in the first medical image data;
Calculating the amount of pulsation that is the amount of change in shape due to pulsation of the lesioned part in the second medical image data;
Calculating the amount of growth of the lesion between the first medical image data and the second medical image data;
The program which calculates the said index value which combined the pulsation amount and the growth amount of the said lesion part in the said 1st medical image data and the said 2nd medical image data for every pixel in the surface of the said lesion part .