WO2016076074A1 - Image processing device, x-ray ct device, and image processing method - Google Patents

Abstract

The purpose of the invention is to provide an image processing device, an X-ray CT device, and an image processing method which are capable of determining and showing the optimal liver resection line for a tumor. The image processing device 122 acquires image data depicting the interior of a subject including the liver and hepatic reserve data that is data relating to regional hepatic reserve; separates and extracts a liver parenchymal area, the tumor, and blood vessels from the image data; calculates a dominant region for arteries and for veins in the extracted liver parenchymal area on the basis of the hepatic reserve data; determines, on the basis of the locations of the calculated dominant regions and tumor, blood vessel cutting positions and a liver resection line which minimize a liver resection region by minimizing the liver resection region so that blood stasis volume is minimized; and displays the determined blood vessel cutting positions and liver resection line on a display device 125.

Description

Image processing apparatus, X-ray CT apparatus, and image processing method

The present invention relates to an image processing apparatus, an X-ray CT apparatus, and an image processing method, and more particularly to an organ extraction from a CT image and an image processing technique of the extracted organ.

An image obtained with an X-ray CT apparatus describes the shape of an organ in a subject and is used for diagnostic imaging. In recent years, as described in Patent Document 1, it is possible to display a simulation of an excision region of an organ such as a liver by using an image taken by an X-ray CT apparatus, which is useful for an operation plan.

Hepatectomy includes non-systematic hepatectomy and systematic hepatectomy. Non-systematic hepatectomy includes enucleation and partial resection, where enucleation removes only the tumor, while partial resection provides a margin for the tumor and removes the tumor and the area containing the margin. Systematic excision includes lobectomy, segmental excision, and subsegmental excision. These are determined in consideration of the position, size and number of tumors and liver function (liver reserve capacity). Also, it is desirable that the volume of the liver parenchyma to be excised is smaller.

In an operation plan for systematic resection, it is necessary to determine a hepatic resection line of the liver parenchyma, identify a blood vessel to be cut (ligated), and determine a cutting position. In the prior art, the cutting is performed on a branch unit of the blood vessel, and the cutting position is set to the branch point of the blood vessel, so when the blood vessel spans multiple regions (leaves, sections, sub-sections), the blood vessel is once excised, and then Vascular reconstruction may be done. Patent Document 1 describes a process of specifying an arterial control region and a vein control region, specifying an ablation region based on these information, and displaying the simulation.
In order to reduce the burden on the subject, it is desirable to reduce the resection capacity of the liver parenchyma.

JP 2004-337257 A JP 2008-307145 JP

In the method of Patent Document 1, the cutting is set as a branch unit, and the branch point is set as the cutting position. Therefore, the resection volume of the liver parenchyma is not necessarily the minimum volume. In Patent Document 1, the dominant region is calculated from the relationship between a plurality of blood vessels and their blood vessel diameters. This is a case where the reserve capacity of the liver parenchyma is assumed to be constant depending on the location. Liver parenchymal reserve is not always constant, and in order to more accurately minimize excision volume, determine vascular cutting position and hepatectomy region considering local liver reserve changes There is a need.

The present invention has been made in view of the above problems, and provides an image processing apparatus, an X-ray CT apparatus, and an image processing method capable of obtaining and presenting an optimal hepatectomy line for a tumor. For the purpose.

In order to achieve the above-described object, the present invention provides a data acquisition unit that acquires image data depicting the inside of a subject including the liver and liver reserve data that is data related to a local reserve of the liver, and the image data An extraction unit that separates and extracts a liver parenchymal region, a tumor, and a blood vessel from a blood vessel control region calculation unit that calculates each control region of an artery and a vein in the extracted liver parenchymal region based on the liver reserve capacity data; A hepatectomy line determination unit that determines a vascular cutting position and a hepatectomy line based on the arrangement of each dominant region and the tumor, and a display unit that displays the vascular cutting position and the hepatectomy line. An image processing apparatus.

Also, an X-ray CT apparatus provided with the image processing apparatus.

Further, the image processing apparatus executes the step of obtaining image data depicting the inside of the subject including the liver and liver reserve data which is data relating to the local reserve of the liver, and the liver parenchymal region from the image data, A step of separating and extracting tumors and blood vessels, a step of calculating each of the dominant regions of arteries and veins in the extracted liver parenchymal region based on the liver reserve data, and the arrangement of the calculated dominant regions and the tumor An image processing method comprising: determining a blood vessel cutting position and a hepatectomy line based on the step; and displaying the blood vessel cutting position and the hepatectomy line on a display device.

The present invention can provide an image processing apparatus, an X-ray CT apparatus, and an image processing method capable of obtaining and presenting an optimal hepatectomy line for a tumor.

Diagram showing the overall configuration of the X-ray CT apparatus 1 The block diagram which shows the function structure of the image processing apparatus 122 Flow chart explaining the flow of hepatectomy region determination processing Example of hepatic parenchymal region 11, arteries 21 to 23, veins 31 to 33, and tumor 41 isolated and extracted from the image The figure which shows the boundary 25 of arterial control area | regions 26 and 27 of arteries 22 and 23, and arterial control area | region The figure explaining the method of calculating the boundary 25 of an arterial control area | region based on contrast agent diffusion speed The figure which shows the vein control area | regions 36 and 37 of the veins 32 and 33, and the boundary 35 of the vein control area A diagram in which the arterial control regions 26 and 27 and the vein control regions 36 and 37 shown in FIGS. 5 and 7 are overlapped. Diagram showing blood stasis area 71 Diagram showing blood vessel cutting position (arterial / venous cutting position) 81, 82 and hepatectomy region 83 Diagram showing blood vessel cutting position (arterial / venous cutting position) 91, 92 and hepatectomy region 93 Diagram showing blood vessel cutting positions (arterial / venous cutting positions) 91, 1001, hepatectomy region 1002, and hepatectomy line 1003 Diagram explaining how to determine the hepatectomy line Diagram showing the determined hepatectomy region 1201 The figure explaining the determination method of the blood vessel cutting position and the hepatectomy line according to the arrangement of the tumor The figure explaining the determination method of the blood vessel cutting position and the hepatectomy line according to the arrangement of the tumor The figure explaining the method of determining the blood vessel dominating region by the contour line of the arrival time of the contrast agent Figure showing an example of the operation screen 5

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[First embodiment]
First, the overall configuration of the X-ray CT apparatus 1 will be described with reference to FIG.

As shown in FIG. 1, the X-ray CT apparatus 1 includes a scan gantry unit 100, a bed 105, and a console 120. The scan gantry unit 100 is an apparatus that irradiates a subject with X-rays and detects X-rays transmitted through the subject. The console 120 is a device that controls each part of the scan gantry unit 100, acquires transmission X-ray data measured by the scan gantry unit 100, and generates an image. The bed 105 is a device that places a subject on the bed and carries the subject in and out of the X-ray irradiation range of the scan gantry unit 100.

The scan gantry unit 100 includes an X-ray source 101, a turntable 102, a collimator 103, an X-ray detector 106, a data collection device 107, a gantry control device 108, a bed control device 109, and an X-ray control device 110.

The console 120 includes an input device 121, an image processing device 122, a storage device 123, a system control device 124, and a display device 125.

The rotating plate 102 of the scan gantry unit 100 is provided with an opening 104, and the X-ray source 101 and the X-ray detector 106 are arranged to face each other through the opening 104. The subject placed on the bed 105 is inserted into the opening 104. The turntable 102 rotates around the subject by a driving force transmitted from the turntable drive device through a drive transmission system. The turntable driving device is controlled by a gantry control device.

The X-ray source 101 is controlled by the X-ray control device 110 to irradiate X-rays having a predetermined intensity continuously or intermittently. The X-ray controller 110 controls the X-ray tube voltage and the X-ray tube current applied or supplied to the X-ray source 101 according to the X-ray tube voltage and the X-ray tube current determined by the system controller 124 of the console 120. To do.

A collimator 103 is provided at the X-ray irradiation port of the X-ray source 101. The collimator 103 limits the irradiation range of the X-rays emitted from the X-ray tube 101. For example, it is formed into a cone beam (conical or pyramidal beam). The opening width of the collimator 103 is controlled by the system controller 124.

The X-rays irradiated from the X-ray source 101, passed through the collimator 103, and transmitted through the subject enter the X-ray detector 106.

The X-ray detector 106 is a two-dimensional array of X-ray detection element groups configured by, for example, a combination of a scintillator and a photodiode, in the channel direction (circumferential direction) and the column direction (body axis direction). The X-ray detector 106 is disposed so as to face the X-ray source 101 through the subject. The X-ray detector 106 detects the X-ray dose irradiated from the X-ray source 101 and transmitted through the subject, and outputs it to the data collection device 107.

The data collection device 107 collects X-ray doses detected by the individual X-ray detection elements of the X-ray detector 106, converts them into digital signals, and sequentially outputs them to the image processing device 122 of the console 120 as transmitted X-ray data. To do.

The image processing device 122 is a computer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and the like. The image processing device 122 acquires transmission X-ray data input from the data collection device 107, and performs preprocessing such as logarithmic conversion and sensitivity correction to create projection data necessary for reconstruction. The image processing apparatus 122 reconstructs an image depicting the inside of the subject such as a tomogram using the generated projection data. The system control device 124 stores the image data reconstructed by the image processing device 122 in the storage device 123 and displays it on the display device 125.

Also, the image processing apparatus 122 executes a process for determining a blood vessel cutting position and a hepatectomy line (hepatectomy area determination process) in the hepatectomy using the reconstructed image data. Details of the hepatectomy region determination process will be described later (see FIG. 3).

The system control device 124 is a computer that includes a CPU, a ROM, a RAM, and the like.
The storage device 123 is a data recording device such as a hard disk, and stores programs, data, and the like for realizing the functions of the X-ray CT apparatus 1 in advance.

The display device 125 includes a display device such as a liquid crystal panel and a CRT monitor, and a logic circuit for executing display processing in cooperation with the display device, and is connected to the system control device 124. The display device 125 displays the image data output from the image processing device 122 and various information handled by the system control device 124.

The input device 121 includes, for example, a keyboard, a pointing device such as a mouse, a numeric keypad, and various switch buttons, and outputs various instructions and information input by the operator to the system control device 124. The operator operates the X-ray CT apparatus 1 interactively using the display device 125 and the input device 121. The input device 121 may be a touch panel type input device configured integrally with the display screen of the display device 125.

The couch 105 includes a couch for placing a subject, a vertical movement device, and a couch drive device. The couch control device 109 controls the couch height to move up and down and move back and forth in the body axis direction. Or move left and right in the direction perpendicular to the body axis and parallel to the floor (left and right direction). During imaging, the couch controller 109 moves the couch at the couch moving speed and moving direction determined by the system controller 124.

Next, the functional configuration of the image processing apparatus 122 according to the present invention will be described with reference to FIG.

As shown in FIG. 2, the image processing apparatus 122 includes a data acquisition unit 122a, an extraction unit 122b, a blood vessel dominating region calculation unit 122c, a hepatectomy line determination unit 122d, a display unit 122e, and an input unit 122f.

The data acquisition unit 122a acquires image data depicting the inside of the subject including the liver and liver reserve data that is data related to the local reserve of the liver. The image data is three-dimensional original image data obtained by stacking a plurality of tomographic images obtained by imaging a subject using an X-ray CT apparatus, an MR apparatus, or the like. Hereinafter, a case where the input image is a CT image will be described as an example.

肝 Liver reserve data is data indicating the local reserve capability of the liver as described above. Specifically, the contrast agent diffusion rate at any plurality of points in the liver parenchyma region (see FIG. 6), and a line connecting the points of the liver parenchyma region where the contrast agent flowing out from each blood vessel reaches the same time (hereinafter, This is referred to as “contrast arrival time contour line” (see FIG. 17). The contour lines of the contrast medium diffusion speed and the contrast medium arrival time are calculated from the contrast medium monitoring data measured at the time of imaging. Specific examples of the contrast medium monitoring data include TDC (Time Density Curve).

The data acquisition unit 122a acquires the contrast medium diffusion speed, the contrast medium arrival time contours, and the like together with the image data as hepatic reserve capacity data. When the contrast medium diffusion speed and the contour line of the contrast medium arrival time are not calculated in advance, the data acquisition unit 122a acquires the contrast medium monitoring data at the time of image capturing, and the contour line of the contrast medium diffusion speed and the contrast medium arrival time. Calculate liver reserve capacity data.

The extraction unit 122b separates and extracts each organ such as blood vessels including liver parenchyma, tumor, and arteriovenous based on the luminance value of the image data. In order to separate and extract each organ on the image, for example, segmentation, region growing, and other various methods can be used. Segmentation is a method of extracting an area by binarizing an image with a threshold value. Region glowing is a method that compares the brightness value of an arbitrary pixel with the brightness values of its surrounding pixels, and extracts a region while combining pixels as the same region if the difference between the two is equal to or less than a set threshold value. .

The blood vessel dominating region calculating unit 122c calculates the dominating region of each blood vessel in the liver parenchymal region extracted by the extracting unit 122b based on the above-mentioned liver reserve data. Further, the blood vessel dominating region calculation unit 122c acquires the contrast medium monitoring data as necessary, and based on the contrast medium monitoring data, hepatic reserve capacity data such as the contrast medium diffusion speed and the contour line of the arrival time at each point of the image is obtained. calculate.

The hepatectomy line determination unit 122d determines the vascular cutting position where the hepatectomy region is minimized based on the control region of each blood vessel calculated by the blood vessel control region calculation unit 122c and the arrangement of the tumor. As a specific determination procedure, first, a nutritional blood vessel of a tumor to be excised is identified, a branching point of the nutritional blood vessel is obtained, each control region of the artery and vein extending from the branching point is specified, and the arterial control region and The overlapping portion of the vein-dominated region is defined as a blood stagnation region.

Furthermore, a blood vessel cutting position for excising the tumor and the blood stagnation region is set, and an optimal hepatectomy line is calculated at the set blood vessel cutting position. At this time, the hepatectomy line determination unit 122d calculates the volume of the hepatectomy region (hepatectomy volume) and the volume of the blood stasis region (blood stasis capacity) according to the blood vessel cutting position. The hepatectomy line determination unit 122d executes a process for minimizing the hepatectomy region so that the blood stasis capacity is minimized.

In this minimization process, the blood vessel cutting position of the artery that is the feeding blood vessel is moved from, for example, the vicinity of the branch point of the blood vessel toward the distal side, and the hepatectomy line that minimizes the blood stasis capacity while excising the tumor is obtained. decide.

The display unit 122e displays the blood vessel cutting position and the hepatectomy line (or hepatectomy region) determined by the hepatectomy region determination unit 122d on the image. At this time, the relationship between the blood vessel cutting position and the blood stasis region may be shown, or the hepatectomy volume may be displayed.

The input unit 122f receives input of designation of a blood vessel cutting position and various parameters used for calculation of a hepatectomy region.

Next, the flow of hepatectomy region determination processing executed by the image processing apparatus 122 of the first embodiment will be described with reference to the flowchart of FIG.

The image processing apparatus 122 first acquires image data such as a CT image including a liver region and liver reserve capacity data (step S101). The image processing device 122 separates and extracts liver parenchyma, blood vessels, and tumor from the input image data (steps S102 to S104).

The blood vessels extracted in step S103 are arteries 21, 22, and 23 including portal veins and veins 31, 32, and 33 as shown in FIG. In FIG. 4, 11 indicates the liver parenchyma and 41 indicates the tumor.

Extraction of each organ (liver parenchyma 11, arteries 21, 22, 23, veins 31, 32, 33, and tumor 41) in steps S102 to S104 may be performed by a known method such as segmentation or region growing. The threshold used for organ extraction may be input by the operator via the input device 121 or the like, or may be a preset value.

Next, the image processing apparatus 122 identifies a nutritional blood vessel that supplies nutrition to the tumor 41 to be excised (step S105). For example, the method described in Patent Document 2 may be used for the nutritional blood vessel specifying process. Specifically, a processing start point for specifying a blood vessel connected to a tumor is set, and a nutrient blood vessel is specified by a technique such as region growing.

The image processing device 122 calculates a branch point of the blood vessel (step S106). The blood vessel branch points shown in FIG. 4 include an arterial branch point 24 and a venous branch point 34. The image processing device 122 calculates the core line of each blood vessel extracted in step S103, and sets the branch part of the core line as the arterial branch point 24 and the vein branch point 34, respectively.

Next, the image processing apparatus 122 identifies the control region of each blood vessel (step S107, step S108). Hereinafter, the arterial control region is referred to as an arterial control region, and the vein control region is referred to as a vein control region.

As shown in FIG. 5, the arterial control region is determined by the arterial control regions 26 and 27 of the adjacent arteries 22 and 23 and the boundary 25 of the arterial control region. When calculating the arterial dominance region, the image processing device 122 acquires or calculates liver reserve capacity data that is data related to the local reserve capacity of the liver, and uses the liver reserve capacity data to determine the arterial dominance area (arteries 22, Each of the 23 arterial control regions 26 and 27 and the boundary 25) of the arterial control region are determined.

Here, a method for calculating liver reserve capacity data will be described with reference to FIG.

FIG. 6 (a) shows time series data (TDC; Time Density Curve) indicating the contrast agent arrival time in each pixel, and FIG. 6 (b) shows calculation points A, B, and C set in the vicinity of the arteries 22 and 23. , D.

The image processing device 122 calculates the contrast agent diffusion speed around each blood vessel from the TDC peak time tp at each calculation point and the distance between the two points (distance between point A and point B, distance between point C and point D). .

The contrast medium diffusion rate at the point A in the vicinity of the artery 22 can be obtained from the following equation (1).

Similarly, the contrast agent diffusion rate at point C in the vicinity of the artery 23 can be obtained from the following equation (2).

The image processing device 122 obtains the ratio of the contrast agent diffusion speed at the points A and C in the vicinity of the arteries 22 and 23, and the obtained ratio is the distance d1 from the artery 22 to the boundary 25 of the arterial control region and the artery 23 to the artery. The artery control region boundary 25 is calculated so as to have a ratio to the distance d2 to the control region boundary 25. The following equation (3) is an equation representing the ratio of the distance d1 from the artery 22 to the boundary 25 of the arterial dominating region and the distance d2 from the artery 23 to the boundary 25 of the arterial dominating region.

The ranges from the calculated boundary 25 of the arterial dominating region to the respective arteries 22 and 23 are defined as arterial dominating regions 26 and 27 that are symmetrically expanded around the arteries 22 and 23, respectively.

In FIG. 6 (b), two points A and B (or points C and D) on the line perpendicular to the blood vessel core line from the blood vessel cross-sectional position separated from the branch points of the arteries 22 and 23 by a predetermined distance are calculated points. An example is shown. The image processing device 122 sets calculation points in the same way at each blood vessel cross-sectional position from the branch point to the end of each blood vessel, and based on the ratio of the contrast agent diffusion speed at each calculation point, the boundary between the artery and the arterial control region A distance ratio up to 25 (distance d1: d2) is obtained, and thereby the position of the boundary 25 at each blood vessel cross-sectional position is calculated.

Note that the calculation points (points A, B, points C, D) are not limited to the example of being points on a line perpendicular to the blood vessel core line. For example, calculation points are set radially from the blood vessel core line, or calculation points (points A, B, C, D) are set on points on a plurality of parallel lines set at equal intervals from the branch points 24 of the arteries 22, 23, respectively. ) May be set.

The image processing apparatus 122 similarly identifies the vein-dominated region (the boundary 35 of the vein-dominated region and the vein-dominated regions 36, 37) of each vein 32, 33 for the vein (step S108). FIG. 7 is a diagram showing the vein-dominated region (the boundary 35 of the vein-dominated region and the vein-dominated regions 36 and 37).

After calculating the artery-dominated region and the vein-dominated region, the image processing device 122 next identifies the blood stagnation region 71 (step S109).

FIG. 8 is a diagram showing the arterial dominating region of FIG. 5 and the venous dominating region of FIG. 7 in an overlapping manner, and FIG. 9 shows a blood stagnation region 71 when the vein 33 is excised in the vicinity of a branch point. FIG. The blood stagnation region 71 is a region that becomes congested because there is no vein from which blood flowing in from the artery flows out when the vein is excised. That is, the blood stagnation region 71 is determined by the positional relationship between the artery-dominated region and the vein-dominated region and the blood vessel cutting position.

As shown in FIG. 9, the blood stagnation region when the vein 33 is removed from the vicinity of the branch point 34 is a region 71 where the arterial control region 27 and the vein control region 37 overlap. In the hepatectomy, it is necessary to determine the hepatectomy line so that the blood stagnation region 71 is removed together with the tumor.

The image processing device 122 sets the cutting position of each blood vessel (step S110). FIG. 10 shows a hepatectomy region when an arterial cutting position (blood vessel cutting position) 81 is set near the arterial branch point 24 and a venous cutting position (blood vessel cutting position) 82 is set near the venous branch point 34. FIG. First, the image processing apparatus 122 sets a cutting position (arterial cutting position) 81 at a position close to the branch point 24 of the artery 22 that is a feeding blood vessel of the tumor 41. Further, the vein cutting position 82 is set on a line perpendicular to the core line of the vein 33.
The core wire of the vein 33 is obtained at the time of calculation in step S105.

The image processing apparatus 122 calculates a hepatectomy line at the blood vessel cutting position set in step S110 (step S111). A hepatectomy line (line surrounding the hepatectomy area 83) is defined as an area 83 surrounded by the arterial control area 26, the blood stasis area 71, the extension line of the arterial cutting position 81, and the extension line of the venous cutting position 82. calculate.

The image processing apparatus 122 calculates the hepatectomy volume and the blood stasis capacity in the hepatectomy line calculated in step S111 (step S112), and stores them in the RAM or the like. Then, it is determined whether or not minimization of the hepatectomy region (minimization of blood stasis capacity) is possible (step S113). In the determination process of step S113, for example, the artery cutting position 81 can be moved from the position of the tumor 41 to the distal side, or if the artery cutting position 81 has reached the movement limit to the distal side, the vein It is determined whether the cutting position 82 can be moved to the distal side independently. When any one of these conditions is satisfied, it is determined that the blood stasis capacity can be reduced and the hepatectomy region can be minimized.

When the liver resection area can be minimized (step S113; Yes), the image processing apparatus 122 performs the liver resection area minimization process. Specifically, the process returns to step S110, and the arterial cutting position (blood vessel cutting position) 91 is moved to the distal side along the core line of the artery 22 as shown in FIG. The arterial cutting position 91 is automatically set from the position of the tumor 41 and a preset tumor margin. The vein cutting position (blood vessel cutting position) 92 at this time is set on a line perpendicular to the core line of the artery 22 at the artery cutting position 91 after movement. When the arterial cutting position 91 and the vein cutting position 92 are thus set, the hepatectomy region 93 is determined, and the hepatectomy line is calculated from the hepatectomy region 93. The image processing apparatus 122 calculates the hepatectomy volume and the blood stasis capacity when excision is performed on the calculated hepatectomy line, and stores it in the RAM (steps S110 to S112).

When the movement of the arterial cutting position 91 reaches the limit, the cutting position of the artery is determined.

The image processing device 122 further determines whether or not the liver resection region can be minimized (step S113), and performs the minimization processing if possible.

In the minimization process after determining the arterial cutting position, the image processing device 122 fixes only the venous cutting position (blood vessel cutting position) 1001 along the core line of the vein 33 while the arterial cutting position 91 is fixed as shown in FIG. Move to the distal side. The region 1002 is the hepatectomy region when the position 1001 is set as the vein cutting position.

The image processing apparatus 122 calculates the hepatectomy line 1003 from the hepatectomy region 1002, calculates the hepatectomy volume and blood stasis capacity when the hepatectomy line 1003 is excised, and stores it in the RAM. In the example shown in FIG. 12, the vein resection position 1001 reaches the vicinity of the end of the vein 33. The image processing apparatus 122 may further search for a hepatectomy line that eliminates the need for cutting the vein 33 from this state. That is, it is determined whether or not the vein 33 needs to be excised from the traveling direction of the distal end portion of the vein 33 and the positional relationship with another tumor.

If it is not necessary to excise the vein 33, the blood stagnation region 71 does not occur, and in this case, the hepatectomy region can be further reduced. That is, the hepatectomy line 1003 can be set as the position of the boundary 25 (line 1105 in FIG. 13) of the arterial region of the artery 22. As shown in FIG. 14, the hepatectomy region 1201 can be further reduced. The search for the hepatectomy line may be performed by a method such as adjusting (rotating) the angle of the line indicating the vein cutting position 1001 to positions 1102, 1103, 1104, and 1105 as shown in FIG. If it is known in advance that there is no tumor in the blood stagnation region 71, the angle of the line indicating the vein cutting position 1001 may be switched to the position of the boundary 25.

As shown in FIG. 15, when a tumor 42 other than the tumor 41 is present in the blood stagnation region 71, the image processing apparatus 122 determines a hepatectomy line in consideration of the position of the tumor 42. In the example of FIG. 15, the hepatic resection region 1301 is determined so that the vein 33 is not excised but the tumor 42 is included.

Also, as shown in FIG. 16 (a), when a tumor 43 other than the tumor 41 is present above the extension line of the arterial cutting position 91, the image processing device 122 is shown in FIG. The hepatectomy line 1403 may be set so as to include the tumor 43 by adjusting (rotating) the angle of the hepatectomy line near the vein cutting position (blood vessel cutting position) 1401. Thereby, it is possible to minimize the blood stagnation region and the hepatectomy region while resecting a plurality of tumors.

The cutting position of each blood vessel and the hepatectomy line where the blood stagnation volume is minimized are determined by the minimization process in steps S110 to S113 (step S114).

The image processing device 122 displays on the image the blood vessel cutting position and the hepatectomy line determined in the processing of steps S101 to S114 (step S115). At this time, it is desirable to further display the hepatectomy volume calculated in step S112.

In the above description, the example in which the hepatectomy region is minimized by moving the blood vessel cutting position from the branch point of the blood vessel to the end side is shown. On the contrary, from the end side of the blood vessel, It is also possible to minimize the hepatectomy region by moving the cutting position to the branch point side.

In addition, the procedure (Fig. 10) for determining the blood stasis capacity by placing the blood vessel cutting position at the branch point is omitted, and the arterial cutting position is set near the tumor 41 from the beginning to determine the blood stasis capacity, and the minimization process is performed. It may be a procedure to start.

As described above, the image processing apparatus 122 according to the first embodiment acquires the liver reserve capacity data, which is image data depicting the inside of the subject including the liver and data related to the local reserve capacity of the liver, A liver parenchyma region, a tumor, and a blood vessel are separated and extracted from the image data, and the dominant regions of the artery and vein in the extracted liver parenchyma region are calculated based on the liver reserve data. Then, the blood vessel cutting position and the hepatectomy line that minimize the hepatic resection region are determined based on the calculated arrangement of each dominant region and the tumor, and the determined blood vessel cutting position and the hepatectomy line are displayed on the display device 125.

This makes it possible to set the blood vessel cutting position on the terminal side of the branch point, and to determine and present a smaller resection area. In addition, since it is possible to specify an accurate blood vessel dominating region in consideration of a local liver reserve capacity change, an optimal hepatectomy line can be accurately obtained and presented.

In the hepatectomy region determination process, the image processing device 122 may correct the blood vessel cutting position and the hepatectomy line based on clinical data related to the tumor. That is, the data acquisition unit 122a acquires the clinical data regarding the extracted tumor as a correction parameter related to the determination of the blood vessel cutting position and the hepatectomy line, and the hepatectomy line determination unit 122d further determines the hepatectomy region based on the correction parameter. It is desirable to determine the minimal vessel cutting position and hepatectomy line.

Clinical data regarding tumors include, for example, tumor size, position, degree of growth, excision time, excision range, excision volume, and the like. Clinical data relating to this tumor is stored in, for example, a database for managing patient diagnosis information. The data acquisition unit 122a reads the clinical data of the patient as a correction parameter from the database.

Furthermore, the hepatectomy line determination unit 122d may calculate the hepatectomy line according to the operation time of the tumor and the operation time based on the past clinical data.

[Second Embodiment]
Next, another example of the blood vessel dominating region calculation process in steps S107 and S108 in FIG. 3 will be described.

When calculating the blood vessel dominating region in the hepatectomy region determination process shown in FIG. 3, in the first embodiment, the image processing device 122 calculates using the contrast agent diffusion rate ratio, but in the second embodiment, Furthermore, it is desirable to calculate the blood vessel dominating region in consideration of the blood vessel diameter.

That is, the image processing apparatus 122 first sets at least two points (point A and point B, point C and point D) on a line perpendicular to each blood vessel core line as shown in FIG. The contrast agent diffusion rates at points A and C are obtained from the peak time tp (FIG. 6 (a)) and the distance between two points (distance between point A and point B, distance between point C and point D).

The contrast agent diffusion rate at the point A in the vicinity of the artery 22 is obtained from the above equation (1), and the contrast agent diffusion rate at the point C in the vicinity of the artery 23 is obtained from the above equation (2).

The image processing device 122 calculates the boundary 25 between the control regions of the arteries 22 and 23 in consideration of the contrast agent diffusion speed and the blood vessel diameter at the points A and C in the vicinity of the arteries 22 and 23. The following equation (4) is an equation representing the ratio of the distance d1 from the artery 22 to the boundary 25 of the arterial dominating region and the distance d2 from the artery 23 to the boundary 25 of the arterial dominating region.

In equation (4), the diameter of the blood vessel is the diameter at the cross-sectional position on the perpendicular drawn from the calculation point to the blood vessel core line.

Since the blood flow volume varies depending on the blood vessel diameter, the contrast medium flow rate also varies. By considering the blood vessel diameter together with the contrast agent diffusion rate, the blood vessel dominating region can be calculated more accurately.

[Third embodiment]
When calculating the blood vessel dominating region, the image processing device 122 calculates, as liver reserve data, contour lines of arrival time for the contrast medium flowing out from each blood vessel to reach each point in the liver parenchymal region, and the contour lines for each blood vessel are calculated. The intersecting boundary may be the boundary of the blood vessel dominating region.

FIG. 17 (a) shows time-series data (TDC) indicating the contrast medium arrival time at each pixel, and FIG. 17 (b) shows the contrast medium flowing out from the arteries 22 and 23 reaching each point in the liver parenchyma region. It is a figure which shows the contour line which connects the points with equal arrival time tp. This contour line represents the diffusion state of the contrast agent.

The image processing device 122 sets a point where the contour lines generated from the artery 22 and the artery 23 intersect as a boundary 25 of the blood vessel control region.

Similarly, the contour line of the contrast medium arrival time is also obtained for the liver parenchymal region around the vein, and the point where the contour lines generated from the blood vessel 32 and the vein 33 intersect is defined as the boundary 35 of the blood vessel control region.

In the third embodiment, since the diffusion state of the contrast agent is obtained from the distribution of the contrast agent arrival time at each point around the blood vessel, finer local liver reserve data can be obtained. Thereby, a more accurate blood vessel dominating region can be obtained.

[Fourth embodiment]
FIG. 18 is a diagram showing a user interface suitable for the hepatectomy region determination process executed by the image processing apparatus 122 of the present invention.

18 has an image display area 51, a parameter setting area 52, an image selection area 53, a retouch instruction button 54, and the like.

In the image display area 51, the image 61 to be processed is displayed in the format selected in the image selection area 53. For example, if “3D” is selected in the image selection area 53, a 3D image created based on the original three-dimensional original image data is displayed. If “MPR” is selected in the image selection area 53, an MPR (Multi-Planar Reconstruction) image created based on the original three-dimensional original image data is displayed.

In the displayed image 61, blood vessels or tumors extracted by the extraction processing in steps S102 to S104 in FIG. 3 may be clearly shown so as to be distinguishable from the liver parenchyma. Also, lines 62 and 63 indicating the blood vessel cutting positions calculated in step S110 of FIG. 3 are displayed on each blood vessel. Further, it is desirable that the hepatectomy region 66 corresponding to the blood vessel cutting position is clearly indicated by a mask display or the like, or the hepatectomy line is clearly indicated.

In addition, each region is clearly shown on the image 61, such as a translucent mask superimposed on the blood vessel dominating region 64 calculated in step S107 and step S108, the line 67 indicating the boundary, and the blood stasis region 65 calculated in step S109. It is desirable.

The lines 62 and 63 indicating the blood vessel cutting position and the boundary line 67 are movable with a mouse or the like. When each line is moved, the hepatectomy region 66, the blood stagnation region 65, and the like are updated according to the line position.

The parameter setting area 52 is provided with an input field for receiving input of various parameters used in the hepatectomy region determination process. The parameters include, for example, hepatectomy volume, arterial cutting position (X, Y, Z), venous cutting position (X, Y, Z), tumor margin, and the like.

The image selection area 53 is displayed so that the type of image displayed in the image display area 51 can be selected. The types of images are not limited to 3D and MPR, and may include various images that can be created based on 3D original image data.

The retouch instruction button 54 is operated when an image displayed in the image display area 51 is updated. That is, when the retouch instruction button 54 is pressed after moving the lines 62 and 63 indicating the blood vessel cutting position, the boundary line 67, and the like, the image processing device 122 displays the hepatectomy capacity of the hepatectomy region according to the line position after the movement, The blood stagnation volume is recalculated, and the shape of the mask indicating each region is changed.

As described above, according to the fourth embodiment, the blood vessel cutting position can be specified for the displayed image data using the input device 121 such as a mouse. Further, when determining the hepatectomy line, the image processing apparatus 122 determines the hepatectomy line that minimizes the resection volume (blood stasis capacity) at the vascular cutting position specified on the image, and performs the vascular cutting on the operation screen 5. Update the display of position, hepatectomy line, and resection volume. Thus, since a user interface suitable for the hepatectomy region determination process can be provided, the operability can be improved.

Note that the hepatectomy region determination process described in each of the above embodiments may be executed by a general computer instead of the image processing apparatus 122 provided in the X-ray CT apparatus 1. Further, the system control device 124 of the X-ray CT apparatus 1 may perform the hepatectomy region determination process described in each of the above embodiments.

The preferred embodiments of the image processing apparatus and the like according to the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to such examples. It will be apparent to those skilled in the art that various changes or modifications can be conceived within the scope of the technical idea disclosed in the present application, and these naturally belong to the technical scope of the present invention. Understood.

1 X-ray CT device, 100 scan gantry unit, 101 X-ray source, 102 turntable, 104 opening, 105 bed, 106 X-ray detector, 107 data collection device, 120 console, 121 input device, 122 image processing device , 123 storage device, 124 system control device, 125 display device, 25 arterial control region boundary, 26, 27 arterial control region, 35 vein control region boundary, 36, 37 vein control region, 41, 42 tumor, 5 operation screen , 61 Image data, 71 Blood stagnation area, 81, 82, 91, 92, 1001, 1401 Blood vessel cutting position, 83, 93, 1002, 1201, 1301, 1404 Hepatectomy area

Claims (10)

A data acquisition unit that acquires image data depicting the inside of the subject including the liver and liver reserve data that is data related to the local reserve of the liver;
An extraction unit that separates and extracts a hepatic parenchymal region, a tumor, and a blood vessel from the image data;
A blood vessel dominating region calculating unit for calculating each dominating region of arteries and veins in the extracted liver parenchymal region based on the liver reserve capacity data;
A hepatectomy line determination unit that determines a vascular cutting position and a hepatectomy line based on the calculated location of each dominant region and the tumor;
A display unit for displaying the blood vessel cutting position and the hepatectomy line;
An image processing apparatus comprising: 2. The image processing apparatus according to claim 1, further comprising a liver reserve capacity data calculation unit that calculates the liver reserve capacity data based on contrast medium monitoring data. The liver reserve capacity data calculating unit calculates a contrast medium diffusion rate obtained from a transition of contrast medium arrival time at a plurality of arbitrary points in the liver parenchymal region as the liver reserve capacity data. An image processing apparatus according to 1. 4. The image processing apparatus according to claim 3, wherein the blood vessel dominating region calculation unit calculates the dominating region based on the contrast agent diffusion rate and the blood vessel diameter. The liver reserve capacity data calculating unit calculates the contour lines of the arrival time when the contrast medium flowing out from each blood vessel reaches each point of the liver parenchymal region as the liver reserve capacity data,
3. The image processing apparatus according to claim 2, wherein the blood vessel dominating region calculation unit sets a boundary where the contour lines of each blood vessel intersect as a boundary of the dominating region. 2. The image processing apparatus according to claim 1, wherein the display unit displays the resection volume as well as the blood vessel cutting position and the hepatectomy line on the image data. An input unit for designating the blood vessel cutting position for the displayed image data;
The hepatectomy line determination unit determines a hepatectomy line that minimizes the excision capacity at the designated blood vessel cutting position,
2. The image processing apparatus according to claim 1, wherein the display unit updates display of a blood vessel cutting position, a hepatectomy line, and an excision volume. The data acquisition unit acquires clinical data regarding the extracted tumor as a correction parameter related to the determination of the blood vessel cutting position and the hepatectomy line,
2. The image processing apparatus according to claim 1, wherein the hepatectomy line determination unit further determines a blood vessel cutting position and a hepatectomy line that minimize the hepatectomy region based on the correction parameter. An X-ray CT apparatus comprising the image processing apparatus according to claim 1. Executed by the image processing device,
Obtaining image data depicting the interior of the subject including the liver and liver reserve data that is data relating to the local reserve of the liver;
Separating and extracting liver parenchymal regions, tumors, and blood vessels from the image data;
Calculating the dominant regions of arteries and veins in the extracted liver parenchymal region based on the liver reserve data;
Determining a vascular cutting position and a hepatectomy line based on the calculated location of each dominant region and the tumor;
Displaying the blood vessel cutting position and the hepatectomy line on a display device;
An image processing method comprising:

Images