An imaging follow-up system after aortic dissection repair

Abstract

The present invention relates to the field of follow-up adjustment technology, and specifically to an imaging follow-up system after aortic dissection repair. The system includes an image acquisition module for acquiring and identifying the aortic region of the vascular cross-sectional image during follow-up; an image registration module for registering the aortic regions in adjacent follow-ups; a false lumen expansion analysis module for determining the false lumen region, and quantifying the area and extension direction changes of the false lumen to obtain an expansion index; a false lumen recovery evaluation module for obtaining a remodeling index by combining the stability of the false lumen region distribution and the expansion index with the grayscale distribution of the true lumen region, and obtaining a false lumen recovery index by combining the remodeling time series changes with the initial false lumen severity; and a follow-up adjustment module for adjusting the follow-up interval based on the false lumen recovery index. The present invention provides a more reasonable and reliable adjustment scheme by registering the aortic regions in multiple follow-ups, analyzing the influence of the false lumen expansion degree and direction on the recovery stability, evaluating the false lumen recovery and adjusting the follow-up strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of follow-up adjustment, and in particular to an imaging follow-up system after aortic dissection repair. Background Art

[0002] Aortic dissection is a life-threatening acute cardiovascular disease characterized by a tear in the aortic intima, allowing blood to leak into the media, forming a false lumen. Without prompt intervention, continued expansion of the false lumen can lead to aortic rupture, which carries a high mortality rate. The use of minimally invasive techniques such as thoracic endovascular aortic repair (TEVAR) has significantly improved patient outcomes. However, postoperative thrombosis of the false lumen, remodeling of the true lumen, and long-term complications such as aortic dilatation and endoleaks still require long-term imaging follow-up monitoring.

[0003] Traditional follow-up systems often use CTA reexaminations at fixed time intervals. However, due to individual differences among patients and the dynamic evolution of the disease, some patients' false lumens are completely thrombotic in the early postoperative period and do not require high-frequency follow-up. In contrast, some patients' false lumens continue to be patent or dilated and require more intensive monitoring to prevent the risk of rupture. Therefore, dynamic adjustment of follow-up is necessary.

[0004] Semantic segmentation is currently commonly used to obtain the patient's aortic region from the patient's CT image, and the processed image is transmitted to 3D modeling software to obtain a 3D model of the patient's aorta, so as to analyze the patient's recovery degree based on the ratio of the area of ​​the patient's true and false lumens. However, the position and shape of the aorta in the human body vary greatly among different patients, and the impact of blood flow on the false lumen varies, resulting in errors in the distinction of the patient's aortic region, and unable to reflect the difference in the impact of the patient's false lumen expansion on the patient's prognosis, making it difficult to provide a more reliable reference value and affecting the subsequent follow-up effect. Summary of the Invention

[0005] In order to solve the technical problems in the prior art that the position and shape of the aorta in different patients vary greatly, and the impact of blood flow on the false lumen varies, resulting in errors in distinguishing the patient's aortic region, and failing to reflect the differences in the impact of the patient's false lumen expansion on the patient's prognosis, making it difficult to provide a more reliable reference value, the purpose of the present invention is to provide an imaging follow-up system after aortic dissection repair. The technical solutions adopted are as follows:

[0006] The present invention provides an imaging follow-up system after aortic dissection repair, the system comprising:

[0007] An image acquisition module is used to obtain a cross-sectional image of the blood vessels obtained by CTA during each follow-up visit of the patient; the aorta region is determined based on the grayscale and morphological position distribution of the region in the cross-sectional image of the blood vessels;

[0008] an image registration module for determining a matching region for each aortic region in each follow-up in a previous follow-up based on similarities of aortic regions between different vascular cross-sectional images between two adjacent follow-ups;

[0009] The false lumen expansion analysis module is used to screen out false lumen regions from the aortic region based on the distribution of local aortic regions at edge points in vascular cross-sectional images. The expansion index of each false lumen region is obtained based on the changes in the area and extension direction between each false lumen region and the corresponding matching region during each follow-up.

[0010] The false lumen recovery assessment module is used to obtain the false lumen remodeling index at each follow-up based on the stability and distribution of expansion indicators of all false lumen areas at each follow-up, as well as the grayscale distribution of the aortic area in the non-false lumen area at each follow-up. The false lumen recovery index at the current follow-up is obtained by comparing the growth of the false lumen remodeling index in the consecutive follow-ups before the current follow-up with the false lumen area at the initial follow-up.

[0011] The follow-up adjustment module is used to adjust the next follow-up interval based on the false lumen recovery index.

[0012] Furthermore, the method for obtaining the aorta region includes:

[0013] Obtain the suspected area in the cross-sectional image of the blood vessel by edge segmentation;

[0014] For any suspected region in a single blood vessel cross-sectional image, the ratio of the mean to the range of the grayscale values ​​in the suspected region is used as the grayscale distribution characteristic value of the suspected region;

[0015] The maximum curvature on the edge of the suspected region is used as the contour curvature of the suspected region; the ratio of the mean gradient value of the edge points of the suspected region boundary to the contour curvature is used as the shape distribution characteristic value of the suspected region;

[0016] Performing negative correlation mapping on the distance between the center point of the suspected area and the center point of the cross-sectional image of the blood vessel in which it is located, to obtain a position distribution characteristic value of the suspected area;

[0017] Combining the grayscale distribution characteristic value, shape distribution characteristic value and position distribution characteristic value of the suspected area, obtaining the possible index of the aorta of the suspected area;

[0018] The suspected area with possible aortic indicators greater than the preset screening threshold is regarded as the aortic area.

[0019] Furthermore, the method for obtaining the matching region of the aorta region includes:

[0020] For any vascular cross-sectional image in a single follow-up, the similarity of pixel value distribution between the vascular cross-sectional image and each vascular cross-sectional image in the previous follow-up is analyzed, and a matching vascular image of the vascular cross-sectional image is determined from the previous follow-up;

[0021] For any aortic region in the cross-sectional image of the blood vessel, each aortic region in the matching blood vessel image is sequentially used as an analysis region; and an area similarity index is obtained based on the degree of similarity between the area size of the aortic region and the analysis region;

[0022] The differences in possible aortic indices between the aorta region and the analysis region are negatively correlated to obtain a similarity index of regional characteristics;

[0023] The distance between the center coordinates of the aorta region and the analysis region is negatively correlated to obtain the regional position similarity index;

[0024] Combining the area similarity index, regional feature similarity index and regional position similarity index between the aorta region and the analysis region, a matching index between the aorta region and the analysis region is obtained;

[0025] The aorta region with the maximum matching index in the matching blood vessel image is used as the matching region of the aorta region.

[0026] Furthermore, the method for obtaining the false lumen area includes:

[0027] For any edge point of the aortic region, a perpendicular line is drawn to the tangent line at the edge point; when the perpendicular line passes through two different aortic regions on both sides of the edge point, the edge point is regarded as the separation layer edge point;

[0028] The area connected by the edge points of the separation layer is taken as the separation layer area; the two aorta areas on both sides of the separation layer area with the smallest grayscale mean are taken as the false lumen area.

[0029] Furthermore, the method for obtaining the expansion index includes:

[0030] The center of gravity of the false cavity area is pointed toward the farthest edge point as the extension direction of the false cavity area;

[0031] For any false lumen area in a single follow-up, the ratio of the area size between the false lumen area and the corresponding matching area is used as the area change index of the false lumen area;

[0032] Obtaining a direction change index of the false cavity region according to an included angle between the extension directions of the false cavity region and the corresponding matching region;

[0033] The expansion index of the false lumen region is obtained by combining the area change index and the direction change index of the false lumen region.

[0034] Furthermore, the method for obtaining the false lumen remodeling index includes:

[0035] For any follow-up, the cross-sectional image of the blood vessels in the area with the false lumen in that follow-up was used as the target image;

[0036] The ratio of the number of all vascular cross-sectional images in the follow-up to the number of target images is used as the false lumen distribution coefficient of the follow-up;

[0037] Calculate the grayscale mean of the aorta region in all non-false lumen regions in the target image during the follow-up to obtain the true lumen impact index of the follow-up;

[0038] Perform negative correlation mapping on the product of the mean and range of the expansion index in the follow-up to obtain the expansion stability index of the follow-up;

[0039] The false lumen remodeling index of this follow-up was obtained by combining the false lumen distribution coefficient, true lumen influence index and expansion stability index of this follow-up.

[0040] Furthermore, the method for obtaining the false lumen recovery index includes:

[0041] The ratio of the false lumen remodeling index of a single follow-up to the false lumen remodeling index of the previous follow-up was taken as the effective recovery value of a single follow-up; when the effective gray value was greater than 1, the corresponding follow-up was recorded as a recovery follow-up;

[0042] The maximum number of consecutive recovery follow-ups was counted to obtain the number of effective recovery follow-ups; the ratio of the number of effective recovery follow-ups to the total number of follow-ups was used as the indicator of the stable recovery duration of the current follow-up;

[0043] The mean of the effective recovery values ​​of all follow-ups was used as the recovery amplitude indicator of the current follow-up; the mean of the area size of all false lumen regions in the first follow-up in time series was negatively correlated and mapped as the initial state indicator of the current follow-up;

[0044] The false lumen recovery index of the current follow-up is obtained by combining the stable recovery time index, recovery amplitude index and initial state index of the current follow-up.

[0045] Furthermore, adjusting the next follow-up interval based on the false lumen recovery index includes:

[0046] The false lumen recovery index of the current follow-up was normalized to obtain the adjustment coefficient;

[0047] The product of the adjustment coefficient and the interval duration of the next follow-up is used as the adjustment degree; the sum of the adjustment degree and the interval duration is rounded to obtain the adjusted interval duration of the next follow-up.

[0048] Furthermore, the method for obtaining the matching blood vessel image includes:

[0049] Each vascular cross-sectional image in the previous follow-up was used as the image to be matched;

[0050] The cross-sectional image of the blood vessel is binarized and then subtracted from the image to be matched, and the number of pixels whose subtraction result is zero is counted as the similarity number;

[0051] The corresponding vascular cross-sectional image in the previous follow-up when the similarity number is the largest is used as the matching vascular image of the vascular cross-sectional image.

[0052] Furthermore, the method for obtaining the suspected area includes:

[0053] The blood vessel cross-sectional image is segmented using the Sobel operator, and the segmentation results are subjected to a morphological closing operation, and the resulting closed area is used as the suspected area.

[0054] The present invention has the following beneficial effects:

[0055] The present invention accurately identifies the aortic region based on the grayscale distribution and position characteristics of the cross-sectional image of the blood vessels, and further similarly aligns the image regions during different follow-up periods to reduce the problem of plane misalignment caused by differences in patient posture or changes in aortic morphology during detection at different periods, ensuring that the anatomical positions of different follow-up images are aligned, and providing a reliable basis for subsequent time series comparison. In the evaluation of false lumen recovery, the expansion index is obtained by quantifying the changes in the false lumen area and extension direction, and the false lumen expansion of the patient is evaluated in combination with the false lumen morphology analysis. The impact of the false lumen recovery is considered and analyzed, so that a more comprehensive analysis of the false lumen recovery can be made later. The changes in the false lumen expansion trend and the functional status of the true lumen are combined, and the remodeling index is obtained by combining the distribution of the false lumen area and the stability of the expansion index with the grayscale distribution of the true lumen area. This provides a dynamic basis for identifying the progress of recovery, and the false lumen recovery index is obtained by combining the time series remodeling situation with the initial severity of the false lumen. The follow-up interval strategy is adjusted based on the false lumen recovery index to improve the follow-up effect. The present invention aligns the aortic regions at different stages and analyzes the impact of the false lumen expansion degree and direction on the recovery and stability of patients with aortic dissection based on the morphological changes of the false lumen at different stages, thereby evaluating the recovery status and adjusting the follow-up strategy, providing a more reasonable and reliable adjustment plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 This is a structural diagram of an imaging follow-up system after aortic dissection repair provided by one embodiment of the present invention;

[0058] Figure 2 A schematic diagram of a cross-sectional image of a blood vessel provided by one embodiment of the present invention;

[0059] Figure 3 A schematic diagram of a segmentation result provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] To further illustrate the technical means and effectiveness of the present invention to achieve its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of an imaging follow-up system for aortic dissection repair according to the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0061] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0062] The specific scheme of the imaging follow-up system after aortic dissection repair provided by the present invention is described in detail below with reference to the accompanying drawings.

[0063] See also Figure 1 , which shows a structural diagram of an imaging follow-up system after aortic dissection repair provided by an embodiment of the present invention, the system includes: an image acquisition module 101, an image registration module 102, a false lumen expansion analysis module 103, a false lumen recovery assessment module 104 and a follow-up adjustment module 105.

[0064] The image acquisition module 101 is used to acquire a vascular cross-sectional image obtained by CTA during each follow-up of the patient; and determine the aorta region based on the grayscale and morphological position distribution of the region in the vascular cross-sectional image.

[0065] Follow-up is the work done by hospitals to maintain contact with patients after diagnosis and treatment or require patients to come to the hospital for regular checkups based on the needs of medical treatment, scientific research, and teaching, and to continue to track and observe the patient's disease efficacy and development status. The embodiment of the present invention analyzes the patient's condition through imaging and adjusts the frequency of postoperative follow-up.

[0066] In the embodiment of the present invention, at each follow-up examination, the patient is placed supine on a CT bed and a contrast agent is injected into the patient, so that the contrast agent is distributed in the blood vessels along with the blood flow. A CTA image of the patient's aorta is obtained using a CT scanner. The cross-sectional image after the plain scan is used as the vascular cross-sectional image. During the layer-by-layer scanning process, a cross-sectional image is generated for each layer, and multiple vascular cross-sectional images are obtained during a single follow-up examination. Figure 2 , which shows a schematic diagram of a blood vessel cross-sectional image provided by an embodiment of the present invention, which is a cross-sectional image of a patient at the aortic arch layer.

[0067] Based on the CTA imaging characteristics of the aorta, segmenting the aorta facilitates subsequent analysis. Under the influence of contrast agents, the aorta exhibits high grayscale and uniform grayscale distribution, significantly different from other human structures. This means that the gradient amplitude at the region's edges is large. The aorta's regular shape results in smoother contours at the edges of its cross-sectional regions. In cross-sectional imaging, the aorta is typically located in the center of the image. Therefore, the aorta region is determined by combining the grayscale, morphological, and positional characteristics of the region in the cross-sectional image.

[0068] Preferably, in an embodiment of the present invention, the method for acquiring the aorta region includes:

[0069] First, edge segmentation is performed to obtain the suspected region in the cross-sectional image of the blood vessel. In the embodiment of the present invention, the cross-sectional image of the blood vessel is segmented using the Sobel operator, and the region boundaries are extracted by edge detection to segment the image. After the segmentation result is subjected to morphological closing operation, that is, the broken edges are filled, the closed region formed is regarded as the suspected region. Figure 3 , which shows a schematic diagram of a segmentation result provided by an embodiment of the present invention. It should be noted that the Sobel operator and the morphological closing operation are both well-known technical means to those skilled in the art and will not be described in detail here.

[0070] First, for any suspected area in a single vascular cross-sectional image, the ratio of the mean to the range of the grayscale values ​​in the suspected area is used as the grayscale distribution characteristic value of the suspected area. Through angiography, the grayscale value of the vascular part is high and uniform. Therefore, when the grayscale distribution characteristic value is larger, it means that the grayscale fluctuation in the area is smaller and the overall distribution of the grayscale value is higher, and the area is more likely to be the aorta area.

[0071] The maximum curvature at the edge of the suspected region is then used as the contour curvature of the suspected region. By calculating the curvature at each point on the region's edge, the maximum curvature reflects the most dramatic change in the morphological boundary. The ratio of the mean gradient value of the suspected region's edge points to the contour curvature is then used as the shape distribution characteristic of the suspected region. A higher overall gradient amplitude indicates a greater region's distinctness, while a smaller contour curvature indicates a smoother boundary and a higher likelihood of the region being an aorta.

[0072] A negative correlation mapping is then performed between the center point of the suspected region and the center point of the cross-sectional image of the vessel in which it is located to obtain a position distribution characteristic value for the suspected region. The smaller the distance between the center points, the more the region is distributed toward the center of the image, and the higher the likelihood that it is an aortic region. It should be noted that calculating the distance between two points and negative correlation mapping are both well-known techniques familiar to those skilled in the art. Distance calculation can use Euclidean distance, and negative correlation mapping can use a negative exponential form. These techniques are not further elaborated or limited herein.

[0073] Finally, the grayscale distribution characteristic value, shape distribution characteristic value and position distribution characteristic value of the suspected area are combined to obtain the possible index of the aorta of the suspected area. In an embodiment of the present invention, the product of the grayscale distribution characteristic value, the shape distribution characteristic value and the position distribution characteristic value is normalized as the possible index of the aorta of the suspected area. The larger the possible index of the aorta is, the more likely the area is to be the corresponding area of ​​the aorta.

[0074] Therefore, suspected regions with aortic probabilities greater than a preset screening threshold are considered aortic regions. In the embodiment of the present invention, the preset screening threshold is set to 0.8, and the specific value can be adjusted by the implementer. It should be noted that normalization is a technical means well known to those skilled in the art, and the normalization method can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0075] The image registration module 102 is configured to determine a matching region of each aortic region in each follow-up in a previous follow-up based on similarities of the aortic regions between different vascular cross-sectional images between two adjacent follow-ups.

[0076] Aortic dissection occurs when the intima is damaged by the impact of blood, allowing blood to enter the middle layer of the aortic wall and accumulate in the media, thus forming a new cavity, the false lumen. After repair surgery, aortic remodeling is performed to prevent the continued expansion of the false lumen. During the remodeling period, the morphology of the true and false aortic lumens changes to a certain extent, and there will be multiple aortic regions in the cross-sectional images of the blood vessels, such as cross-sectional images of the chest and abdomen. Therefore, registration is required to provide a data basis for subsequent analysis of changes. Because the patient's body position or breathing depth varies at each follow-up, the aortic layering during the scan will be different. Therefore, before performing inter-regional registration, it is necessary to first screen images of similar layers and then perform inter-regional similarity analysis.

[0077] Preferably, in an embodiment of the present invention, the method for acquiring the matching region of the aorta region includes:

[0078] First, for any vascular cross-sectional image in a single follow-up, the similarity of pixel value distribution between the vascular cross-sectional image and each vascular cross-sectional image in the previous follow-up is analyzed, and the matching vascular image of the vascular cross-sectional image is determined from the previous follow-up.

[0079] In this embodiment of the present invention, each vascular cross-sectional image from the previous follow-up visit is sequentially used as the image to be matched, and the images from the previous follow-up visit are analyzed sequentially. The vascular cross-sectional image and the image to be matched are binarized and then subtracted. The number of pixels with a zero result after the subtraction is counted as the similarity factor. The greater the number of zero pixels after the subtraction, the more similar the patient's anatomy in the two images, and the greater the likelihood that the two corresponding images represent examination results of similar layers of the patient. Therefore, the vascular cross-sectional image from the previous follow-up visit with the largest similarity factor is selected as the matching vascular image for that vascular cross-sectional image.

[0080] Since the position of the aorta of the same patient changes little at different stages, and the deformation degree of the aorta in a single follow-up is relatively similar to that in the previous follow-up, that is, its grayscale distribution and regional area should also be relatively similar, registration analysis is performed based on area, regional characteristics and position.

[0081] For any aortic region in the cross-sectional vascular image, each aortic region in the matching vascular image is sequentially used as an analysis region, and an approximate analysis is performed on each region between the matching images. An area similarity index is obtained based on the degree of similarity between the area sizes of the aortic region and the analysis region. In this embodiment of the present invention, the total number of pixels in the region is used as the area size of the region. The difference in area size between the aortic region and the analysis region is negatively correlated to obtain the area similarity index. The absolute value of the difference is used as the difference in area size. The smaller the difference in area size, the more similar the areas are.

[0082] In other embodiments of the present invention, the difference in area between the aorta region and the analysis region can also be used as the area deviation, and the ratio of the area size of the active region to the area deviation can be used as the area similarity index. The degree of similarity can be reflected by combining the area size of the active region with the analysis area difference.

[0083] The aorta region is negatively correlated with the difference in possible aorta indicators between the analysis regions to obtain the regional feature similarity index. The possible aorta indicators reflect the aorta characteristics in the region, and the difference between possible aorta indicators is used to reflect the feature deviation between regions. The smaller the difference, the more similar the regions are.

[0084] The distance between the center coordinates of the aortic region and the analysis region is negatively correlated to obtain the regional position similarity index. The smaller the distance, the more the regions correspond to the same position and the higher the possibility that they are the same aortic region.

[0085] Finally, the area similarity index, regional feature similarity index and regional position similarity index between the aorta region and the analysis region are combined to obtain the matching index between the aorta region and the analysis region. In an embodiment of the present invention, the area similarity index, regional feature similarity index and regional position similarity index between the aorta region and the analysis region are multiplied to obtain the matching index between the aorta region and the analysis region. The larger the matching index, the more similar the two regions are.

[0086] When the matching index is the largest, the two regions are considered to be the imaging manifestations of the same aorta region at different follow-up times. Therefore, the aorta region with the largest matching index in the matching vascular image is used as the matching region of the aorta region.

[0087] The false lumen expansion analysis module 103 is used to screen out the false lumen area from the aortic area based on the local distribution of the aortic area at the edge points in the vascular cross-sectional image; and obtain the expansion index of each false lumen area based on the changes in the area and extension direction between each false lumen area and the corresponding matching area in each follow-up.

[0088] Aortic dissection repair promotes thrombosis and ossified absorption of the false lumen. The imaging results of the false lumen also change with the process of aortic dissection repair. For example, before thrombosis, under the continuous impact of blood flow, the false lumen may have a certain expansion trend. As the thrombus forms and ossified absorption occurs, the volume of the false lumen may be smaller than that in the early stage of thrombosis. Therefore, in order to obtain the repair status of the patient's false lumen, it is necessary to analyze the expansion of the patient's false lumen at each follow-up.

[0089] First, it is necessary to distinguish between the true and false lumen. Since the true lumen is the channel for normal blood circulation, the blood flow velocity is faster, the contrast agent is quickly filled, and the density under CTA imaging is higher, while the blood flow velocity in the false lumen is slower, the pressure is higher, and blood accumulation is formed due to damage to the intima. Therefore, the presence of the false lumen can be judged and analyzed by the distribution of the aortic area on both sides of the membrane edge.

[0090] Preferably, in an embodiment of the present invention, the method for obtaining the false lumen region includes:

[0091] Because the true and false lumens of the aorta are separated by the intima and media, known as the separation layer, we traverse the edge pixels of the aorta region and analyze them. For any edge point in the aorta, we draw a perpendicular line to the tangent line at that edge point. When the perpendicular line passes through two different aortic regions on either side of the edge point, it indicates the presence of a false lumen region, and this edge point is considered the separation layer edge point. By marking the separation layer pixels, the area connected by the separation layer edge points is considered the separation layer region, and the two aortic regions are distributed on both sides of the separation layer region.

[0092] Furthermore, the aorta region with the smallest grayscale mean value on both sides of the separation layer region is taken as the false lumen region, and the other aorta region is taken as the true lumen region.

[0093] The expansion condition is analyzed by determining the false lumen area. In an embodiment of the present invention, the expansion condition is reflected by changes in area and extension to obtain an expansion index. The method for obtaining the expansion index includes:

[0094] First, the center of gravity of the false cavity area is pointed to the direction of the farthest edge point as the extension direction of the false cavity area. The farthest edge point is the edge point where the distance between the center of gravity and all edge points is the largest. The extension direction reflects the main expansion and compression direction of the false cavity area.

[0095] Furthermore, for any false lumen area in a single follow-up, the ratio of the area size between the false lumen area and the corresponding matching area is used as the area change index of the false lumen area. The larger the area change index, the greater the expansion of the current false lumen area compared with the previous follow-up.

[0096] Further, based on the angle between the extension directions of the false cavity area and the corresponding matching area, the direction change index of the false cavity area is obtained, and the extension direction difference is reflected by the angle. The larger the angle, the larger the direction change index, the greater the direction difference, and the more unstable the extension direction change.

[0097] In an embodiment of the present invention, the cosine value of the angle between the false lumen region and the corresponding matching region is calculated by cosine value quantization, and negative correlation mapping and normalization are performed to obtain a direction change index. In other embodiments of the present invention, the radian value of the angle can also be directly used for normalization to directly reflect the angle size and obtain a direction change index, which will not be described in detail here.

[0098] Finally, the area change index and the direction change index of the false lumen region are combined to obtain the expansion index of the false lumen region. In an embodiment of the present invention, the product of the area change index and the direction change index of the false lumen region is used as the expansion index of the false lumen region. The larger the expansion index, the more significant the expansion trend of the false lumen region.

[0099] The false lumen recovery evaluation module 104 is used to obtain the false lumen remodeling index of each follow-up based on the stability and distribution quantity of the expansion indicators of all false lumen areas in each follow-up, as well as the grayscale distribution of the aortic area in the non-false lumen area in each follow-up; and to obtain the false lumen recovery index of the current follow-up through the growth of the false lumen remodeling index of the continuous follow-up before the current follow-up and the area of ​​the false lumen area in the initial follow-up.

[0100] Aortic dissection repair usually promotes the formation and absorption of thrombus in the false lumen, so that the blood flow in the true lumen approaches normal. The expansion dynamics in the false lumen gradually weaken, so that the expansion direction and volume of the false lumen can remain stable, and the volume of the false lumen may even decrease or disappear. Therefore, the remodeling of the patient's aortic dissection is analyzed based on the degree of false lumen expansion during the patient's follow-up.

[0101] If the direction of false lumen expansion gradually stabilizes during historical follow-up, and the degree of expansion decreases, and the fewer CTA slices detect the false lumen, the better the remodeling effect of aortic dissection. Therefore, the more images containing the false lumen during follow-up, the greater the longitudinal extension of the false lumen, and the greater the expansion of the false lumen area in each image relative to the previous follow-up, the less smooth the blood flow in the true lumen area, that is, the more uneven the contrast agent passing through, and the smaller the grayscale value of the imaging area, then the worse the false lumen recurrence in the patient's current follow-up, and the smaller the false lumen remodeling index.

[0102] Preferably, in an embodiment of the present invention, the method for obtaining the false lumen remodeling index includes:

[0103] For any follow-up, the cross-sectional image of the vessel with the false lumen in that follow-up was used as the target image, and the ratio of the number of all cross-sectional images of the vessel in that follow-up to the number of target images was used as the false lumen distribution coefficient of that follow-up. The larger the false lumen distribution coefficient, the smaller the proportion of target images, the smaller the longitudinal extension of the false lumen along the vessel, and the better the remodeling.

[0104] Furthermore, the grayscale mean in the aorta area of ​​all non-false lumen areas in the target image during the follow-up was calculated to obtain the true lumen influence index of the follow-up, that is, to analyze the flow of the true lumen when the false lumen area existed. The larger the overall grayscale mean, that is, the larger the true lumen influence index, the less affected the flow of the true lumen was and the better the remodeling was.

[0105] Furthermore, the product of the mean and range of the expansion index in the follow-up was negatively correlated and mapped to obtain the expansion stability index of the follow-up. The smaller the range of the expansion index and the smaller the overall distribution of the values, that is, the larger the expansion stability index, the more stable the expansion situation and the lower the occurrence rate, indicating that the recovery state is stable and the remodeling situation is better.

[0106] Finally, the false lumen remodeling index for that follow-up is obtained by combining the false lumen distribution coefficient, true lumen influence index, and expansion stability index of that follow-up. In an embodiment of the present invention, the false lumen distribution coefficient, true lumen influence index, and expansion stability index of that follow-up are cumulatively multiplied to obtain the false lumen remodeling index for that follow-up. The false lumen remodeling index reflects the remodeling quality of a single follow-up.

[0107] Furthermore, the stability of remodeling over time can be combined to reflect effective recovery, and the severity of the false lumen at the initial follow-up can be combined to assess recovery at the current follow-up. If the degree of false lumen remodeling before the current follow-up is relatively stable, that is, the patient has a large number of follow-up visits in a state of effective recovery after aortic repair and the degree of recovery is significant, and the smaller the initial false lumen area, the higher the effective evaluation of aortic dissection recovery at the current follow-up.

[0108] Preferably, in an embodiment of the present invention, the method for obtaining the false lumen recovery index includes:

[0109] The ratio of the false lumen remodeling index at a single follow-up to the false lumen remodeling index at the previous follow-up was taken as the effective recovery value of a single follow-up. When the effective grayscale value was greater than 1, it indicated that the aortic false lumen had recovered better than that at the previous follow-up, and the corresponding follow-up was recorded as a recovery follow-up.

[0110] The maximum number of continuous distributions of recovery follow-ups was counted to obtain the number of effective recovery follow-ups. The ratio of the number of effective recovery follow-ups to the total number of follow-ups was used as the stable recovery duration indicator for the current follow-up. The larger the stable recovery duration indicator, the more and more stable the patient's effective recovery times in the time sequence of the follow-up process, and the better the recovery status.

[0111] The mean of the effective recovery values ​​of all follow-up visits was further used as the recovery amplitude index of the current follow-up visit. The larger the recovery amplitude index, the more significant the recovery degree and the better the patient's recovery status.

[0112] The mean area size of all false cavity regions in the first follow-up in time series was further negatively correlated and mapped as the initial state indicator of the current follow-up. The total distribution of the false cavity area in the first follow-up reflected the severity of the initial false cavity. The larger the area size distribution of the initial false cavity region, the smaller the initial state indicator, the more severe the initial state, the more difficult it is for the patient to recover to the ideal state, and the greater the limitation on the patient's recovery assessment.

[0113] Finally, the current follow-up stable recovery time index, recovery amplitude index, and initial state index are combined to obtain the current follow-up false lumen recovery index. In an embodiment of the present invention, the current follow-up stable recovery time index, recovery amplitude index, and initial state index are cumulatively multiplied to obtain the current follow-up false lumen recovery index. The larger the stable recovery time index, recovery amplitude index, and initial state index, the better the patient's recovery state and the less severe the initial state. At this time, the patient's false lumen recovery is better, so the false lumen recovery index is larger.

[0114] The follow-up adjustment module 105 is configured to adjust the next follow-up interval based on the false lumen recovery index.

[0115] The recovery status of the patient is reflected by the false lumen recovery index. The worse the patient's aortic recovery is, the more frequently the progression of the patient's disease needs to be monitored. This allows medical staff to obtain the patient's disease progression in a timely manner and adjust the treatment plan. Conversely, the follow-up frequency can be reduced and the efficiency of follow-up resource utilization can be improved.

[0116] In an embodiment of the present invention, the false lumen recovery index of the current follow-up is normalized to obtain an adjustment coefficient. It should be noted that the normalization of the false lumen recovery index maps the value range of the adjustment coefficient to [-1, 1], which is convenient for directly adjusting the time interval. The product of the adjustment coefficient and the interval duration of the next follow-up is used as the adjustment degree to reflect the degree to which the duration needs to be adjusted. The sum of the adjustment degree and the interval duration is rounded to obtain the adjusted interval duration of the next follow-up. It should be noted that rounding is a technical means well known to those skilled in the art, and rounding up can be used, etc., which is not limited here.

[0117] By outputting the adjusted interval for the next follow-up visit, it provides medical staff with an auxiliary reference for adjusting the follow-up strategy, making it easier to provide patients with a more appropriate follow-up strategy.

[0118] It should be noted that, for ease of calculation, all indicator data involved in the calculation in the embodiments of the present invention are pre-processed to eliminate dimension effects. Specific means of eliminating dimension effects are well known to those skilled in the art and are not limited here.

[0119] In summary, the present invention accurately identifies the aortic region based on the grayscale distribution and position characteristics of the cross-sectional image of the blood vessels, and further similarly aligns the image regions during different follow-up periods to reduce the problem of plane misalignment caused by differences in patient posture or changes in aortic morphology during detection at different periods, ensuring that the anatomical positions of different follow-up images are aligned, and providing a reliable basis for subsequent time series comparison. In the evaluation of false lumen recovery, the expansion index is obtained by quantifying the changes in the false lumen area and extension direction, and the false lumen expansion of the patient is evaluated in combination with the false lumen morphology analysis. The impact of the false lumen recovery is considered and analyzed, so that a more comprehensive analysis of the false lumen recovery can be made later. The changes in the false lumen expansion trend and the functional status of the true lumen are combined, and the remodeling index is obtained by combining the distribution of the false lumen area and the stability of the expansion index with the grayscale distribution of the true lumen area. This provides a dynamic basis for identifying the progress of recovery, and the false lumen recovery index is obtained by combining the time series remodeling situation with the initial severity of the false lumen. The follow-up interval strategy is adjusted based on the false lumen recovery index to improve the follow-up effect. The present invention aligns the aortic regions at different stages and analyzes the impact of the false lumen expansion degree and direction on the recovery and stability of patients with aortic dissection based on the morphological changes of the false lumen at different stages, thereby evaluating the recovery status and adjusting the follow-up strategy, providing a more reasonable and reliable adjustment plan.

[0120] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0121] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. An imaging follow-up system after aortic dissection repair, characterized in that: The system comprises: An image acquisition module is used to obtain a cross-sectional image of the blood vessels obtained by CTA during each follow-up visit of the patient; the aorta region is determined based on the grayscale and morphological position distribution of the region in the cross-sectional image of the blood vessels; an image registration module for determining a matching region for each aortic region in each follow-up in a previous follow-up based on similarities of aortic regions between different vascular cross-sectional images between two adjacent follow-ups; The false lumen expansion analysis module is used to screen out false lumen regions from the aortic region based on the distribution of local aortic regions at edge points in vascular cross-sectional images. The expansion index of each false lumen region is obtained based on the changes in the area and extension direction between each false lumen region and the corresponding matching region during each follow-up. The false lumen recovery assessment module is used to obtain the false lumen remodeling index at each follow-up based on the stability and distribution of expansion indicators of all false lumen areas at each follow-up, as well as the grayscale distribution of the aortic area in the non-false lumen area at each follow-up. The false lumen recovery index at the current follow-up is obtained by comparing the growth of the false lumen remodeling index in the consecutive follow-ups before the current follow-up with the false lumen area at the initial follow-up. The follow-up adjustment module is used to adjust the next follow-up interval based on the false lumen recovery index.

2. The imaging follow-up system after aortic dissection repair according to claim 1, characterized in that: The method for obtaining the aorta region includes: Obtain the suspected area in the cross-sectional image of the blood vessel by edge segmentation; For any suspected region in a single blood vessel cross-sectional image, the ratio of the mean to the range of the grayscale values ​​in the suspected region is used as the grayscale distribution characteristic value of the suspected region; The maximum curvature on the edge of the suspected region is used as the contour curvature of the suspected region; the ratio of the mean gradient value of the edge points of the suspected region boundary to the contour curvature is used as the shape distribution characteristic value of the suspected region; Performing negative correlation mapping on the distance between the center point of the suspected area and the center point of the cross-sectional image of the blood vessel in which it is located, to obtain a position distribution characteristic value of the suspected area; Combining the grayscale distribution characteristic value, shape distribution characteristic value and position distribution characteristic value of the suspected area, obtaining the possible index of the aorta of the suspected area; The suspected area with possible aortic indicators greater than the preset screening threshold is regarded as the aortic area.

3. The imaging follow-up system after aortic dissection repair according to claim 2, characterized in that: The method for obtaining the matching region of the aorta region includes: For any vascular cross-sectional image in a single follow-up, the similarity of pixel value distribution between the vascular cross-sectional image and each vascular cross-sectional image in the previous follow-up is analyzed, and a matching vascular image of the vascular cross-sectional image is determined from the previous follow-up; For any aortic region in the cross-sectional image of the blood vessel, each aortic region in the matching blood vessel image is sequentially used as an analysis region; and an area similarity index is obtained based on the degree of similarity between the area size of the aortic region and the analysis region; The differences in possible aortic indices between the aorta region and the analysis region are negatively correlated to obtain a similarity index of regional characteristics; The distance between the center coordinates of the aorta region and the analysis region is negatively correlated to obtain the regional position similarity index; Combining the area similarity index, regional feature similarity index and regional position similarity index between the aorta region and the analysis region, a matching index between the aorta region and the analysis region is obtained; The aorta region with the maximum matching index in the matching blood vessel image is used as the matching region of the aorta region.

4. The imaging follow-up system after aortic dissection repair according to claim 1, characterized in that: The method for obtaining the false lumen area includes: For any edge point of the aortic region, a perpendicular line is drawn to the tangent line at the edge point; when the perpendicular line passes through two different aortic regions on both sides of the edge point, the edge point is regarded as the separation layer edge point; The area connected by the edge points of the separation layer is taken as the separation layer area; the two aorta areas on both sides of the separation layer area with the smallest grayscale mean are taken as the false lumen area.

5. The imaging follow-up system after aortic dissection repair according to claim 1, characterized in that: The method for obtaining the expansion index includes: The center of gravity of the false cavity area is pointed toward the farthest edge point as the extension direction of the false cavity area; For any false lumen area in a single follow-up, the ratio of the area size between the false lumen area and the corresponding matching area is used as the area change index of the false lumen area; Obtaining a direction change index of the false cavity region according to an included angle between the extension directions of the false cavity region and the corresponding matching region; The expansion index of the false lumen region is obtained by combining the area change index and the direction change index of the false lumen region.

6. The imaging follow-up system after aortic dissection repair according to claim 1, characterized in that: The method for obtaining the false lumen remodeling index includes: For any follow-up, the cross-sectional image of the blood vessels in the area with the false lumen in that follow-up was used as the target image; The ratio of the number of all vascular cross-sectional images in the follow-up to the number of target images is used as the false lumen distribution coefficient of the follow-up; Calculate the grayscale mean of the aorta region in all non-false lumen regions in the target image during the follow-up to obtain the true lumen impact index of the follow-up; Perform negative correlation mapping on the product of the mean and range of the expansion index in the follow-up to obtain the expansion stability index of the follow-up; The false lumen remodeling index of this follow-up was obtained by combining the false lumen distribution coefficient, true lumen influence index and expansion stability index of this follow-up.

7. The imaging follow-up system after aortic dissection repair according to claim 1, characterized in that: The method for obtaining the false lumen recovery index includes: The ratio of the false lumen remodeling index of a single follow-up to the false lumen remodeling index of the previous follow-up was taken as the effective recovery value of a single follow-up; when the effective gray value was greater than 1, the corresponding follow-up was recorded as a recovery follow-up; The maximum number of consecutive recovery follow-ups was counted to obtain the number of effective recovery follow-ups; the ratio of the number of effective recovery follow-ups to the total number of follow-ups was used as the indicator of the stable recovery duration of the current follow-up; The mean of the effective recovery values ​​of all follow-ups was used as the recovery amplitude indicator of the current follow-up; the mean of the area size of all false lumen regions in the first follow-up in time series was negatively correlated and mapped as the initial state indicator of the current follow-up; The false lumen recovery index of the current follow-up is obtained by combining the stable recovery time index, recovery amplitude index and initial state index of the current follow-up.

8. The imaging follow-up system after aortic dissection repair according to claim 1, characterized in that: The adjustment of the next follow-up interval based on the false lumen recovery index includes: The false lumen recovery index of the current follow-up was normalized to obtain the adjustment coefficient; The product of the adjustment coefficient and the interval duration of the next follow-up is used as the adjustment degree; the sum of the adjustment degree and the interval duration is rounded to obtain the adjusted interval duration of the next follow-up.

9. The imaging follow-up system after aortic dissection repair according to claim 3, characterized in that: The method for obtaining the matching blood vessel image includes: Each vascular cross-sectional image in the previous follow-up was used as the image to be matched; The cross-sectional image of the blood vessel is binarized and then subtracted from the image to be matched, and the number of pixels whose subtraction result is zero is counted as the similarity number; The corresponding vascular cross-sectional image in the previous follow-up when the similarity number is the largest is used as the matching vascular image of the vascular cross-sectional image.

10. The imaging follow-up system after aortic dissection repair according to claim 2, characterized in that: The method for obtaining the suspected area includes: The blood vessel cross-sectional image is segmented using the Sobel operator, and the segmentation results are subjected to a morphological closing operation, and the resulting closed area is used as the suspected area.

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