CN112674872A - Aorta complex anatomical feature measuring method - Google Patents
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Abstract
The invention belongs to the technical field of medical treatment, and particularly discloses an aorta complex anatomical feature measurement method, which comprises the steps of collecting CT angiography data in a cardiac cycle, carrying out image reconstruction according to 20 time phases, carrying out the following operations on the CT angiography data of each time phase, segmenting a coronary artery tree, and obtaining a segmented coronary artery three-dimensional data set S; cutting the Valsalvs sinus to obtain a key surface and a key part of the Valsalvs sinus; coronary artery opening detection; transversely dividing the Valsalvs sinuses, and determining a sinotubular junction plane, an aortic valve annulus plane and an aortic sinus middle plane; vertically subdividing the Valsalvs sinus, dividing the non-coronary sinus, the right coronary sinus and the left coronary sinus. The invention can carry out 4D quantitative evaluation on the fine dissection of the aortic root, comprehensively evaluate the complex rotation, translation and scaling movement modes of the aortic root, provide the movement amplitude and range parameters by the statistical model established on the basis, and can provide early warning for abnormal conditions and provide basis for optimizing the operation scheme.
Description
Technical Field
The invention relates to an automatic measuring method for anatomical features of a four-dimensional voxel model, in particular to an anatomical feature measuring method for an aorta complex.
Background
At present, with the advent of minimally invasive surgical methods such as transcatheter aortic valve replacement (TAVR/TAVI), the possibility is provided for reducing the surgical risk of patients with aortic stenosis and improving the quality of life of patients after surgery, however, complications such as aortic dissection, valve abscission and displacement, paravalvular leakage, atrioventricular block, coronary artery blockage and the like easily occur after TAVR/TAVI surgery, and even death is caused. Among other things, the mismatch in prosthesis size and anatomical features of the patient's aortic complex is a major cause of its complications.
Therefore, accurate understanding and assessment of the geometric and anatomical features of the aortic valve complex are crucial to optimally selecting or designing prosthesis dimensions, identifying surgical risk factors, and the like. With the rapid progress of imaging technology, CT has become the golden standard for TAVI preoperative image evaluation, and CTA (CT Angiography) can clearly display anatomical structures and adjacent relations such as aorta, aortic sinus (also called Valsalva sinus), coronary artery opening, and the like, and provide image reference data for selecting a proper implant in surgery, reducing complications, postoperative recurrence, follow-up visit, and the like. The CTA image is used for dynamic quantitative evaluation of the aortic valve complex to automatically measure anatomical features, and the method has important significance for TAVR preoperative and postoperative image evaluation and postoperative cardiovascular and cerebrovascular event prevention.
Anatomical features of the aortic complex include measurements of the sinotubular junction, aortic annulus, Valsalva sinus, leaflets, and coronary height. Currently, clinical measurement of aortic root size is usually focused on the systolic phase, however, the aortic root changes its size with the periodic motion of the heart, and static anatomical measurement only in the systolic phase is usually prone to false estimation of over-or under-sizing of the prosthesis.
The limitations of the prior art mainly include the following aspects:
1. only a single phase (systolic phase or diastolic phase) is processed, and complicated positioning steps are involved, and the conventional imaging plane needs to be accurately positioned to the valve annulus plane through 7 steps, so that the operation process is complicated, time-consuming and labor-consuming;
2. the single measurement of the aortic anatomy in the systolic or diastolic phase results in large differences in the final measurement values, and the experts in 2019 have agreed that the measurement of the annulus size should be the largest size in the whole cardiac cycle, however, the largest size of the aortic complex is not fixed in the systolic or diastolic phase, and thus it is difficult to obtain accurate measurement values;
3. the accurate positioning of the anatomical features is mainly performed by the combination of image features and geometric features, and most of the prior art only measures the complicated anatomical structure of the aortic root from the image features, so that errors are easy to generate.
Disclosure of Invention
The invention aims to provide an aorta complex anatomical feature measuring method, which can automatically acquire an aorta root four-dimensional anatomical feature value according to ECG data in one cardiac cycle in a CTA image.
In order to achieve the purpose, the technical scheme of the invention is as follows: an aortic complex anatomical feature measurement method comprising the steps of:
s1, acquiring CT data for processing, acquiring CT angiography data in a cardiac cycle under the control of an electrocardiogram gate, performing image reconstruction on images acquired in the whole cardiac cycle according to 20 time phases, importing the images into MATLAB, and sequentially performing the following operations on the CT angiography data of each time phase;
s2, segmenting the coronary artery tree to obtain a segmented coronary artery three-dimensional data set S;
s3, cutting the Valsalvs sinus, obtaining a key surface and a key part of the Valsalvs sinus and determining geometric parameters of the key surface and the key part;
s31, coronary artery opening detection, constructing a detection region which can contain an aorta, detecting the detection region from the bottom to the top of a data set S, calculating a communication region of each image, detecting a peak value of the communication region of each image, wherein the positions of two coronary artery openings are respectively at the two maximum peak values in the data set S;
s32, transversely dividing the Valsalvs sinuses, determining a sinotubular junction plane, an aortic annular plane and an aortic sinus middle plane, calculating the circumferences, the areas and the maximum diameters of the sinotubular junction plane, the aortic annular plane and the aortic sinus middle plane, and calculating the distance between the midpoint of the sinotubular junction plane and the midpoint of the aortic annular plane to determine the aortic sinus height;
s33, vertically dividing the Valsalvs sinus, dividing the non-coronary sinus, the right coronary sinus and the left coronary sinus, calculating the distance from the lowest point of the non-coronary sinus, the right coronary sinus and the left coronary sinus to a sinus duct junction plane, determining the height of the non-coronary sinus, the right coronary sinus and the left coronary sinus, reading the pixel sum of each sinus part, wherein the volume of each sinus part is the sum of all pixels in the area multiplied by the pixel resolution ratio and then multiplied by the sum of the pixel layer spacing.
Preferably, step S32 includes passing through the apexes a of the triangle between the three leaflets of the aorta1(xA1，yA1，zA1)、A2(xA2，yA2，zA2)、A3(xA3，yA3，zA3) Creating a plane STJ, wherein the STJ plane is a sinotubular junction plane and passes through the lowest points B of three sinuses at the root of the aorta1(xB1，yB1，zB1)、B2(xB2，yB2，zB2)、B3(xB3，yB3，zB3) And (3) creating a Base plane, wherein the Base plane is the aortic annular plane, taking the middle part of the Valsalvs Sinus to create a Sinus plane, and the Sinus plane is the aortic Sinus middle plane.
Preferably, step S32 further includes calculating the height of the coronary ostium, reading the coordinate O of the left coronary sinus ostiumLCA(xL，yL，zL) And the coordinate O of the right coronary sinus ostiumRCA(xR，yR，zR) Projecting the left coronary sinus ostium and the coronary sinus ostium to the Base plane to obtain the projection image OLCA(x’L，y’L，Z’L) Is OLCAProjected coordinates in the Base plane, O'RCA(x’R，y’R，Z’R) Is ORCAProjection coordinates on the Base plane, height h of the left and right coronary artery openingsLAnd hRRespectively as follows:
preferably, in step S32, the specific method for calculating the perimeter, area and maximum diameter of the STJ plane, Base plane and Sinus plane is to cut the STJ, Base and Sinus image plane into rectangles with the length and width of T1 according to the center position, and to binarize the f (x, y) value by T2 to obtain a binary image fBW(x，y)，
Wherein T1 is a critical value of the rectangular length and width, T2 is a critical threshold value, and ROI area is fBW(x, y) covering a maximum connected area in the center of the area;
area: with fBWMultiplying the pixel resolution of the image by the sum of pixels 1 in a continuous region with the origin at the center of (x, y) to obtain the area A of the STJ, Base, Sinus plane ROISTJ，ABase，ASinus；
Perimeter Perimeter: obtaining the outermost edge pixel by calculating the farthest distance between each adjacent pixel pair around the ROI regional boundary, and obtaining the perimeter by accumulating the number of the outermost edge pixels to obtain PSTJ，PBase，PSinus；
Diameter: area A through ROISTJ，ABase，ASinusCalculating
Thereby obtaining DSTJ，DBase，Dsinus。
Preferably, in step S32, the value of the pixels of the STJ, Base, and Sinus images is calculated by calculating the normal vector of the STJ plane
As is noted above, the number of the channels,
ASTJ，BSTJ，CSTJcoordinates of the normal vector in X, Y and Z axes respectively; a. the1And A2Two points on the plane, A1A2‘＝(xA1-xA2，yA1-yA2，zA1-zA2) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
the value of each pixel point on the Base plane and the Sinus plane is the same as the STJ plane calculation method.
Preferably, step S33 includes establishing three mutually orthogonal planes P1, P2 and P3 perpendicular to the STJ plane, wherein the three planes P1, P2 and P3 all pass through the middle point 0 (x) of the STJ planeO，yO，zO) And the midpoint 0' of the Base plane (x)O′，yO′，zO′) Planes P1, P2, P3 divide the Valsalvs sinus into three portions, NCC, RCC, LCC.
Preferably, in step S33, the NCC, RCC, and LCC partial volumes are calculated by finding the pixel value in the three-dimensional pixel space between the STJ plane and the Base plane, which is greater than the threshold T3, to obtain the volume function V of the sinus regionROI(ii) a The P1, P2 and P3 planes are perpendicular to the VROIIs divided into three parts, each of which is VNCC、VRCCAnd VLCC，VNCC、VRCCAnd VLCCIs the sum of all pixels in the region multiplied by the pixel resolution multiplied by the sum of the pixel layer spacing.
Preferably, the pixel values of the P1, P2 and P3 panels in step S33 are obtained by using the normal vector of the P1 plane
As is noted above, the number of the channels,
are respectively normal vector
Coordinates in the X, Y, Z axes;
A1and 0 is two points on the plane, A1O‘＝(xA1-xO，yA1-yO，zA1-zO) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
the Z value of each pixel point on the P2 plane and the P3 plane is the same as the calculation method of the P1 plane.
Preferably, the method further comprises a step S3 of automatically counting the anatomical geometric feature value of one cardiac cycle through MATLAB,
fphase(S)＝(ft1(S)，ft2(S)，ft3(S)，...，ftn(S))
wherein, phase is all phases of a cardiac cycle, and n is 20; s is the vector of anatomical feature statistics for each phase (a ═ a)STJ，ABase，ASinus，PBase，PSinus，PSTJ，DSTJ，DBase，DSinus，VNCC，VRCC，VLCC，hL，hR)。
The beneficial effect of this scheme:
1. the established 4D visualization new method can make up the limitation that the prior CTA image post-processing technology is difficult to accurately evaluate the anatomical features of the aortic root in the cardiac cycle, can carry out 4D quantitative evaluation on the fine anatomy of the aortic root, comprehensively evaluates the anatomical feature change in the complex motion mode of the aortic root, provides the motion amplitude and range parameters for a statistical model established on the basis, can provide early warning for abnormal conditions and provides a basis for optimizing a surgical scheme;
2. the measuring method can realize automatic measurement of the distance from the opening of the coronary artery to the plane of the aortic valve annulus and automatic measurement of various anatomical features, quickly and accurately provide important parameters of the artificial valve for workers, assist the artificial valve replacement to perform preoperative evaluation, improve the success rate of the operation and reduce postoperative complications;
3. the measuring method can perform dynamic characteristic tracking on the sinotubular junction, the aortic sinus middle plane and the aortic annulus plane according to the major axis direction of the aorta, the area and the diameter extracted on the basis can improve the measuring accuracy of the sinotubular junction, and the parameters in the systole, the diastole or other periods are calculated and counted, so that an important basis is provided for finding out the required parameter values, the accuracy of the prosthesis size is ensured, and the measuring method is suitable for measuring the aorta of different patients;
4. by implementing the method, the anatomical assessment of the aortic root can be developed from plane to space and from static state to state, and the method can be developed from simple geometric assessment to comprehensive quantitative assessment combining anatomy and plaque load, can be used for accurately measuring the complex anatomical structure of the aortic root, and ensures the accuracy of data.
Drawings
FIG. 1 is a schematic representation of the aortic root features of an embodiment of the present invention;
FIG. 2 is a schematic view of a sinoaortic dissection in accordance with an embodiment of the present invention;
FIG. 3 is a schematic view of a sinotubular junction plane at 20 different time phases according to an embodiment of the present invention;
FIG. 4 is a schematic view of the aortic sinus mid-plane at 20 different phases in accordance with an embodiment of the present invention;
fig. 5 is a schematic representation of the aortic annulus plane at 20 different phases according to an embodiment of the present invention.
Detailed Description
The application provides an aorta complex anatomical feature measuring method, which can automatically acquire four-dimensional anatomical feature data of an aorta root according to ECG data in one cardiac cycle under the influence of CTA.
The following detailed description of the application refers to the accompanying drawings in which:
the method for measuring the anatomical features of the aortic complex provided by the embodiment comprises the following steps,
and S1, acquiring CT data, acquiring CT angiography data in one cardiac cycle, and carrying out image reconstruction on the images acquired in the whole cardiac cycle according to 20 time phases.
Specifically, retrospective analysis of retrospective cardiac gated CT images of the hearts of 30 patients without heart disease, with an average age of 53.5 ± 8.6 years, excluded populations with aortic calcification, atrial fibrillation, atrial flutter, escape rhythms, cardiac pacemaker installation, and used different coronary CTA contrast agent concentrations and injection flow rates according to patient weight. CT angiography data acquisition parameters comprise detector collimation 0.6mm, rotation time 330ms, tube voltage 100-120kV and tube current 400mA, synchronous continuous scanning images are obtained in the whole ECG period by adopting a retrospective electrocardiogram gating mode to form a contrast enhanced volume data set, and images acquired in the whole cardiac cycle are subjected to image reconstruction according to 20 time phases. Wherein, the image reconstruction layer thickness is 0.75mm, the reconstruction interval is 0.4mm, the reconstruction convolution kernel B26f, the resolution of a single image is 512 x 512 pixels, and the pixel resolution is 0.12mm x 0.12mm-0.45mm x 0.45 mm.
The CTA data was reconstructed at 20 time phase points and poured into MATLAB (R2019a, MathWorks, Inc) software to perform the following operations for each time phase.
S2, segmenting the coronary artery tree to obtain a segmented coronary artery three-dimensional data set S, and obtaining the coronary artery three-dimensional data set S in the simulation process by using the existing segmentation algorithm, for example, the specific obtaining method of the three-dimensional data set S in this embodiment is to obtain the segmented coronary artery three-dimensional data set S according to the extracting method in the "coronary artery blood vessel automatic extracting method based on three-dimensional morphology (CN201510497617.3A)" in the prior art, and the specific principle may be described in the patent literature, and is not described in detail in this embodiment.
S3, cutting the Valsalvs sinus (aortic sinus), obtaining key surfaces and key parts of the Valsalvs sinus and determining the geometrical parameters of the key surfaces and the key parts.
The critical surfaces referred to in this embodiment include, but are not limited to, the sinotubular junction plane, the aortic annulus plane, and the aortic sinus mid-plane, and the critical portions include, but are not limited to, the two coronary ostia, the non-coronary sinus, the right coronary sinus, and the left coronary sinus. The geometric parameters mainly comprise characteristic values such as the area, the perimeter, the maximum diameter and the like of an image where the plane is located, the positions, the heights and the like of openings of two coronary arteries, the volumes, the heights and the like of an uncarped sinus, a right coronary sinus and a left coronary sinus.
Specifically, S3 includes the steps of:
s31, coronary ostial detection
Starting from the bottom of the data set S, a circular structure is detected, and a detection region containing the aorta is constructed, and according to the size of the aorta section, the region of interest during detection is the region range of 128 × 128 of the image center in the embodiment. In the detection process, a connected region of each image detected from the bottom of the data set S is calculated, a statistical function F (S) of the connected region is established, the statistical function detects the peak value of the connected region of each image, and the positions of the two front maximum values of the F (S) are detected, namely the positions of the openings of the two coronary arteries respectively.
F(S)＝max(f1(x，y)，fi(x，y))，if fi(x，y)＞Troi(ii) a Wherein T isroiIn this example 5000, fiAnd (x, y) is the number of pixels in the ith connected region larger than 180, i is 1 … n, n is the number of connected regions, and the value of S is the number of layers of the CT image.
Reading corresponding characteristic value from MATLAB, wherein the coordinate of the left coronary sinus ostium is OLCA(xL，yL，zL) The coordinate of the right coronary sinus orifice is ORCA(xR，yR，zR). Referring to fig. 1, the junction of the left coronary artery LCA and the left coronary sinus LCC in fig. 1 is the left coronary sinus ostium OLCAThe joint of the right coronary artery RCA and the right coronary sinus RCC is the right coronary sinus ostium point ORCA。
S22, transversely dividing the Valsalvs sinuses, and determining a sinotubular boundary plane, an aortic annular plane and an aortic sinus middle plane
Firstly, an aorta root model is reconstructed, and six points are selected in a manual interactive mode and are respectively the vertexes A of triangles among three valve leaflets1(xA1，yA1，zA1)、A2(xA2，yA2，zA2)、A3(xA3，yA3，zA3) And the lowest point B of the three sinuses at the root of the aorta1(xB1，yB1，zB1)、B2(xB2，yB2，zB2)、B3(xB3，yB3，zB3)。
Then, passing through A1、A2、A3Three points create a plane STJ, which is the sinotubular junction plane, passing through B1、B2、B3The three points create a Base plane, which is the aortic annulus plane, and the median part of the vallsvs Sinus is taken to create a Sinus plane, which is the median plane of the aortic Sinus. Wherein, the middle part of Valsalvs sinus takes the STJ plane and the Base plane as the reference, and the midpoint O (x) of the STJ plane is read in MATLAB softwareO，yO，zO) Center point of Base plane O' (x)O′，yO′，ZO′)。0(xO，yO，zO) And O' (x)O′，yO′，zO') middle point of the line OSinusI.e. the middle part of the Valsalvs Sinus, the point of passing O of the Sinus planeSinusAnd 0 (x)O，yO，zO) And 0' (x)O′，yO′，zO′) The connecting line between the two is vertical to the Sinus plane. Between STJ plane and Base planeThe portion of (a) is the vallsvs sinus portion. Specifically, referring to fig. 2, reference numeral 1 is an STJ plane, reference numeral 2 is a Sinus plane, and reference numeral 3 is a Base plane.
(1) Solving STJ and Base planes
Specifically, the normal vector of the STJ plane is calculated
As is noted above, the number of the channels,
AsTJ，BSTJ，CSTJcoordinates of the normal vector in X, Y and Z axes respectively; a. the1And A2Two points on the STJ plane, A1A2‘＝(xA1-xA2，yA1-yA2，zA1-zA2) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
the solution of the Base plane is the same as the STJ plane, specifically, the normal vector of the Base plane is calculated
As is noted above, the number of the channels,
ABase，BBase，CBasecoordinates of the normal vector in X, Y and Z axes respectively;
B1and B2Two points on the plane, B1B2‘＝(xB1-xB2，yB1-yB2，zB1-zB2) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
the solution of the STJ plane and the Base plane, namely the feature of the sinotubular junction plane and the aortic annular plane is refined, and a basis is provided for the calculation of the perimeter, the area and the maximum diameter of the sinotubular junction plane and the aortic annular plane.
(2) Coronary ostial height calculation
The left coronary sinus ostium OLCAAnd the right coronary sinus ostium ORCAProjecting onto the Base plane to obtain OLCA(x’L，y’L，z’L) Is OLCAProjected coordinates in the Base plane, O'RCA(x’R，y’R，z’R) Is ORCAThe height h of the opening of the left and right coronary arteries can be obtained according to a distance formula between two points on the projection coordinates of a Base planeLAnd hRRespectively is as follows:
(3) aortic sinus height calculation
The midpoint of the STJ plane is 0 (x)O，yO，zO) The midpoint of the Base plane is 0' (x)O′，yO′，zO′) The distance between 0 and 0' is the height of the aortic sinus, the height of the aortic sinus can be calculated according to the distance formula between the two points,
(4) perimeter, area, and maximum diameter calculations for the STJ, Base, and Sinus planes
Cutting STJ, Base and Sinus image planes into a moment with the length and width of T1 according to the center positionThe shape is expressed by a function f (x, y), and the f (x, y) value is binarized by T2 to obtain a binary image fBW(x, y) wherein
T1 is a critical value of the length and width of the rectangle, T2 is a critical threshold, in this embodiment, T1 is 80, i.e., 80 × 80 rectangles, and T2 is 180, i.e., the connected region is found within the range of the threshold of 180. ROI area is fBW(x, y) covering the maximum connected region at the center of the region, and calculating the area, the perimeter and the diameter of the ROI, namely calculating the area, the perimeter and the diameter of an STJ plane, a Base plane and a Sinus plane;
area: with fBWMultiplying the pixel resolution of the image by the sum of pixels 1 in a continuous region with the origin at the center of (x, y) to obtain the area A of the STJ, Base, Sinus plane ROISTJ，ABase，ASinus；
Perimeter Perimeter: calculating the farthest distance between each adjacent pixel pair around the ROI regional boundary by using MATLAB to obtain the outermost edge pixel, and accumulating the number of the outermost edge pixels to obtain the perimeter to obtain PSTJ，PBase，PSinus；
Diameter: area A through ROISTJ，ABase，ASinusCalculating
Thereby obtaining DSTJ，DBase，DSinus。
S33, vertically dividing Valsalvs sinuses and dividing non-coronary sinus, right coronary sinus and left coronary sinus
Three mutually orthogonal planes P1, P2, P3 are established perpendicular to the STJ plane, the planes P1, P2, P3 all passing through the midpoint 0 (x) of the STJ planeO，yO，zO) And the midpoint 0' of the Base plane (x)O′，yO′，zO′) Planes P1, P2, P3 divide the Valsalvs sinus into three portions, the non-coronary sinus, the right coronary sinus, and the left coronary sinus, hereinafter referred to as NCC, RCC, LCC, see fig. 1 in particular.
Wherein, the P1 plane: is too much A1(xA1，yA1，zA1) Midpoint 0 (x) of the STJ planeO，yO，zO) And the midpoint 0' of the Base plane (x)O′，yO′，zO′) Plane of (2), normal vector
As is noted above, the number of the channels,
are respectively normal vector
Coordinates in the X, Y, Z axes;
A1and 0 is two points on the plane, A1O‘＝(xA1-xO，yA1-yO，zA1-zO) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
p2 plane: is too much A2(xA2，yA2，zA2) Midpoint 0 (x) of the STJ planeO，yO，zO) And the midpoint 0' of the Base plane (x)O′，yO′，zO′) Plane of (2), normal vector
As is noted above, the number of the channels,
are respectively normal vector
Coordinates in the X, Y, Z axes;
a2 and O are two points on the plane, A2O‘＝(xA2-xO，yA2-yO，zA2-zO) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
p3 plane: is too much A3(xA3，yA3，zA3) Midpoint O (x) of the STJ planeO，yO，zO) And the midpoint O' (x) of the Base planeO′，yO′，zO′) Plane of (2), normal vector
As is noted above, the number of the channels,
are respectively normal vector
Coordinates in the X, Y, Z axes;
A3and 0 is two points on the plane, A3O‘＝(xA3-xO，yA3-yO，zA3-zO) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
through solving the P1, P2 and P3 planes, the position information of the non-coronary sinus, the right coronary sinus and the left coronary sinus can be embodied through specific data, and referring to fig. 1, the part between P1 and P2 is the left coronary sinus, the part between P1 and P3 is the right coronary sinus, and the part between P3 and P2 is the non-coronary sinus.
(1) Height of non-coronary sinus, right coronary sinus and left coronary sinus
The coordinate of the lowest point of the left coronary sinus is known as B1(xB1，yB1，zB1) The coordinate of the lowest point of the non-coronary sinus is B2(xB2，yB2，zB2) The coordinate of the lowest point of the right coronary sinus is B3(xB3，yB3，zB3). Projecting the lowest points of the non-coronary sinus, the right coronary sinus and the left coronary sinus to an STJ plane to obtain the compound B1’(x’B1，y’B1，z’B1) Is B1(xB1，yB1，zB1) Projection coordinates in STJ plane, B2’(x’B2，y’B2，z’B2) Is B2(xB2，yB2，zB2) Projection coordinates in STJ plane, B3’(x’B3，y’B3，z’B3) Is B3(xB3，yB3，zB3) In the projection coordinate of the STJ plane, the heights of the left coronary sinus, the non-coronary sinus and the right coronary sinus can be calculated according to a distance formula between the two points, and the heights are respectively as follows:
(2) volume of NCC, RCC, LCC
Between STJ, Base planes in voxel spacePartial pixel values larger than the threshold value T3 are obtained to obtain the volume function V of the sinus regionROIWherein T3 is 180 in this embodiment;
p1, P2 and P3 convert VROIIs divided into three parts, each of which is VNCC、VRCCAnd VLCC；
VNCC、VRCCAnd VLCCThe volume size of (a) is the sum of all pixels in the region multiplied by the pixel resolution multiplied by the sum of the pixel layer spacing.
Further, the measurement method of the present example further includes step S3, automatically counting the anatomical geometric feature value of one cardiac cycle by MATLAB,
fphase(S)＝(ft1(S)，ft2(S)，ft3(S)，...，ftn(S))
wherein, phase is all phases of a cardiac cycle, and n is 20; m is the vector M ═ of anatomical feature statistics for each phase (a)STJ，ABase，ASinus，PBase，PSinus，PSTJ，DSTJ，DBase，DSinus，VNCC，VRCC，VLCC，hL，hR)。
The automatic statistics is carried out on the anatomical geometric characteristic values through MATLAB, the characteristic values under each time phase can be quickly called and identified, and follow-up work is conveniently carried out.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (9)
1. An aorta complex anatomical feature measurement method is characterized in that:
s1, acquiring CT data for processing, acquiring CT angiography data in a cardiac cycle under the control of an electrocardiogram gate, performing image reconstruction on images acquired in the whole cardiac cycle according to 20 time phases, importing the images into MATLAB, and sequentially performing the following operations on the CT angiography data of each time phase;
s2, segmenting the coronary artery tree to obtain a segmented coronary artery three-dimensional data set S;
s3, cutting the Valsalvs sinus, obtaining a key surface and a key part of the Valsalvs sinus and determining geometric parameters of the key surface and the key part;
s31, coronary artery opening detection, constructing a detection region which can contain an aorta, detecting the detection region from the bottom to the top of a data set S, calculating a communication region of each image, detecting a peak value of the communication region of each image, wherein the positions of two coronary artery openings are respectively at the two maximum peak values in the data set S;
s32, transversely dividing the Valsalvs sinuses, determining a sinotubular junction plane, an aortic annular plane and an aortic sinus middle plane, calculating the circumferences, the areas and the maximum diameters of the sinotubular junction plane, the aortic annular plane and the aortic sinus middle plane, and calculating the distance between the midpoint of the sinotubular junction plane and the midpoint of the aortic annular plane to determine the aortic sinus height;
s33, vertically dividing the Valsalvs sinus, dividing the non-coronary sinus, the right coronary sinus and the left coronary sinus, calculating the distance from the lowest point of the non-coronary sinus, the right coronary sinus and the left coronary sinus to a sinus duct junction plane, determining the height of the non-coronary sinus, the right coronary sinus and the left coronary sinus, reading the pixel sum of each sinus part, wherein the volume of each sinus part is the sum of all pixels in the area multiplied by the pixel resolution ratio and then multiplied by the sum of the pixel layer spacing.
2. The method for measuring anatomical features of an aortic complex as claimed in claim 1, wherein: step S32 includes passing the apex A of the triangle between the three leaflets of the aorta1(xA1，yA1，zA1)、A2(xA2，yA2，zA2)、A3(xA3，yA3，zA3) Creating a plane STJ, wherein the STJ plane is a sinotubular junction plane and passes through the mainLowest point B of three sinuses at the root of artery1(xB1，yB1，zB1)、B2(xB2，yB2，zB2)、B3(xB3，yB3，zB3) And (3) creating a Base plane, wherein the Base plane is the aortic annular plane, taking the middle part of the Valsalvs Sinus to create a Sinus plane, and the Sinus plane is the aortic Sinus middle plane.
3. The method for measuring anatomical features of an aortic complex as claimed in claim 2, wherein: step S32, calculating the height of coronary ostia, reading the coordinate O of left coronary sinus ostiaLCA(xL，yL，zL) And the coordinate O of the right coronary sinus ostiumRCA(xR，yR，zR) Projecting the left coronary sinus ostium and the coronary sinus ostium to the Base plane to obtain the projection image OLCA(x’L，y’L，z’L) Is OLCAProjected coordinates in the Base plane, O'RCA(x’R，y’R，z’R) Is ORCAProjection coordinates on the Base plane, height h of the left and right coronary artery openingsLAnd hRRespectively as follows:
4. the method for measuring anatomical features of an aortic complex as claimed in claim 2 or claim 3, wherein: in step S32, the specific method of calculating the perimeter, area, and maximum diameter of the STJ plane, Base plane, and Sinus plane is to cut the STJ, Base, and Sinus image plane into rectangles with a length and width of T1 according to the center position, and to represent the rectangles with the length and width of T1 as a function f (x, y), and to binarize the f (x, y) value using T2 to obtain the valueTo binary image fBW(x，y)，
Wherein T1 is a critical value of the rectangular length and width, T2 is a critical threshold value, and ROI area is fBW(x, y) covering a maximum connected area in the center of the area;
area: with fBWMultiplying the pixel resolution of the image by the sum of pixels 1 in a continuous region with the origin at the center of (x, y) to obtain the area A of the STJ, Base, Sinus plane ROISTJ，ABase，ASinus；
Perimeter Perimeter: obtaining the outermost edge pixel by calculating the farthest distance between each adjacent pixel pair around the ROI regional boundary, and obtaining the perimeter by accumulating the number of the outermost edge pixels to obtain PSTJ，PBase，PSinus；
Diameter: area A through ROISTJ，ABase，ASinusCalculating
Thereby obtaining DSTJ，DBase，DSinus。
5. The method for measuring anatomical features of an aortic complex as claimed in claim 4, wherein: in step S32, the pixel points of the STJ, Base, and Sinus images are evaluated by calculating the normal vector of the STJ plane
As is noted above, the number of the channels,
ASTJ，BSTJ，CSTJcoordinates of the normal vector in X, Y and Z axes respectively; a. the1And A2Two points on the plane, A1A2‘＝(xA1-xA2，yA1-yA2，zA1-zA2) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
the value of each pixel point on the Base plane and the Sinus plane is the same as the STJ plane calculation method.
6. The method for measuring anatomical features of the aortic complex as claimed in claim 2, 3 or 5, wherein: step S33 includes establishing three mutually orthogonal planes P1, P2 and P3 perpendicular to the STJ plane, wherein the three planes P1, P2 and P3 all pass through the midpoint O (x) of the STJ planeO，yO，zO) And the midpoint O' (x) of the Base planeO′，yO′，zO') plane P1, P2, P3 divides the Valsalvs sinus into the NCC, RCC, LCC three parts.
7. The method for measuring anatomical features of an aortic complex as claimed in claim 6, wherein: in step S33, the NCC, RCC, and LCC partial volumes are calculated by finding the pixel value in the three-dimensional pixel space where the portion between the STJ plane and the Base plane is greater than the threshold T3 to obtain the volume function V of the sinus regionROI(ii) a The P1, P2 and P3 planes are perpendicular to the VROIIs divided into three parts, each of which is VNCC、VRCCAnd VLCC，VNCC、VRCCAnd VLCCIs the sum of all pixels in the region multiplied by the pixel resolution multiplied by the sum of the pixel layer spacing.
8. The method for measuring anatomical features of an aortic complex as claimed in claim 7, wherein: in the step S33, the pixel values of the P1, P2 and P3 panels are obtained by the method that the normal vector of the P1 plane
As is noted above, the number of the channels,
are respectively normal vector
Coordinates in the X, Y, Z axes;
A1and 0 is two points on the plane, A1O‘＝(xA1-xO，yA1-yO，zA1-zO) (ii) a Obtaining the value of each pixel point Z on the plane according to a point method equation of the space plane and the following formula:
the Z value of each pixel point on the P2 plane and the P3 plane is the same as the calculation method of the P1 plane.
9. The method for measuring anatomical features of an aortic complex as claimed in claim 8, wherein: also includes step S3, automatically counting the anatomical geometric characteristic value of one cardiac cycle through MATLAB,
fphase(S)＝(ft1(S)，ft2(S)，ft3(S)，...，ftn(S))
wherein, phase is all phases of a cardiac cycle, and n is 20; s is the vector of anatomical feature statistics for each phase (a ═ a)STJ，ABase，ASinus，PBase，PSinus，PSTJ，DSTJ，DBase，DSinus，VNCC，VRCC，VLCC，hL，hR)。
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113450322A (en) * | 2021-06-22 | 2021-09-28 | 沈阳先进医疗设备技术孵化中心有限公司 | Method and device for judging origin abnormality of coronary artery |
| CN113749766A (en) * | 2021-08-31 | 2021-12-07 | 拓微摹心数据科技(南京)有限公司 | Method for calculating contrast suggested projection angle in transcatheter aortic valve replacement |
| CN113782202A (en) * | 2021-08-31 | 2021-12-10 | 拓微摹心数据科技(南京)有限公司 | Transverse heart risk assessment method based on virtual annulus plane included angle of aortic valve root |
| CN113974667A (en) * | 2021-11-02 | 2022-01-28 | 东北大学 | Automatic positioning device and method for TAVI preoperative key target |
| CN115619750A (en) * | 2022-10-27 | 2023-01-17 | 拓微摹心数据科技(北京)有限公司 | Method for calculating contrast projection angle in TAVR (percutaneous transluminal coronary angiography) operation by taking coronary sinus as reference |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070014451A1 (en) * | 2004-11-10 | 2007-01-18 | Jeff Dwyer | Anatomical visualization and measurement system |
| CN106780720A (en) * | 2016-11-30 | 2017-05-31 | 上海联影医疗科技有限公司 | Medical image display method and device |
| CN108764221A (en) * | 2018-08-09 | 2018-11-06 | 于存涛 | Aorta image analysis methods and system |
| US20190240025A1 (en) * | 2018-01-31 | 2019-08-08 | Gary Michael Silberbach | Methods for creating sinus-matched aortic valves |
| CN110570424A (en) * | 2019-10-08 | 2019-12-13 | 中国人民解放军陆军军医大学 | aortic valve semi-automatic segmentation method based on CTA dynamic image |
| US20200160527A1 (en) * | 2018-11-20 | 2020-05-21 | Siemens Healthcare Gmbh | Automatic Detection and Quantification of the Aorta from Medical Images |
| CN111465353A (en) * | 2018-11-22 | 2020-07-28 | 佳能医疗系统株式会社 | Medical image processing apparatus, medical image processing method, and storage medium |
| CN111523549A (en) * | 2020-05-06 | 2020-08-11 | 沈阳先进医疗设备技术孵化中心有限公司 | Aortic valve assessment method and device and computer equipment |
-
2020
- 2020-12-22 CN CN202011526616.4A patent/CN112674872B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070014451A1 (en) * | 2004-11-10 | 2007-01-18 | Jeff Dwyer | Anatomical visualization and measurement system |
| CN106780720A (en) * | 2016-11-30 | 2017-05-31 | 上海联影医疗科技有限公司 | Medical image display method and device |
| US20190240025A1 (en) * | 2018-01-31 | 2019-08-08 | Gary Michael Silberbach | Methods for creating sinus-matched aortic valves |
| CN108764221A (en) * | 2018-08-09 | 2018-11-06 | 于存涛 | Aorta image analysis methods and system |
| US20200160527A1 (en) * | 2018-11-20 | 2020-05-21 | Siemens Healthcare Gmbh | Automatic Detection and Quantification of the Aorta from Medical Images |
| CN111465353A (en) * | 2018-11-22 | 2020-07-28 | 佳能医疗系统株式会社 | Medical image processing apparatus, medical image processing method, and storage medium |
| CN110570424A (en) * | 2019-10-08 | 2019-12-13 | 中国人民解放军陆军军医大学 | aortic valve semi-automatic segmentation method based on CTA dynamic image |
| CN111523549A (en) * | 2020-05-06 | 2020-08-11 | 沈阳先进医疗设备技术孵化中心有限公司 | Aortic valve assessment method and device and computer equipment |
Non-Patent Citations (1)
| Title |
|---|
| 李英凯等: "主动脉根部的结构及无创测量方法的研究进展", 《心血管病学进展》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113450322A (en) * | 2021-06-22 | 2021-09-28 | 沈阳先进医疗设备技术孵化中心有限公司 | Method and device for judging origin abnormality of coronary artery |
| CN113450322B (en) * | 2021-06-22 | 2024-05-24 | 东软医疗系统股份有限公司 | Method and device for judging provenance abnormality of coronary artery |
| CN113749766A (en) * | 2021-08-31 | 2021-12-07 | 拓微摹心数据科技(南京)有限公司 | Method for calculating contrast suggested projection angle in transcatheter aortic valve replacement |
| CN113782202A (en) * | 2021-08-31 | 2021-12-10 | 拓微摹心数据科技(南京)有限公司 | Transverse heart risk assessment method based on virtual annulus plane included angle of aortic valve root |
| CN113749766B (en) * | 2021-08-31 | 2023-02-03 | 拓微摹心数据科技(南京)有限公司 | Method for calculating contrast suggested projection angle in transcatheter aortic valve replacement |
| CN113782202B (en) * | 2021-08-31 | 2023-08-01 | 拓微摹心数据科技(南京)有限公司 | Transverse heart risk assessment method for virtual annulus plane included angle based on aortic valve root |
| CN113974667A (en) * | 2021-11-02 | 2022-01-28 | 东北大学 | Automatic positioning device and method for TAVI preoperative key target |
| CN115619750A (en) * | 2022-10-27 | 2023-01-17 | 拓微摹心数据科技(北京)有限公司 | Method for calculating contrast projection angle in TAVR (percutaneous transluminal coronary angiography) operation by taking coronary sinus as reference |
| CN115619750B (en) * | 2022-10-27 | 2023-09-22 | 拓微摹心数据科技(南京)有限公司 | Calculation method of contrast projection angle in TAVR (total automated video computing) operation based on coronary sinus |
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