A cardiac three-dimensional mapping data acquisition system and method
By combining MR and CT scans with sparsity partitioning and electrode mapping catheter technology, the problem of relying on experience for the selection of mapping sample points in existing technologies has been solved, achieving accurate and rapid data acquisition for cardiac three-dimensional mapping and constructing representative mapping maps.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN YINGTAI LIANKANG MEDICAL SCI & TECH CO LTD
- Filing Date
- 2023-07-12
- Publication Date
- 2026-06-26
AI Technical Summary
Existing three-dimensional cardiac mapping methods rely heavily on the experience of medical personnel in determining the location and number of mapping sample points, which is challenging and increases the difficulty and time required for surgery.
Anatomical data of multiple continuous parts of the heart were obtained through MR and CT scans, and three-dimensional reconstruction was performed. The model was divided into multiple sub-regions using sparsity to determine target mapping points. Three-dimensional mapping data were collected using electrode mapping catheters and combined with ECG and respiratory gating data to create a three-dimensional mapping map.
It enabled more accurate and faster acquisition of three-dimensional mapping data, constructed a representative three-dimensional mapping map of the heart, and reduced the difficulty and time of surgery.
Smart Images
Figure CN116869482B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of electrocardiogram monitoring technology, and in particular relates to a cardiac three-dimensional mapping data acquisition system and method. Background Technology
[0002] Due to the complexity of the heart's three-dimensional structure, especially the deformation it undergoes during respiration, two-dimensional tomographic images can only represent local information about the organ. Furthermore, with a large number of two-dimensional images, comparing differences between these images to diagnose conditions is time-consuming, cumbersome, and inaccurate. Therefore, three-dimensional mapping-assisted diagnostic systems have emerged to assist cardiologists in diagnosis and clinical treatment. Cardiac three-dimensional reconstruction technology can create three-dimensional models of human organs or tissues based on two-dimensional image information. Based on these models, the internal structure of organs can be observed intuitively; adding coordinate information to the three-dimensional model allows for the calculation of the location, size, and shape of lesions; and transformations of the three-dimensional model enable multi-directional observation, helping doctors accurately locate cardiac lesions. Therefore, three-dimensional mapping-assisted diagnostic systems are of great significance in clinical applications.
[0003] For example, Chinese invention patent application CN202210722516.1 proposes a non-contact cardiac electrophysiological three-dimensional mapping method, which uses intracardiac ultrasound to establish a three-dimensional model of the endocardium; uses electrode catheters to obtain continuous potential signals of intracardiac electrodes within one heartbeat cycle; uses triangular meshes to approximate the three-dimensional model of the endocardium, and obtains the centroid, normal vector, and area of each triangular mesh; and calculates the three-dimensional distribution information of charge density of the endocardium within one heartbeat cycle based on the potential signals, centroid, normal vector, and area.
[0004] However, current methods for three-dimensional cardiac mapping still need improvement in areas such as the selection of mapping sample point locations and the determination of the number of mapping sample points. The mapping process relies heavily on the experience of medical personnel, making mapping difficult and increasing the difficulty and time required for subsequent surgeries. Summary of the Invention
[0005] To address the aforementioned technical problems, this invention proposes a cardiac three-dimensional mapping data acquisition system and method.
[0006] Specifically, in the first aspect of the present invention, a method for acquiring three-dimensional cardiac mapping data is proposed, the method comprising steps S1-S5, the specific implementation of each step being as follows:
[0007] S1: Obtain the set of 3D reconstruction coordinates corresponding to the 3D reconstruction model of the target heart;
[0008] The three-dimensional reconstruction coordinate set is represented as V3Set{Xi, Yj, Zk}, i = 1, 2, ..., I; j = 1, 2, ..., J; k = 1, 2, ..., K, where I, J, and K are all greater than 2;
[0009] S2: Based on the sparsity of the three-dimensional reconstruction coordinate set, the three-dimensional reconstruction model is divided into multiple sub-regions;
[0010] S3: For each sub-region, determine at least one target measurement point;
[0011] S4: Collect cardiac 3D mapping data for each target point;
[0012] S5: Establish a three-dimensional cardiac mapping map based on the acquired three-dimensional cardiac mapping data.
[0013] Furthermore, step S1 specifically includes:
[0014] S11: Obtain the cardiac anatomical structure of multiple consecutive sites in the subject through MR enhanced scanning;
[0015] S12: Obtain multiple tomographic data corresponding to the cardiac cavity anatomy of the multiple consecutive locations through CT scanning;
[0016] S13: Based on the multiple tomographic data corresponding to the cardiac cavity anatomy of the multiple continuous sites, a three-dimensional reconstruction model of the target heart is obtained by three-dimensional reconstruction of the target heart. The three-dimensional reconstruction model includes a set of three-dimensional reconstruction coordinates of the first order of magnitude.
[0017] Based on this, step S2 specifically includes:
[0018] S21: Determine the target plane for three-dimensional cardiac mapping; the target plane includes a first dimension A and a second dimension B;
[0019] S22: Obtain the planar coordinate set V2Set{Am, Bn} of the three-dimensional reconstructed coordinate set on the target plane; m = 1, 2, ..., M; n = 1, 2, ..., N; M and N are both greater than 2;
[0020] S23: Obtain the sparsity distribution value SparsityA in the first dimension and the sparsity distribution value SparsityB in the second dimension;
[0021] S24: Based on the first dimension sparsity distribution value SparsityA and the second dimension sparsity distribution value SparsityB, the three-dimensional reconstructed coordinate set is divided into multiple subsets, each subset corresponding to a sub-region.
[0022] Furthermore, step S3 specifically includes:
[0023] S31: For the first sub-region, obtain the first number of 3D reconstructed coordinates contained in the first sub-region;
[0024] S32: Determine at least one adjacent sub-region of the first sub-region, and obtain a second number of three-dimensional reconstructed coordinates contained in the at least one adjacent sub-region;
[0025] S32: If there is at least one second quantity whose difference from the first quantity is less than a preset value, then the first target measurement point of the first sub-region is determined based on the three-dimensional reconstructed coordinates of the first quantity contained in the first sub-region.
[0026] Otherwise, based on the combination of a first number of 3D reconstructed coordinates contained in the first sub-region and a second number of 3D reconstructed coordinates contained in all adjacent sub-regions of the first sub-region, the second target mapping point of the first sub-region is determined.
[0027] In practical applications, step S4 specifically includes:
[0028] The endocardium at the target point of the electrode mapping catheter is contacted to obtain a three-dimensional cardiac mapping data, which includes an electrical potential signal map.
[0029] Step S5 specifically includes:
[0030] Summarize the three-dimensional mapping data of the heart obtained from multiple target point locations;
[0031] By combining the three-dimensional coordinates of multiple target points, the mapping sequence, and synchronized ECG and respiratory gating data, a three-dimensional cardiac mapping map is established.
[0032] In a second aspect of the invention, a cardiac three-dimensional mapping data acquisition system is provided, the system comprising an electrode mapping catheter.
[0033] In terms of functional unit structure, the system also includes:
[0034] A cardiac 3D reconstruction unit, which performs 3D reconstruction of the target heart based on multiple tomographic data corresponding to the cardiac cavity anatomy of multiple consecutive sites to obtain a 3D reconstruction model of the target heart, wherein the 3D reconstruction model includes a set of 3D reconstruction coordinates of the first order of magnitude.
[0035] A three-dimensional reconstruction coordinate extraction unit is used to extract the set of three-dimensional reconstruction coordinates corresponding to the three-dimensional reconstruction model of the target heart.
[0036] A 3D reconstruction model partitioning unit, which divides the 3D reconstruction model into multiple sub-regions based on the sparsity of the 3D reconstruction coordinate set;
[0037] The target measurement point determination unit determines at least one target measurement point for each sub-region.
[0038] The mapping data acquisition unit controls the electrode mapping catheter to acquire cardiac three-dimensional mapping data for each target point to obtain cardiac three-dimensional mapping data.
[0039] The mapping establishment unit establishes a three-dimensional mapping of the heart based on the acquired three-dimensional mapping data of the heart.
[0040] The target measurement point determination unit determines target measurement points of a second order of magnitude; the second order of magnitude is different from the first order of magnitude, and the first order of magnitude is at least two orders of magnitude higher than the second order of magnitude.
[0041] Preferably, the system further includes:
[0042] A cardiac mapping target plane determination unit determines the target plane for three-dimensional cardiac mapping; the target plane includes a first dimension A and a second dimension B.
[0043] The first dimension A and the second dimension B are selected from any two dimensions of the three-dimensional reconstruction model of the target heart.
[0044] In practical applications, the system also includes an electrocardiogram (ECG) monitor.
[0045] The electrocardiogram monitor simultaneously acquires electrocardiogram and respiratory gating data when the mapping data acquisition unit is working;
[0046] The mapping unit summarizes the cardiac three-dimensional mapping data measured at multiple target points, and combines the three-dimensional coordinates of multiple target points, the mapping sequence, and the synchronized electrocardiogram and respiratory gating data to establish a cardiac three-dimensional mapping.
[0047] The cardiac three-dimensional mapping data acquisition system and method proposed in this invention can more accurately and quickly acquire three-dimensional mapping data to construct a representative cardiac three-dimensional mapping map.
[0048] Further advantages of the present invention will be further detailed in the Specific Embodiments section in conjunction with the accompanying drawings. Attached Figure Description
[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0050] Figure 1 This is a flowchart illustrating the main process of a cardiac three-dimensional mapping data acquisition method according to an embodiment of the present invention.
[0051] Figure 2 This is a schematic diagram illustrating the process of obtaining a three-dimensional reconstruction model of the target heart.
[0052] Figure 3 This is a schematic diagram illustrating the steps involved in dividing a 3D reconstructed model into multiple sub-regions.
[0053] Figure 4 This is a three-dimensional schematic diagram of the target heart reconstructed according to an embodiment of the present invention.
[0054] Figure 5 This is a schematic diagram of a process for determining a target plane according to an embodiment of the present invention.
[0055] Figure 6 This is a schematic diagram illustrating how the target plane for three-dimensional cardiac mapping is divided into multiple sub-regions according to an embodiment of the present invention.
[0056] Figure 7 This is a schematic diagram of the functional unit composition of a cardiac three-dimensional mapping data acquisition system according to an embodiment of the present invention.
[0057] Figure 8 This is a schematic diagram of the functional units of a cardiac three-dimensional mapping data acquisition system according to a preferred embodiment of the present invention. Detailed Implementation
[0058] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application.
[0059] Furthermore, it should be understood that the illustrative drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed in order or performed simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.
[0060] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0061] Figure 1 This is a flowchart of the main process of a cardiac three-dimensional mapping data acquisition method according to an embodiment of the present invention.
[0062] Figure 1 The main process of the method includes steps S1-S5, and the specific implementation of each step is as follows:
[0063] S1: Obtain the set of 3D reconstruction coordinates corresponding to the 3D reconstruction model of the target heart;
[0064] The three-dimensional reconstruction coordinate set is represented as V3Set{Xi, Yj, Zk}, i = 1, 2, ..., I; j = 1, 2, ..., J; k = 1, 2, ..., K, where I, J, and K are all greater than 2;
[0065] S2: Based on the sparsity of the three-dimensional reconstruction coordinate set, the three-dimensional reconstruction model is divided into multiple sub-regions;
[0066] S3: For each sub-region, determine at least one target measurement point;
[0067] S4: Collect cardiac 3D mapping data for each target point;
[0068] S5: Establish a three-dimensional cardiac mapping map based on the acquired three-dimensional cardiac mapping data.
[0069] Next, combined Figures 2-6 The specific implementation of each of the above steps will be explained in detail.
[0070] In step S1, it is first necessary to obtain the set of three-dimensional reconstruction coordinates corresponding to the three-dimensional reconstruction model of the target heart;
[0071] Specifically, step S1 includes the following sub-steps:
[0072] S11: Obtain the cardiac anatomical structure of multiple consecutive sites in the subject through MR enhanced scanning;
[0073] S12: Obtain multiple tomographic data corresponding to the cardiac cavity anatomy of the multiple consecutive locations through CT scanning;
[0074] As is known to those skilled in the art, since the 1970s and 1980s, advanced imaging equipment such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (UCG), positron emission tomography (PET), and photoelectron emission tomography (SPECT) have emerged. Medical professionals can use these devices to periodically acquire two-dimensional tomographic images of a patient's organ or tissue to track changes in lesions and diagnose the patient's condition by comparing the information from these scan images.
[0075] However, two-dimensional tomographic images can only represent local information of organs. Furthermore, when there are a large number of two-dimensional images, it is not only time-consuming and troublesome for medical professionals to diagnose diseases by comparing the differences between planar image information, but also not accurate enough.
[0076] Therefore, based on steps S11 and S12, step S13 is performed: based on multiple tomographic data corresponding to the cardiac anatomical structures of the multiple consecutive locations, the target heart is reconstructed in three dimensions to obtain a three-dimensional reconstruction model of the target heart, wherein the three-dimensional reconstruction model includes a set of three-dimensional reconstruction coordinates of the first order of magnitude.
[0077] Specifically, one implementation of step S13 is as follows: Preliminary 3D reconstruction is performed on the acquired 2D heart image to obtain the heart's 3D coordinates. Here, the preliminary 3D reconstruction can be based on various algorithms for constructing a 3D model from a 2D image, such as the Marching Cubes (MC) algorithm. Of course, there are other methods for preliminary 3D reconstruction based on the acquired 2D heart image; please refer to relevant existing technologies. This embodiment uses the Marching Cubes algorithm as an example to briefly introduce its principle.
[0078] The specific operation of the moving cube algorithm is as follows:
[0079] Read the four slices of the image into memory;
[0080] Two slices were scanned using voxel scanning;
[0081] The cube's index is calculated by comparing the values of its eight vertices with the obtained isosurface values; the edge list is then retrieved from the lookup table using the index.
[0082] Using the grayscale value of each edge vertex, the exact position of the triangle facet vertex is calculated through linear interpolation; the unit normal of each voxel vertex is calculated and interpolated to each vertex of the triangle facet; the vertices and normals of the triangle facet are output.
[0083] Figure 4 This is a three-dimensional schematic diagram illustrating a three-dimensional reconstruction model of the target heart established according to an embodiment of the present invention.
[0084] In this way, after initially constructing a three-dimensional model of the heart, the three-dimensional reconstructed coordinates of the heart can be obtained, i.e. Figure 4 The vertex coordinates of each triangular facet.
[0085] Therefore, the three-dimensional reconstructed coordinate set is represented as V3Set{Xi, Yj, Zk}, i = 1, 2, ..., I; j = 1, 2, ..., J; k = 1, 2, ..., K, where I, J, and K are all greater than 2;
[0086] Next, see Figure 3 . Figure 3 This is a schematic diagram of the method steps in step S2, which divides the 3D reconstruction model into multiple sub-regions.
[0087] Specifically, step S2 includes:
[0088] S21: Determine the target plane for three-dimensional cardiac mapping; the target plane includes a first dimension A and a second dimension B;
[0089] S22: Obtain the planar coordinate set V2Set{Am, Bn} of the three-dimensional reconstructed coordinate set on the target plane; m = 1, 2, ..., M; n = 1, 2, ..., N; M and N are both greater than 2;
[0090] S23: Obtain the sparsity distribution value SparsityA in the first dimension and the sparsity distribution value SparsityB in the second dimension;
[0091] S24: Based on the first dimension sparsity distribution value SparsityA and the second dimension sparsity distribution value SparsityB, the three-dimensional reconstructed coordinate set is divided into multiple subsets, each subset corresponding to a sub-region.
[0092] Back Figure 4 As can be seen, the three-dimensional reconstruction model of the target heart includes three dimensions XYZ; step S21 determines that the target plane for the three-dimensional mapping of the heart includes two of the plane dimensions.
[0093] Figure 5 An example of a target plane for calibration is shown, in which the XY plane is selected as the target plane for calibration, with the first dimension A being the X dimension and the second dimension B being the Y dimension;
[0094] Then, obtain the planar coordinate set V2Set{Am,Bn} of the three-dimensional reconstructed coordinate set on the target plane (XY); m=1,2,…,M;n=1,2,…,N;M,N are both greater than 2;
[0095] It is understandable that at this point, only the coordinate values in the X and Y dimensions are considered, while the Z dimension is not considered.
[0096] Next, obtain the sparsity distribution values of the first dimension SparsityA and the second dimension SparsityB;
[0097] Specifically, the first dimension sparsity distribution value SparsityA is the sparsity distribution value in the X dimension, which is used to characterize the farthest aggregation distance of the planar coordinate set V2Set{Am, Bn} in the X dimension; the second dimension sparsity distribution value SparsityB is the sparsity distribution value in the Y dimension, which is used to characterize the farthest aggregation distance of the planar coordinate set V2Set{Am, Bn} in the Y dimension.
[0098] For more details, see Figure 6 The sparsity distribution values SparsityA in the first dimension and SparsityB in the second dimension can form a rectangular scanning box. SparsityA in the first dimension is the length of the rectangular scanning box, and SparsityB in the second dimension is the width of the rectangular scanning box.
[0099] By moving the rectangular scanning frame on the target mapping plane, a subset of plane coordinate points with the maximum number of plane coordinate points can fall into the rectangular scanning frame, thereby making each rectangular scanning frame constitute a sub-region.
[0100] Therefore, based on the first dimension sparsity distribution value SparsityA and the second dimension sparsity distribution value SparsityB, the three-dimensional reconstructed coordinate set can be divided into multiple subsets, each subset corresponding to a sub-region.
[0101] Based on this, step S3 is performed as follows:
[0102] S31: For the first sub-region, obtain the first number of 3D reconstructed coordinates contained in the first sub-region;
[0103] S32: Determine at least one adjacent sub-region of the first sub-region, and obtain a second number of three-dimensional reconstructed coordinates contained in the at least one adjacent sub-region;
[0104] S32: If there is at least one second quantity whose difference from the first quantity is less than a preset value, then the first target measurement point of the first sub-region is determined based on the three-dimensional reconstructed coordinates of the first quantity contained in the first sub-region.
[0105] Otherwise, based on the combination of a first number of 3D reconstructed coordinates contained in the first sub-region and a second number of 3D reconstructed coordinates contained in all adjacent sub-regions of the first sub-region, the second target mapping point of the first sub-region is determined.
[0106] It can be understood that the aforementioned "first sub-region" refers to any one of the "multiple sub-regions" corresponding to the "multiple subsets";
[0107] If the first number of 3D reconstructed coordinates contained in the first sub-region is the same as or not significantly different from the second number of 3D reconstructed coordinates contained in the adjacent sub-region, it means that the 3D structure density of the two regions is similar and related. In this case, to ensure the representativeness of different regions, the first target marker of the first sub-region is determined based only on the first number of 3D reconstructed coordinates contained in the first sub-region.
[0108] Specifically, a weighted average of all the first number of 3D reconstructed coordinates contained in the first sub-region can be calculated to obtain at least one weighted average coordinate value.
[0109] If the weighted average coordinate value belongs to the three-dimensional reconstruction coordinate set, then the weighted average coordinate value is used as the first target measurement point of the first sub-region;
[0110] If the weighted average coordinate value does not belong to the three-dimensional reconstruction coordinate set, then the coordinate point in the three-dimensional reconstruction coordinate set that is closest to the weighted average coordinate value is taken as the first target measurement point of the first sub-region.
[0111] If the first number of 3D reconstructed coordinates contained in the first sub-region is different from the second number of 3D reconstructed coordinates contained in the adjacent sub-regions, and is significantly different, then the independent representativeness of the two regions is weak. In this case, to ensure the representativeness of the corresponding region, for the "first sub-region", it is necessary to determine the second target marker point of the first sub-region based on the combination of the first number of 3D reconstructed coordinates contained in the first sub-region and the second number of 3D reconstructed coordinates contained in all the adjacent sub-regions of the first sub-region.
[0112] Specifically, a weighted average can be calculated by taking the first number of 3D reconstructed coordinates contained in the first sub-region and the second number of 3D reconstructed coordinates contained in all adjacent sub-regions of the first sub-region, and obtaining at least one weighted average coordinate value.
[0113] If the weighted average coordinate value belongs to the three-dimensional reconstruction coordinate set, then the weighted average coordinate value is used as the second target measurement point of the first sub-region;
[0114] If the weighted average coordinate value does not belong to the three-dimensional reconstruction coordinate set, then the coordinate point in the three-dimensional reconstruction coordinate set that is closest to the weighted average coordinate value is taken as the second target measurement point of the first sub-region.
[0115] Specifically, assume that the first sub-region contains M 3D reconstructed coordinates V3i (i = 1, 2, ..., M), and all adjacent sub-regions of the first sub-region contain N reconstructed coordinates U3j (j = 1, 2, ..., N);
[0116] Then the weighted average coordinate value
[0117] Through the above steps, the technical solution of the present invention can quickly locate representative sample mapping points for cardiac three-dimensional mapping.
[0118] After determining the sample mapping points, continue with steps S4 and S5, namely:
[0119] The endocardium at the target point of the electrode mapping catheter is contacted to obtain a three-dimensional cardiac mapping data, which includes an electrical potential signal map.
[0120] Summarize the three-dimensional mapping data of the heart obtained from multiple target point locations;
[0121] By combining the three-dimensional coordinates of multiple target points, the mapping sequence, and synchronized ECG and respiratory gating data, a three-dimensional cardiac mapping map is established.
[0122] Specifically, three-dimensional electrophysiological mapping of the heart often requires the use of multiple multi-electrode mapping catheters, which are inserted into the heart chambers via the femoral vein in a minimally invasive manner. The electrodes directly contact the endocardium, thereby measuring the electrical potential signal at the contact point within one cardiac cycle (the electrical potential signal is conducted from the endocardium to the blood flow within the heart chambers). After measuring one cardiac cycle, the catheter is moved to another endocardial location for contact measurement, and the three-dimensional spatial coordinates of the contact point are recorded until the clinically relevant region is measured. By combining the measured electrical potential signals and activation sequence at different locations with ECG and respiratory gating data obtained from the monitor for time synchronization, a three-dimensional mapping of the cardiac activation process, including the electrical potential signal amplitude and activation sequence, can be established.
[0123] To achieve Figures 1-6 For the steps of the embodiment, see Figures 7-8 This invention proposes a cardiac three-dimensional mapping data acquisition system with different embodiments.
[0124] See Figure 7The system includes an electrode mapping catheter; specifically, the system further includes:
[0125] A cardiac 3D reconstruction unit, which performs 3D reconstruction of the target heart based on multiple tomographic data corresponding to the cardiac cavity anatomy of multiple consecutive sites to obtain a 3D reconstruction model of the target heart, wherein the 3D reconstruction model includes a set of 3D reconstruction coordinates of the first order of magnitude.
[0126] A three-dimensional reconstruction coordinate extraction unit is used to extract the set of three-dimensional reconstruction coordinates corresponding to the three-dimensional reconstruction model of the target heart.
[0127] A 3D reconstruction model partitioning unit, which divides the 3D reconstruction model into multiple sub-regions based on the sparsity of the 3D reconstruction coordinate set;
[0128] The target measurement point determination unit determines at least one target measurement point for each sub-region.
[0129] The mapping data acquisition unit controls the electrode mapping catheter to acquire cardiac three-dimensional mapping data for each target point to obtain cardiac three-dimensional mapping data.
[0130] The mapping establishment unit establishes a three-dimensional mapping of the heart based on the acquired three-dimensional mapping data of the heart.
[0131] In the specific execution process, the target measurement point determination unit determines the target measurement points of the second order of magnitude; the second order of magnitude is different from the first order of magnitude, and the first order of magnitude is at least two orders of magnitude higher than the second order of magnitude.
[0132] Preferably, the numerical range represented by the first order of magnitude is at least 10 times the numerical range represented by the second order of magnitude.
[0133] For example, if the first order of magnitude is [100, 1000], then the second order of magnitude is [10, 100].
[0134] exist Figure 7 Based on this, see further Figure 8 .
[0135] Figure 8 The system further includes: a cardiac mapping target plane determination unit, which determines the target plane for three-dimensional cardiac mapping; the target plane includes a first dimension A and a second dimension B;
[0136] The first dimension A and the second dimension B are selected from any two dimensions of the three-dimensional reconstruction model of the target heart.
[0137] It is understandable that at least three target planes can be identified, such as the XY, YZ, and ZX planes. For each target plane, the corresponding steps of the above-mentioned cardiac three-dimensional mapping data acquisition method can be performed.
[0138] exist Figure 8 The system also includes an electrocardiogram (ECG) monitor.
[0139] The electrocardiogram monitor simultaneously acquires electrocardiogram and respiratory gating data when the mapping data acquisition unit is working;
[0140] The mapping unit summarizes the cardiac three-dimensional mapping data measured at multiple target points, and combines the three-dimensional coordinates of multiple target points, the mapping sequence, and the synchronized electrocardiogram and respiratory gating data to establish a cardiac three-dimensional mapping.
[0141] As can be seen, this invention first obtains the set of three-dimensional reconstruction coordinates corresponding to the three-dimensional reconstruction model of the target heart; then, based on the sparsity of the three-dimensional reconstruction coordinate set, the three-dimensional reconstruction model is divided into multiple sub-regions; thereby, for each sub-region, at least one target mapping point is determined; then, three-dimensional mapping data of the heart is collected for each target point; and a three-dimensional mapping map of the heart is established based on the collected three-dimensional mapping data of the heart, which can more accurately and quickly realize the collection of three-dimensional mapping data and thus construct a representative three-dimensional mapping map of the heart.
[0142] Although the accompanying drawings are not shown, those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above.
[0143] A computer can read storage media using any combination of one or more readable media. A readable medium can be a readable signal medium or a readable storage medium. A readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. In the systems and methods of this application, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions to this application.
Claims
1. A cardiac three-dimensional mapping data acquisition system, the system comprising an electrode mapping catheter, characterized in that, The system also includes: A cardiac 3D reconstruction unit, which performs 3D reconstruction of the target heart based on multiple tomographic data corresponding to the cardiac chamber anatomy of multiple consecutive locations to obtain a 3D reconstruction model of the target heart, wherein the 3D reconstruction model includes a set of 3D reconstruction coordinates of the first order of magnitude. A three-dimensional reconstruction coordinate extraction unit is used to extract the set of three-dimensional reconstruction coordinates corresponding to the three-dimensional reconstruction model of the target heart. A 3D reconstruction model partitioning unit, which divides the 3D reconstruction model into multiple sub-regions based on the sparsity of the 3D reconstruction coordinate set; The target measurement point determination unit determines at least one target measurement point for each sub-region. The mapping data acquisition unit controls the electrode mapping catheter to acquire cardiac three-dimensional mapping data for each target point to obtain cardiac three-dimensional mapping data. A mapping establishment unit, which establishes a three-dimensional cardiac mapping based on the acquired three-dimensional cardiac mapping data; Specifically, the target mapping point determination unit determines at least one target mapping point for each sub-region, including: for a first sub-region, obtaining a first number of 3D reconstructed coordinates contained in the first sub-region; determining at least one adjacent sub-region of the first sub-region and obtaining a second number of 3D reconstructed coordinates contained in the at least one adjacent sub-region; if there is at least one second number whose difference from the first number is less than a preset value, then determining a first target mapping point of the first sub-region based on the first number of 3D reconstructed coordinates contained in the first sub-region; otherwise, determining a second target mapping point of the first sub-region based on a combination of the first number of 3D reconstructed coordinates contained in the first sub-region and the second number of 3D reconstructed coordinates contained in all adjacent sub-regions of the first sub-region.
2. The cardiac three-dimensional mapping data acquisition system as described in claim 1, characterized in that: The target measurement point determination unit determines target measurement points of a second order of magnitude; the second order of magnitude is different from the first order of magnitude, and the first order of magnitude is at least two orders of magnitude higher than the second order of magnitude.
3. The cardiac three-dimensional mapping data acquisition system as described in claim 1, characterized in that, The system also includes: A cardiac mapping target plane determination unit determines the target plane for three-dimensional cardiac mapping; the target plane includes a first dimension A and a second dimension B. The first dimension A and the second dimension B are selected from any two dimensions of the three-dimensional reconstruction model of the target heart.
4. The cardiac three-dimensional mapping data acquisition system as described in claim 1, characterized in that, The system also includes an electrocardiogram (ECG) monitor. The electrocardiogram monitor simultaneously acquires electrocardiogram and respiratory gating data when the mapping data acquisition unit is working; The mapping unit summarizes the cardiac three-dimensional mapping data measured at multiple target points, and combines the three-dimensional coordinates of multiple target points, the mapping sequence, and the synchronized electrocardiogram and respiratory gating data to establish a cardiac three-dimensional mapping.