A method for determining myocardial activity concentration and related apparatus

Abstract

The application discloses a method for determining myocardial activity concentration and a related device, and relates to the technical field of nuclear medical heart imaging. The method converts myocardial body data in a human body coordinate system into myocardial body data in a cardiac axis coordinate system. The myocardial body data in the cardiac axis coordinate system is divided into ellipsoidal myocardial body data and cylindrical myocardial body data along the myocardial short axis direction of the cardiac axis coordinate system. The ellipsoidal myocardial body data and the cylindrical myocardial body data are respectively subjected to fan sampling and parallel sampling to obtain multi-layer ellipsoidal myocardial short axis data and multi-layer cylindrical myocardial short axis data. The ellipsoidal myocardial short axis data and the cylindrical myocardial short axis data are respectively subjected to data sampling to obtain myocardial activity concentration of a left ventricle, myocardial activity concentration of a left atrium and myocardial activity concentration of a basal part. Based on comprehensive calculation of the myocardial activity concentration of the three regions obtained by data sampling, more accurate myocardial activity concentration is determined.

Description

Technical Field

[0001] This application relates to the field of nuclear medicine cardiac imaging technology, and in particular to a method and related apparatus for determining myocardial activity concentration. Background Technology

[0002] Quantitative analysis of myocardial viability concentration is central to nuclear medicine cardiac imaging, as this parameter directly relates to the scientific assessment of myocardial blood flow supply. While myocardial viability concentration cannot determine a person's health status, such as whether they have a certain disease, it can serve as an intermediate result.

[0003] Currently, existing automated analysis technologies generally simplify the three-dimensional myocardial body data geometrically, that is, approximate the irregularly shaped real myocardium as a regular geometric body, and based on this simplified geometric model, perform uniform data sampling on the myocardial body data to obtain myocardial activity concentration.

[0004] However, this simplified geometric model differs significantly from the actual anatomical morphology of the heart from the apex to the base. Unifying the data sampling of the myocardial body data corresponding to the simplified geometric model may further amplify the data sampling error, thus leading to a lower accuracy in the final determined myocardial activity concentration. Summary of the Invention

[0005] In view of the above problems, this application provides a method and related apparatus for determining myocardial activity concentration. To improve the accuracy of the determined myocardial activity concentration, the specific solution is as follows:

[0006] The first aspect of this application provides a method for determining myocardial activity concentration, comprising:

[0007] Acquire myocardial body data in the human body coordinate system and convert the myocardial body data in the human body coordinate system into myocardial body data in the heart axis coordinate system;

[0008] For the myocardial body data in the said cardiac axis coordinate system, the myocardial body data in the said cardiac axis coordinate system is divided into ellipsoidal myocardial body data and cylindrical myocardial body data along the direction of the minor axis of the myocardium in the said cardiac axis coordinate system.

[0009] Using the ellipsoidal center of the ellipsoidal myocardial body data as the sampling vertex, fan-shaped sampling is performed on the ellipsoidal myocardial body data along the direction of the myocardial short axis to obtain multi-layer ellipsoidal myocardial short axis data. Using the vertical section of the cylindrical myocardial body data as the sampling plane, parallel sampling is performed on the cylindrical myocardial body data along the direction of the myocardial short axis to obtain multi-layer cylindrical myocardial short axis data.

[0010] Data samples were collected from the ellipsoidal myocardial short-axis data and the cylindrical myocardial short-axis data of each layer to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0011] The myocardial activity concentration is calculated based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0012] In one possible implementation, dividing the myocardial body data in the cardiac axis coordinate system into ellipsoidal myocardial body data and cylindrical myocardial body data along the minor axis direction of the myocardium in the cardiac axis coordinate system includes:

[0013] The myocardial body data in the aforementioned axial coordinate system is subjected to contour smoothing to obtain contour-smoothed myocardial body data.

[0014] The smoothed myocardial body data is converted into a binary myocardial image, and the myocardial coordinates in the binary myocardial image are obtained along the short axis of the myocardium in the myocardial coordinate system. The myocardial coordinates in the binary myocardial image include myocardial contour coordinates.

[0015] The myocardial contour coordinates are fitted using the ellipsoid equation to obtain ellipsoidal myocardial contour coordinates. The data corresponding to the myocardial coordinates that coincide with the myocardial coordinates inside the myocardial contour coordinates are determined as the ellipsoidal myocardial body data.

[0016] The cylindrical myocardial contour coordinates are obtained by fitting other myocardial contour coordinates using the cylindrical equation. The data corresponding to the myocardial coordinates that coincide with the myocardial coordinates inside the cylindrical myocardial contour coordinates are determined as the cylindrical myocardial body data. The other myocardial contour coordinates are the myocardial coordinates in the binary myocardial image other than the myocardial coordinates that coincide with the myocardial coordinates inside the ellipsoidal myocardial contour coordinates.

[0017] In one possible implementation, the step of sampling the short-axis data of the ellipsoidal myocardium of each layer and the short-axis data of the cylindrical myocardium of each layer to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region includes:

[0018] Data sampling was performed on the short axis data of the myocardium in each layer to obtain the myocardial activity concentration of the multilayer ellipsoid, and the average value of the myocardial activity concentration of the multilayer ellipsoid was taken as the myocardial activity concentration of the left ventricle.

[0019] Based on the vertical cross-section of the cylindrical myocardial body data, the short axis data of each layer of cylindrical myocardium are divided into multiple layers of first cylindrical myocardial body short axis data and multiple layers of second cylindrical myocardial body short axis data. The distance between the first cylindrical myocardial body short axis data and the ellipsoidal myocardial body short axis data of each layer is less than the distance between the second cylindrical myocardial body short axis data and the ellipsoidal myocardial body short axis data of each layer.

[0020] Data sampling was performed on the short-axis data of the first cylindrical myocardium in each layer to obtain the activity concentration of the first cylindrical myocardium in multiple layers, and the average value of the activity concentration of the first cylindrical myocardium in multiple layers was taken as the myocardial activity concentration of the basal part.

[0021] Data sampling was performed on the short-axis data of the second cylindrical myocardium in each layer to obtain the multi-layer second cylindrical myocardial activity concentration, and the average value of the multi-layer second cylindrical myocardial activity concentration was taken as the myocardial activity concentration of the left atrium.

[0022] In one possible implementation, after calculating the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, the method further includes:

[0023] Calculate the median of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, and determine the median as the arterial blood concentration;

[0024] Based on the myocardial activity concentration and arterial blood concentration obtained at multiple time points, the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase are calculated.

[0025] Myocardial blood flow reserve is calculated based on the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase.

[0026] In one possible implementation, converting the myocardial body data in the human body coordinate system to myocardial body data in the cardiac axis coordinate system includes:

[0027] Obtain the X-axis rotation angle, Y-axis rotation angle, and Z-axis rotation angle of the human body coordinate system;

[0028] The myocardial body data under the X-axis of the human body coordinate system is rotated based on the rotation angle of the X-axis of the human body coordinate system, the myocardial body data under the Y-axis of the human body coordinate system is rotated based on the rotation angle of the Y-axis of the human body coordinate system, and the myocardial body data under the Z-axis of the human body coordinate system is rotated based on the rotation angle of the Z-axis of the human body coordinate system to obtain the myocardial body data under the cardiac axis coordinate system.

[0029] In one possible implementation, calculating the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region includes:

[0030] The average value of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region is calculated, and the average value is determined as the myocardial activity concentration.

[0031] A second aspect of this application provides an apparatus for determining myocardial activity concentration, comprising:

[0032] A conversion unit is used to acquire myocardial body data in the human body coordinate system and convert the myocardial body data in the human body coordinate system into myocardial body data in the heart axis coordinate system.

[0033] A partitioning unit is used to divide the myocardial body data in the cardiac axis coordinate system into ellipsoidal myocardial body data and cylindrical myocardial body data along the minor axis direction of the cardiac axis coordinate system.

[0034] The first sampling unit is used to perform fan-shaped sampling of the ellipsoidal myocardial body data along the direction of the myocardial short axis, with the ellipsoidal center of the ellipsoidal myocardial body data as the sampling vertex, to obtain multi-layer ellipsoidal myocardial short axis data, and to perform parallel sampling of the cylindrical myocardial body data along the direction of the myocardial short axis, with the vertical cross-section of the cylindrical myocardial body data as the sampling plane, to obtain multi-layer cylindrical myocardial short axis data.

[0035] The second sampling unit is used to sample the short-axis data of the ellipsoidal myocardium in each layer and the short-axis data of the cylindrical myocardium in each layer, respectively, to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0036] The first calculation unit is used to calculate the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0037] A third aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the method for determining myocardial activity concentration described in the first aspect or any implementation thereof.

[0038] A fourth aspect of this application provides an electronic device, including at least one processor and a memory connected to the processor, wherein:

[0039] The memory is used to store computer programs;

[0040] The processor is used to execute the computer program so that the electronic device can implement the method for determining myocardial activity concentration in the first aspect or any implementation thereof.

[0041] The fifth aspect of this application provides a computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to determine the method for determining myocardial activity concentration as described in the first aspect or any implementation thereof.

[0042] Using the above technical solution, this application provides a method and related apparatus for determining myocardial activity concentration. The method includes: acquiring myocardial body data in the human body coordinate system and converting the myocardial body data in the human body coordinate system into myocardial body data in the cardiac axis coordinate system; unifying the original images acquired under different body positions and different scanning conditions into a coordinate system based on the anatomical axis of the heart itself, eliminating errors caused by differences in patient movement or placement, and providing stable and repeatable reference data for subsequent analysis. For myocardial body data in the cardiac axis coordinate system, the data is divided into ellipsoidal and cylindrical myocardial body data along the short axis of the cardiac axis coordinate system. Using the center of the ellipsoid as the sampling vertex, fan-shaped sampling is performed along the short axis of the ellipsoidal myocardial body data to obtain multi-layer ellipsoidal myocardial short axis data. Similarly, using the vertical section of the cylindrical myocardial body data as the sampling plane, parallel sampling is performed along the short axis of the cylindrical myocardial body data to obtain multi-layer cylindrical myocardial short axis data. Since the heart is not a simple geometric shape but a complex organ composed of different geometric forms, this differentiated processing of volumetric data improves the consistency between the volumetric data and the actual physiological heart. Data sampling is performed on each layer of ellipsoidal and cylindrical myocardial short axis data to obtain the myocardial activity concentration of the left ventricle, left atrium, and basal region. Based on these concentrations, the myocardial activity concentration is calculated. By sampling and comprehensively calculating data from three regions—the left ventricle, left atrium, and basal region—a more accurate myocardial activity concentration can be determined. Attached Figure Description

[0043] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0044] Figure 1 A flowchart illustrating a method for determining myocardial activity concentration provided in an embodiment of this application;

[0045] Figure 2 A schematic diagram illustrating the transformation from the human body coordinate system to the mandibular axis coordinate system, provided for an embodiment of this application;

[0046] Figure 3 A schematic diagram of an ellipsoidal myocardial profile and a cylindrical myocardial profile on a horizontal or vertical major axis, provided for embodiments of this application;

[0047] Figure 4 A schematic diagram of sector sampling and parallel sampling on a horizontal or vertical major axis provided in the embodiments of this application;

[0048] Figure 5 A schematic diagram of the left ventricle, basal body, and left atrium along a horizontal or vertical major axis, provided for embodiments of this application;

[0049] Figure 6 This is a schematic diagram illustrating data sampling of myocardial short-axis data, provided as an embodiment of this application.

[0050] Figure 7 A schematic diagram of an apparatus for determining myocardial activity concentration provided in an embodiment of this application;

[0051] Figure 8 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0052] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0053] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0054] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0055] To improve the accuracy of the determined myocardial activity concentration, this application provides a method for determining myocardial activity concentration. The method for determining myocardial activity concentration provided in this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] Please see the appendix Figure 1 , Figure 1 This is a flowchart illustrating a method for determining myocardial activity concentration, provided as an embodiment of this application. The method may include the following steps:

[0057] Step S101: Obtain myocardial body data in the human body coordinate system and convert the myocardial body data in the human body coordinate system into myocardial body data in the heart axis coordinate system.

[0058] It's important to note that the human body coordinate system is a global, fixed coordinate system. Its axes are aligned with the patient's anatomical position and are typically defined as follows: X-axis: left-right direction (from the patient's right side to the left); Y-axis: front-back direction (from the patient's back to the abdomen); Z-axis: up-down direction (from the patient's feet to the head). The orientation of the data within this coordinate system will vary depending on the patient's lying position during the scan (e.g., slightly turned to the side). The cardiac axis coordinate system is a personalized coordinate system defined by the heart's own anatomical structure. It is typically defined as follows: vertical major axis of the myocardium: from the apex to the base of the heart; minor axis of the myocardium: in the minor axis plane, typically pointing towards the left ventricular lateral wall; horizontal major axis of the myocardium: in the minor axis plane, perpendicular to the minor axis of the myocardium, typically pointing towards the anterior septum / posterior lateral wall. In the cardiac axis coordinate system, regardless of whether the patient is supine, prone, or lateral, and regardless of whether the heart is vertically or horizontally positioned, the heart's major axis is aligned with the Z-axis, and the minor axis plane is aligned with the XY plane; that is, the heart is upright.

[0059] In this application, the X-axis rotation angle, Y-axis rotation angle, and Z-axis rotation angle of the human body coordinate system can be obtained. The myocardial body data under the X-axis of the human body coordinate system can be rotated based on the X-axis rotation angle, the myocardial body data under the Y-axis of the human body coordinate system can be rotated based on the Y-axis rotation angle, and the myocardial body data under the Z-axis of the human body coordinate system can be rotated based on the Z-axis rotation angle to obtain the myocardial body data in the cardiac axis coordinate system.

[0060] Specifically, rotation angles refer to the degrees required to rotate the human body coordinate system around the X, Y, and Z axes of the human body coordinate system to align it with the cardiac coordinate system. These three angles (often referred to as Euler angles) are calculated by analyzing raw cardiac imaging data. The algorithm automatically identifies the major and minor axes of the heart and then calculates the deviation angles relative to the original human body coordinate system.

[0061] This application employs a split-type multi-hole collimator and a V-shaped detector to acquire cardiac data under resting and load conditions. The two detectors of the V-shaped detector are arranged at a V-angle, working in conjunction with the split-type pinhole collimator to form a V-mode. This geometry can rotate back and forth within an angular range, starting at 111°, acquiring data from 10 pinholes at this angle (referred to as the 10-hole position); then rotating to 78°, acquiring data from 4 pinholes at this angle (referred to as the 4-hole position). The gantry then returns to the 111° 10-hole position for the next acquisition, and this cycle repeats. The entire acquisition process can last 12 minutes. To capture early rapid hemodynamic changes and later slower metabolic processes, a specific time frame sequence can be followed: 10 seconds × 10 frames + 20 seconds × 5 frames + 60 seconds × 4 frames + 280 seconds × 1 frame. This cyclical rotation (including one 10-hole acquisition and one 4-hole acquisition) generates two frames of projected data.

[0062] A set of corresponding 10-well and 4-well projection data was iteratively reconstructed using the OSEM algorithm. The OSEM algorithm effectively handles noise and limited projection data, producing high-quality 3D tomographic images. A dual-energy window method was employed, estimating the distribution of scattered photons by setting an auxiliary energy window near a main energy window and subtracting it from the main energy window data to improve image contrast. Attenuation correction was performed using CT images. Human density maps obtained from CT scans on the same gantry were used to calculate the attenuation of photons in different tissues and correct for it, thus obtaining a quantitatively accurate activity distribution. After the above reconstruction and correction, a 3D volumetric data was obtained. The coordinate system of this volumetric data is a fixed human coordinate system. Under continuous dynamic acquisition for 12 minutes, 20 loop processes were implemented, ultimately reconstructing 20 3D volumetric data points at different time points, each with its corresponding time information. The OSEM algorithm can be used for tomographic reconstruction, and scattering and attenuation corrections can be applied to obtain initial volumetric data in the human coordinate system. This initial volumetric data includes the heart, surrounding organs, and other tissues.

[0063] To perform standardized cardiac function analysis, the heart, which is tilted in the human coordinate system, needs to be aligned. This can be achieved by rotating the volumetric data of the X-axis in the human coordinate system by an angle. This allows us to align the volume data of the myocardium's minor axis (X1) with the cardiac axis coordinate system. Rotating the volume data of the human body's Y-axis by an angle θ aligns it with the volume data of the myocardium's horizontal major axis (Y1) with the cardiac axis coordinate system. Once the volume data of the myocardium's minor axis and horizontal major axis in the cardiac axis coordinate system are determined, the volume data of the myocardium's vertical major axis (Z1) in the cardiac axis coordinate system is also determined. This is a continuous or combined rotational transformation that maps the coordinates of all pixels in the original volume data to the new cardiac axis coordinate system. For a more detailed explanation, please refer to [link to documentation]. Figure 2 , Figure 2 This diagram illustrates a transformation from a human body coordinate system to a cardiac axis coordinate system, as provided in an embodiment of this application. In the cardiac axis coordinate system (X1, Y1, Z1), the transformed volume data is resampled. A slice is taken along the vertical major axis Z1 of the myocardium to generate a minor axis image; a slice is taken along the horizontal major axis Y1 of the myocardium to generate a horizontal major axis image; and a slice is taken along the minor axis X1 of the myocardium to generate a vertical major axis image, ultimately obtaining the initial volume data in the cardiac axis coordinate system.

[0064] To automatically separate myocardial tissue from surrounding organs (such as the liver) in an image, the Otsu method can be used to automatically determine the image segmentation threshold. By statistically analyzing the gray-level histogram of the initial volume data in the cardiac axis coordinate system, an optimal gray value is found as the threshold. This maximizes the inter-class variance of the foreground (myocardial) and background (non-myocardial) pixels segmented according to this threshold, distinguishing the brighter myocardial pixels from the darker surrounding tissue pixels, resulting in a three-dimensional binary mask limited to myocardial tissue. The volume data obtained from automatic segmentation may be incomplete, especially at the apex (where the myocardium is thinnest and the signal may be weak) and the base (connected to structures such as the aorta and left atrium, with blurred boundaries). The Otsu algorithm may underestimate the actual extent of the myocardium. Therefore, the segmented volume data is directionally augmented to ensure complete myocardial information is captured. Specifically, at least three frames (three consecutive slices) are extended outward from the apex along the short axis of the myocardium to ensure that even weak signals at the apex are included in the analysis, avoiding apical truncation. Along the short-axis of the myocardium, extend 6 mm lateral to the base of the heart to ensure that the region connecting the left ventricle and left atrium, as well as part of the left atrium itself, is included in the subsequent volume data. This ultimately generates an augmented myocardial body dataset, i.e., myocardial body data in the axial coordinate system.

[0065] Step S102: For the myocardial body data in the cardiac axis coordinate system, divide the myocardial body data in the cardiac axis coordinate system into ellipsoidal myocardial body data and cylindrical myocardial body data along the direction of the short axis of the myocardium in the cardiac axis coordinate system.

[0066] In this application, firstly, the myocardial body data in the axial coordinate system can be smoothed to obtain smoothed myocardial body data. Then, the smoothed myocardial body data can be converted into a binary myocardial image, and the myocardial coordinates in the binary myocardial image are obtained along the minor axis of the myocardium in the axial coordinate system. The myocardial coordinates in the binary myocardial image include myocardial contour coordinates. Next, the myocardial contour coordinates can be fitted using the ellipsoid equation to obtain ellipsoidal myocardial contour coordinates, and the data corresponding to myocardial coordinates that coincide with the myocardial coordinates within the ellipsoidal myocardial contour coordinates are identified as ellipsoidal myocardial body data. Finally, other myocardial contour coordinates can be fitted using the cylinder equation to obtain cylindrical myocardial contour coordinates, and the data corresponding to myocardial coordinates that coincide with the myocardial coordinates within the cylindrical myocardial contour coordinates are identified as cylindrical myocardial body data. Other myocardial contour coordinates are the myocardial coordinates in the binary myocardial image excluding those coinciding with the myocardial coordinates within the ellipsoidal myocardial contour coordinates.

[0067] Specifically, to automatically segment the left ventricular myocardium into two parts according to its natural geometry: an ellipsoidal region at the apex and a cylindrical region at the base of the ventricle, this division is based on the actual anatomical structure of the left ventricle—the apex resembles an ellipsoid cut in half, while the main body of the ventricle approximates a hollow cylinder. The first step in achieving this segmentation is data preparation and optimization. The myocardial body data, already converted to the cardiac axis coordinate system, is preprocessed. First, morphological closing operations are used to smooth the myocardial contour. This operation effectively eliminates image noise and fine spurs, resulting in a clearer and more continuous myocardial body contour.

[0068] After obtaining the smoothed myocardial body data, the Otsu adaptive thresholding method can be used to convert the grayscale image into a binary myocardial image (either black or white). Then, the binary myocardial image is traversed to extract all contour coordinate points defining the myocardial boundary. Next, the ellipsoid equation and least squares method are used to perform a three-dimensional fitting of all contour coordinates to find an ideal ellipsoid that best matches the overall myocardial shape. After successful fitting, this ideal ellipsoid is not directly used; instead, its intersection with the real myocardial contour is calculated: only those myocardial coordinate points that are both inside the real myocardium and inside the fitted ellipsoid are retained. This overlapping region is precisely defined as the ellipsoidal myocardial body data, representing the apex of the left ventricle.

[0069] After extracting the apical ellipsoid region, the remaining myocardium mainly constitutes the cylindrical part of the ventricle. The contour coordinates of the remaining myocardial region are then modeled. Similarly, the contour coordinates of these remaining regions are obtained from the binary image, but this time a cylindrical equation is used for fitting. To better reflect the anatomical fact that the myocardium is a wall-like structure and to ensure the model's reasonableness, the fitting process simultaneously constructs a large cylinder representing the epicardial boundary and a small cylinder representing the endocardial boundary, thus directly fitting a cylindrical ring. This process imposes strict concentric and coaxial constraints to ensure that the central axis of the cylinder is aligned with the long axis of the heart, and optimizes using the least squares method to find the best-fitting cylindrical model. Finally, again by taking the intersection, the region where the remaining real myocardial contour overlaps with the interior of the fitted cylindrical ring is identified as the cylindrical myocardial body data.

[0070] Through the series of steps outlined above, the complex three-dimensional morphology of the ventricle is decomposed into two regular geometric models: an ellipsoid and a cylinder. For a clearer understanding, please refer to [link to relevant documentation]. Figure 3 , Figure 3 This is a schematic diagram of an ellipsoidal myocardial profile and a cylindrical myocardial profile on a horizontal or vertical major axis, provided for embodiments of this application.

[0071] Step S103: Using the ellipsoidal center of the ellipsoidal myocardial body data as the sampling vertex, perform fan-shaped sampling along the short axis of the myocardium to obtain multi-layer ellipsoidal myocardial short axis data. Using the vertical section of the cylindrical myocardial body data as the sampling plane, perform parallel sampling along the short axis of the myocardium to obtain multi-layer cylindrical myocardial short axis data.

[0072] To slice three-dimensional myocardial body data into a series of continuous two-dimensional slices, different sampling strategies may be needed for the ellipsoidal and cylindrical regions of the heart due to their different geometric properties. This ensures that the final slices most realistically and accurately reflect the myocardium's condition at various locations. For a clearer understanding, please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is a schematic diagram of sector sampling and parallel sampling on a horizontal or vertical major axis, provided as an embodiment of this application.

[0073] Specifically, for the ellipsoidal region, its shape expands upwards from the apex of the heart. If parallel planes were used to cut it, the slices near the apex would be very small and irregular. Therefore, sector sampling (or conical sampling) is used here. Specifically, this involves radiating a series of conical surfaces outwards from the center of the ellipsoidal region (i.e., the apex of the cone) along the short axis of the myocardium (roughly from the apex to the base) at fixed cone angle intervals (e.g., 10°). When each conical surface intersects the three-dimensional myocardial body data, it cuts out a ring-shaped region (because the intersection of the cone and the hollow myocardium forms a ring). Each such ring constitutes a layer of hemispherical myocardial short axis data. By setting nine cones with 10° cone angle intervals consecutively, nine layers of continuous, rounded short axis sampling data can be obtained, starting from the apex and increasing in size.

[0074] Next, for the cylindrical region (i.e., the cylindrical myocardial body data), its shape is regular and uniform, resembling a vertical cylinder. Therefore, a more intuitive parallel sampling method can be used. This method uses a series of planes with normal vectors parallel to the short axis of the myocardium as cutting surfaces, and cuts the cylindrical myocardial body data at equal or non-equal intervals along the short axis. Each cutting plane intersects the cylindrical myocardium, resulting in a standard and approximately uniformly sized annular cross-section. These cross-sections are the short axis data of the cylindrical myocardium. Assuming n layers are sampled, the cylindrical portion contributes n layers of short axis data.

[0075] Finally, the data obtained from the two sampling methods were seamlessly stitched together. The 9-layer sector sampling data from the apex of the heart and the n-layer parallel sampling data from the ventricular body together formed a complete set of (n+9) layers of myocardial short-axis sampling data extending from the apex to the base of the heart.

[0076] Step S104: Sample the short-axis data of the ellipsoidal myocardium and the short-axis data of the cylindrical myocardium of each layer to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0077] In this application, firstly, multi-layer ellipsoidal myocardial activity concentrations can be obtained by sampling the short-axis data of each layer of ellipsoidal myocardium, and the average value of the multi-layer ellipsoidal myocardial activity concentrations can be used as the myocardial activity concentration of the left ventricle. Then, based on the vertical cross-section of the cylindrical myocardial body data, the short-axis data of each layer of cylindrical myocardium can be averaged to obtain multi-layer first cylindrical myocardial activity concentrations and multi-layer second cylindrical myocardial activity concentrations, where the distance between the first cylindrical myocardial activity concentrations and the ellipsoidal myocardial activity concentrations is less than the distance between the second cylindrical myocardial activity concentrations and the ellipsoidal myocardial activity concentrations. Next, multi-layer first cylindrical myocardial activity concentrations can be obtained by sampling the short-axis data of each layer of first cylindrical myocardium, and the average value of the multi-layer first cylindrical myocardial activity concentrations can be used as the myocardial activity concentration of the basal region. Finally, multi-layer second cylindrical myocardial activity concentrations can be obtained by sampling the short-axis data of each layer of second cylindrical myocardium, and the average value of the multi-layer second cylindrical myocardial activity concentrations can be used as the myocardial activity concentration of the left atrium.

[0078] Specifically, sampling the activity concentration of this ellipsoidal region data can represent the overall condition of the left ventricular myocardium. The specific procedure is as follows: Based on the previously obtained multi-layered ellipsoidal myocardial short-axis data, data is sampled from each short-axis annulus. Each short-axis data layer contains a ring-shaped region with numerous pixels. This data sampling calculates the average activity of all pixels within this annular region, thus obtaining the myocardial activity concentration of a single ellipsoidal layer. Finally, this average from all layers (e.g., 9 layers) is averaged together to obtain the final value, which represents the myocardial activity concentration of the left ventricle.

[0079] Next, the cylindrical region is divided into two equal parts. The division is based on the vertical cross-section of the cylindrical myocardial body data and the relative distance between each layer's minor axis data and the ellipsoidal region. Specifically, on each layer's minor axis annulus, the half closer to the ellipsoidal region is designated as the first cylindrical myocardial minor axis data; the half farther away is designated as the second cylindrical myocardial minor axis data. The former corresponds to the basal region, and the latter to the left atrium. Activity concentrations are calculated for these two newly divided regions. The process is similar to that of the left ventricle: the basal region of each layer is sampled to obtain multi-layer activity concentration values, and then the average value is calculated, which is the myocardial activity concentration at the basal region. Similarly, the left atrium of each layer is sampled and averaged to obtain the myocardial activity concentration of the left atrium. For easier understanding, please refer to [link to relevant documentation]. Figure 5 , Figure 5 This is a schematic diagram of the left ventricle, basal body, and left atrium along a horizontal or vertical long axis, provided for an embodiment of this application.

[0080] Regarding the details of sampling points, to ensure data representativeness and consistency, standardized sampling can be performed on each layer of short-axis annulus. The number of sampling points is automatically allocated based on the diameter of each annulus layer, ensuring a reasonable sampling density across annulus layers of different sizes. For example, in the (n+9) layers of short-axis data for the entire myocardium, each layer is uniformly divided into 16 sampling points, resulting in a total of 16×(n+9) sampling points across the entire left ventricular myocardium. For a clearer understanding, please refer to [link / reference needed]. Figure 6 , Figure 6 This is a schematic diagram illustrating data sampling of myocardial short-axis data, provided as an embodiment of this application.

[0081] Step S105: Calculate the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0082] In this application, the average values ​​of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region can be calculated, and the average value is determined as the myocardial activity concentration.

[0083] Specifically, this can be applied to the myocardial activity concentrations of the left ventricle, left atrium, and basal region at the aforementioned 20 different time points. The average myocardial activity concentrations of the left ventricle, left atrium, and basal region at these 20 time points can be calculated, and a time-myocardial activity concentration representation of these averages can be generated. Then, the averages of these average myocardial activity concentrations at the 20 different time points are calculated, resulting in the myocardial activity concentrations at 20 different time points, and a time-myocardial activity concentration representation C can be generated. activity (t).

[0084] In summary, this application provides a method for determining myocardial viability concentration. The method includes: acquiring myocardial body data in a human coordinate system and converting the myocardial body data in the human coordinate system into myocardial body data in a cardiac axis coordinate system; unifying the original images acquired under different body positions and scanning conditions into a coordinate system based on the anatomical axis of the heart itself, eliminating errors caused by differences in patient movement or placement, and providing stable and repeatable benchmark data for subsequent analysis. For myocardial body data in the cardiac axis coordinate system, the data is divided into ellipsoidal and cylindrical myocardial body data along the short axis of the cardiac axis coordinate system. Using the center of the ellipsoid as the sampling vertex, fan-shaped sampling is performed along the short axis of the ellipsoidal myocardial body data to obtain multi-layer ellipsoidal myocardial short axis data. Similarly, using the vertical section of the cylindrical myocardial body data as the sampling plane, parallel sampling is performed along the short axis of the cylindrical myocardial body data to obtain multi-layer cylindrical myocardial short axis data. Since the heart is not a simple geometric shape but a complex organ composed of different geometric forms, this differentiated processing of volumetric data improves the consistency between the volumetric data and the actual physiological heart. Data sampling is performed on each layer of ellipsoidal and cylindrical myocardial short axis data to obtain the myocardial activity concentration of the left ventricle, left atrium, and basal region. Based on these concentrations, the myocardial activity concentration is calculated. By sampling and comprehensively calculating data from three regions—the left ventricle, left atrium, and basal region—a more accurate myocardial activity concentration can be determined.

[0085] Furthermore, based on the above embodiments, the method may further include the following steps: First, the median of the myocardial activity concentration in the left ventricle, the myocardial activity concentration in the left atrium, and the myocardial activity concentration in the basal region can be calculated, and the median can be determined as the arterial blood concentration. Then, based on the acquired myocardial activity concentration and arterial blood concentration at multiple time points, the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase can be calculated. Finally, based on the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase, the myocardial blood flow reserve can be calculated.

[0086] In this application, the median of the average myocardial activity concentration of the left ventricle, the average myocardial activity concentration of the left atrium, and the average myocardial activity concentration of the basal region at 20 different time points is calculated, i.e., the arterial blood concentration at 20 different time points, and a time-arterial blood concentration representation C can be generated. blood (t).

[0087] Myocardial blood flow (MBF) is the ultimate target parameter, measured in mL / min / g, representing the blood flow rate per gram of myocardial tissue per minute. Rate constant. This is the rate constant of tracer uptake from the blood into myocardial tissue (unit: mL / min / g); rate constant It is the rate constant of tracer elution from myocardial tissue back into the blood (unit: Volume of distribution (DV) describes the concentration ratio of the tracer in tissues and blood when equilibrium is reached, and is determined by two rate constants: DV = / This formula establishes the fundamental relationship between the rate constant and the distribution volume. Fractional blood volume (FBV) refers to the volume fraction of blood within an image pixel.

[0088] Myocardial blood flow (MBF) cannot be directly measured and must be indirectly calculated through the tracer uptake process. This step links macroscopic MBF with microscopic capillary exchange function through two key formulas. PS (permeability permeability) is the product of capillary wall permeability and vascular surface area, and it is related to blood flow. An empirical formula can be used to estimate it: PS(MBF) = 0.63 + 0.2 × MBF. The extraction fraction E represents the proportion of tracer retained by the tissue in the blood flowing through the myocardium. It is determined by both PS and MBF, following the Renkin-Crone model: E(MBF) = 1 - e -PS(MBF) / MBF The formula indicates that extraction efficiency decreases with increasing blood flow. The rate at which the tracer is taken up by the myocardium. It is equal to the product of blood flow and extraction score: =MBF×E(MBF), this formula combines the MBF we want to solve for with the parameters that can be obtained through model fitting. Directly connected.

[0089] With the theoretical foundation established, a computational mathematical model needs to be constructed to simulate the actual imaging process: tissue activity concentration originates from the tracer actually taken up by cardiomyocytes. Its time-activity curve C... conc (t) is a convolution process that depends on the ingestion rate. Distribution volume DV (i.e. / ) and arterial input function C blood (t): C conc (t)= ×e -( / DV)×t ×C blood (t). The signal measured by PET images includes both the activity in myocardial tissue and the blood activity remaining in the blood vessels within that pixel. Therefore, the total activity estimation model is: C estimate (t)=FBV×C blood (t)+(1-FBV)×C conc (t). The curve C calculated by the modelestimate (t) must be as close as possible to the actually measured time-myocardial activity concentration C. activity The difference between the two is measured by the cost function: Cost(t) = Σ||C estimate (t)-C activity (t)||². Optimization algorithms such as BFGS can be used to automatically adjust the values ​​of parameters MBF and FBV to minimize the cost function Cost(t). When the optimization process converges, the corresponding MBF value is the final calculated myocardial blood flow. The above process requires calculation of data under resting and overload conditions to obtain the resting myocardial blood flow (RMBF) and overload myocardial blood flow (SMBF). Finally, myocardial blood flow reserve is calculated from the resting myocardial blood flow (RMBF) and overload myocardial blood flow (SMBF): MFR = SMBF / RMBF.

[0090] In summary, this application provides a method for determining myocardial blood flow reserve. This method determines arterial blood concentration by calculating the median activity concentration of the left ventricle, left atrium, and basal region. This effectively suppresses outlier interference caused by image registration errors or noise, thereby obtaining a more robust and accurate arterial input function. Based on this, myocardial activity concentration and arterial blood concentration obtained at multiple time points during both load and resting phases are used to quantitatively calculate the load myocardial blood flow and resting myocardial blood flow using a kinetic model. Finally, by dividing the two, the key clinical indicator of myocardial blood flow reserve is obtained, achieving an objective and quantitative assessment of coronary artery blood flow reserve capacity.

[0091] The above describes a method for determining myocardial activity concentration provided by the embodiments of this application. The following will describe the apparatus for determining myocardial activity concentration that performs the above description.

[0092] Please see Figure 7 , Figure 7 This is a schematic diagram of a device for determining myocardial activity concentration provided in an embodiment of this application. Figure 7 As shown, the device for determining myocardial activity concentration includes:

[0093] The conversion unit 11 is used to acquire myocardial body data in the human body coordinate system and convert the myocardial body data in the human body coordinate system into myocardial body data in the heart axis coordinate system.

[0094] The partitioning unit 12 is used to partition the myocardial body data in the cardiac axis coordinate system into ellipsoidal myocardial body data and cylindrical myocardial body data along the minor axis direction of the myocardium in the cardiac axis coordinate system.

[0095] The first sampling unit 13 is used to perform fan-shaped sampling of the ellipsoidal myocardial body data along the short axis of the myocardium, with the ellipsoidal center of the ellipsoidal myocardial body data as the sampling vertex, to obtain multi-layer ellipsoidal myocardial short axis data, and to perform parallel sampling of the cylindrical myocardial body data along the short axis of the myocardium, with the vertical cross-section of the cylindrical myocardial body data as the sampling plane, to obtain multi-layer cylindrical myocardial short axis data.

[0096] The second sampling unit 14 is used to sample the short-axis data of the ellipsoidal myocardium in each layer and the short-axis data of the cylindrical myocardium in each layer, respectively, to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0097] The first calculation unit 15 is used to calculate the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

[0098] In one possible implementation, the partitioning unit 12 includes:

[0099] The processing subunit is used to perform contour smoothing on the myocardial body data in the heart axis coordinate system to obtain contour smoothed myocardial body data.

[0100] The transformation subunit is used to convert the contour-smoothed myocardial body data into a binary myocardial image, and to obtain the myocardial coordinates in the binary myocardial image along the minor axis of the myocardial coordinate system. The myocardial coordinates in the binary myocardial image include myocardial contour coordinates.

[0101] The first fitting subunit is used to fit the myocardial contour coordinates using the ellipsoid equation to obtain ellipsoidal myocardial contour coordinates, and to determine the data corresponding to the myocardial coordinates that coincide with the myocardial coordinates inside the myocardial contour coordinates as the ellipsoidal myocardial body data.

[0102] The second fitting subunit is used to fit other myocardial contour coordinates using the cylindrical equation to obtain cylindrical myocardial contour coordinates, and to determine the data corresponding to the myocardial coordinates that coincide with the myocardial coordinates inside the myocardial contour coordinates as the cylindrical myocardial body data. The other myocardial contour coordinates are the myocardial coordinates in the binary myocardial image other than the myocardial coordinates that coincide with the myocardial coordinates inside the ellipsoidal myocardial contour coordinates.

[0103] In one possible implementation, the second sampling unit 14 includes:

[0104] The first sampling subunit is used to sample the short axis data of the myocardium in each layer of the ellipsoid to obtain the multi-layer ellipsoid myocardial activity concentration, and to take the average value of the multi-layer ellipsoid myocardial activity concentration as the myocardial activity concentration of the left ventricle.

[0105] The sub-unit is used to divide the short-axis data of each layer of cylindrical myocardium based on the vertical cross-section of the cylindrical myocardium data, so as to obtain multi-layer first cylindrical myocardium short-axis data and multi-layer second cylindrical myocardium short-axis data. The distance between the first cylindrical myocardium short-axis data and the ellipsoidal myocardium short-axis data of each layer is less than the distance between the second cylindrical myocardium short-axis data and the ellipsoidal myocardium short-axis data of each layer.

[0106] The second sampling subunit is used to sample the short-axis data of the first cylindrical myocardium in each layer to obtain the multi-layer first cylindrical myocardial activity concentration, and to take the average value of the multi-layer first cylindrical myocardial activity concentration as the myocardial activity concentration of the basal part.

[0107] The third sampling subunit is used to sample the short-axis data of the second cylindrical myocardium in each layer to obtain the multi-layer second cylindrical myocardial activity concentration, and to take the average value of the multi-layer second cylindrical myocardial activity concentration as the myocardial activity concentration of the left atrium.

[0108] In one possible implementation, the device further includes:

[0109] The second calculation unit is used to calculate the median of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, and to determine the median as the arterial blood concentration.

[0110] The third calculation unit is used to calculate the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase based on the myocardial activity concentration and the arterial blood concentration at multiple times.

[0111] The fourth calculation unit is used to calculate the myocardial blood flow reserve based on the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase.

[0112] In one possible implementation, the conversion unit 11 includes:

[0113] The acquisition sub-unit is used to acquire the X-axis rotation angle, Y-axis rotation angle, and Z-axis rotation angle of the human body coordinate system.

[0114] The rotation subunit is used to rotate the myocardial body data under the X-axis of the human body coordinate system based on the rotation angle of the X-axis of the human body coordinate system, rotate the myocardial body data under the Y-axis of the human body coordinate system based on the rotation angle of the Y-axis of the human body coordinate system, and rotate the myocardial body data under the Z-axis of the human body coordinate system based on the rotation angle of the Z-axis of the human body coordinate system, so as to obtain the myocardial body data under the cardiac axis coordinate system.

[0115] In one possible implementation, the first computing unit 15 includes:

[0116] The calculation subunit is used to calculate the average value of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, and to determine the average value as the myocardial activity concentration.

[0117] This application also provides an electronic device in its embodiments. (See reference...) Figure 8 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 8 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0118] like Figure 8 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 into a random access memory (RAM) 803. When the electronic device is powered on, the RAM 803 also stores various programs and data required for the operation of the electronic device. The processing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0119] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 808 including, for example, memory cards, hard drives, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0120] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the methods for determining myocardial viability concentration provided in this application.

[0121] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the methods for determining myocardial viability concentration provided in this application.

[0122] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0123] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0124] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0125] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method for determining myocardial activity concentration, characterized in that, include: Acquire myocardial body data in the human body coordinate system and convert the myocardial body data in the human body coordinate system into myocardial body data in the heart axis coordinate system; For the myocardial body data in the said cardiac axis coordinate system, the myocardial body data in the said cardiac axis coordinate system is divided into ellipsoidal myocardial body data and cylindrical myocardial body data along the direction of the minor axis of the myocardium in the said cardiac axis coordinate system. Using the ellipsoidal center of the ellipsoidal myocardial body data as the sampling vertex, fan-shaped sampling is performed on the ellipsoidal myocardial body data along the direction of the myocardial short axis to obtain multi-layer ellipsoidal myocardial short axis data. Using the vertical section of the cylindrical myocardial body data as the sampling plane, parallel sampling is performed on the cylindrical myocardial body data along the direction of the myocardial short axis to obtain multi-layer cylindrical myocardial short axis data. Data samples were collected from the ellipsoidal myocardial short-axis data and the cylindrical myocardial short-axis data of each layer to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region. The myocardial activity concentration is calculated based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region. The division of myocardial body data in the cardiac axis coordinate system into ellipsoidal myocardial body data and cylindrical myocardial body data along the minor axis direction of the myocardium in the cardiac axis coordinate system includes: The myocardial body data in the aforementioned axial coordinate system is subjected to contour smoothing to obtain contour-smoothed myocardial body data. The smoothed myocardial body data is converted into a binary myocardial image, and the myocardial coordinates in the binary myocardial image are obtained along the short axis of the myocardium in the myocardial coordinate system. The myocardial coordinates in the binary myocardial image include myocardial contour coordinates. The myocardial contour coordinates are fitted using the ellipsoid equation to obtain ellipsoidal myocardial contour coordinates. The data corresponding to the myocardial coordinates that coincide with the myocardial coordinates inside the myocardial contour coordinates are determined as the ellipsoidal myocardial body data. The cylindrical myocardial contour coordinates are obtained by fitting other myocardial contour coordinates using the cylindrical equation. The data corresponding to the myocardial coordinates that coincide with the myocardial coordinates inside the cylindrical myocardial contour coordinates are determined as the cylindrical myocardial body data. The other myocardial contour coordinates are the myocardial coordinates in the binary myocardial image other than the myocardial coordinates that coincide with the myocardial coordinates inside the ellipsoidal myocardial contour coordinates. The process involves sampling data from the ellipsoidal myocardial short-axis data and the cylindrical myocardial short-axis data of each layer to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, including: Data sampling was performed on the short axis data of the myocardium in each layer to obtain the myocardial activity concentration of the multilayer ellipsoid, and the average value of the myocardial activity concentration of the multilayer ellipsoid was taken as the myocardial activity concentration of the left ventricle. Based on the vertical cross-section of the cylindrical myocardial body data, the short axis data of each layer of cylindrical myocardium are divided into multiple layers of first cylindrical myocardial body short axis data and multiple layers of second cylindrical myocardial body short axis data. The distance between the first cylindrical myocardial body short axis data and the ellipsoidal myocardial body short axis data of each layer is less than the distance between the second cylindrical myocardial body short axis data and the ellipsoidal myocardial body short axis data of each layer. Data sampling was performed on the short-axis data of the first cylindrical myocardium in each layer to obtain the activity concentration of the first cylindrical myocardium in multiple layers, and the average value of the activity concentration of the first cylindrical myocardium in multiple layers was taken as the myocardial activity concentration of the basal part. Data sampling was performed on the short-axis data of the second cylindrical myocardium in each layer to obtain the multi-layer second cylindrical myocardial activity concentration, and the average value of the multi-layer second cylindrical myocardial activity concentration was taken as the myocardial activity concentration of the left atrium.

2. The method for determining myocardial activity concentration according to claim 1, characterized in that, After calculating the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, the method further includes: Calculate the median of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region, and determine the median as the arterial blood concentration; Based on the myocardial activity concentration and arterial blood concentration obtained at multiple time points, the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase are calculated. Myocardial blood flow reserve is calculated based on the myocardial blood flow during the load phase and the myocardial blood flow during the resting phase.

3. The method for determining myocardial activity concentration according to claim 1, characterized in that, The process of converting the myocardial body data in the human body coordinate system to the myocardial body data in the cardiac axis coordinate system includes: Obtain the X-axis rotation angle, Y-axis rotation angle, and Z-axis rotation angle of the human body coordinate system; The myocardial body data under the X-axis of the human body coordinate system is rotated based on the rotation angle of the X-axis of the human body coordinate system, the myocardial body data under the Y-axis of the human body coordinate system is rotated based on the rotation angle of the Y-axis of the human body coordinate system, and the myocardial body data under the Z-axis of the human body coordinate system is rotated based on the rotation angle of the Z-axis of the human body coordinate system to obtain the myocardial body data under the cardiac axis coordinate system.

4. The method for determining myocardial activity concentration according to claim 1, characterized in that, The calculation of myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region includes: The average value of the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region is calculated, and the average value is determined as the myocardial activity concentration.

5. A device for determining myocardial activity concentration, characterized in that, The apparatus for implementing the method according to any one of claims 1 to 4 comprises: A conversion unit is used to acquire myocardial body data in the human body coordinate system and convert the myocardial body data in the human body coordinate system into myocardial body data in the heart axis coordinate system. A partitioning unit is used to divide the myocardial body data in the cardiac axis coordinate system into ellipsoidal myocardial body data and cylindrical myocardial body data along the minor axis direction of the cardiac axis coordinate system. The first sampling unit is used to perform fan-shaped sampling of the ellipsoidal myocardial body data along the direction of the myocardial short axis, with the ellipsoidal center of the ellipsoidal myocardial body data as the sampling vertex, to obtain multi-layer ellipsoidal myocardial short axis data, and to perform parallel sampling of the cylindrical myocardial body data along the direction of the myocardial short axis, with the vertical cross-section of the cylindrical myocardial body data as the sampling plane, to obtain multi-layer cylindrical myocardial short axis data. The second sampling unit is used to sample the short-axis data of the ellipsoidal myocardium in each layer and the short-axis data of the cylindrical myocardium in each layer, respectively, to obtain the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region. The first calculation unit is used to calculate the myocardial activity concentration based on the myocardial activity concentration of the left ventricle, the myocardial activity concentration of the left atrium, and the myocardial activity concentration of the basal region.

6. A computer program product, characterized in that, Includes computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the method for determining myocardial activity concentration as described in any one of claims 1 to 4.

7. An electronic device, characterized in that, It includes at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program to enable the electronic device to implement the method for determining myocardial activity concentration as described in any one of claims 1 to 4.

8. A computer storage medium, characterized in that, The storage medium carries one or more computer programs that, when executed by an electronic device, enable the electronic device to implement the method for determining myocardial viability concentration as described in any one of claims 1 to 4.

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