Space imaging method and system for atherosclerosis micro-calcification area

Abstract

The invention discloses an atherosclerosis micro-calcification area space imaging method and system. The method comprises the following steps: constructing an aorta microcalcified plaque model of a target animal; for the aortic microcalcified plaque model, image segmentation of a biological specimen is carried out, in combination with histomorphological characteristics, multiple structural micro-regions are screened out in situ based on metabolic characteristics, and the multiple structural micro-regions are related to atherosclerosis; and carrying out metabolic heterogeneity analysis on the various structural micro-regions, and screening characteristic metabolic molecules to obtain heterogeneity spatial distribution. According to the method, the in-situ micro-calcification region can be accurately identified, and the molecular characteristics and metabolic heterogeneity characteristics of the in-situ micro-calcification region can be obtained, so that an important research strategy and a molecular basis are provided for occurrence and development of related cardiovascular and cerebrovascular diseases, molecular mechanism research, diagnosis and treatment and the like; the method has important value for accurately understanding the occurrence and development process of serious diseases, formulating personalized treatment schemes and evaluating and screening the efficacy of related drugs.

Description

Technical Field

[0001] The present invention relates to the technical field of detection and analysis, and more specifically, to a method and system for spatial imaging of atherosclerotic microcalcification regions. Background Art

[0002] Vascular calcification is one of the hallmark features of atherosclerosis and is closely related to adverse cardiovascular events. Calcifications of different periods and sizes can induce different clinical outcomes. Early calcifications appear as microcalcifications (with diameters ranging from <0.5 μm to 15 μm), and as the plaque progresses, they become punctate calcifications (with diameters of 15 μm - 1 mm), fragmented calcifications (with diameters >1 mm), and finally form sheet-like calcifications (with diameters >3 mm). Studies have shown that compared with large calcifications such as sheet-like calcifications, microcalcifications and punctate calcifications are more dangerous.

[0003] Atherosclerotic microcalcifications directly promote plaque progression and rupture, seriously threatening human health. Studies have shown that most patients with acute myocardial infarction have micro- and punctate calcifications, while patients with stable angina mostly show large calcifications. By studying optical coherence tomography images, it is found that plaque rupture is positively correlated with the number of micro- and punctate calcifications and negatively correlated with the number of large calcifications. In addition, microcalcifications can greatly increase the probability of plaque rupture through the "grinding wheel effect" of vascular contraction and relaxation, and can also trigger and amplify plaque inflammation. Kelly-Arnold et al. used 2.1 μm high-resolution micro-computed tomography (Micro-CT) to study the spatial distribution, clustering, and shape of nearly 35,000 microcalcifications ≥5 μm in the fibrous caps of 22 unruptured human atherosclerotic plaques. It was found that almost all fibrous caps of atherosclerotic plaques contain microcalcifications smaller than 5 μm, and microcalcifications larger than 10 μm generate more dangerous mechanical stresses. Nadra et al. found that calcium phosphate crystals smaller than 1 μm can activate macrophages to release inflammatory factors such as TNF-α, IL-1β, and IL-8, promoting the progression of atherosclerotic inflammation.

[0004] In summary, microcalcifications are widely distributed and highly harmful in the atherosclerotic population. There is an urgent need to develop research methods for microcalcifications to accurately locate them in situ, which is of great value for in-depth exploration of the pathogenesis of cardiovascular and cerebrovascular diseases, searching for effective diagnosis and treatment methods, thereby reducing the risk of cardiovascular diseases and the social and economic burden.

[0005] In conventional in-situ localization studies of microcalcifications, histological morphology and clinical medical imaging techniques are usually used for identification and analysis. Currently, clinical CT (Computed Tomography) and MRI (Magnetic Resonance Imaging) are limited by spatial resolution and are difficult to detect microcalcification regions. IVUS (Intravascular Ultrasound) cannot penetrate calcifications and will cause acoustic shadow formation, so it often cannot accurately evaluate the degree of microcalcification. Optical Coherence Tomography has high spatial resolution and is suitable for detecting microcalcifications, but its imaging depth is limited, unable to detect microcalcifications in regions such as the vessel lumen and adventitia, and unable to provide information at the molecular level related to blood vessels. Functional Near-Infrared Spectroscopy Imaging lacks imaging agents available for clinical detection. 18F-sodium fluoride PET-CT can indirectly show micro and punctate calcifications by utilizing the adsorption of fluoride by minerals such as bone and calcification. However, compared with ex vivo imaging, in vivo 18F-sodium fluoride imaging may be affected by factors such as the density of vasa vasorum in plaques, resulting in lower detection sensitivity. Therefore, there is an urgent need for in-situ localization methods for early clinical detection of microcalcifications.

[0006] The process of disease occurrence and development is inseparable from the metabolism and synthesis of a large number of biomolecules. This process can not only provide a large number of essential biomembrane components for the rapid division and proliferation of disease-related cells, but also promote the development of diseases by synthesizing a series of sphingolipids, phosphatidylinositols and oxidative signaling molecules. Compared with genes and proteins, metabolites are at the end of the regulation of life activities and are closer to the biological phenotype than genes and proteins. Studies have found that lipid metabolites are involved in the pathological process of atherosclerotic microcalcification. During the formation of microcalcifications, macrophages and other cells will release extracellular vesicles such as exosomes and apoptotic bodies. Local extracellular vesicles contain abundant substances such as cholesterol, diacylglycerol, sphingolipids and ceramides, which can accumulate calcium and phosphorus (Pi) and provide microcalcification nucleation sites composed of phosphatidylserine and annexin, developing the aggregated calcium and phosphorus (Pi) into amorphous calcium phosphate, and finally forming the crystal structure of microcalcifications, such as hydroxyapatite. In addition, the membrane of extracellular vesicles is rich in glycosylphosphatidylinositol-anchored tissue non-specific alkaline phosphatase (TNAP), which can hydrolyze pyrophosphate (PPi), enabling the microcalcification crystals that have migrated to the extracellular environment to grow together with the collagen matrix. In summary, screening biomarkers related to atherosclerotic microcalcifications, which can label biochemical indicators of characteristic organizational structures, cells and subcellular structural and functional changes, has important guiding significance for exploring the molecular mechanism of disease occurrence and development, accurately judging its phenotype and developing related drugs.

[0007] Mass spectrometry spatial omics technology is a new analytical method that combines high-end imaging technology with mass spectrometry imaging (MSI) on the basis of mass spectrometry. Without the need for labeling, it can perform targeted and untargeted analyses on the properties, quantitative changes, and spatial distribution changes of various substance molecules in a sample. These substance molecules include metabolites, lipids, polypeptides, proteins, glycans, metals, drugs, environmental pollutants, etc., and have advantages such as high sensitivity and high throughput. Mass spectrometry spatial omics technology includes multiple ionization methods, and can be divided into matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), desorption electrospray ionization mass spectrometry imaging (DESI-MSI), and secondary ion mass spectrometry imaging (SIMS-MSI) according to different ionization methods. Mass spectrometry spatial omics technology maintains the integrity of the molecular information of tissue sections, and its imaging results can be correlated with histological features, which helps to obtain the molecular characteristics of biological specimens and provides a visual method strategy for in-depth understanding of the process of disease occurrence and development, the microregions related to disease development, and the evolution of their microenvironments.

[0008] Currently, research based on mass spectrometry spatial omics technology has focused on cardiovascular and cerebrovascular diseases, but there are few reports on the identification and molecular feature research of atherosclerotic microcalcification areas. Li et al. collected human specimens and performed mass spectrometry spatial omics analysis on human carotid atherosclerotic specimens at four typical pathological stages: pre-sclerosis, atherosclerosis, fibroatherosclerosis, and complication stage. They found that 55 lipids had characteristic spatial distributions: 26 were distributed in the cross-sectional area, 13 were distributed in the lipid-rich area, and 16 were distributed in the collagen-rich area. Through enrichment pathway analysis, it was shown that pathways such as lipid metabolism absorption and cholesterol metabolism were enriched in the cross-sectional area, the sphingolipid signaling pathway was enriched in the lipid-rich area, and glycerophospholipid and ether lipid metabolism were enriched in the collagen-rich area. The study suggests that the metabolic characteristics of different regions of carotid plaques may play multiple important roles in the progression of atherosclerosis (Atherosclerosis, 2023, 364, 20-28). Greco et al. selected symptomatic and asymptomatic human carotid atherosclerotic plaques and carried out mass spectrometry spatial omics research to compare the metabolic changes in specific histopathological regions within the plaques. The study found that the lipid profiles of macrophage-rich areas and intimal vascular smooth muscle cells were most correlated with plaque outcomes. Among them, sphingomyelin was highly expressed in the macrophage-rich area in symptomatic specimens, and cholesterol and cholesteryl esters were highly expressed in the area rich in intimal vascular smooth muscle cells. The above research methods and conclusions indicate that mass spectrometry spatial omics technology is an important tool for studying diseases such as heterogeneous atherosclerosis (Metabolites 2021, 11, 250).

[0009] In summary, it is worth noting that metabolites and their metabolic processes play a key role in the progression of atherosclerosis, and are closely related to the formation of heterogeneous complex structures (such as microcalcification, calcification, hematoma and thrombus, etc.), inflammatory responses, and the activation of macrophages. Conventional mass spectrometry-based multi-omics analysis techniques cannot provide spatial distribution information of metabolites, and thus cannot accurately locate characteristic regions and obtain their molecular characteristics. Mass spectrometry spatial omics technology developed from mass spectrometry multi-omics technology has advantages such as label-free, high-throughput, and high sensitivity, and can simultaneously conduct qualitative, quantitative, and spatial localization studies on multiple substance molecules, making it a hot technology in the field of analytical chemistry. However, in the existing technology, for the study of atherosclerotic microcalcification, it usually focuses on in-situ analysis based on tissue morphology, and the detection indicators are limited. Summary of the Invention

[0010] The object of the present invention is to overcome the defects of the above-mentioned existing technologies and provide a method and system for spatial imaging of atherosclerotic microcalcification regions.

[0011] According to the first aspect of the present invention, a method for spatial imaging of atherosclerotic microcalcification regions is provided. The method includes the following steps:

[0012] Construct an aortic microcalcification plaque model of a target animal;

[0013] For the aortic microcalcification plaque model, perform image segmentation of biological specimens, and in combination with tissue morphological characteristics, in-situ screen out multiple structural micro-regions based on metabolic characteristics, and the multiple structural micro-regions are related to atherosclerosis;

[0014] For the multiple structural micro-regions, perform metabolic heterogeneity analysis, and obtain heterogeneous spatial distributions through the screening of characteristic metabolic molecules.

[0015] According to the second aspect of the present invention, a system for spatial imaging of atherosclerotic microcalcification regions is provided. The system includes:

[0016] Animal model construction module: used to construct an aortic microcalcification plaque model of a target animal;

[0017] Image segmentation module: used to perform image segmentation of biological specimens for the aortic microcalcification plaque model, and in combination with tissue morphological characteristics, in-situ screen out multiple structural micro-regions based on metabolic characteristics, and the multiple structural micro-regions are related to atherosclerosis;

[0018] Metabolic analysis module: used to perform metabolic heterogeneity analysis for the multiple structural micro-regions, and obtain heterogeneous spatial distributions through the screening of characteristic metabolic molecules.

[0019] Compared with the prior art, the advantages of the present invention are as follows: It provides a whole process for identifying atherosclerotic microcalcification regions and analyzing metabolic heterogeneity based on mass spectrometry spatial omics technology, which can accurately identify in-situ microcalcification regions and obtain their molecular characteristics and metabolic heterogeneity characteristics, thereby providing important research strategies and molecular bases for the occurrence, development, molecular mechanism research, diagnosis and treatment of related cardiovascular and cerebrovascular diseases. It has important value for accurately understanding the occurrence and development process of major diseases, providing in-situ lesion localization for clinicians, formulating personalized treatment plans, and evaluating and screening the efficacy of related drugs.

[0020] Other features and advantages of the present invention will become clear from the following detailed description of exemplary embodiments of the invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings incorporated in the specification and constituting a part of the specification illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0022] Figure 1 is a flowchart of a spatial imaging method for atherosclerotic microcalcification regions according to an embodiment of the present invention;

[0023] Figure 2 is a schematic diagram of the tissue morphology of a mouse aortic root plaque according to an embodiment of the present invention;

[0024] Figure 3 is an image segmentation diagram of mass spectrometry spatial omics data according to an embodiment of the present invention;

[0025] Figure 4 is a principal component analysis diagram of mass spectrometry spatial omics data according to an embodiment of the present invention;

[0026] Figure 5 is a spatial distribution diagram of representative substance molecules according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] Now, various exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that: Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present invention.

[0028] The following description of at least one exemplary embodiment is merely illustrative in nature and in no way limits the present invention, its application, or its use.

[0029] Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies, methods, and devices should be regarded as part of the specification.

[0030] In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.

[0031] It should be noted that like reference numerals and letters refer to like items in the following figures; thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

[0032] See Figure 1 As shown, the provided method for spatially imaging atherosclerotic microcalcification regions includes the following steps:

[0033] Step S110, for a target animal, construct an animal model of aortic microcalcified plaque.

[0034] In one embodiment, taking mice as an example, construct an animal model of mouse aortic microcalcified plaque according to the following steps:

[0035] Step 11, adaptively feed 6-week-old ApoE- / - mice with a regular diet in an SPF-level environment for 1 week.

[0036] Step 12, fast the ApoE- / - mice for 1 night.

[0037] Step 13, change the regular diet to an atherogenic diet, such as 22% fat and 0.12% cholesterol.

[0038] Step 14, continue to feed the ApoE- / - mice in an SPF-level environment for 24 weeks to obtain a mouse aortic microcalcified plaque model.

[0039] It should be understood that the target animal can be various types such as mice and rats, and the conditions for constructing the animal model of aortic microcalcified plaque can be set according to actual needs.

[0040] Step S120, identify atherosclerotic microcalcification regions in the aorta.

[0041] For example, based on the metabolic full spectrum, perform image segmentation of biological specimens, and in combination with tissue morphological characteristics, in-situ screen structural regions such as atherosclerotic microcalcification mainly characterized by metabolic characteristics. Specifically, identify atherosclerotic microcalcification regions in the aorta according to the following steps:

[0042] Step 21, based on the constructed animal model of mouse aortic microcalcified plaque, obtain plaque specimens, quickly freeze them, collect frozen sections of the specimens (such as 12 - 14 μm / slice), transfer the slices to a glass slide with an ITO coating, and then place them at -80 °C for storage of the frozen sections. Before the experiment, put them in a desiccator and dry for 40 minutes.

[0043] Step 22, perform spraying treatment on the matrix, and then use a mass spectrometry imaging instrument to perform a mass spectrometry imaging scan experiment on the ROI (regions of interest).

[0044] For example, the set imaging conditions are: positive ion mode, SmartBeam 3D laser (355 nm), scanning range of m / z 200 - 900 Da, laser intensity of 40%, etc.

[0045] Step 23, perform segmentation processing on the mass spectrometry imaging data, and combine the tissue morphology spectrogram to identify and label multiple characteristic regions of the specimen.

[0046] Specifically, the overall operation process of step S23 includes finding mass spectrometry peaks, peak alignment, noise reduction, and using the aligned results to perform image segmentation processing using K-Means. Among them, during the process of finding mass spectrometry peaks, 100 mass spectrometry peaks are found in each spectrogram with a step of 16 spectrograms; peak alignment is calculated using the average spectrum of the complete mass spectrometry imaging dataset. After segmentation processing, combine the tissue morphology spectrogram to identify and label multiple characteristic regions of the specimen, such as 6 microstructural regions including the vascular lumen area, myocardial area, vascular adventitial connective tissue area, atherosclerotic microcalcification area, atherosclerotic non-microcalcification area, and valve area, etc.

[0047] In one embodiment, imaging techniques such as a trained deep learning model can also be used for image segmentation. This deep learning model reflects the correspondence between spectral features and feature region annotations.

[0048] Step S130, perform metabolic analysis on multiple structural microregions related to aortic atherosclerosis.

[0049] For the analysis of metabolic heterogeneity of multiple structural microregions related to atherosclerosis, the metabolic space information provided by mass spectrometry spatial omics technology can be used to analyze the metabolic characteristics of multiple structural microregions (such as the vascular lumen area, myocardial area, vascular adventitial connective tissue area, atherosclerotic microcalcification area, atherosclerotic non-microcalcification area, and valve area, etc.).

[0050] In one embodiment, use probabilistic latent semantic analysis PLSA (Probabilistic latent semantic analysis, random initialization) to select 6 principal components for multivariate statistical analysis of spatial data, and select a 95% confidence interval for screening characteristic metabolic molecules under each principal component condition. It can be obtained that the characteristic metabolic molecules show significant spatial distribution differences in regions such as the atherosclerotic microcalcification area, non-microcalcification area, and vascular lumen area, that is, observe the spatial distribution heterogeneity of the characteristic structural microregions of the plaque specimen at the metabolic molecule level.

[0051] Correspondingly, the present invention further provides a spatial imaging system for atherosclerotic microcalcified regions, which is used to implement one or more aspects of the above method. For example, the system includes: an animal model construction module: used to construct an aortic microcalcified plaque model of a target animal; an image segmentation module: used to perform image segmentation of biological specimens for the aortic microcalcified plaque model, and in combination with tissue morphological characteristics, in-situ screen out multiple structural microregions based on metabolic characteristics, and the multiple structural microregions are related to atherosclerosis; a metabolic analysis module: used to perform metabolic heterogeneity analysis on the multiple structural microregions, and obtain heterogeneous spatial distributions through the screening of characteristic metabolic molecules.

[0052] To further verify the effect of the present invention, an experimental verification was carried out on a mouse aortic microcalcified plaque animal model. The experimental process was as follows: a mouse aortic microcalcified plaque model was established and dissected after 24 weeks of an atherogenic diet; after freezing embedding with OCT (optical coherence tomography) freezing embedding agent, serial sections were made with a cryostat, the section thickness was 5 μm, and the sections were adhered to conventional glass slides and ITO (indium tin oxide) coated glass slides and stored frozen at -80 °C; the conventional glass slide samples were subjected to hematoxylin-eosin staining and immunofluorescence detection of calcification-related proteins. After the above treatment, a mass spectrometry spatial omics experiment was carried out on the mouse aortic root microcalcified plaque specimens.

[0053] The specific experimental results are as follows:

[0054] 1) Select a mouse aortic microcalcified plaque animal model, and use the present invention to obtain the histopathological characteristics of the mouse aortic root microcalcified plaque tissue. It includes the vascular lumen surrounded by the aorta, the myocardial tissue at the connection between the aortic root and the heart, the connective tissue of the aortic adventitia, the atherosclerotic plaque in the vascular intima, etc. Figure 2 It shows that the region positive for immunofluorescence detection of calcification-related osteocalcin is the microcalcified region, the region negative for immunofluorescence detection is the non-calcified region, and the heart valve in the aortic vascular lumen.

[0055] 2) Select a mouse aortic microcalcified plaque animal model, and use the present invention to obtain the heterogeneous spatial distribution of multiple structural microregions of the mouse plaque specimens. Figure 3 It respectively shows the vascular lumen region, the myocardial region, the adventitial connective tissue region, the atherosclerotic-non-microcalcified region, the atherosclerotic microcalcified region, and the valve region.

[0056] 3) Select an animal model of aortic microcalcified plaque in mice. With the present invention, differential distributions of multiple metabolic molecules can be obtained in different characteristic regions. For example, compared with other characteristic regions, m / z193.079, 194.040, and 615.126 are upregulated in the microcalcified region of the mouse plaque specimen, m / z 210.933 is upregulated in the vascular lumen region, and m / z 885.412 is upregulated in the non-microcalcified region. See Figure 4 the principal component analysis diagram of the mass spectrometry spatial omics data of Figure 5 and the representative substance molecular spatial distribution diagram of

[0057] It should be noted that, without departing from the spirit and scope of the present invention, those skilled in the art can make appropriate changes or modifications to the above embodiments. For example, the present invention can be applied to the research on the occurrence and development of various diseases or tumors, early disease diagnosis, the development of targeted drugs, etc. In addition, the mass spectrometry spatial omics technology can use a variety of ion sources, including MALDI, DESI-MSI, and SIMS, etc., or it can be a combined mass spectrometry technology. For example, the mass spectrometry spatial omics technology can be combined with multi-omics methods based on mass spectrometry, mass cytometry technology, spatial transcriptomics, and epigenomics technology respectively, etc.

[0058] In summary, compared with the prior art, the present invention has the following advantages:

[0059] 1) The present invention describes a whole-process method that integrates the spatial information of substance molecules and tissue morphology information. Through tissue morphology analysis, accurate pathological annotations of biological specimens can be obtained. Moreover, considering that this method cannot comprehensively explain the molecular characteristics of multiple structural microregions at the substance level, as well as the spatiotemporal distribution heterogeneity of characteristic molecules during the disease development process and before and after drug treatment. More importantly, the spatiotemporal distribution heterogeneity of molecules is closely related to the occurrence and development of diseases and may serve as biomarkers for early disease diagnosis. Therefore, introducing the in-situ spatial distribution detection technology of molecules on the basis of tissue morphology research can greatly increase the application scope and value of related clinical analysis technologies. Based on this, the present invention further introduces the mass spectrometry spatial omics technology on the basis of tissue morphology analysis, fully combining the advantages of the two technologies, that is, the mass spectrometry spatial omics provides a full metabolic map of different structural partitions, and tissue morphology provides accurate pathological annotations of different structural partitions, and the two methods can be mutually verified after combination.

[0060] 2) Using the mass spectrometry spatial omics method developed by the present invention, it is observed at the metabolic molecule level that the plaque specimens of the animal model are composed of multiple characteristic structural microregions, and the microregion distribution has spatial heterogeneity. For example, the discovered structural microregions include the vascular lumen region, myocardial region, vascular adventitial connective tissue region, atherosclerotic microcalcified region, atherosclerotic non-microcalcified region, valve region, etc.

[0061] 3) The present invention broadens the application scope of mass spectrometry spatial omics technology and tissue morphology technology in the fields of clinical medicine and precision diagnosis; improves the coverage rate, detection accuracy and sensitivity of biomarkers in the research of cardiovascular and cerebrovascular diseases; and improves the flexibility of the detection and analysis method, and can combine tissue morphology and mass spectrometry spatial omics combined with tissue morphology experimental methods according to the different degrees of development of cardiovascular and cerebrovascular diseases, so as to meet the research of the disease development process and molecular mechanism.

[0062] The present invention may be a system, a method, and / or a computer program product. The computer program product may include a computer-readable storage medium having thereon computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0063] The computer-readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of the computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device such as a punched card or raised structures in grooves having instructions stored thereon, and any suitable combination of the foregoing. The computer-readable storage medium as used herein is not construed as a transitory signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated through a waveguide or other transmission medium (e.g., an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0064] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0065] The computer program instructions for performing the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine - related instructions, microcode, firmware instructions, state - setting data, or source code or object code written in any combination of one or more programming languages, including object - oriented programming languages such as Smalltalk, C++, Python, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer - readable program instructions may be executed entirely on the user's computer, partially on the user's computer, executed as a stand - alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via an Internet service provider through the Internet). In some embodiments, by using the state information of the computer - readable program instructions to customize an electronic circuit, such as a programmable logic circuit, a field - programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer - readable program instructions to implement various aspects of the present invention.

[0066] Aspects of the present invention are described herein with reference to the flowchart and / or block diagram of a method, apparatus (system), and computer program product according to embodiments of the present invention. It should be understood that each block of the flowchart and / or block diagram, and the combinations of blocks in the flowchart and / or block diagram, can be implemented by computer - readable program instructions.

[0067] These computer - readable program instructions can be provided to a processor of a general - purpose computer, a special - purpose computer, or other programmable data - processing apparatus to produce a machine such that when these instructions are executed by the processor of the computer or other programmable data - processing apparatus, a device is produced that implements the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer - readable program instructions can also be stored in a computer - readable storage medium, and these instructions cause the computer, programmable data - processing apparatus, and / or other devices to operate in a specific manner. Thus, the computer - readable medium storing the instructions includes a manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0068] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices, causing a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other devices to produce a computer-implemented process, such that the instructions executed on the computer, other programmable data processing apparatus, or other devices implement the functions / acts specified in one or more blocks of the flowchart and / or block diagram.

[0069] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block of the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or acts, or by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are equivalent.

[0070] The embodiments of the present invention have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the market, or to enable other ordinary skilled in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A method for spatial imaging of microcalcification areas of atherosclerosis, comprising the following steps: Constructing an aortic microcalcified plaque model of target animals; For the aortic microcalcified plaque model, image segmentation of biological specimens is performed, and multiple structural micro-regions are screened in situ based on metabolic characteristics in combination with tissue morphological characteristics, and the multiple structural micro-regions are related to atherosclerosis; Metabolic heterogeneity analysis is performed on the various structural microregions, and the spatial distribution of heterogeneity is obtained by screening characteristic metabolic molecules.

2. The method according to claim 1, characterized in that: The various structural micro-regions include a vascular cavity region, a myocardial region, a vascular adventitia connective tissue region, an atherosclerotic microcalcification region, an atherosclerotic non-microcalcification region, and a valve region.

3. The method according to claim 1, characterized in that: The mass spectrometry imaging data is segmented using a trained deep learning model, wherein the deep learning model reflects the correspondence between the features of the mass spectrometry imaging data and the structural micro-regions.

4. The method according to claim 1, characterized in that: The target animal is a mouse.

5. The method according to claim 4, characterized in that The aortic microcalcification plaque model of the target animal is obtained according to the following steps: Six-week-old ApoE- / - mice were fed a regular diet in an SPF environment for 1 week; ApoE- / - mice were fasted for 1 night; Replace your regular diet with an atherogenic diet; ApoE- / - mice were fed in an SPF environment for 24 weeks to obtain a mouse aortic microcalcification plaque model.

6. The method according to claim 1, characterized in that For the aorta microcalcified plaque model, performing image segmentation of the biological specimen includes: Using the aortic microcalcified plaque model, a plaque specimen is obtained, frozen sections of the specimen are collected after freezing, and the sections are transferred to a glass slide with an ITO coating, and then placed at -80°C for storage of the frozen sections; The frozen sections are subjected to a matrix spraying treatment, and a mass spectrometry imaging scanning experiment of a region of interest (ROI) is performed using a mass spectrometry imager under set imaging conditions to obtain a scanned image; The image segmentation of the biological specimen is performed on the scanned image, including: searching for mass spectrum peaks, searching for 100 mass spectrum peaks in each spectrum with 16 spectrum steps in the process of searching for mass spectrum peaks; peak alignment: peak alignment is performed using the average spectrum of the mass spectrum imaging data set; denoising the data after peak alignment to obtain denoised data; and performing image segmentation processing on the denoised data using K-Means.

7. The method according to claim 1, characterized in that The heterogeneous spatial distribution includes atherosclerotic microcalcification areas, non-microcalcification areas, and vascular cavity areas.

8. The method according to claim 1, characterized in that: A metabolic heterogeneity analysis is performed on the multiple structural micro-regions, and the heterogeneous spatial distribution is obtained by screening characteristic metabolic molecules, including: using probabilistic latent semantic analysis (PLSA) to select the multiple structural micro-regions as principal components for multivariate statistical analysis of spatial data, and selecting a set confidence interval under each principal component condition to screen characteristic metabolic molecules, and observing the spatial distribution heterogeneity of the characteristic structural micro-regions of the plaque specimens from the metabolic molecule level.

9. A spatial imaging system for microcalcification areas of atherosclerosis, comprising: Animal model construction module: used to construct an aortic microcalcification plaque model of the target animal; Image segmentation module: for performing image segmentation of biological specimens for the aortic microcalcified plaque model, and in situ screening out a variety of structural micro-regions based on metabolic characteristics in combination with tissue morphological characteristics, wherein the various structural micro-regions are related to atherosclerosis; Metabolic analysis module: used to perform metabolic heterogeneity analysis on the various structural micro-regions, and obtain the heterogeneous spatial distribution by screening characteristic metabolic molecules.

10. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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