A method, device and medium for metabolic flux analysis based on mass spectrometry imaging

Abstract

The application discloses a kind of metabolic flow analysis methods, equipment and medium based on mass spectrum imaging, it is related to mass spectrum imaging technical field, including, according to metabolic flow analysis constraint record judgment initial mass spectrum imaging acquisition record isotope envelope mass state, and carries out mass spectrum imaging compensation scanning, generates compensation mass spectrum imaging acquisition record, based on metabolic flow analysis constraint record correction compensation mass spectrum imaging acquisition record isotope peak group and carries out partition mapping processing, generates spatial isotope label matrix;According to spatial isotope label matrix and metabolic flow analysis constraint record, each metabolic flow partition is carried out metabolic flow solving and result tracing processing, determines the metabolic flow direction between each metabolic flow partition, relative metabolic flow support intensity and abnormal metabolic flow source, generates spatial metabolic flow tracing atlas.The application improves the accuracy of metabolic flow direction, intensity analysis and abnormal source traceability by cross-slice spatial consistency partition and peak group abnormal compensation tracing.

Description

Technical Field

[0001] This invention relates to the field of mass spectrometry imaging technology, and in particular to a method, device and medium for metabolic flux analysis based on mass spectrometry imaging. Background Technology

[0002] Mass spectrometry imaging technology can acquire metabolic charge ratio signals while maintaining the spatial location information of tissues. It has been gradually applied to research scenarios such as tumor metabolic heterogeneity, metabolic reprogramming in pathological regions, drug distribution evaluation, and tissue microenvironment analysis. Compared with conventional liquid chromatography-mass spectrometry detection, mass spectrometry imaging can correlate the intensity of metabolite response with the morphological region of tissue, expanding metabolic detection from the average level of the whole sample to the spatial partition level. With the development of stable isotope tracing, histological imaging registration, spatial transcriptome analysis, and high-resolution mass spectrometry acquisition technology, researchers have begun to try to introduce isotope peak group information into tissue section imaging analysis to observe substrate consumption, product generation, and spatial differences in metabolic pathways between different pathological regions, providing a new technical basis for inferring the direction and intensity of metabolic flow in biological tissues.

[0003] Existing methods still have certain shortcomings. Current mass spectrometry imaging metabolic analysis mainly focuses on the spatial display of metabolite abundance maps obtained from a single scan. It usually compares the peak intensity of the target metabolite based on the mass-to-charge ratio of the target metabolite between different tissue regions. It is difficult to unify and solidify the detection purpose, tracer sampling conditions, tissue preservation status, slice layer relationship, isotope peak range, and peak mass judgment boundary into the same analysis chain. Stable isotope peaks are easily affected by peak group missingness, mass deviation, discontinuous peak response, natural abundance background, isotopic interference, and additive peak interference during tissue mass spectrometry imaging. Existing processing methods mostly perform overall correction after acquisition, lacking compensation scans, peak group takeover, and anomaly source tracing mechanisms for specific acquired pixels and metabolic flow partitions. As a result, it is difficult to establish a traceable relationship between the determination results of metabolic flow direction and relative metabolic flow support strength and the original peak mass state. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a metabolic flow analysis method based on mass spectrometry imaging to solve the problems of difficulty in coordinating tracer conditions and spatial partitioning, as well as the lack of peak group quality traceability in metabolic flow results.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a metabolic flux analysis method based on mass spectrometry imaging, comprising: processing tracer condition configuration for metabolic flux analysis requirement data and sample attribute data of the biological tissue to be tested, determining the target metabolite and metabolic flux detection execution conditions, and generating a tracer sampling control record and a metabolic flux analysis constraint record; defining the sampling sequence and tissue state of the biological tissue to be tested according to the tracer sampling control record, and performing mass spectrometry imaging adaptation processing in conjunction with the metabolic flux analysis constraint record to generate a spatially faithful tissue slice group; dividing the metabolic flux into partitions by analyzing the spatial correspondence between the spatially faithful tissue slices in the spatially faithful tissue slice group, and generating a metabolic flux partition map; and collecting isotopes of the target metabolite under the constraints of the metabolic flux analysis constraint record. The isotope peak groups are identified and spatially bound to each metabolic flow partition in the metabolic flow partitioning map to generate an initial mass spectrometry imaging acquisition record. Based on the metabolic flow analysis constraint record, the isotope envelope mass state of the initial mass spectrometry imaging acquisition record is determined, and a mass spectrometry imaging compensation scan is performed to generate a compensated mass spectrometry imaging acquisition record. Based on the metabolic flow analysis constraint record, the isotope peak groups of the compensated mass spectrometry imaging acquisition record are corrected and partitioned, generating a spatial isotope label matrix. Based on the spatial isotope label matrix and the metabolic flow analysis constraint record, metabolic flow is solved and the results are traced for each metabolic flow partition to determine the metabolic flow direction, relative metabolic flow support strength, and sources of abnormal metabolic flow between each metabolic flow partition, generating a spatial metabolic flow traceability map.

[0008] As a preferred embodiment of the metabolic flux analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating tracer sampling control records and metabolic flux analysis constraint records are as follows:

[0009] By analyzing the detection purpose, pathological region type and metabolic changes to be observed in the biological tissue to be tested, the metabolic transformation pathways to be tracked and the corresponding range of imageable metabolites are determined, and a metabolic flow target record is generated.

[0010] Based on the metabolic flow target record, the sample attribute data is subjected to tracer imaging adaptation processing. Each imageable metabolite in the range of imageable metabolites is adapted to tissue type, tissue preservation status, slice thickness requirements, spatial resolution requirements and ionization response relationship to generate candidate tracer imaging configuration records.

[0011] The candidate tracer imaging configuration record is processed for imaging executability verification. Based on the isotope peak group acquisition status, sampling time sequence maintenance status and mass spectrometry imaging adaptation status of each imageable metabolite, the target metabolite and the corresponding metabolic flux detection execution conditions are determined, and the target tracer imaging configuration record is generated.

[0012] Based on the target tracer imaging configuration record, sampling and imaging constraint solidification processing is performed to obtain the sampling control parameters, imaging constraint parameters, isotope peak range and peak quality judgment boundary corresponding to the target metabolite, and solidify them into tracer sampling control record and metabolic flow analysis constraint record, respectively.

[0013] As a preferred embodiment of the metabolic flux analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating spatially accurate tissue slice groups are as follows:

[0014] The preparation path is arranged for tracer sampling control records and metabolic flux analysis constraint records. According to the sampling sequence, tissue state preservation requirements, slice position correspondence rules, imaging constraint parameters and isotope peak range, the sampling batch, continuous slice layer, layer numbering rules, histological imaging identifier, spatial expression acquisition identifier, mass spectrometry imaging acquisition identifier and mass spectrometry imaging preparation path of the biological tissue to be tested are determined, and a spatially faithful preparation path table is generated.

[0015] According to the spatial fidelity preparation path table, the biological tissue to be tested is processed by layer-association sectioning. Continuous tissue sections from the same sampling batch are configured with histological imaging labels, spatial expression acquisition labels and mass spectrometry imaging acquisition labels according to the layer numbering rules, and layer correspondence is established to generate spatial fidelity tissue section groups.

[0016] As a preferred embodiment of the metabolic flux analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating the metabolic flux partition map are as follows:

[0017] Acquire histological images of spatially fidelity tissue sections with histological imaging markers, and extract the outer boundary of the tissue, the boundary of the pathological region, and the layer reference points from the histological images to generate a tissue spatial reference image;

[0018] Based on the layer correspondence between spatially fidelity tissue slices, spatially fidelity tissue slices with spatial representation acquisition markers and spatially fidelity tissue slices with mass spectrometry imaging acquisition markers are registered to the tissue spatial reference, generating a cross-slice spatial correspondence table.

[0019] Spatial consistency is checked on the cross-slice spatial correspondence table. Metabolic flow partitions are divided according to the offset of the layer reference point, the degree of overlap of tissue boundaries and the offset of the pathological area boundaries. Partition numbers and spatial boundaries are configured to generate a metabolic flow partition map.

[0020] As a preferred embodiment of the metabolic flux analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating the initial mass spectrometry imaging acquisition record are as follows:

[0021] Based on the metabolic flux partition map and metabolic flux analysis constraint records, the spatial boundaries of each metabolic flux partition are converted into mass spectrometry imaging acquisition coordinates, and the isotope peak group ranges corresponding to the target metabolites are matched to the mass spectrometry imaging acquisition coordinates to generate a partition acquisition coordinate table.

[0022] According to the partition acquisition coordinate table, the spatially fidelity tissue slices with mass spectrometry imaging acquisition marks are initially scanned by mass spectrometry imaging. The isotope peak group signals corresponding to the target metabolites are acquired at each mass spectrometry imaging acquisition coordinate, and the acquisition coordinates, scanning order, detection polarity and peak group response status are recorded to generate the initial pixel spectrum record.

[0023] The initial pixel spectrum record is processed by pixel partitioning and binding based on the metabolic flow partition map. The acquired pixels corresponding to each acquisition coordinate are assigned to the corresponding metabolic flow partition. The corresponding relationship between the acquired pixels, partition number, isotope peak group signal and peak group response state is established to generate the initial mass spectrometry imaging acquisition record.

[0024] As a preferred embodiment of the metabolic flux analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating compensated mass spectrometry imaging acquisition records are as follows:

[0025] Based on the isotope peak range and peak mass determination boundary in the metabolic flow analysis constraint record, the envelope state of the isotope peak signal in the initial mass spectrometry imaging acquisition record is identified, and the peak missing state, mass deviation state and peak response continuity state corresponding to each acquisition pixel are determined to generate an isotope envelope quality state record.

[0026] Based on the partition numbers in the isotope envelope mass state record and the initial mass spectrometry imaging acquisition record, the acquisition pixels that do not meet the peak group quality judgment boundary in at least one of the peak group missing state, mass deviation state, and peak group response continuity state are located, and merged according to the acquisition coordinate adjacency relationship within the same metabolic flow partition to generate a compensated acquisition area record.

[0027] Based on the imaging constraint parameters in the compensated acquisition area record and the metabolic flow analysis constraint record, the compensated scan sequence, compensated acquisition coordinates, detection polarity and peak group acquisition index are configured for the compensated acquisition area, and a compensated scan task record is generated.

[0028] Mass spectrometry imaging compensation scanning is performed on spatially faithful tissue sections with mass spectrometry imaging acquisition markers according to the compensation scanning task record. The compensation isotope peak group signals corresponding to the target metabolites in the compensation acquisition area are acquired, and the correspondence between the compensation isotope peak group signals and the corresponding pre-compensation isotope peak group signals, acquisition pixels and partition numbers are established to generate a compensation mass spectrometry imaging acquisition record.

[0029] As a preferred embodiment of the metabolic flux analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating the spatial isotope labeling matrix are as follows:

[0030] The compensation mapping relationship, compensation source type, compensation acquisition pixel, pre-compensation peak group signal and post-compensation peak group signal in the compensation mass spectrometry imaging acquisition record are statistically analyzed. The effective isotope peak group is located according to the compensation mapping relationship and the peak group quality judgment boundary in the metabolic flow analysis constraint record, and the post-compensation peak group takeover record is generated.

[0031] Based on the isotope peak group range and imaging constraint parameters in the metabolic flux analysis constraint record, the effective isotope peak groups in the compensated peak group takeover record are corrected for natural abundance, excluded for isotope interference, and merged for peaks to generate a corrected isotope peak group record.

[0032] Based on the acquisition pixel position and partition number in the corrected isotope peak group record, the corrected isotope peak group is mapped to the corresponding metabolic flow partition, and the corrected peak group signals in the same metabolic flow partition are partitioned and aggregated to generate a spatial isotope label matrix.

[0033] As a preferred embodiment of the metabolic flow analysis method based on mass spectrometry imaging described in this invention, the specific steps for generating a spatial metabolic flow tracing map are as follows:

[0034] Based on the spatial isotope labeling matrix, the target metabolites, isotope peak intensity, peak mass status and compensated acquisition status corresponding to each metabolic flux partition are extracted, and the extraction results are correlated with the metabolic transformation paths to be tracked in the metabolic flux analysis constraint record to generate partition labeling path records.

[0035] The partitioned marked path records are subjected to inter-regional metabolic transformation comparison processing. Based on the isotope peak group intensity changes, upstream and downstream correspondence of target metabolites, and peak group quality status between adjacent metabolic flow partitions, the metabolic flow direction and relative metabolic flow support strength between adjacent metabolic flow partitions are determined, and partitioned metabolic flow edge records are generated.

[0036] Anomaly source tracing processing is performed on the partitioned metabolic flow edge records. Partitioned metabolic flow edges with abnormal metabolic flow direction, abnormal changes in relative metabolic flow support strength, and inconsistent upstream and downstream labels are matched with the corresponding compensated acquisition status, peak group quality status, and metabolic transformation path to be tracked to determine the source of abnormal metabolic flow and generate abnormal metabolic flow tracing records.

[0037] Based on the partitioned path records, partitioned metabolic flow edge records, and abnormal metabolic flow tracing records, a graph-based association process is performed to establish graph relationships between metabolic flow partitions, target metabolites, metabolic flow directions, relative metabolic flow support strength, abnormal metabolic flow sources, and quality tracing information, thereby generating a spatial metabolic flow tracing graph.

[0038] In a second aspect, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein the computer program, when executed by the processor, implements any step of the metabolic flux analysis method based on mass spectrometry imaging as described in the first aspect of the present invention.

[0039] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the metabolic flux analysis method based on mass spectrometry imaging as described in the first aspect of the present invention.

[0040] The beneficial effects of this invention are as follows: By achieving consistent zoning across slice space, it realizes unified constraints on histological, spatial expression, and mass spectrometry imaging positions, giving the metabolic flow analysis area a clear layered origin and pathological boundary, thereby improving the accuracy of spatial zoning and the reliability of metabolic flow direction determination; by peak group anomaly compensation and tracing, it realizes the location, compensation, takeover, and correction of isotope peak group missingness, quality deviation, and response discontinuity, enabling the calculation of relative metabolic flow support strength to be associated with peak group quality status, thereby improving the accuracy of metabolic flow direction and relative metabolic flow support strength determination results and the traceability of anomaly sources. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of a metabolic flux analysis method based on mass spectrometry imaging.

[0043] Figure 2 Generate graphs for tracer sampling control records and metabolic flux analysis constraint records.

[0044] Figure 3 Generate maps for metabolic flux partitioning and initial mass spectrometry imaging acquisition records.

[0045] Figure 4 Generate maps for spatial isotope labeling matrices and spatial metabolic flow tracing maps. Detailed Implementation

[0046] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0047] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0048] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0049] Reference Figures 1-4 This is one embodiment of the present invention, which provides a metabolic flux analysis method based on mass spectrometry imaging, including the following steps:

[0050] S1. Perform tracer condition configuration processing on the metabolic flux analysis requirements data and sample attribute data of the biological tissue to be tested, determine the target metabolites and metabolic flux detection execution conditions, and generate tracer sampling control records and metabolic flux analysis constraint records.

[0051] S1.1 By analyzing the detection purpose, pathological region type, and metabolic changes to be observed in the biological tissue to be tested, the metabolic transformation pathway to be tracked and the corresponding range of imageable metabolites are determined, and a metabolic flow target record is generated.

[0052] It should be noted that the data required for metabolic flux analysis is formed from the information entered in the detection task, the initial pathological screening information, and the research protocol information. It records the detection purpose, sample grouping identifier, target spatial resolution, pathological region type, pathological region coordinates, pathological region boundary, metabolic changes to be observed, candidate metabolic node list, and candidate node connection relationship. The candidate metabolic node list records the candidate metabolic node name, node type, molecular formula, adduct type, and labelable element field. The candidate node connection relationship records the upstream node, downstream node, and node connection order.

[0053] Sample attribute data is formed from sample registration information, tissue preservation records, slide pre-examination information, and pre-acquisition mass spectrometry information. It records tissue type, tissue preservation status, tissue condition maintenance requirements, expected slide thickness, tissue fragility, risk areas of slide detachment, tissue morphology reference points, ionization response reference information, and matrix interference status. The ionization response reference information records the resolvable mass-to-charge ratio peaks and corresponding ion patterns corresponding to candidate metabolic nodes.

[0054] When identifying targets for metabolic flux analysis data, candidate metabolic nodes whose node type matches the metabolic node type in the observed metabolic change and whose change direction corresponds to the observed metabolic change are identified as change-related nodes. Candidate metabolic transformation paths are then generated along the upstream and downstream nodes of these change-related nodes. A candidate metabolic transformation path containing change-related nodes, and where these nodes are connected to at least one upstream node and at least one downstream node, is retained as a valid candidate path. If multiple valid candidate paths exist, the metabolic transformation path to be tracked is determined in the following order: the fewest number of nodes traversed, the presence of both a start and end node, the smallest node connection sequence number of the start node in the candidate node connection relationship, and the smallest generation sequence number corresponding to the path identifier. The generation sequence number corresponding to the path identifier is generated according to the order in which the candidate metabolic transformation paths were generated. If no valid candidate path exists, a path verification mark is generated, and the determination of the imageable metabolite range under the corresponding detection objective is stopped.

[0055] Substrate nodes, intermediate metabolite nodes, and product nodes in the metabolic transformation pathway to be tracked are designated as metabolites to be screened. If the molecular formula of the metabolite to be screened contains the elements recorded in the labelable element field, the theoretical isotope peak group contains both unlabeled and labeled peaks, the pre-acquired mass spectrometry information contains a corresponding resolvable mass-to-charge ratio peak, and the corresponding resolvable mass-to-charge ratio peak does not overlap with the matrix peaks in the matrix interference state record, the corresponding metabolite to be screened is written into the imageable metabolite range. Metabolites to be screened that do not meet the conditions are not written into the imageable metabolite range, and the reason for not writing is recorded.

[0056] Establish a correspondence between the detection purpose, pathological region type, target spatial resolution, pathological region coordinates, metabolic changes to be observed, metabolic transformation pathways to be tracked, range of imageable metabolites, pathway verification markers, and reasons for not being written, and generate a metabolic flow target record.

[0057] S1.2. Based on the metabolic flow target record, perform tracer imaging adaptation processing on the sample attribute data, and adapt each imageable metabolite in the imageable metabolite range to the tissue type, tissue preservation status, slice thickness requirements, spatial resolution requirements and ionization response relationship to generate candidate tracer imaging configuration records.

[0058] It should be noted that when performing tracer imaging adaptation processing on sample attribute data based on metabolic flow target records, candidate adaptation entries are established for each imageable metabolite in the imageable metabolite range. Each candidate adaptation entry inherits the traceable metabolic transformation pathway, imageable metabolite name, molecular formula, adduct type, labelable element field, and target spatial resolution, and calls the tissue type, tissue preservation status, tissue state retention requirements, expected slice thickness, tissue fragility, detachment risk area, ionization response reference information, and matrix interference status from the sample attribute data.

[0059] Sampling and adaptation processing is performed on candidate adaptation entries: the sampling window is determined based on tissue type, tissue preservation status, and tissue preservation requirements; the slice numbering rules, slice position correspondence rules, and slice bearing requirements are determined based on expected slice thickness, tissue fragility, risk areas of detachment, and target spatial resolution; the slice position correspondence rules record the allowable interval between adjacent slices, the selection method of slice reference points, and the slice correspondence method between histological imaging markers, spatial expression acquisition markers, and mass spectrometry imaging acquisition markers.

[0060] When determining the allowable interval between adjacent slices, the slice numbers corresponding to histological imaging identifiers, spatial expression acquisition identifiers, and mass spectrometry imaging acquisition identifiers are obtained according to the slice numbering rules. The slice number difference between any two corresponding slices is calculated, and the product of the slice number difference and the expected slice thickness is taken as the actual physical interval. The upper limit of the allowable slice number difference is obtained from the research protocol information, the allowable range of tissue boundary deformation and the allowable range of pathological region boundary deformation are obtained from the slice pre-examination information, and the resolvable scale of the partition boundary is obtained from the target spatial resolution. The physical interval corresponding to the upper limit of the allowable slice number difference and the tissue... The registerable layer intervals corresponding to the allowable range of outer boundary deformation, the registerable layer intervals corresponding to the allowable range of pathological region boundary deformation, and the distinguishable layer intervals corresponding to the resolvable scale of the partition boundary are compared, and the layer interval with the smallest value is taken as the allowable interval between adjacent layers. If the actual physical interval of the layer does not exceed the allowable interval between adjacent layers, and the deformation records of the tissue outer boundary and the deformation records of the pathological region boundary between the corresponding slices are both within their respective allowable ranges, the corresponding slices are written into the same layer correspondence relationship. Otherwise, the corresponding candidate adaptation entry is marked as layer parameter pending verification, and the corresponding layer correspondence relationship is not generated.

[0061] When the tissue's brittle state corresponds to the area of ​​risk of detachment, a load-bearing enhancement mark is generated; when the tissue preservation state does not meet the tissue preservation requirements, or when the sampling window is inconsistent with the tissue preservation requirements, a sampling timing verification mark is generated; thus, candidate sampling control parameters are generated.

[0062] Imaging adaptation processing is performed on candidate matching entries: The candidate acquisition coordinate spacing is determined based on the target spatial resolution and expected slice thickness. Using the imageable metabolite name, molecular formula, and adduct type as search fields, the resolvable mass-to-charge ratio peaks and corresponding ion modes for the same imageable metabolite and adduct type are retrieved from the ionization response reference information. When the corresponding ion mode is a positive ion mode, the candidate detection polarity is set to positive; when the corresponding ion mode is a negative ion mode, the candidate detection polarity is set to negative. When the same imageable metabolite has resolvable mass-to-charge ratio peaks in both positive and negative ion modes, the ion mode with a larger number of resolvable mass-to-charge ratio peaks is preferentially selected. When the number of resolvable mass-to-charge ratio peaks corresponding to the two ion modes is the same, the ion mode with fewer peaks overlapping with the matrix peaks is selected. When the number of resolvable mass-to-charge ratio peaks and the number of overlapping peaks corresponding to the two ion modes are the same, the ion mode recorded earlier in the ionization response reference information is selected. The candidate detection polarity is set to the polarity corresponding to the selected ion mode.

[0063] Under candidate detection polarity, the resolvable mass-to-charge ratio peaks corresponding to the same imageable metabolite and the same adduct type are written into the candidate mass-to-charge ratio peaks; when the candidate mass-to-charge ratio peaks overlap with matrix peaks in the matrix interference state, the corresponding candidate mass-to-charge ratio peaks are excluded, and the matrix interference exclusion result is recorded; when the candidate mass-to-charge ratio peaks do not overlap with matrix peaks, the corresponding candidate mass-to-charge ratio peaks are retained; the candidate isotope peak group range is determined based on the labelable element field and the retained candidate mass-to-charge ratio peaks; the candidate mass-to-charge ratio peaks record the imageable metabolite identifier, adduct type, corresponding candidate detection polarity, and the correspondence between the resolvable mass-to-charge ratio peaks and the ionization response reference information; when there are no resolvable mass-to-charge ratio peaks in the ionization response reference information, or when all candidate mass-to-charge ratio peaks are excluded, an imaging response verification marker is generated.

[0064] Establish a correspondence between candidate sampling control parameters, candidate imaging constraint parameters, candidate isotope peak ranges and adaptation markers to generate candidate tracer imaging configuration records; the adaptation markers include load enhancement markers, sampling timing verification markers, imaging response verification markers and matrix interference exclusion results.

[0065] S1.3 Perform imaging executability verification processing on the candidate tracer imaging configuration record. Based on the isotope peak group acquisition status, sampling time sequence maintenance status and mass spectrometry imaging adaptation status corresponding to each imageable metabolite, determine the target metabolite and the corresponding metabolic flux detection execution conditions, and generate the target tracer imaging configuration record.

[0066] It should be noted that when performing imaging executability verification processing on candidate tracer imaging configuration records, the collectability status of isotope peak groups is determined based on the range of candidate isotope peak groups, candidate mass-to-charge ratio peaks, and matrix interference elimination results. If both unlabeled and labeled peaks within the range of candidate isotope peak groups have corresponding candidate mass-to-charge ratio peaks, and the matrix interference elimination results show no overlap, the peaks are marked as collectable; otherwise, they are marked as uncollectible.

[0067] The sampling timing can be maintained based on the sampling window, tissue state maintenance requirements and sampling timing verification flag in the candidate sampling control parameters. If the sampling window and tissue state maintenance requirements are complete and there is no sampling timing verification flag, it is marked as maintainable; otherwise, it is marked as pending verification.

[0068] The mass spectrometry imaging adaptation status is determined based on the candidate acquisition coordinate spacing, candidate detection polarity, candidate mass-to-charge ratio peak, and imaging response verification marker in the candidate imaging constraint parameters. If the candidate acquisition coordinate spacing can correspond to the target spatial resolution, the candidate mass-to-charge ratio peaks are all located within the acquisition mode corresponding to the candidate detection polarity, and there is no imaging response verification marker, it is marked as adapted; otherwise, it is marked as pending verification.

[0069] Imageable metabolites whose isotope peaks are in an acquireable state, whose sampling time sequence is maintainable, and whose mass spectrometry imaging is compatible are identified as target metabolites; imageable metabolites that are in an unacquireable state or a state pending verification are not included in the target metabolites, and the reason for not being selected is retained.

[0070] For each target metabolite, the corresponding candidate sampling control parameters, candidate imaging constraint parameters, and candidate isotope peak ranges are determined as sampling control parameters, imaging constraint parameters, and isotope peak ranges, respectively. The candidate detection polarity in the candidate imaging constraint parameters is determined as the detection polarity, and the candidate acquisition coordinate spacing is determined as the acquisition coordinate spacing, and these are written into the imaging constraint parameters corresponding to the target metabolite. Peak group quality judgment boundaries are generated based on the candidate isotope peak ranges, candidate mass-to-charge ratio peaks, and candidate acquisition coordinate spacing. The peak group quality judgment boundaries include peak group missing judgment boundaries, quality deviation judgment boundaries, peak group response continuity judgment boundaries, and matrix interference exclusion boundaries.

[0071] When generating peak group quality judgment boundaries, the candidate isotope peak group range, candidate mass-to-charge ratio peak, candidate detection polarity, candidate acquisition coordinate spacing, pre-acquisition mass spectrometry information, and matrix interference exclusion results are used as boundary source fields, and the correspondence between boundary source fields is established according to the target metabolite identifier.

[0072] The peak group missing determination boundary consists of the list of peaks to be collected, the correspondence between candidate mass-to-charge ratio peaks, and the correspondence between resolvable mass-to-charge ratio peaks: Unlabeled and labeled peaks corresponding to the target metabolites in the candidate isotope peak group range are written into the list of peaks to be collected, and each peak to be collected in the list is matched with a candidate mass-to-charge ratio peak according to the candidate detection polarity; when each peak to be collected has a corresponding candidate mass-to-charge ratio peak, and the corresponding candidate mass-to-charge ratio peak can be matched with a resolvable mass-to-charge ratio peak in the pre-collected mass spectrometry information, the peak group missing determination boundary outputs a non-missing condition; when there is a peak to be collected that does not correspond to a candidate mass-to-charge ratio peak, or when the corresponding candidate mass-to-charge ratio peak does not correspond to a resolvable mass-to-charge ratio peak in the pre-collected mass spectrometry information, the peak group missing determination boundary outputs a missing condition.

[0073] The quality deviation judgment boundary is composed of the correspondence between candidate mass-to-charge ratio peaks and the correspondence between pre-acquired peak positions: the candidate mass-to-charge ratio peaks are matched with the resolvable mass-to-charge ratio peaks of the same target metabolite and the same candidate detection polarity in the pre-acquired mass spectrometry information; when the candidate mass-to-charge ratio peaks can establish a peak position correspondence with the resolvable mass-to-charge ratio peaks, the quality deviation judgment boundary outputs the deviation qualification condition; when the candidate mass-to-charge ratio peaks fail to establish a peak position correspondence with the resolvable mass-to-charge ratio peaks, the quality deviation judgment boundary outputs the deviation abnormal condition.

[0074] The peak group response continuity determination boundary is composed of adjacent acquisition location groups, the correspondence between candidate mass-to-charge ratio peaks, and the correspondence between collectable states: adjacent acquisition location groups are generated within the same metabolic flow partition according to the candidate acquisition coordinate spacing, and the collectable states of the same target metabolite and the same candidate mass-to-charge ratio peak corresponding to each acquisition location in the adjacent acquisition location group are matched; when each acquisition location in the adjacent acquisition location group has the same target metabolite and the same candidate mass-to-charge ratio peak collectable state, the peak group response continuity determination boundary outputs the response continuity condition; when there are acquisition locations in the adjacent acquisition location group that have not formed a corresponding collectable state, the peak group response continuity determination boundary outputs the response discontinuity condition.

[0075] The matrix interference exclusion boundary is formed by the overlap state between the candidate mass-to-charge ratio peak and the matrix peak: the overlap state between the candidate mass-to-charge ratio peak and the matrix peak is called in the matrix interference exclusion result, and the correspondence between the overlap states is established according to the candidate mass-to-charge ratio peak; when the candidate mass-to-charge ratio peak does not overlap with the matrix peak, the matrix interference exclusion boundary outputs the matrix interference excluded condition; when the candidate mass-to-charge ratio peak overlaps with the matrix peak, the matrix interference exclusion boundary outputs the matrix interference not excluded condition.

[0076] If any of the peak group missing judgment boundary, quality deviation judgment boundary, peak group response continuity judgment boundary, and matrix interference exclusion boundary lacks a boundary source field, or if any boundary cannot form a corresponding relationship, the corresponding target metabolite will be marked as a peak group boundary pending verification.

[0077] Establish a correspondence between the target metabolite, sampling control parameters, imaging constraint parameters, isotope peak range, peak quality judgment boundary, metabolic transformation pathway to be tracked, and reasons for not being selected, and generate a target tracing imaging configuration record.

[0078] S1.4. Based on the target tracer imaging configuration record, perform sampling and imaging constraint solidification processing to obtain the sampling control parameters, imaging constraint parameters, isotope peak range and peak quality judgment boundary corresponding to the target metabolite, and solidify them into tracer sampling control record and metabolic flow analysis constraint record, respectively.

[0079] It should be noted that when sampling and imaging constraint solidification processing is performed on the target tracer imaging configuration record, the integrity of the sampling control parameters, imaging constraint parameters, isotope peak range, and peak quality judgment boundary corresponding to the target metabolite is verified: the boundary source field, boundary correspondence, and peak boundary pending verification status in the peak quality judgment boundary are verified; if any of the following conditions are met, such as missing boundary source field, inability to form boundary correspondence, or pending verification status of peak boundary, the target metabolite lacking any field is marked as having an unclosed constraint status, and the reason for the unclosed constraint is recorded.

[0080] Sampling constraints are solidified for target metabolites that have passed integrity verification. The sampling control parameters are correlated with the metabolic transformation pathways to be tracked, and a tracer sampling control record is generated. The tracer sampling control record records the target metabolite identifier, sampling window, tissue state maintenance requirements, slice location correspondence rules, and layer numbering rules.

[0081] For target metabolites that have passed integrity verification, imaging constraints are solidified. Correspondence is established between imaging constraint parameters, isotope peak range, peak quality judgment boundary, molecular formula, adduct type, detection polarity, labelable element field and metabolic transformation pathway to be tracked, and metabolic flow analysis constraint records are generated.

[0082] S2. According to the tracer sampling control record, the sampling time sequence and tissue state of the biological tissue to be tested are limited, and the mass spectrometry imaging adaptation process is performed in combination with the metabolic flow analysis constraint record to generate a spatially faithful tissue slice group. By analyzing the spatial correspondence between each spatially faithful tissue slice in the spatially faithful tissue slice group, metabolic flow partitions are divided to generate a metabolic flow partition map.

[0083] S2.1. The preparation path is arranged and processed for the tracer sampling control record and metabolic flow analysis constraint record. According to the sampling sequence, tissue state preservation requirements, slice position correspondence rules, imaging constraint parameters and isotope peak range, the sampling batch, continuous slice layer, layer numbering rules, histological imaging identifier, spatial expression acquisition identifier, mass spectrometry imaging acquisition identifier and mass spectrometry imaging preparation path of the biological tissue to be tested are determined, and a spatially faithful preparation path table is generated.

[0084] It should be noted that the sampling window, tissue state preservation requirements, slice position correspondence rules, and layer numbering rules in the tracer sampling control record are correlated with the target metabolite identifier, imaging constraint parameters, isotope peak range, and metabolic transformation pathway to be tracked in the metabolic flow analysis constraint record to form candidate path entries for the spatially faithful preparation path table.

[0085] In the candidate path entries, tissue samples obtained within the same sampling window and whose tissue states are consistent are grouped into the same sampling batch; the continuous slice layers are determined according to the slice position correspondence rules and the layer numbering rules, and histological imaging identifiers, spatial expression acquisition identifiers and mass spectrometry imaging acquisition identifiers are configured for the continuous slice layers.

[0086] The mass spectrometry imaging preparation path is determined based on imaging constraint parameters and isotope peak ranges. The mass spectrometry imaging preparation path records the slice layer corresponding to the mass spectrometry imaging acquisition identifier, target metabolite identifier, detection polarity, isotope peak range, and mass spectrometry imaging preparation requirements. These requirements define the slice bearing, reaction processing, and matrix coverage for the corresponding spatially accurate tissue slices. If the sampling window, slice numbering rules, and imaging constraint parameters cannot be simultaneously satisfied, a preparation path verification mark is assigned to the corresponding sampling batch.

[0087] Establish a correspondence between sampling batches, continuous slice layers, layer numbering rules, three types of acquisition identifiers, mass spectrometry imaging preparation paths, and preparation path verification marks to generate a spatially accurate preparation path table.

[0088] S2.2. Perform layer-linked sectioning of the biological tissue to be tested according to the spatial fidelity preparation path table. Configure histological imaging identifiers, spatial expression acquisition identifiers and mass spectrometry imaging acquisition identifiers for continuous tissue sections from the same sampling batch according to the layer numbering rules, and establish layer correspondence to generate spatial fidelity tissue section groups.

[0089] It should be noted that when performing layer-linked sectioning of the biological tissue to be tested according to the spatial fidelity preparation path table, sampling batches with preparation path verification marks will not be included in the layer-linked sectioning process; for sampling batches without preparation path verification marks, layer numbers will be assigned to continuous tissue sections under the same sampling batch according to the continuous section layer and layer numbering rules, and the order of adjacent layers will be determined.

[0090] According to the histological imaging identifier, spatial expression acquisition identifier, and mass spectrometry imaging acquisition identifier in the spatial fidelity preparation path table, corresponding acquisition identifiers are configured for continuous tissue sections. Continuous tissue sections with mass spectrometry imaging acquisition identifiers are bound to the corresponding mass spectrometry imaging preparation path, and the section mounting, reaction processing, and matrix coverage are completed according to the mass spectrometry imaging preparation requirements in the mass spectrometry imaging preparation path. Continuous tissue sections with spatial expression acquisition identifiers are bound to the corresponding expression acquisition objects, where the expression acquisition objects are determined by the metabolic enzyme expression objects and transport protein expression objects corresponding to the target metabolites in the metabolic transformation pathway to be tracked, which are used to form the upstream and downstream path node expression constraints of each metabolic flux partition. Continuous tissue sections with completed layer numbering and acquisition identifier configurations are determined as spatial fidelity tissue sections, and the mass spectrometry imaging preparation path is only written to spatial fidelity tissue sections with mass spectrometry imaging acquisition identifiers.

[0091] Using spatially fidelity tissue slices with histological imaging markers as torsional reference slices, to establish torsional correspondences between spatially fidelity tissue slices with spatial expression acquisition markers and spatially fidelity tissue slices with mass spectrometry imaging acquisition markers in adjacent layers and torsional reference slices; to group all spatially fidelity tissue slices that have completed the torsional correspondences in the same sampling batch into the same slice set, generating spatially fidelity tissue slice groups.

[0092] S2.3 Acquire histological images of spatially fidelity tissue sections with histological imaging markers, and extract the outer boundary of the tissue, the boundary of the pathological region, and the layer reference points from the histological images to generate a tissue spatial reference image.

[0093] It should be noted that corresponding sections are selected according to the sampling batch, layer number, and histological imaging identifier in the spatial fidelity tissue section group. Histological images with layer numbers are obtained by histological staining and full-section scanning, and the histological image coordinate system is established to correspond with the sampling batch, layer number, and acquisition identifier.

[0094] Extract the tissue outer boundary, pathological region boundary, and stratum reference point from histological images. The tissue outer boundary is determined by the boundary between the stained tissue area and the background area. When multiple discontinuous tissue areas exist, the continuous tissue area with the highest area ratio and corresponding to the same stratum number is determined as the main tissue area, and the remaining discontinuous tissue areas are recorded as boundary interference areas. Boundary interference areas are not included in the determination of the tissue outer boundary.

[0095] The pathological region boundary is obtained by projecting the pathological region type and coordinates from the initial pathological screening information onto the histological image coordinate system and then correcting it. When the projected region exceeds the outer boundary of the tissue, the pathological region boundary is cropped according to the outer boundary of the tissue, and the boundary correction mark is recorded. The pathological region boundary after boundary correction is entered into the subsequent pathological region boundary offset verification.

[0096] The morphological reference points in the pre-examination information of the slides should be used as the priority for the stratification reference points. If there are fewer than three non-collinear morphological reference points that can be located, supplementary stratification reference points should be selected from the outer boundary of the tissue and the boundary of the pathological area. If there are still fewer than three non-collinear points, the spatial reference status should be recorded as pending review.

[0097] Write the histological image coordinate system, tissue outer boundary, pathological region boundary, layer reference point, layer number, sampling batch, boundary interference area, boundary correction mark, and spatial reference pending review status into the tissue spatial reference.

[0098] S2.4 Based on the layer correspondence between spatially fidelity tissue slices, register spatially fidelity tissue slices with spatial expression acquisition markers and spatially fidelity tissue slices with mass spectrometry imaging acquisition markers to the tissue spatial reference, and generate a cross-slice spatial correspondence table.

[0099] It should be noted that when performing cross-slice registration based on the layer correspondence between spatially fidelity tissue slices, the tissue spatial reference corresponding to the spatially fidelity tissue slice with histological imaging identifier is used as the reference reference, and spatially fidelity tissue slices with spatial expression acquisition identifier and spatially fidelity tissue slices with mass spectrometry imaging acquisition identifier with layer correspondence are identified in the same sampling batch.

[0100] Pre-acquisition localization scanning was performed on spatially fidelity tissue sections with spatial expression acquisition markers. Corresponding metabolic enzyme expression signals and transporter protein expression signals were acquired according to the expression acquisition target, resulting in a spatial expression acquisition location map recording the coordinates of the spatial expression acquisition point, the outer boundary of the section, the boundary of the expression acquisition area, and the expression states of metabolic enzymes and transporters. Pre-acquisition optical preview was performed on spatially fidelity tissue sections with mass spectrometry imaging acquisition markers, resulting in a pre-acquisition location map recording the boundary of the area to be scanned for mass spectrometry imaging, the preset scanning coordinate range, and the outer boundary of the section.

[0101] The spatial representation acquisition location map and the mass spectrometry imaging pre-acquisition location map are registered to the tissue spatial reference map respectively to obtain the first spatial mapping relationship and the second spatial mapping relationship. When registering, the layer reference point is used first. When there are fewer than three non-collinear points of the layer reference point, the common boundary features of the outer boundary of the slice and the boundary of the pathological area are used for supplementary registration. The supplementary registration result is directly incorporated into the first spatial mapping relationship and the second spatial mapping relationship.

[0102] Based on the first spatial mapping relationship and the second spatial mapping relationship, the spatial expression acquisition location, the mass spectrometry imaging scan location, and the histological image coordinates are unified into the tissue spatial reference, generating a cross-slice spatial correspondence table.

[0103] S2.5 Perform spatial consistency verification on the cross-slice spatial correspondence table, divide the metabolic flow partitions according to the offset of the layer reference point, the degree of overlap of the tissue boundary and the offset of the pathological area boundary, configure the partition number and spatial boundary, and generate a metabolic flow partition map.

[0104] It should be noted that when performing spatial consistency verification on the cross-slice spatial correspondence table, the first spatial mapping relationship, the second spatial mapping relationship, the spatial expression acquisition location map, the mass spectrometry imaging pre-acquisition location map, the tissue spatial reference map, and the slice location correspondence rules are called to verify the offset of the layer reference point, the overlap of tissue boundaries, and the offset of the pathological region boundaries.

[0105] Based on the hierarchical correspondence between the three types of acquisition identifiers, spatially fidelity tissue slices participating in the same spatial verification are determined; when the hierarchical interval does not meet the allowable interval between adjacent hierarchical segments, the hierarchical segment pending verification status is recorded; when the corresponding candidate adaptation entry is configured with a hierarchical parameter pending verification status, the spatial expression acquisition position and the mass spectrometry imaging scanning position under the corresponding hierarchical number do not enter the effective spatial corresponding area, and the hierarchical parameter pending verification status is written into the partition exclusion reason.

[0106] Based on the method of selecting layer reference points, determine the same-name layer reference points and the same-order layer reference points. Transform the layer reference points in the spatial representation acquisition location map and the mass spectrometry imaging pre-acquisition location map to the histological image coordinate system, and calculate the offset relative to the corresponding layer reference points in the tissue spatial reference map. When there is no corresponding relationship between the same-name layer reference points and no corresponding relationship between the same-order layer reference points, record the reference point pending verification status.

[0107] The outer boundaries of the slices in the spatial representation acquisition location map and the mass spectrometry imaging pre-acquisition location map are transformed to the histological image coordinate system and compared with the tissue outer boundary. The area covered by the three is determined as the candidate consistent region, and the part of the recording boundary that does not enter the candidate consistent region is marked as removed.

[0108] The boundaries of the acquisition area and the mass spectrometry imaging area to be scanned are transformed into the histological image coordinate system and compared with the boundaries of the pathological area. Areas located within the candidate consistent area and having spatial intersection with the boundaries of the pathological area are identified as valid spatial corresponding areas, while the parts that do not form spatial intersection are recorded as pathological boundaries and excluded.

[0109] The collectable range of a partition is determined by the overlapping area within the effective space corresponding to the spatial expression acquisition coordinates and the mass spectrometry imaging pre-acquisition coordinates. Metabolic flow partitions are generated according to the pathological region type. The collectable range of a partition that spans multiple pathological region types is divided according to the pathological region boundaries. Regions that do not simultaneously cover the spatial expression acquisition coordinates and the mass spectrometry imaging pre-acquisition coordinates are not generated into metabolic flow partitions, and the reasons for partition exclusion are recorded.

[0110] For each generated metabolic flow partition, the expression status of metabolic enzymes and transport proteins corresponding to the spatial expression acquisition coordinates within that partition are retrieved, and a correspondence is established between the expression acquisition objects and the upstream and downstream target metabolites in the metabolic transformation pathway to be tracked. When the expression acquisition object can correspond to both the upstream and downstream target metabolites, the corresponding metabolic flow partition is marked as a node expression constraint support state. When the expression acquisition object cannot correspond to both the upstream and downstream target metabolites, the corresponding metabolic flow partition is marked as a node expression constraint pending verification state.

[0111] Write the partition number, sampling batch, layer number, pathological region type, histological image spatial boundary, spatial expression acquisition boundary, mass spectrometry imaging acquisition boundary, metabolic enzyme expression status, transport protein expression status, node expression constraint status, layer pending verification status, reference point pending verification status, boundary removal marker, pathological boundary exclusion marker, and partition exclusion reason into the metabolic flow partition map.

[0112] S3. Under the constraints of metabolic flux analysis, collect isotope peak group signals of the target metabolites and establish spatial binding relationships with each metabolic flux partition in the metabolic flux partitioning map to generate the initial mass spectrometry imaging acquisition record.

[0113] S3.1 Based on the metabolic flux partition map and metabolic flux analysis constraint records, convert the spatial boundaries of each metabolic flux partition into mass spectrometry imaging acquisition coordinates, and match the isotope peak range corresponding to the target metabolite to the mass spectrometry imaging acquisition coordinates to generate a partition acquisition coordinate table.

[0114] It should be noted that when generating the zoning acquisition coordinate table based on the metabolic flow zoning map and metabolic flow analysis constraint records, for metabolic flow zoning with any of the following conditions: tomographic verification status, reference point verification status, boundary removal marker, and pathological boundary exclusion marker, mass spectrometry imaging acquisition coordinate transformation is not performed, and the corresponding reason for coordinate transformation exclusion is written into the zoning acquisition coordinate table; for metabolic flow zoning without corresponding status and marker, the mass spectrometry imaging acquisition area is determined according to the mass spectrometry imaging acquisition boundary, and a mass spectrometry imaging acquisition coordinate sequence is generated according to the acquisition coordinate spacing and detection polarity in the imaging constraint parameters; when the mass spectrometry imaging acquisition coordinates fall into the overlapping area of ​​the boundaries of two metabolic flow zoning ...

[0115] Based on the target metabolites and isotope peak ranges in the metabolic flow analysis constraint record, configure peak group acquisition indexes for mass spectrometry imaging acquisition coordinates; when the same mass spectrometry imaging acquisition coordinates correspond to multiple target metabolites, configure peak group acquisition indexes according to the order of the target metabolites in the metabolic flow analysis constraint record.

[0116] Write the partition number, layer number, pathological region type, mass spectrometry imaging acquisition boundary, mass spectrometry imaging acquisition coordinates, acquisition coordinate order, target metabolite identifier, peak group acquisition index, detection polarity, boundary assignment marker, and coordinate transformation exclusion reason into the partition acquisition coordinate table.

[0117] S3.2. Perform initial mass spectrometry imaging scans on spatially fidelity tissue slices marked with mass spectrometry imaging acquisition markers according to the partition acquisition coordinate table. Acquire isotope peak group signals corresponding to target metabolites at each mass spectrometry imaging acquisition coordinate, and record the acquisition coordinates, scanning order, detection polarity and peak group response status to generate initial pixel spectrum records.

[0118] It should be noted that, in the spatial fidelity tissue slice group, spatial fidelity tissue slices with consistent layer numbers and mass spectrometry imaging acquisition identifiers are selected as the slices to be scanned, and the mass spectrometry imaging acquisition coordinates in the partition acquisition coordinate table are mapped to the mass spectrometry imaging scanning coordinate system of the slice to be scanned; when the mass spectrometry imaging acquisition coordinates exceed the mass spectrometry imaging acquisition boundary recorded in the partition acquisition coordinate table, a coordinate anomaly mark is configured for the corresponding acquisition coordinates.

[0119] For mass spectrometry imaging acquisition coordinates without configured coordinate anomaly markers, an initial mass spectrometry imaging scan is performed according to the acquisition coordinate order, detection polarity, and peak group acquisition index. Isotope peak group signals corresponding to the target metabolite are acquired, and the original spectra and scan order are recorded. Peak group response status is generated based on the correspondence between isotope peak group signals and peak group acquisition indexes. When no corresponding peak signal is acquired, it is recorded as peak group non-response status; when a correspondence can be established, it is recorded as peak group responded status; when coordinate anomaly markers are present, it is recorded as coordinate anomaly response status.

[0120] Write the mass spectrometry imaging acquisition coordinates, partition number, target metabolite identifier, detection polarity, peak group acquisition index, raw spectrum, isotope peak group signal, peak group response status, and coordinate anomaly marker into the initial pixel spectrum record.

[0121] S3.3. Perform pixel partitioning and binding processing on the initial pixel spectrum record according to the metabolic flow partitioning map, assign the acquired pixels corresponding to each acquisition coordinate to the corresponding metabolic flow partition, and establish a correspondence between the acquired pixels, partition number, isotope peak group signal and peak group response state to generate the initial mass spectrometry imaging acquisition record.

[0122] It should be noted that when performing pixel partitioning and binding processing on the initial pixel spectrum record based on the metabolic flow partition map, the scan point corresponding to the mass spectrometry imaging acquisition coordinate without any coordinate anomaly markers is determined as the acquisition pixel, and the position of the acquisition pixel is compared with the mass spectrometry imaging acquisition boundary in the metabolic flow partition map.

[0123] When the location of a acquired pixel falls within the mass spectrometry imaging acquisition boundary of a metabolic flow partition, the acquired pixel is assigned to the corresponding metabolic flow partition; when the location of an acquired pixel falls within the overlapping area of ​​the boundaries of two metabolic flow partitions, the corresponding metabolic flow partition is determined according to the boundary assignment mark in the initial pixel spectrum record; when the location of an acquired pixel does not fall within the mass spectrometry imaging acquisition boundary of any metabolic flow partition, an unassigned pixel mark is generated.

[0124] Write the acquired pixel, mass spectrometry imaging acquisition coordinates, partition number, target metabolite identifier, isotope peak group signal, peak group response status, original spectrum, coordinate anomaly marker, and pixel unassigned marker into the initial mass spectrometry imaging acquisition record; when the same acquired pixel corresponds to multiple target metabolites, record the isotope peak group signal according to the target metabolite identifier.

[0125] S4. Determine the isotopic envelope mass state of the initial mass spectrometry imaging acquisition record based on the metabolic flow analysis constraint record, perform mass spectrometry imaging compensation scan, generate compensated mass spectrometry imaging acquisition record, correct the isotopic peak group of the compensated mass spectrometry imaging acquisition record based on the metabolic flow analysis constraint record, perform partition mapping processing, and generate a spatial isotopic label matrix.

[0126] S4.1 Based on the isotope peak range and peak mass determination boundary in the metabolic flow analysis constraint record, identify the envelope state of the isotope peak signal in the initial mass spectrometry imaging acquisition record, determine the peak missing state, mass deviation state and peak response continuity state corresponding to each acquisition pixel, and generate an isotope envelope mass state record.

[0127] It should be noted that the envelope state identification of the isotope peak group signals in the initial mass spectrometry imaging acquisition record is performed as follows: the unlabeled peaks, labeled peaks, and candidate mass-to-charge ratio peaks in the isotope peak group range are matched with the isotope peak group signals in the initial mass spectrometry imaging acquisition record to determine the peak group missing state; the measured positions of the candidate mass-to-charge ratio peaks in the original spectrum are compared with the corresponding candidate mass-to-charge ratio peak positions in the isotope peak group range to determine the mass deviation state; according to the adjacency relationship of the acquisition coordinates of adjacent acquisition pixels in the same metabolic flux partition, the peak group response state of the same target metabolite in adjacent acquisition pixels is compared to determine the peak group response continuity state.

[0128] When both unlabeled and labeled peaks can be correlated in the original spectrum of the same acquired pixel, the peak group missing status is marked as not missing; if this condition is not met, the peak group missing status is marked as missing, and the missing peak type is recorded. When the measured position of the candidate mass-to-charge ratio peak meets the mass deviation judgment boundary, the mass deviation status is marked as acceptable; if this condition is not met, the mass deviation status is marked as abnormal, and the abnormal peak position is recorded. When the peak group response status between adjacent acquired pixels meets the peak group response continuity judgment boundary, the peak group response continuity status is marked as continuous; if this condition is not met, the peak group response continuity status is marked as discontinuous, and the discontinuous acquired pixel position is recorded.

[0129] The acquired pixels, partition numbers, target metabolite identifiers, isotope peak ranges, peak missing status, quality deviation status, peak response continuity status, and corresponding abnormal positions are written into the isotope envelope quality status record.

[0130] S4.2 Based on the partition number in the isotope envelope mass state record and the initial mass spectrometry imaging acquisition record, locate the acquisition pixels that do not meet the peak group quality judgment boundary in at least one of the peak group missing state, mass deviation state and peak group response continuity state, and merge them according to the acquisition coordinate adjacency relationship within the same metabolic flow partition to generate a compensated acquisition area record.

[0131] It should be noted that when locating the compensated acquisition area based on the isotope envelope mass state record and the initial mass spectrometry imaging acquisition record, a compensation trigger determination is performed for each acquired pixel: when the peak group missing state is not missing, the mass deviation state is within acceptable deviation, and the peak group response continuity state is continuous, the corresponding acquired pixel is marked as a pixel that does not need compensation; when there is an abnormal state among the peak group missing state, mass deviation state, and peak group response continuity state, the corresponding acquired pixel is marked as a pixel to be compensated, and the state type, target metabolite identifier, partition number, and layer number that trigger compensation are recorded.

[0132] Pixels to be compensated are grouped according to the same partition number, and the adjacency relationship of the acquisition coordinates is established according to the mass spectrometry imaging acquisition coordinates and the order of acquisition coordinates. Pixels to be compensated with the same partition number and continuous acquisition coordinates are merged into the same compensation candidate region, and pixels to be compensated with discontinuous acquisition coordinates form different compensation candidate regions respectively. Acquisition pixels with coordinate anomaly markers and unassigned pixel markers are not included in the merging, and the reasons for exclusion are recorded.

[0133] The boundary of the compensation region is determined based on the mass spectrometry imaging acquisition coordinates of the pixels to be compensated within the compensation candidate region. When there is no pixel gap that does not need to be compensated between adjacent compensation candidate regions within the same metabolic flow partition, they are merged into the same compensation acquisition region. When there is a pixel gap that does not need to be compensated, compensation region numbers are configured separately.

[0134] Write the compensation area number, partition number, layer number, target metabolite identifier, pixel to be compensated, mass spectrometry imaging acquisition coordinates, state type of compensation trigger, compensation area boundary, and reason for exclusion into the compensation acquisition area record.

[0135] S4.3 Based on the imaging constraint parameters in the compensated acquisition area record and the metabolic flow analysis constraint record, configure the compensated scan sequence, compensated acquisition coordinates, detection polarity and peak group acquisition index for the compensated acquisition area, and generate the compensated scan task record.

[0136] It should be noted that when generating the compensation scan task record based on the compensation acquisition area record and the metabolic flux analysis constraint record, the compensation scan order is configured according to the partition number, compensation area number, and acquisition coordinate order; when there are multiple compensation acquisition areas within the same metabolic flux partition, the compensation scan priority is determined according to the order of peak group missing, quality deviation, and peak group response continuity status as discontinuous.

[0137] The mass spectrometry imaging acquisition coordinates corresponding to the pixel to be compensated in the compensation acquisition area record are determined as the basic compensation acquisition coordinates. When the state type of the triggered compensation is continuous peak group response or discontinuous state, the acquisition coordinates that are adjacent to the acquisition coordinates of the pixel to be compensated within the same compensation area boundary are incorporated into the basic compensation acquisition coordinates to form the compensation acquisition coordinates. When the compensation acquisition coordinates exceed the compensation area boundary, they are not written into the compensation scan task record, and the reason for coordinate exclusion is recorded.

[0138] When configuring compensation sources for compensation acquisition coordinates, the acquisition pixels that have already undergone initial scanning in the initial mass spectrometry imaging acquisition record are marked as scanned and occupied positions. If there are acquisition coordinates adjacent to the pixel to be compensated within the boundary of the same compensation area that are not marked as scanned and occupied positions, the corresponding acquisition coordinates are determined as adjacent unoccupied compensation coordinates. If there are no adjacent unoccupied compensation coordinates, the mass spectrometry imaging acquisition coordinates on the spatial fidelity tissue slices with mass spectrometry imaging acquisition markers in consecutive adjacent layers are determined as layer-corresponding compensation coordinates based on the layer-level correspondence in the spatial fidelity tissue slice group. If neither adjacent unoccupied compensation coordinates nor layer-corresponding compensation coordinates can be formed, the corresponding pixel to be compensated is marked as a compensation source pending verification state and is not written into the compensation scan task record.

[0139] The detection polarity is determined according to the imaging constraint parameters corresponding to the target metabolite in the metabolic flow analysis constraint record; when there are multiple detection polarities in the same compensated acquisition area, compensated scanning subtasks are generated according to the detection polarity; the peak group acquisition index is configured according to the state type of the triggered compensation: peak group missing corresponds to the missing peak and the adjacent labeled peak in the same isotope peak group, mass deviation corresponds to the candidate mass-to-charge ratio peak corresponding to the abnormal peak position, and peak group response continuity state is discontinuous, corresponding to the complete isotope peak group of the target metabolite.

[0140] Write the compensation area number, partition number, layer number, target metabolite identifier, compensation scan order, compensation acquisition coordinates, compensation source type, detection polarity, peak group acquisition index, compensation trigger status type, compensation source pending verification status, and coordinate exclusion reason into the compensation scan task record.

[0141] S4.4. Perform mass spectrometry imaging compensation scanning on the spatially faithful tissue slices with mass spectrometry imaging acquisition markers according to the compensation scanning task record, acquire the compensation isotope peak group signals corresponding to the target metabolites in the compensation acquisition area, and establish a correspondence between the compensation isotope peak group signals and the corresponding pre-compensation isotope peak group signals, acquisition pixels and partition numbers to generate a compensation mass spectrometry imaging acquisition record.

[0142] It should be noted that when performing mass spectrometry imaging compensation scanning according to the compensation scanning task record, the spatial fidelity tissue slice with the same layer number and bearing the mass spectrometry imaging acquisition mark is selected as the compensation scanning object from the spatial fidelity tissue slice group based on the layer number in the compensation scanning task record; when the compensation source type is adjacent unoccupied compensation coordinates, the compensation scanning object is the spatial fidelity tissue slice with the mass spectrometry imaging acquisition mark under the current layer; when the compensation source type is layer-corresponding compensation coordinates, the compensation scanning object is the spatial fidelity tissue slice with the mass spectrometry imaging acquisition mark within consecutive adjacent layers and establishing a layer correspondence with the pixel to be compensated.

[0143] The compensated acquisition coordinates are mapped to the mass spectrometry imaging coordinate system of the compensated scan object according to the compensated scan sequence, and the compensated isotope peak group signal corresponding to the target metabolite is acquired according to the detection polarity and peak group acquisition index. The compensated acquisition coordinates with coordinate exclusion reasons and compensation source pending verification are not compensated acquisitions. When the compensated acquisition coordinate is a scanned and occupied position, the compensated acquisition is not performed, and the scanned and occupied position is written into the coordinate exclusion reason.

[0144] Based on the compensation source type in the compensation scan task record, a compensation mapping relationship is established between the compensation acquisition coordinates and the pixels to be compensated. When the compensation source type is adjacent unoccupied compensation coordinates, a compensation mapping relationship is established between the adjacent unoccupied compensation coordinates and the corresponding pixels to be compensated within the same compensation area. When the compensation source type is layer-corresponding compensation coordinates, a compensation mapping relationship is established between the layer-corresponding compensation coordinates and the pixels to be compensated under the layer-corresponding relationship. Based on the compensation mapping relationship, target metabolite identifier, and partition number, the pre-compensation isotope peak group signal corresponding to the pixels to be compensated is extracted from the initial mass spectrometry imaging acquisition record. The pre-compensation isotope peak group signal is kept in its original recording state, and the compensation mapping relationship, the pre-compensation isotope peak group signal, and the post-compensation isotope peak group signal are written into the compensation mass spectrometry imaging acquisition record.

[0145] S4.5 Statistically compensate the compensation mapping relationship, compensation source type, compensation acquisition pixel, pre-compensation peak group signal and post-compensation peak group signal in the compensated mass spectrometry imaging acquisition record, and locate the effective isotope peak group according to the compensation mapping relationship and the peak group quality judgment boundary in the metabolic flow analysis constraint record, and generate the post-compensation peak group takeover record.

[0146] It should be noted that when performing peak group takeover processing on compensated mass spectrometry imaging acquisition records, the pixel to be compensated corresponding to the compensated isotope peak group signal is determined according to the compensation mapping relationship, and the pixel to be compensated, the compensation source type, the isotope peak group signal before compensation, and the compensated isotope peak group signal after compensation are established as a peak group object in the same group. If the compensation mapping relationship is missing, or the compensated isotope peak group signal cannot be mapped to the pixel to be compensated, the corresponding compensated acquisition pixel is marked as a mapping pending verification state, and the reason for the mapping pending verification is recorded. The compensated isotope peak group signal in the same group object is mapped to the isotope peak group range in the metabolic flow analysis constraint record, and is verified according to the peak group quality judgment boundary. When the compensated isotope peak group signal meets the peak group missing judgment boundary, the quality deviation judgment boundary, the peak group response continuity judgment boundary, and the matrix interference exclusion boundary, it is marked as a valid isotope peak group. If any judgment boundary is not met, it is marked as a compensation not takenover state, and the reason for not takingover is recorded.

[0147] Based on the peak group missing state, quality deviation state, and peak group response continuity state in the isotope envelope quality state record corresponding to the pixels to be compensated in the same peak group object, the anomaly type of the isotope peak group signal before compensation is determined: when the isotope peak group signal before compensation has an anomaly type and the isotope peak group signal after compensation is a valid isotope peak group, the isotope peak group signal after compensation is determined as the takeover peak group; when both the isotope peak group signal before compensation and the isotope peak group signal after compensation meet the peak group quality judgment boundary, the isotope peak group signal before compensation is determined as the original peak group, and the isotope peak group signal after compensation is determined as the original peak group. The peak groups are recorded as compensation verification peak groups. At the same time, the judgment states of the original peak groups and the compensation verification peak groups are compared item by item under the peak group missing judgment boundary, quality deviation judgment boundary, peak group response continuity judgment boundary, and matrix interference exclusion boundary. When all four judgment states are consistent, a compensation verification consistent state is generated. When any judgment state is inconsistent, a compensation verification inconsistent state is generated, and the corresponding pixel to be compensated is marked as the peak group to be verified state. When the compensated isotope peak group signal does not take over and the isotope peak group signal before compensation still has abnormal types, the corresponding pixel to be compensated is marked as the peak group to be verified state.

[0148] Quality traceability information is generated based on the peak group to be taken over, the original peak group, the compensation verification peak group, the compensation verification consistency status, the compensation verification inconsistency status, the compensation not taken over status, the mapping pending verification status, the peak group pending verification status, and the reason for not being taken over. The pixel position to be compensated, the compensation acquisition coordinates, the compensation mapping relationship, the compensation source type, the partition number, the layer number, the target metabolite identifier, the original peak group, the peak group to be taken over, the compensation verification verification consistency status, the compensation verification inconsistency status, the compensation not taken over status, the mapping pending verification status, the reason for the mapping pending verification, the peak group pending verification status, the reason for not being taken over, and the quality traceability information are written into the peak group takeover record after compensation.

[0149] S4.6. Based on the isotope peak group range and imaging constraint parameters in the metabolic flux analysis constraint record, perform natural abundance correction, isotope interference elimination and peak merging processing on the effective isotope peak groups in the compensated peak group takeover record to generate a corrected isotope peak group record.

[0150] It should be noted that, based on the isotope peak group range, imaging constraint parameters, molecular formula, and labelable element fields in the metabolic flux analysis constraint record, the takeover peak group and the original peak group in the compensated peak group takeover record are corrected. If either the compensated but not takenover state or the peak group awaiting verification state exists, the corresponding acquired pixel is not included in this correction process, and the reason for not correcting is recorded; for acquired pixels with a takeover peak group, the takeover peak group is used as the peak group to be corrected; for acquired pixels with an original peak group that meets the peak group quality judgment boundary, the original peak group is used as the peak group to be corrected.

[0151] When performing natural abundance correction on the peak group to be corrected, the peak order relationship between unlabeled peaks, labeled peaks, and candidate mass-to-charge ratio peaks is determined according to the isotope peak group range, and the natural abundance background contribution is deducted based on the molecular formula and labelable element field; peak positions with negative peak intensity after deduction are marked as natural abundance correction anomalies, and the corrected peak intensity of the corresponding peak position is determined as a zero value occupant, while keeping the original peak intensity and original mass-to-charge ratio position unchanged; when performing isotope interference exclusion, overlapping peak positions between different target metabolites within the same acquisition pixel are identified according to the detection polarity and candidate mass-to-charge ratio peaks; peak positions whose source can be distinguished by adjacent peak order relationship are retained, and peak positions whose source cannot be distinguished are marked as isotope interference peaks and excluded from the correction peak group of the corresponding target metabolite; when performing addendum peak merging processing, addendum peaks in the candidate mass-to-charge ratio peaks that can be attributed are merged under the same target metabolite identifier, and addendum peaks that cannot establish a peak position order correspondence with the isotope peak group range are recorded as the reason for addendum peak exclusion.

[0152] The collected pixel location, partition number, layer number, target metabolite identifier, corrected isotope peak group, reason for uncorrection, abnormal natural abundance correction, isotope interference peaks, reasons for exclusion of addition peaks, and quality traceability information are written into the corrected isotope peak group record.

[0153] S4.7 Based on the acquisition pixel position and partition number in the corrected isotope peak group record, the corrected isotope peak group is mapped to the corresponding metabolic flow partition, and the corrected peak group signals in the same metabolic flow partition are partitioned and aggregated to generate a spatial isotope label matrix.

[0154] It should be noted that the partition mapping process is based on the corrected isotope peak group records: the acquired pixels in the isotope envelope quality state record whose peak group missing state is not missing, whose quality deviation state is qualified, and whose peak group response continuity state is continuous are determined as pixels that do not need compensation; the isotope peak group signals that meet the peak group quality judgment boundary in the initial mass spectrometry imaging acquisition records are used as the initial qualified peak groups to participate in the partition mapping, and the corresponding compensation acquisition state is recorded as non-triggered compensation.

[0155] For pixels with a corrected isotope peak group, the corrected isotope peak group is used for partition mapping. When the corrected isotope peak group originates from the takeover peak group, the corresponding compensated acquisition state is recorded as compensated takeover. When the corrected isotope peak group originates from the original peak group and the corresponding acquired pixel has a compensated verification peak group, the corresponding compensated acquisition state is recorded as compensated verification. For pixels with a compensated but not takenover state, the corresponding compensated acquisition state is recorded as compensated but not takenover.

[0156] Initial qualified peak groups and corrected isotope peak groups are mapped to corresponding metabolic flux partitions according to the acquired pixel location and partition number. When a boundary assignment marker exists at the acquired pixel location, the metabolic flux partition to which it belongs is determined according to the boundary assignment marker. If an acquired pixel location does not correspond to any metabolic flux partition, partition aggregation is not performed, and the reason for non-mapping is recorded. For peak group signals belonging to the same target metabolite within the same metabolic flux partition and for which no reason for non-mapping is recorded, partition aggregation is performed: Acquired pixels with usable peak group quality status and no reason for non-mapping within the corresponding metabolic flux partition are determined as valid acquired pixels; the intensity of peak group signals corresponding to the same target metabolite in each valid acquired pixel is summarized to obtain the partition peak group summary intensity; the partition peak group summary intensity is normalized according to the number of valid acquired pixels to obtain the corresponding isotope peak group intensity.

[0157] The initial qualified peak groups and corrected isotope peak groups participating in the isotope peak group intensity aggregation are marked as usable in terms of their corresponding peak group quality status. If any of the following reasons exist, such as uncorrected reasons, abnormal natural abundance correction, isotope interference peaks, reasons for exclusion of adduct peaks, or reasons for unmapping, the peak groups will not participate in the isotope peak group intensity aggregation, and the corresponding peak group quality status will be marked as pending verification. If the number of effective acquired pixels is zero, the corresponding isotope peak group intensity will not be generated, and the corresponding metabolic flux partition and target metabolite will be marked as partition intensity pending verification status.

[0158] Based on the results of the zoning aggregation, a correspondence is established between the metabolic flow zoning, target metabolites, isotope peak group intensity, number of effective acquisition pixels, zoning peak group aggregated intensity, zoning intensity pending verification status, peak group quality status, compensated acquisition status, and quality traceability information, and a spatial isotope labeling matrix is ​​generated.

[0159] S5. Based on the spatial isotope labeling matrix and metabolic flow analysis constraint records, perform metabolic flow solution and result tracing processing for each metabolic flow partition, determine the metabolic flow direction, relative metabolic flow support strength and abnormal metabolic flow source between each metabolic flow partition, and generate a spatial metabolic flow tracing map.

[0160] S5.1 Based on the spatial isotope labeling matrix, extract the target metabolites, isotope peak intensity, peak mass status and compensation acquisition status corresponding to each metabolic flux partition, and establish a correspondence between the extraction results and the metabolic transformation paths to be tracked in the metabolic flux analysis constraint record to generate partition labeling path records.

[0161] It should be noted that the target metabolite identifier in the spatial isotope labeling matrix is ​​matched with the metabolic transformation path to be tracked in the metabolic flow analysis constraint record; when the target metabolite identifier corresponds to any of the start node, intermediate node, or end node in the metabolic transformation path to be tracked, the target metabolite is written to the corresponding node position, and the path identifier and node connection order are recorded; when it cannot correspond to any node position, the target metabolite is marked as a path mismatch state, and the corresponding metabolic flow partition, isotope peak group intensity, and peak group quality status are retained.

[0162] The target metabolites that have completed path matching are labeled and their status is organized as follows: if the peak group quality status is available, and the compensation acquisition status is any of the following: compensation not triggered, compensation takeover, or compensation verification, and there is no partition intensity pending verification status, the corresponding isotope peak group intensity is determined as the partition label intensity; if the peak group quality status is pending verification, or the compensation acquisition status is compensation not takenover, the corresponding isotope peak group intensity is labeled as a low confidence label intensity, and the reason for the low confidence is recorded.

[0163] Write the metabolic flow partition, target metabolite, path identifier, node connection order, partition marker strength, number of effective acquired pixels, partition strength pending verification status, peak group quality status, compensated acquisition status, quality traceability information, path mismatch status, and low confidence reason into the partition marker path record.

[0164] S5.2 Perform inter-regional metabolic transformation comparison processing on the partitioned marked path records. Based on the isotope peak group intensity changes, upstream and downstream correspondence of target metabolites, and peak group quality status between adjacent metabolic flow partitions, determine the metabolic flow direction and relative metabolic flow support strength between adjacent metabolic flow partitions, and generate partitioned metabolic flow edge records.

[0165] It should be noted that when performing interval metabolic transformation comparison processing on the partitioned marked path records, adjacent metabolic flow partitions are determined according to the spatial boundaries in the metabolic flow partition map; two metabolic flow partitions are determined to be adjacent metabolic flow partitions when they share a boundary or their spatial boundaries are continuously connected within the same pathological region type; metabolic flow partitions that do not form a shared boundary and do not form a continuous connection relationship are not included in this interval metabolic transformation comparison processing.

[0166] For each group of adjacent metabolic flow partitions, the partition label intensity of the upstream node target metabolite and the downstream node target metabolite is extracted according to the same path identifier and the same node connection order. If any target metabolite of the upstream node target metabolite or the downstream node target metabolite under the same path identifier is missing, the corresponding partition alignment entry is marked as an incomplete path node state, and the metabolic flow direction determination of the corresponding partition alignment entry is stopped.

[0167] The first metabolic flow partition pointing to the second metabolic flow partition is taken as the first candidate direction, and the second metabolic flow partition pointing to the first metabolic flow partition is taken as the second candidate direction. The support values ​​of the first candidate direction and the second candidate direction are calculated according to the support value expression of the candidate direction, respectively. When the support value of the candidate direction cannot be calculated, the corresponding candidate direction is marked as a state where the support item cannot be calculated.

[0168] The metabolic flow support values ​​for the first candidate direction and the second candidate direction are compared: if the metabolic flow support value for the first candidate direction is greater than that for the second candidate direction, and the metabolic flow support value for the first candidate direction is greater than zero, the metabolic flow direction is determined to be from the candidate starting point of the first candidate direction to the candidate ending point of the first candidate direction, and the metabolic flow support value for the first candidate direction is determined as the relative metabolic flow support strength; if the metabolic flow support value for the second candidate direction is greater than that for the first candidate direction, and the metabolic flow support value for the second candidate direction is greater than zero, the metabolic flow direction is determined to be from the candidate starting point of the second candidate direction to the candidate ending point of the second candidate direction, and the metabolic flow support value for the second candidate direction is determined as the relative metabolic flow support strength.

[0169] In any of the following situations, the corresponding partition alignment entry will be marked as a direction pending verification, and no relative metabolic flow support strength will be generated: the metabolic flow support values ​​of both candidate directions are not greater than zero; the metabolic flow support values ​​of both candidate directions are equal; the metabolic flow support value of any candidate direction is not generated because the denominator is zero; the metabolic flow support values ​​of the two candidate directions cannot form a strict size relationship; the upstream support term and the downstream support term in any candidate direction have opposite signs.

[0170] In the partitioned alignment entries where the direction of metabolic flow has been determined but the direction is not marked for verification, if the peak group quality status of the upstream and downstream target metabolites involved in determining the relative metabolic flow support strength is available and the corresponding compensation acquisition status is not compensation not taken over, the corresponding relative metabolic flow support strength is retained; if any of the following situations exist, such as peak group quality status being pending verification, compensation acquisition status being compensation not taken over, or low confidence reason, the determined relative metabolic flow support strength is marked as low confidence support strength.

[0171] Write the first metabolic flow partition, the second metabolic flow partition, the path identifier, the node connection order, the candidate direction metabolic flow support value, the metabolic flow direction, the relative metabolic flow support strength, the incomplete status of the path node, the direction pending verification status, the low confidence support strength, and the quality traceability information into the partition metabolic flow edge record.

[0172] The expression for calculating the support value of candidate directional metabolic flow is:

[0173] ;

[0174] in, Indicates the first The metabolic flux partition points to the first Support values ​​for candidate directional metabolic flows in each metabolic flow partition. Indicates the first Target metabolites in upstream nodes of each metabolic flux partition The strength of the partition marker, Indicates the first Target metabolites in upstream nodes of each metabolic flux partition The strength of the partition marker, Indicates the first Target metabolites in downstream nodes of each metabolic flow partition The strength of the partition marker, Indicates the first Target metabolites in downstream nodes of each metabolic flow partition The strength of the partition marker.

[0175] It should also be noted that the first term in the formula is the upstream support term, used to characterize the upstream node target metabolite in the [missing term]. The metabolic flux partition is relative to the first The label retention relation of each metabolic flux partition; the second term of the formula is the downstream support term, used to characterize the target metabolite of the downstream node in the first... The metabolic flux partition is relative to the first The label enhancement relationship of each metabolic flux partition; since the numerator and denominator of the first and second terms of the formula are both composed of the partition label intensity, the calculation result of a single term is a dimensionless ratio, and the candidate directional metabolic flux support value is a dimensionless directional support result.

[0176] When the denominator of the first term in the formula is zero, the upstream support term is not calculated; when the denominator of the second term in the formula is zero, the downstream support term is not calculated; when any support term cannot be calculated, the corresponding candidate direction metabolic flux support value is not generated, and the corresponding partition alignment entry is marked as direction pending verification; the relative metabolic flux support strength is used to characterize the degree of relative directional support between adjacent metabolic flux partitions based on the upstream and downstream label distribution relationship, and does not represent the absolute metabolic flux per unit time.

[0177] S5.3 Perform abnormal source tracing processing on the partitioned metabolic flow edge records. Match the partitioned metabolic flow edges with abnormal metabolic flow direction, abnormal changes in relative metabolic flow support strength, and inconsistent upstream and downstream labels with the corresponding compensated acquisition status, peak group quality status, and metabolic transformation path to be tracked to determine the source of abnormal metabolic flow and generate abnormal metabolic flow tracing records.

[0178] It should be noted that when performing anomaly source tracing processing on the side records of the partitioned metabolic flow, the anomaly type is generated based on the direction of the metabolic flow, the relative support strength of the metabolic flow, the strength of the upstream and downstream node markers, the peak group quality status, the compensation acquisition status, and the metabolic transformation path to be traced.

[0179] When a metabolic flow edge in a region has a direction pending verification, or when the determined metabolic flow direction does not correspond to the node connection order in the metabolic transformation path to be tracked, it is marked as an abnormal metabolic flow direction. When the relative metabolic flow support strength is low confidence support strength, the corresponding metabolic flow edge in the region is marked as having low confidence relative metabolic flow support strength. When there are two metabolic flow edges in the same path identifier with consecutive node connection order and consecutive spatial boundaries, the two metabolic flow edges in the region are determined as adjacent metabolic flow edges. The first adjacent edge is determined according to the metabolic flow edge in the node connection order that comes first, and the second adjacent edge is determined according to the metabolic flow edge in the node connection order that comes later. When the relative metabolic flow support strength of the second adjacent edge is greater than that of the first adjacent edge, it is recorded as edge support enhancement. When the relative metabolic flow support strength of the second adjacent edge is less than that of the first adjacent edge, it is recorded as edge support weakening. When the two relative metabolic flow support strengths are equal, it is recorded as edge support being equal.

[0180] When the partition label strength of the target metabolite of the downstream node corresponding to the second adjacent edge is greater than that of the target metabolite of the downstream node corresponding to the first adjacent edge, it is recorded as node label enhancement; when the partition label strength of the target metabolite of the downstream node corresponding to the second adjacent edge is less than that of the target metabolite of the downstream node corresponding to the first adjacent edge, it is recorded as node label weakening; when the two partition label strengths are equal, it is recorded as node label balancing; when any of the following conditions are met, it is marked as abnormal change in relative metabolic flow support strength: edge support enhancement and node label weakening, edge support weakening and node label enhancement, edge support balancing and node label enhancement, edge support balancing and node label weakening; when the low confidence state of relative metabolic flow support strength and abnormal change in relative metabolic flow support strength are written together into the anomaly type; when the partition label strength changes of the target metabolite of the upstream node and the target metabolite of the downstream node cannot simultaneously support the determined metabolic flow direction, it is marked as upstream and downstream label inconsistency.

[0181] For metabolite flow edges in partitions that have completed anomaly type marking, the source of the anomaly is attributed as follows: when any of the following conditions occur, such as peak group quality status being pending verification, compensation acquisition status being compensation not taken over, or having a low confidence cause, the anomaly source is attributed to peak group quality; when there is an incomplete path node status, or when the upstream node target metabolite and the downstream node target metabolite cannot form a continuous node connection relationship in the metabolic transformation path to be tracked, the anomaly source is attributed to path constraint source; when there is a node expression constraint pending verification status in the first and second metabolic flow partitions corresponding to the partitioned metabolic flow edge, the anomaly source is attributed to expression constraint source; when the peak group quality status is available, the compensation acquisition status is compensation not triggered, compensation taken over after compensation, or compensation verification, the node connection relationship in the metabolic transformation path to be tracked is complete, and the node expression constraint status is node expression constraint supported, the anomaly source is attributed to partitioned metabolic source.

[0182] When there are multiple abnormal sources in the same region's metabolic flow edge, the main source is determined in the order of peak group quality source, path constraint source, expression constraint source, and region metabolic source, and the remaining sources are considered as accompanying sources. The corresponding pathological region type is determined by the pathological region type of the first and second metabolic flow regions in the metabolic flow edge record of the corresponding region in the metabolic flow partition map.

[0183] Write the corresponding partition metabolic flow edge record, path identifier, anomaly type, anomaly source, main source, accompanying source, peak group quality status, compensated acquisition status, low confidence reason, and corresponding pathological region type into the abnormal metabolic flow tracing record.

[0184] S5.4. Based on the partitioned marked path records, partitioned metabolic flow edge records, and abnormal metabolic flow tracing records, perform graph-based association processing to establish graph relationships between metabolic flow partitions, target metabolites, metabolic flow directions, relative metabolic flow support strength, abnormal metabolic flow sources, and quality tracing information, and generate a spatial metabolic flow tracing graph.

[0185] It should be noted that metabolic flow partitions are used as spatial partition objects, target metabolites are used as metabolite objects, partitioned metabolic flow edge records are used as inter-partition metabolic flow relationships, and abnormal metabolic flow tracing records are used as abnormal tracing relationships.

[0186] Establish a partition labeling relationship for the target metabolites, partition labeling intensity, peak group quality status, and compensation acquisition status within the same metabolic flow partition. When the peak group quality status is available and the compensation acquisition status is in any of the following states: compensation not triggered, compensation taken over, or compensation verification, the partition labeling relationship is marked as available for metabolic flow display. When there is any of the following situations: pending verification, compensation not taken over, or low confidence reason, the partition labeling relationship is marked as quality to be traced.

[0187] Based on the first metabolic flow partition, second metabolic flow partition, metabolic flow direction, and relative metabolic flow support strength in the partitioned metabolic flow edge record, directed metabolic flow edges are established between spatial partition objects. When there is a direction to be verified, the corresponding directed metabolic flow edge is marked as a direction to be verified edge; when there is low confidence support strength, it is marked as a support strength low confidence edge. The abnormality type, abnormality source, main source, and accompanying source in the abnormal metabolic flow tracing record are written into the corresponding directed metabolic flow edge, and the peak group quality status, path identifier, node connection order, metabolic flow partition where the abnormality occurred, and corresponding pathological region type are associated according to the peak group quality source, path constraint source, and partitioned metabolic source, respectively.

[0188] By associating spatial partitioning objects, metabolite objects, partitioning label relationships, directed metabolic flow edges, and anomaly tracing relationships, a spatial metabolic flow tracing map is generated.

[0189] This embodiment also provides a computer device applicable to the metabolic flow analysis method based on mass spectrometry imaging, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the metabolic flow analysis method based on mass spectrometry imaging as proposed in the above embodiment.

[0190] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0191] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the metabolic flux analysis method based on mass spectrometry imaging as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0192] In summary, this invention achieves unified constraints on histological, spatial expression, and mass spectrometry imaging positions through cross-slice spatial consistency partitioning, ensuring that the metabolic flow analysis area has a clear stromal origin and pathological boundary, thereby improving the accuracy of spatial partitioning and the reliability of metabolic flow direction determination; through peak group anomaly compensation and tracing, it achieves the location, compensation, takeover, and correction of isotope peak group missingness, quality deviation, and response discontinuity, enabling the calculation of relative metabolic flow support strength to be correlated with peak group quality status, thereby improving the accuracy of metabolic flow direction and relative metabolic flow support strength determination results and the traceability of anomaly sources.

[0193] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A metabolic flux analysis method based on mass spectrometry imaging, characterized in that, include: The tracer condition configuration process is performed on the metabolic flux analysis requirements data and sample attribute data of the biological tissue to be tested, the target metabolites and metabolic flux detection execution conditions are determined, and tracer sampling control records and metabolic flux analysis constraint records are generated. According to the tracer sampling control record, the sampling time sequence and tissue state of the biological tissue to be tested are defined. Mass spectrometry imaging adaptation processing is performed in combination with metabolic flow analysis constraint record to generate a spatially faithful tissue slice group. By analyzing the spatial correspondence between each spatially faithful tissue slice in the spatially faithful tissue slice group, metabolic flow partitions are divided to generate a metabolic flow partition map. Under the constraints of metabolic flux analysis, isotopic peak signals of target metabolites are acquired and spatially bound to each metabolic flux partition in the metabolic flux partitioning map to generate initial mass spectrometry imaging acquisition records. The isotopic envelope mass state of the initial mass spectrometry imaging acquisition record is determined based on the metabolic flow analysis constraint record, and a mass spectrometry imaging compensation scan is performed to generate a compensated mass spectrometry imaging acquisition record. Based on the metabolic flow analysis constraint record, the isotopic peak group of the compensated mass spectrometry imaging acquisition record is corrected and partition mapping is performed to generate a spatial isotopic label matrix. Based on the spatial isotope labeling matrix and metabolic flow analysis constraint records, metabolic flow is solved and results are traced for each metabolic flow partition. The metabolic flow direction, relative metabolic flow support strength and abnormal metabolic flow source between each metabolic flow partition are determined, and a spatial metabolic flow traceability map is generated.

2. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 1, characterized in that, The specific steps for generating tracer sampling control records and metabolic flux analysis constraint records are as follows: By analyzing the detection purpose, pathological region type and metabolic changes to be observed in the biological tissue to be tested, the metabolic transformation pathways to be tracked and the corresponding range of imageable metabolites are determined, and a metabolic flow target record is generated. Based on the metabolic flow target record, the sample attribute data is subjected to tracer imaging adaptation processing. Each imageable metabolite in the range of imageable metabolites is adapted to tissue type, tissue preservation status, slice thickness requirements, spatial resolution requirements and ionization response relationship to generate candidate tracer imaging configuration records. The candidate tracer imaging configuration record is processed for imaging executability verification. Based on the isotope peak group acquisition status, sampling time sequence maintenance status and mass spectrometry imaging adaptation status of each imageable metabolite, the target metabolite and the corresponding metabolic flux detection execution conditions are determined, and the target tracer imaging configuration record is generated. Based on the target tracer imaging configuration record, sampling and imaging constraint solidification processing is performed to obtain the sampling control parameters, imaging constraint parameters, isotope peak range and peak quality judgment boundary corresponding to the target metabolite, and solidify them into tracer sampling control record and metabolic flow analysis constraint record, respectively.

3. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 2, characterized in that, The specific steps for generating spatially faithful tissue slice groups are as follows: The preparation path is arranged for tracer sampling control records and metabolic flux analysis constraint records. According to the sampling sequence, tissue state preservation requirements, slice position correspondence rules, imaging constraint parameters and isotope peak range, the sampling batch, continuous slice layer, layer numbering rules, histological imaging identifier, spatial expression acquisition identifier, mass spectrometry imaging acquisition identifier and mass spectrometry imaging preparation path of the biological tissue to be tested are determined, and a spatially faithful preparation path table is generated. According to the spatial fidelity preparation path table, the biological tissue to be tested is processed by layer-association sectioning. Continuous tissue sections from the same sampling batch are configured with histological imaging labels, spatial expression acquisition labels and mass spectrometry imaging acquisition labels according to the layer numbering rules, and layer correspondence is established to generate spatial fidelity tissue section groups.

4. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 3, characterized in that, The specific steps for generating the metabolic flux partition map are as follows: Acquire histological images of spatially fidelity tissue sections with histological imaging markers, and extract the outer boundary of the tissue, the boundary of the pathological region, and the layer reference points from the histological images to generate a tissue spatial reference image; Based on the layer correspondence between spatially fidelity tissue slices, spatially fidelity tissue slices with spatial representation acquisition markers and spatially fidelity tissue slices with mass spectrometry imaging acquisition markers are registered to the tissue spatial reference, generating a cross-slice spatial correspondence table. Spatial consistency is checked on the cross-slice spatial correspondence table. Metabolic flow partitions are divided according to the offset of the layer reference point, the degree of overlap of tissue boundaries and the offset of the pathological area boundaries. Partition numbers and spatial boundaries are configured to generate a metabolic flow partition map.

5. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 3 or 4, characterized in that, The specific steps for generating the initial mass spectrometry imaging acquisition record are as follows: Based on the metabolic flux partition map and metabolic flux analysis constraint records, the spatial boundaries of each metabolic flux partition are converted into mass spectrometry imaging acquisition coordinates, and the isotope peak group ranges corresponding to the target metabolites are matched to the mass spectrometry imaging acquisition coordinates to generate a partition acquisition coordinate table. According to the partition acquisition coordinate table, the spatially fidelity tissue slices with mass spectrometry imaging acquisition marks are initially scanned by mass spectrometry imaging. The isotope peak group signals corresponding to the target metabolites are acquired at each mass spectrometry imaging acquisition coordinate, and the acquisition coordinates, scanning order, detection polarity and peak group response status are recorded to generate the initial pixel spectrum record. The initial pixel spectrum record is processed by pixel partitioning and binding based on the metabolic flow partition map. The acquired pixels corresponding to each acquisition coordinate are assigned to the corresponding metabolic flow partition. The corresponding relationship between the acquired pixels, partition number, isotope peak group signal and peak group response state is established to generate the initial mass spectrometry imaging acquisition record.

6. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 5, characterized in that, The specific steps for generating the compensated mass spectrometry imaging acquisition record are as follows: Based on the isotope peak range and peak mass determination boundary in the metabolic flow analysis constraint record, the envelope state of the isotope peak signal in the initial mass spectrometry imaging acquisition record is identified, and the peak missing state, mass deviation state and peak response continuity state corresponding to each acquisition pixel are determined to generate an isotope envelope quality state record. Based on the partition numbers in the isotope envelope mass state record and the initial mass spectrometry imaging acquisition record, the acquisition pixels that do not meet the peak group quality judgment boundary in at least one of the peak group missing state, mass deviation state, and peak group response continuity state are located, and merged according to the acquisition coordinate adjacency relationship within the same metabolic flow partition to generate a compensated acquisition area record. Based on the imaging constraint parameters in the compensated acquisition area record and the metabolic flow analysis constraint record, the compensated scan sequence, compensated acquisition coordinates, detection polarity and peak group acquisition index are configured for the compensated acquisition area, and a compensated scan task record is generated. Mass spectrometry imaging compensation scanning is performed on spatially faithful tissue sections with mass spectrometry imaging acquisition markers according to the compensation scanning task record. The compensation isotope peak group signals corresponding to the target metabolites in the compensation acquisition area are acquired, and the correspondence between the compensation isotope peak group signals and the corresponding pre-compensation isotope peak group signals, acquisition pixels and partition numbers are established to generate a compensation mass spectrometry imaging acquisition record.

7. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 6, characterized in that, The specific steps for generating the spatial isotope labeling matrix are as follows: The compensation mapping relationship, compensation source type, compensation acquisition pixel, pre-compensation peak group signal and post-compensation peak group signal in the compensation mass spectrometry imaging acquisition record are statistically analyzed. The effective isotope peak group is located according to the compensation mapping relationship and the peak group quality judgment boundary in the metabolic flow analysis constraint record, and the post-compensation peak group takeover record is generated. Based on the isotope peak group range and imaging constraint parameters in the metabolic flux analysis constraint record, the effective isotope peak groups in the compensated peak group takeover record are corrected for natural abundance, excluded for isotope interference, and merged for peaks to generate a corrected isotope peak group record. Based on the acquisition pixel position and partition number in the corrected isotope peak group record, the corrected isotope peak group is mapped to the corresponding metabolic flow partition, and the corrected peak group signals in the same metabolic flow partition are partitioned and aggregated to generate a spatial isotope label matrix.

8. The metabolic flux analysis method based on mass spectrometry imaging as described in claim 7, characterized in that, The specific steps for generating the spatial metabolic flow tracing map are as follows: Based on the spatial isotope labeling matrix, the target metabolites, isotope peak intensity, peak mass status and compensated acquisition status corresponding to each metabolic flux partition are extracted, and the extraction results are correlated with the metabolic transformation paths to be tracked in the metabolic flux analysis constraint record to generate partition labeling path records. The partitioned marked path records are subjected to inter-regional metabolic transformation comparison processing. Based on the isotope peak group intensity changes, upstream and downstream correspondence of target metabolites, and peak group quality status between adjacent metabolic flow partitions, the metabolic flow direction and relative metabolic flow support strength between adjacent metabolic flow partitions are determined, and partitioned metabolic flow edge records are generated. Anomaly source tracing processing is performed on the partitioned metabolic flow edge records. Partitioned metabolic flow edges with abnormal metabolic flow direction, abnormal changes in relative metabolic flow support strength, and inconsistent upstream and downstream labels are matched with the corresponding compensated acquisition status, peak group quality status, and metabolic transformation path to be tracked to determine the source of abnormal metabolic flow and generate abnormal metabolic flow tracing records. Based on the partitioned path records, partitioned metabolic flow edge records, and abnormal metabolic flow tracing records, a graph-based association process is performed to establish graph relationships between metabolic flow partitions, target metabolites, metabolic flow directions, relative metabolic flow support strength, abnormal metabolic flow sources, and quality tracing information, thereby generating a spatial metabolic flow tracing graph.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the metabolic flux analysis method based on mass spectrometry imaging as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the metabolic flux analysis method based on mass spectrometry imaging as described in any one of claims 1 to 8.

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