A tumor immune microenvironment multi-cell recognition and spatial analysis system

By generating initial intrinsic signal vectors, preliminary functional labeling, functional neighborhood construction, and functional determination models, and comprehensively considering the intrinsic state of cells and the local microenvironment, the bias problem in the depiction of the spatial distribution map of functional heterogeneity of the tumor microenvironment in existing technologies is solved, and accurate characterization of cell functional state is achieved.

CN122157256BActive Publication Date: 2026-07-24THE FIRST MEDICAL CENT CHINESE PLA GENERAL HOSPITAL
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Patent Information

Application Number
CN202610628499.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-05-09
Publication Date
2026-07-24
Estimated Expiration
2046-05-09

AI Technical Summary

Technical Problem

Existing technologies have failed to effectively integrate intrinsic cellular state information with local functional microenvironment context information in the tumor microenvironment, resulting in biases in the depiction of the spatial distribution map of functional heterogeneity in the tumor microenvironment.

Method used

By generating initial intrinsic signal vectors, preliminary functional labeling, functional neighborhood construction, composite feature splicing, and functional determination modules, combined with a pre-trained functional determination model, a cell effective functional map under environmental regulation is rendered, comprehensively considering the expression of cell biomarkers and the influence of the local microenvironment.

Benefits of technology

It enables dynamic modeling of cellular functional states, allowing simultaneous examination of individual cell attributes and environmental signals, generating a continuously evolving map of effective cellular functions, avoiding information loss due to hard classification, and providing an accurate representation of the functional state of the tumor microenvironment.

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Abstract

The application provides a tumor immune microenvironment multi-cell recognition and spatial analysis system, comprising: an intrinsic signal generation module generating an initial intrinsic signal vector; a preliminary functional marker module generating a preliminary phenotype classification label map based on spatial centroid coordinates of cell objects; a functional neighborhood construction module calculating and generating a functional neighborhood feature vector; a composite feature splicing module constructing a composite state feature vector; an effective function determination module decoding to obtain a continuous value feature vector output by a function determination model representing the final function strength under the regulation of the microenvironment; and a functional map rendering module rendering to generate a cell effective function map under the regulation of the environment. The application solves the problem that, in the prior art, when interpreting cell functions, the intrinsic state information of the cells and the local functional microenvironment context information cannot be effectively fused, resulting in deviation in the description of the spatial distribution map of tumor microenvironment function heterogeneity.
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