From histopathological imaging to molecular prediction:a multimodal AI-driven paradigm for MSI detection in colorectal cancer
10.7659/j.issn.1005-6947.250349
- VernacularTitle:从病理图像到分子预测:多模态人工智能驱动的结直肠癌MSI检测新范式
- Author:
Ruohan LI
1
;
Wen QIN
Author Information
1. 广西医科大学第一附属医院 病理科,广西 南宁 530021
- Publication Type:Journal Article
- Keywords:
Colorectal Neoplasms;
Microsatellite Instability;
Artificial Intelligence;
Deep Learning;
Review
- From:
Chinese Journal of General Surgery
2025;34(10):2232-2242
- CountryChina
- Language:Chinese
-
Abstract:
Colorectal cancer(CRC)ranks among the leading causes of cancer incidence and mortality worldwide.Microsatellite instability(MSI)is a key molecular biomarker with important implications for prognosis and immunotherapy selection.Although conventional detection methods such as immunohistochemistry,PCR,and next-generation sequencing have been standardized,they remain limited by high costs,technical complexity,and inconsistent results.In recent years,artificial intelligence(AI)has shown great potential in MSI detection by integrating multimodal data that includes histopathological images,genomic information,and medical imaging to achieve accurate prediction and enable a data-driven paradigm in oncology.This review summarizes the latest advances in AI-based multimodal modeling for MSI detection in CRC,compares different methodological approaches and their translational challenges,and discusses future directions such as multimodal integration,model generalizability,and interpretability enhancement,providing new insights for precision medicine.
