ArticleNPJ digital medicine2026
Multimodal digital biopsy for preoperative prediction of occult peritoneal metastasis in gastric cancer.
Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Spectral focused imaging enables enhanced colorectal adenoma detection: a multicenter, parallel randomized controlled trial.BMC medicine · 2026Trial
- Non-invasive prediction of occult peritoneal metastasis (OPM) in gastric cancer using logistic regression and random forest integrative models with CT radiomics and clinical parameters: machine learning prediction of gastric OPM.Journal of gastrointestinal oncology · 2026Article
- The Lymph Node Ratio as a Predictive Biomarker for Individualized Benefit from Adjuvant Chemotherapy in Gastric Cancer: A Retrospective Cohort and Causal Machine Learning Study.Journal of gastrointestinal cancer · 2026Article
- Retrospective analysis of the occurrence pattern of complications and prognostic influencing factors in elderly patients with squamous cell lung cancer after radical surgery.World journal of surgical oncology · 2026Article
- Article
- Study of phosphorylated ribosomal protein S6 (pS6) in the clinical outcomes of patients undergoing hepatectomy for metastatic colorectal cancer.World journal of surgical oncology · 2026Article
- An LSCC-specific R-loop-related model predicts prognosis and neoadjuvant immunotherapy response and identifies EIF5A2-mediated tumor-immune crosstalk.World journal of surgical oncology · 2026Article
- Article
- An albumin-based immune-nutritional score for predicting complete response, organ preservation, and toxicity after neoadjuvant PD-1-based therapy in low rectal cancer.Frontiers in immunology · 2026Article
- Probiotic supplementation as a nutritional strategy for the prevention and management of sarcopenia in older adults.Frontiers in cellular and infection microbiology · 2026Article
- Baseline thyroid function and treatment-emergent thyroid dysfunction predict pathological response and survival after neoadjuvant PD-1 inhibitor plus platinum-based chemotherapy in locally advanced gastric and gastroesophageal junction adenocarcinoma: a multicenter cohort study.Frontiers in endocrinology · 2026Article
- Metabolic syndrome as an independent predictor of response and survival in locally advanced gastric cancer treated with neoadjuvant immunochemotherapy.Frontiers in oncology · 2026Article
- The global clinical trial landscape of PD-1-containing bispecific antibodies for gastric cancer: current status and future directions of targeting immune tolerance.Frontiers in immunology · 2026Review
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Gastric cancer staging is frequently limited by the low sensitivity of routine imaging for occult peritoneal metastasis (OPM), necessitating invasive staging laparoscopy. We developed a Multimodal Model, integrating primary tumor radiomics from CT with clinical factors to non-invasively predict OPM in locally advanced gastric cancer. The model was trained and internally validated in a large cohort (n = 940) and externally validated across two independent multi-center cohorts (n = 309), an incremental cohort (n = 477), and a prospective clinical trial cohort (n = 168). In all cohorts, the model achieved robust performance (AUCs: 0.834-0.857), significantly outperforming single-modality models. Crossover validation showed AI assistance increased the average radiologist AUC from 0.735 to 0.872. Transcriptomic analysis revealed that the model's low-risk stratification correlated with an enhanced antitumor immune microenvironment (CD8 T cells, TNFα signaling). This validated model provides a practical tool for accurate, non-invasive OPM prediction and individualized treatment planning.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.