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Diagnostic Accuracy StudyEditorially reviewed

Computed tomography radiomics to predict microsatellite instability status and immunotherapy response in gastric cancer.

Zhou Li, Zixuan Ding, Yongping Lian, Yongqing Liu, Lei Wang, Pengbo Hu, Fangyuan Zhang, Yan Luo, Hong Qiu

Insights into Imaging · August 14, 2025 · Vol 16 · Issue 1 · p. 177

PMID: 40813941PMCID: PMC12354409DOI: 10.1186/s13244-025-02050-1
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This is an evidence-grounded AI reading aid that has passed human editorial review. Items markedRadWeave readingare our interpretation rather than statements by the authors. It is not a substitute for reading the original publication, and RadWeave does not reproduce the source full text here.

Take-home message

A contrast-enhanced CT radiomics model built from four features and a Random Forest classifier predicted MSI-H status in gastric cancer across a training set and two independent external testing sets, suggesting potential as a noninvasive preoperative MSI screening tool.

Radiotranscriptomic analysis linked higher Radscores to greater CD8+ T-cell infiltration and lower M2 macrophage content, suggesting the model may capture aspects of the tumor immune microenvironment.

RadWeave reading

What the radiologist should know

  • Radscores were an independent predictor of progression-free survival in a separate cohort of advanced unresectable gastric cancer patients receiving first-line immunotherapy, but no significant OS difference was found between high- and low-Radscore groups.

    Evidence grounded · 2 source references

  • In the immunotherapy cohort, patients achieving partial remission had higher baseline Radscores than those with stable or progressive disease, and the high-Radscore group had a markedly higher partial remission rate than the low-Radscore group.

    Evidence grounded · 2 source references

  • Radscores correlated with CD8+ T-cell infiltration and M2 macrophage content in a public radiotranscriptomic dataset, raising the possibility that CT texture may reflect immune microenvironment composition—though this is exploratory and not yet actionable.

    RadWeave reading

    Evidence grounded · 2 source references

  • Radscores showed no significant correlation with established immune checkpoint gene expression markers, which the authors speculate may indicate complementary rather than redundant immune information—a hypothesis requiring prospective validation.

    RadWeave reading

    Evidence grounded · 2 source references

Reporting implications

This paper does not support a change to reporting.

No established routine reporting change is supported. Feature awareness: Model is investigational; external generalizability is inconsistent and prospective validation is absent. Awareness of MSI-H CT radiomics research is useful but no new routine reporting requirement is established.

Practice impact

RadWeave editorial assessment, not a statement by the authors.

Potentially useful

An investigational CT radiomics model for MSI-H prediction in gastric cancer shows cross-cohort promise and immune microenvironment correlates, but inconsistent external performance and small retrospective immunotherapy cohorts preclude practice change.

Evidence grounded · 5 source references

Caveats before applying this

  • The immunotherapy outcome cohort was small and retrospective, and the overall survival analysis was non-significant; results may not generalise to larger or more diverse patient populations, and prospective validation is needed before any clinical translation.

    Evidence grounded · 2 source references

  • The clinical-radiomics model combining Radscores with age, clinical stage, cT-stage, cN-stage, and tumor location showed inconsistent performance across external sets: it outperformed the radiomics-only model in the training set but underperformed it in external testing set 2, highlighting generalizability concerns.

    Evidence grounded · 1 source reference

  • The association between Radscores and immunotherapy response does not establish that CT radiomics can replace or guide molecular testing for MSI-H status; the two analyses were conducted in separate cohorts with different endpoints.

    RadWeave reading

    Evidence grounded · 5 source references

RadWeave bottom line

This investigational CT radiomics model shows promise for noninvasive MSI-H prediction in gastric cancer and suggests links to immune microenvironment features, but inconsistent external performance and small retrospective immunotherapy cohorts mean no change in routine reporting or clinical practice is currently established.

RadWeave reading

Evidence grounded · 5 source references

Study in 20 seconds
Study type
Diagnostic Accuracy Study
Population
Patients with gastric cancer across a training cohort and two independent external testing cohorts, plus a separate advanced unresectable gastric cancer immunotherapy cohort
Modality
Contrast-enhanced CT (portal-venous phase)
Technique
CT radiomics with LASSO feature selection and Random Forest classification; radiotranscriptomic correlation in TCGA/TCIA cohort
Comparator / reference
Three alternative classifiers compared to Random Forest; radiomics-only model compared to combined clinical-radiomics model
Primary endpoint
Prediction of MSI-H status in gastric cancer; secondary endpoints included progression-free survival and objective response in an immunotherapy cohort