Diagnostic Accuracy StudyInsights into Imaging· Aug 14, 2025
Clinical question: 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.
- 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.
- 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.
Diagnostic Accuracy StudyInsights into Imaging· Jan 25, 2024
Clinical question: A CT-based combined model integrating radiomics and clinical features shows promise for predicting lymph node metastasis in bladder cancer, outperforming the clinical model alone on external testing, though validation remains limited.
- Current CT and MRI size-based lymph node assessment in bladder cancer has low sensitivity, meaning nodal metastases are frequently missed at staging; this study attempts to address that gap with a radiomics-based model.
- The combined model is a nomogram incorporating a LightGBM radiomics signature—using hand-crafted and deep learning features—alongside stalk presence and CT-reported lymph node status as clinical predictors.
Diagnostic Accuracy StudyInsights into Imaging· Jul 31, 2025
Clinical question: A multicenter ANN-based combined model integrating CT radiomics and clinicoradiological features stratified stage II colorectal cancer patients into high- and low-risk groups for three-year disease-free survival, outperforming both radiomics-only and clinicoradiological-only models across test and external validation cohorts.
- Rough or irregular outer edge of the intestine on CT was identified as the leading clinicoradiological predictor of recurrence risk in this model, reflecting tumor aggressiveness and deeper tissue invasion. Readers should be aware this association was established within a predictive model context and does not yet constitute a validated standalone reporting standard.
- Five clinicoradiological factors—age, perineural invasion, intestinal obstruction or perforation status, outer edge of the intestine, and ctEMVI—were identified as independent predictors of recurrence by multivariate logistic regression and incorporated into the clinicoradiological model. The clinicoradiological model alone showed modest and declining discrimination across cohorts.
Cohort StudyInsights into Imaging· Aug 30, 2025
Clinical question: Can preoperative MRI-based radiomics predict intratumoural TLS status in GBC, and can such a model stratify recurrence-free survival (RFS) after surgery and overall survival (OS) during immunotherapy?
- Intratumoural TLS presence was the only independent predictor of RFS in multivariate Cox regression (HR 1.86; 95% CI 1.01–3.43; p=0.046); TLS-positive patients had significantly longer RFS than TLS-negative patients (p=0.002).
- Three independent clinico-radiological predictors of TLS status were identified: tumour height (OR 0.67), liver invasion (OR 0.37), and arterial-phase hypo-enhancement (OR 0.33). Eight radiomics features formed the Rad-score; TLS-positive tumours had significantly higher Rad-scores than TLS-negative tumours in both cohorts (p<0.001).