ArticleEuropean radiology2025
Short-term intra- and peri-tumoral spatiotemporal CT radiomics for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer.
Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Efficacy and safety of neoadjuvant chemotherapy with immunotherapy versus chemotherapy alone in esophageal squamous cell carcinoma: a meta-analysis based on randomized controlled trials.Frontiers in immunology · 2026Pooled it
- CT-based radiomics in predicting the efficacy of preoperative neoadjuvant chemoimmunotherapy for non-small cell lung cancer: a systematic review and meta-analysis.Frontiers in immunology · 2026Pooled it
- Externally validated yet undertrained: sample size deficits in machine learning-based radiomics.European radiology · 2026Article
- CT radiomics machine learning for predicting treatment response in unresectable stage III-IV NSCLC: insights from dual chemo-immunotherapy and immunotherapy cohorts.La Radiologia medica · 2026Article
- Delta radiomics for predicting early radiation-induced lung injury after thoracic radiotherapy: a retrospective paired-CT study.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Temporal radiomics for non-invasive preoperative prediction of pathologic complete response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer.Cancer biology & medicine · 2026Article
- Radiomics to understand pre-treatment tumor biology for resectable non-small cell lung cancer.Frontiers in oncology · 2026Review
- Perspective on the integration of radiomics and spatial omics in the analysis of the tumor microenvironment of bladder cancer and prospects for precision diagnosis and treatment.Frontiers in immunology · 2026Review
- Comparative multiphase CT radiomics for differentiating isolated hepatic metastasis from intrahepatic cholangiocarcinoma: a two-center study of native, subtraction, peritumoral, and fusion models.Frontiers in oncology · 2026Article
- Imaging biomarkers related to tumor-associated macrophage in immunotherapy treatment planning for non-small cell lung cancer.Translational lung cancer research · 2025Article
- Integration of intratumoral/peritumoral radiomics and deep learning for predicting overall survival in non-small cell lung cancer patients: a multicenter study.Frontiers in oncology · 2025Article
- Construction of a radiomics model based on CT imaging for predicting capsular invasion in thymomas.Frontiers in radiology · 2025Article
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9 authors.
Funding
Abstract
purposeThis study aims to develop a short-term spatiotemporal CT radiomics model to predict the major pathological response (MPR) to neoadjuvant chemoimmunotherapy (NCI) in NSCLC by decoding the intra- and peri-tumoral imaging phenotypes.
methodsA total of 352 patients undergoing curative surgery following NCI for NSCLC were enrolled from two centers, forming a training cohort (n = 186), an internal validation cohort (n = 80), and an external validation cohort (n = 86). Intra- and peri-tumoral CT radiomics features were computed to capture imaging phenotypes of the tumor microenvironment. Delta radiomics features were also calculated by quantifying changes in each radiomics feature. A support vector machine classifier was utilized to develop the short-term spatiotemporal model by analyzing changes in radiomics features.
resultsThe multi-timepoint short-term spatiotemporal model, incorporating pre-treatment, post-treatment and delta radiomic features, achieved AUC values of 0.84, 0.77, and 0.75 in the training, internal validation, and external validation cohorts, respectively. These results significantly outperformed the RECIST model and pre-treatment model, with p-values < 0.05 indicating statistical significance.
conclusionThis study demonstrates that short-term temporal analysis of intra- and peri-tumoral CT radiomics is a promising approach for predicting MPR to NCI in NSCLC. These findings underscore the potential of radiomics as a non-invasive tool for assessing treatment response and guiding personalized therapy in NSCLC patients. KEY POINTS: Question Neoadjuvant chemoimmunotherapy has improved in major pathological response rate for non-small cell lung cancer (NSCLC), but it is unclear which patients will benefit most. Findings The multi-timepoint short-term spatiotemporal model based on CT pictures demonstrates high predictive performance for assessing major pathological response following neoadjuvant chemoimmunotherapy in NSCLC. Clinical relevance Short-term intra- and peri-tumoral CT radiomics is a promising approach for predicting major pathological response to neoadjuvant chemoimmunotherapy in NSCLC. These findings underscore the potential of radiomics as a non-invasive tool for assessing treatment response in NSCLC.
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