ArticleJournal of translational medicine2024
CT-based delta-radiomics nomogram to predict pathological complete response after neoadjuvant chemoradiotherapy in esophageal squamous cell carcinoma patients.
Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07181850 (Integration of Clinical, Radiomics, and 2.5D Deep Learning-Based Multiple Instance Learning Features for Predicting Pathological Complete Response in Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunotherapy and Chemotherapy), which is not on this map. Cited by 30 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Integration of Clinical, Radiomics, and 2.5D Deep Learning-Based Multiple Instance Learning Features for Predicting Pathological Complete Response in Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunotherapy and Chemotherapy: A Multicenter Comparative Study
Who cites it
30 citing papers in PubMed.
- Intratumoral and peritumoral radiomics for preoperative prediction of pathological complete response to neoadjuvant immunochemotherapy in patients with esophageal squamous cell carcinoma.European journal of radiology open · 2026Article
- DDX21 Enhances Radiosensitivity in Head and Neck Squamous Cell Carcinoma by Suppressing MK2-Mediated DNA Damage Response.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Radiation dose and pathological complete response rate of neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma: a model-based dose-response meta-analysis.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Clinical significance of CD161Journal for immunotherapy of cancer · 2026Article
- Non-Operative Management of Esophageal Cancer with Complete Clinical Response After Neoadjuvant Therapy: Current Status and Future Directions.Journal of personalized medicine · 2026Review
- Post-neoadjuvant Metabolic Response Assessed by ¹⁸F-FDG PET/CT Predicts Pathologic Complete Response and Survival in Esophageal Squamous Cell Carcinoma Treated with the CROSS Regimen.Journal of gastrointestinal cancer · 2026Article
- Lesion-level comparison of primary and secondary tumors after neoadjuvant immunochemotherapy in multifocal esophageal squamous cell carcinoma: a single-center retrospective study.Journal of thoracic disease · 2026Article
- The geriatric nutritional risk index predicts pathological complete response and anastomotic leakage in esophageal cancer patients undergoing neoadjuvant therapy.Journal of thoracic disease · 2026Article
- Unlocking the potential of radiomics in predicting the response of neoadjuvant immunochemotherapy for operable locally advanced esophageal squamous cell carcinoma: a narrative review.Journal of thoracic disease · 2026Review
- Post-treatment triglyceride-glucose index as survival protective factors in patients with esophageal squamous cell carcinoma.World journal of clinical oncology · 2026Article
- Integration of habitat radiomics and traditional radiomic features for predicting pathological complete response in esophageal squamous cell carcinoma following neoadjuvant immunotherapy and chemotherapy: a multicenter comparative study.Journal of translational medicine · 2026Article
- Preoperative CT-based Radiomics for Predicting Response to Neoadjuvant Chemoimmunotherapy in Esophageal Squamous Cell Carcinoma.Radiology. Imaging cancer · 2026Article
- Longitudinal CT-based deep learning radiomics for predicting prognosis in esophageal squamous cell carcinoma treated with definitive chemoradiotherapy: a two-center study.Journal of Cancer · 2026Article
- Predictive value of 18F-FDG PET/CT delta radiomics model for prognosis after neoadjuvant therapy for locally advanced pancreatic cancer.Frontiers in oncology · 2026Article
- Prognostic Value of the PILE Score in Esophageal Squamous Cell Carcinoma Treated with Neoadjuvant Chemoradiotherapy.Diagnostics (Basel, Switzerland) · 2025Article
- CT delta-radiomics predicts the risks of blood transfusion and massive bleeding during spinal tumor surgery.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Radiomics applications in the modern management of esophageal squamous cell carcinoma.Medical oncology (Northwood, London, England) · 2025Review
- Osteosarcopenia as a Predictor of Histopathologic Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer: a Retrospective Cohort Study.Langenbeck's archives of surgery · 2025Article
- Article
- Application of machine learning based on habitat imaging and vision transformer to predict treatment response of locally advanced esophageal squamous cell carcinoma following neoadjuvant chemoimmunotherapy: a multi-center study.Frontiers in immunology · 2025Article
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5 authors.
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Abstract
backgroundThis study developed a nomogram model using CT-based delta-radiomics features and clinical factors to predict pathological complete response (pCR) in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiotherapy (nCRT).
methodsThe study retrospectively analyzed 232 ESCC patients who underwent pretreatment and post-treatment CT scans. Patients were divided into training (n = 186) and validation (n = 46) sets through fivefold cross-validation. 837 radiomics features were extracted from regions of interest (ROIs) delineations on CT images before and after nCRT to calculate delta values. The LASSO algorithm selected delta-radiomics features (DRF) based on classification performance. Logistic regression constructed a nomogram incorporating DRFs and clinical factors. Receiver operating characteristic (ROC) and area under the curve (AUC) analyses evaluated nomogram performance for predicting pCR.
resultsNo significant differences existed between the training and validation datasets. The 4-feature delta-radiomics signature (DRS) demonstrated good predictive accuracy for pCR, with α-binormal-based and empirical AUCs of 0.871 and 0.869. T-stage (p = 0.001) and differentiation degree (p = 0.018) were independent predictors of pCR. The nomogram combined the DRS and clinical factors improved the classification performance in the training dataset (AUC
conclusionsThe CT-based delta-radiomics nomogram model with clinical factors provided high predictive accuracy for pCR in ESCC patients after nCRT.
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