ArticleBMC gastroenterology2025
Dual energy CT-derived quantitative parameters and hematological characteristics predict pathological complete response in neoadjuvant chemoradiotherapy esophageal squamous cell carcinoma patients.
Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Radiomics analysis of dual-layer spectral detector CT-derived iodine density maps for predicting the pathological complete response of esophageal squamous cell carcinoma after neoadjuvant chemoimmunotherapy.European journal of radiology open · 2026Article
- CT-derived extracellular volume fraction and AI-assisted body composition for predicting neoadjuvant therapy response and prognosis in colorectal cancer.Abdominal radiology (New York) · 2026Article
- Role of spectral CT in quantitative evaluation of pathologic response to neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma: a pilot study.Journal of translational medicine · 2026Article
- Baseline dual-layer spectral CT-based habitat analysis for preoperative prediction of recurrence in pancreatic cancer after radical resection and its association with tumor-stroma ratio.Abdominal radiology (New York) · 2026Article
- Construction of a postoperative disease-free survival prediction model for non-small cell lung cancer patients based on dual-energy computed tomography parameters and blood inflammatory indicators.Translational cancer research · 2026Article
- Research progress of the clinical application of dual-layer spectral computed tomography in gastrointestinal malignancies.World journal of radiology · 2026Review
- Dual-energy CT biomarkers for predicting the efficacy of TACE combined with lenvatinib and immune checkpoint inhibitors in unresectable HCC.European radiology experimental · 2026Article
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11 authors.
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Abstract
purposeThere is no gold standard method to predict pathological complete response (pCR) in esophageal squamous cell carcinoma (ESCC) patients before surgery after neoadjuvant chemoradiotherapy (nCRT). This study aims to investigate whether dual layer detector dual energy CT (DECT) quantitative parameters and clinical features could predict pCR for ESCC patients after nCRT. PATIENTS AND
methodsThis study retrospective recruited local advanced ESCC patients who underwent nCRT followed by surgical treatment from December 2019 to May 2023. According to pCR status (no visible cancer cells in primary cancer lesion and lymph nodes), patients were categorized into pCR group (N = 25) and non-pCR group (N = 28). DECT quantitative parameters were derived from conventional CT images, different monoenergetic (MonoE) images, virtual non-contrast (VNC) images, Z-effective (Zeff) images, iodine concentration (IC) images and electron density (ED) images. Slope of spectral curve (λHU), normalized iodine concentration (NIC), arterial enhancement fraction (AEF) and extracellular volume (ECV) were calculated. Difference tests and spearman correlation were used to select quantitative parameters for DECT model building. Multivariate logistic analysis was used to build clinical model, DECT model and combined model.
resultsA total of 53 patients with locally advanced ESCC were enrolled in this study who received nCRT combined with surgery and underwent DECT examination before treatment. After spearman correlation analysis and multivariate logistic analysis, AEF and ECV showed significant roles between pCR and non-pCR groups. These two quantitative parameters were selected for DECT model. Multivariate logistic analysis revealed that LMR and RBC were also independent predictors in clinical model. The combined model showed the highest sensitivity, specificity, PPV and NPV compared to the clinical and DECT model. The AUC of the combined model is 0.893 (95%CI: 0.802-0.983). Delong's test revealed the combined model significantly different from clinical model (Z =-2.741, P = 0.006).
conclusionDual-layer DECT derived ECV fraction and AEF are valuable predictors for pCR in ESCC patients after nCRT. The model combined DECT quantitative parameters and clinical features might be used as a non-invasive tool for individualized treatment decision of those ESCC patients. This study validates the role of DECT in pCR assessment for ESCC and a large external cohort is warranted to ensure the robustness of the proposed DECT evaluation criteria.
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