ArticleJournal of translational medicine2026
Role of spectral CT in quantitative evaluation of pathologic response to neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma: a pilot study.
Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundTo find a useful non-invasive biomarker for evaluating treatment response to neoadjuvant immunochemotherapy (nICT) in patients with esophageal squamous cell carcinoma (ESCC), using spectral computed tomography (CT).
methodsSpectral CT-derived parameters including the 40 keV virtual monoenergetic imaging (VMI), iodine concentration (IC), and normalized iodine concentration (NIC) were obtained before and after nICT in 87 patients with ESCC. Independent samples t-test (normality) or Mann-Whitney U test (non-normality) was used to compare the differences of spectral CT-derived parameters between responders and non-responders. Binary logistic regression analysis was performed to identify independent predictive factors for responders. Diagnostic performance of parameters in predicting response was tested with receiver operating characteristic (ROC) curve analysis.
resultsThe post-area, post-40 keV VMI, post-IC, and post-NIC of the responders were significantly lower than those of the non-responders (p < 0.001, < 0.001, < 0.001, and 0.002, respectively). Post-area (odds ratio [OR], 0.980, 95% confidence interval [95% CI], 0.970-0.990; p < 0.001) and post-NIC (OR, 0.824, 95% CI, 0.723-0.938; p = 0.003) were independent post-treatment predictors of therapeutic efficacy. A predictive model combining post-NIC and post-area showed the most favorable diagnostic performance with an area under the curve of 0.844.
conclusionsPost-NIC and post-area of tumor might serve as independent monitoring biomarkers for assessing pathological response to nICT in ESCC. The model combining post-NIC and post-area may provide preliminary imaging evidence for individualized clinical decisions.
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