ArticleJournal of applied clinical medical physics2026
Predictive value of primary gross tumor volume measured by MRI in response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Article in Journal of applied clinical medical physics, 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
backgroundNeoadjuvant chemoradiotherapy (nCRT) is a standard treatment for locally advanced rectal cancer (LARC), yet individual tumor regression response varies considerably. PURPOSE: This study aimed to identify clinical factors linked to tumor regression grade (TRG) after nCRT in LARC and to evaluate MRI-measured primary gross tumor volume (pGTV) as a predictor of TRG.
methodsWe retrospectively analyzed 123 patients with LARC who underwent nCRT followed by total mesorectal excision (TME) and had pathologically confirmed LARC between 2014 and 2018. The pGTV was measured using MRI. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of TRG. Additionally, the receiver operating characteristic (ROC) curve was employed to calculate the area under the curve (AUC) for pGTV and to determine its optimal cut-off value in predicting TRG.
resultsThe study cohort comprised 52 patients in the favorable TRG group and 71 patients in the unfavorable TRG group. Both univariate and multivariate logistic regression analyses revealed that a smaller pGTV was an independent predictor of improved tumor regression (p < 0.001). No other clinical factors were significantly associated with TRG in the multivariate analysis. The ROC curve analysis showed that a pGTV cut-off value of 49.25 cm
conclusionsMRI-measured pGTV shows promise as a biomarker for predicting TRG after nCRT in LARC, potentially aiding pre-treatment risk assessment. While this preliminary evidence from a retrospective, single-center cohort requires confirmation in prospective, large-scale studies, it provides a rationale for incorporating quantitative tumor volumetry into future research on individualized treatment strategies.
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