Extracellular volume fraction determined by equilibrium contrast-enhanced CT for the prediction of the pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer.

Abstract

To determine the extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC). The ECV fraction before NCRT (ECV_pre) and/or ECV after NCRT (ECV_post) of rectal tumors was assessed, and ECV_Δ was calculated as ECV_post - ECV_pre. The histopathologic tumor regression grading (TRG) was assessed. pCR (TRG 0 grade) was defined as the absence of viable tumor cells in the primary tumor and lymph nodes. Demographic and clinicopathological characteristics and ECV fraction were compared between the pCR and non-pCR groups. A mixed model was constructed by logistic regression. The performance for predicting pCR was assessed with the area under the receiver-operator curve (AUC). The AUCs of the different methods were compared by the method proposed by DeLong et al. RESULTS: Seventy-five patients were included; 17 achieved pCR, and 58 achieved non-pCR. The ECV_post (17.05 ± 2.36% vs. 29.94 ± 1.20%; p < 0.001) and ECV_Δ (- 17.01 ± 3.01% vs. 0.44 ± 1.45%; p < 0.001) values in the pCR group were significantly lower than those in the non-pCR group. The mixed model that combined ECV_post with ECV_Δ achieved an AUC of 0.92 (95% confidence interval (CI) = 0.81-0.98), which was higher than that of ECV_post (AUC, 0.91 (95% CI = 0.80-0.97); p = 0.60) or ECV_Δ (AUC, 0.90 (95% CI = 0.79-0.97); p = 0.61). ECV_post and ECV_Δ determined by using equilibrium contrast-enhanced CT were useful in distinguishing between pCR and non-pCR patients with LARC who received NCRT. • ECV_post and ECV_Δ (ECV_post - ECV_pre) differed significantly between the non-pCR and pCR groups. • ECV_pre cannot be used to predict the efficacy of neoadjuvant chemoradiotherapy. • ECV_post combined with ECV_Δ had the best performance with an AUC of 0.92 for predicting pCR after NCRT in LARC.