Tumor compactness improves the preoperative volumetry-based prediction of the pathological complete response of rectal cancer after preoperative concurrent chemoradiotherapy.

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Tumor compactness improves the preoperative volumetry-based prediction of the pathological complete response of rectal cancer after preoperative concurrent chemoradiotherapy.

Oncotarget. 2016 Dec 10;:

Authors: Hsu CY, Wang CW, Kuo CC, Chen YH, Lan KH, Cheng AL, Kuo SH

Abstract
In addition to clinical factors (tumor and node stage) and treatment factors (equivalent radiotherapy dose and chemotherapy regimen), we assessed whether different performances of various tumor volume measurements help predict the pathological complete response (pCR) of locally advanced rectal cancer (LARC) after preoperative concurrent chemoradiotherapy (CCRT). A total of 122 patients with LARC treated with a long course of CCRT, between December 2009 and March 2015, were enrolled in this bi-institutional study. Tumor delineation was based on standard T2-weighted magnetic resonance imaging or contrast-enhanced computed tomography before CCRT. Tumor compactness was defined as the ratio of the volume and the surface area. The tumor compactness-corrected TV (TCTV) was defined as the ratio of the real TV (RTV) and tumor compactness. Twenty-three (18.9%) patients had a pCR. Areas under the curve of the receiver operating characteristic for pCR prediction calculated using the RTV, cylindrical approximated TV (CATV), and TCTV were 0.724, 0.747, and 0.780, respectively. The prediction performance of TCTV was significantly more efficient than that of both RTV (P = 0.0057) and CATV (P = 0.0329). Multivariate logistic regression analysis revealed tumor compactness (P = 0.001), RTV (P = 0.042), and preoperative clinical nodal status (P = 0.044) as significant predictors of a pCR. In addition, poor tumor compactness was closely associated with lymphovascular space invasion (P = 0.008) and pathological nodal status (P = 0.003). For patients with LARC receiving preoperative CCRT, tumor compactness is a useful radiomic parameter for improving the volumetric based prediction model.

PMID: 27974702 [PubMed - as supplied by publisher]

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