Magnetic resonance based texture parameters as potential imaging biomarkers for predicting long-term survival in locally advanced rectal cancer treated by chemoradiotherapy
Published on Apr 1, 2017in Colorectal Disease2.769
· DOI :10.1111/CODI.13496
Aim The study aimed to investigate whether textural features of rectal cancer on magnetic resonance imaging (MRI) can predict long term survival in patients treated with long-course chemoradiotherapy. Method Textural analysis (TA) using a filtration-histogram technique of T2-weighted pre- and six-week post chemoradiotherapy MRI was undertaken using TexRAD, a proprietary software algorithm. Regions of interest enclosing the largest cross-sectional area of the tumour were manually delineated on the axial images and filtration-step extracted features at different anatomical scales (fine, medium, and coarse) followed by quantification of statistical features (mean intensity, standard-deviation, entropy, skewness, kurtosis and mean of positive pixels [MPP]) using histogram analysis. Cox multiple regression analysis determined which univariate features including textural, radiological and histological, independently predicted overall survival (OS), disease free survival (DFS) and recurrence-free survival (RFS). Results MPP (fine-texture, HR: 6.9, 95% CI [2.43–19.55], p= <0.001), mean (medium-texture, HR: 5.6 [1.4-21.7], p=0.007) and extramural venous invasion (EMVI) on MRI (HR: 2.96, [1.04–8.37], p=0.041) independently predicted OS while mean (medium texture, HR: 4.53, [1.58–12.94], p=0.003), MPP (fine texture, HR: 3.36 [1.36–8.31], p=0.008) and threatened circumferential resection margin (CRM) on MRI (HR: 3.1 [1.01–9.46], p=0.046) predicted DFS. For OS; EMVI on MRI (HR: 4.23 [1.41-12.69], p=0.01) and for DFS; kurtosis (medium-texture, HR: 3.97 [1.44–10.94], p=0.007) and CRM involvement on MRI (HR: 3.36 [1.21–9.32], p=0.02) were the independent post-treatment factors. Only TA independently predicted RFS on pre- or post-treatment analyses. Conclusion MR based TA of rectal cancers can predict outcome before undergoing surgery and could potentially select patients for individualized therapy. This article is protected by copyright. All rights reserved.