Texture Analysis as Imaging Biomarker of Tumoral Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients Studied with 3-T Magnetic Resonance

Objective: The aim of this study was to determine whether texture features of rectal cancer on T2-weighted (T2w) magnetic resonance images can predict tumoral response in patients treated with neoadjuvant chemoradiotherapy (CRT). Materials and Methods: We prospectively enrolled 15 consecutive patients (6 women, 63.2 +/- 13.4 years) with rectal cancer, who underwent pretreatment andmidtreatment 3-T magnetic resonance imaging. Treatment protocol consisted of neoadjuvant CRTwith oxaliplatin and 5-fluorouracile. Texture analysis using a filtration-histogram technique was performed using a commercial research software algorithm (TexRAD Ltd, Somerset, England, United Kingdom) on unenhanced axial T2w images by manually delineating a region of interest around the tumor outline for the largest cross-sectional area. The technique selectively filters and extracts textures at different anatomic scales followed by quantification of the histogram using kurtosis, entropy, skewness, and mean value of positive pixels. After CRT, all patients underwent complete surgical resection and the surgical specimen served as the gold standard. Results: Six patients showed pathological complete response (pCR), and 4 patients, partial response (PR). Five patients were classified as nonresponders (NRs). Pretreatment medium texture-scale quantified as kurtosis was significantly lower in the pCR subgroup in comparison with the PR+NR subgroup (P = 0.01). Midtreatment kurtosis without filtration was significantly higher in pCR in comparison with PR + NR (P = 0.045). The change in kurtosis between midtreatment and pretreatment images was significantly lower in the PR + NR subgroup compared with the pCR subgroup (P = 0.038). Pretreatment area under the receiver operating characteristic curves, to discriminate between pCR and PR + NR, was significantly higher for kurtosis (0.907, P < 0.001) compared with all other parameters. The optimal cutoff value for pretreatment kurtosis was 0.19 or less. Using this value, the sensitivity and specificity for pCR prediction were 100% and 77.8%, respectively. Conclusion: Texture parameters derived from T2w images of rectal cancer have the potential to act as imaging biomarkers of tumoral response to neoadjuvant CRT.