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De Cecco, Carlo N.; Ciolina, Maria; Caruso, Damiano; Rengo, Marco; Ganeshan, Balaji; Meinel, Felix G.; Musio, Daniela; De Felice, Francesca; Tombolini, Vincenzo and Laghi, Andrea (2016): Performance of diffusion-weighted imaging, perfusion imaging, and texture analysis in predicting tumoral response to neoadjuvant chemoradiotherapy in rectal cancer patients studied with 3T MR: initial experience. In: Abdominal Radiology, Vol. 41, No. 9: pp. 1728-1735

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To determine the performance of texture analysis (TA), diffusion-weighted imaging, and perfusion MR (pMRI) in predicting tumoral response in patients treated with neoadjuvant chemoradiotherapy (CRT). 12 consecutive patients (8 females, 4 males, 63.2 +/- 13.4 years) with rectal cancer were prospectively enrolled, and underwent pre-treatment 3T MRI. Treatment protocol consisted of neoadjuvant CRT with oxaliplatin and 5-fluorouracile. Unenhanced T2-weighted images TA (kurtosis), apparent diffusion coefficient (ADC), and pMRI parameters (Ktrans, Kep, Ve, IAUGC) were quantified by manually delineating a region of interest around the tumor outline. After CRT, all patients underwent complete surgical resection and the surgical specimen served as the gold standard. Receiver operating characteristic (ROC) curve analysis was performed to assess the discriminatory power of each quantitative parameter to predict complete response. Pathological complete response (pCR) was reported in six patients and partial response (PR) in three patients. Three patients were classified as non-responders (NR). Pre-treatment kurtosis was significantly lower in the pCR sub-group in comparison with PR + NR (p = .01). Among ADC and pMRI parameters, only Ve was significantly lower in the pCR sub-group compared with PR + NR (p = .01). A significant negative correlation between kurtosis and ADC (r = -0.650, p = .022) was observed. Pre-treatment area under the ROC curves (AUC), to discriminate between pCR and PR + NR, was significantly higher for kurtosis (0.861, p = .001) and Ve (0.861, p = .003) compared to all other parameters. The optimal cutoff value for pre-treatment kurtosis and Ve was aecurrency sign0.19 (100% sensitivity, 67% specificity) and aecurrency sign0.311 (83% sensitivity, 83% specificity), respectively. Pre-treatment kurtosis derived from T2w images and Ve from pMRI have the potential to act as imaging biomarkers of rectal cancer response to neoadjuvant CRT.

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