Haralick textural features on T2‐weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer. Issue 1 (27th June 2016)

• Record Type: Journal Article
• Authors: Gnep, Khémara; Fargeas, Auréline; Gutiérrez‐Carvajal, Ricardo E.; Commandeur, Frédéric; Mathieu, Romain; Ospina, Juan D.; Rolland, Yan; Rohou, Tanguy; Vincendeau, Sébastien; Hatt, Mathieu; Acosta, Oscar; de Crevoisier, Renaud
• Is Part Of: Journal of magnetic resonance imaging. Volume 45:Issue 1(2017)
• Page Start: 103
• Page End: 117
• Publication Date: 2016-06-27
• Subjects: magnetic resonance imaging -- prostate cancer -- radiotherapy -- T2‐weighted imaging -- radiomics -- texture analysis -- imaging biomarkers; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.25335
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Purpose: To explore the association between magnetic resonance imaging (MRI), including Haralick textural features, and biochemical recurrence following prostate cancer radiotherapy. Materials and Methods: In all, 74 patients with peripheral zone localized prostate adenocarcinoma underwent pretreatment 3.0T MRI before external beam radiotherapy. Median follow‐up of 47 months revealed 11 patients with biochemical recurrence. Prostate tumors were segmented on T 2 ‐weighted sequences ( T 2 ‐w) and contours were propagated onto the coregistered apparent diffusion coefficient (ADC) images. We extracted 140 image features from normalized T 2 ‐w and ADC images corresponding to first‐order ( n = 6), gradient‐based ( n = 4), and second‐order Haralick textural features ( n = 130). Four geometrical features (tumor diameter, perimeter, area, and volume) were also computed. Correlations between Gleason score and MRI features were assessed. Cox regression analysis and random survival forests (RSF) were performed to assess the association between MRI features and biochemical recurrence. Results: Three T 2 ‐w and one ADC Haralick textural features were significantly correlated with Gleason score ( P < 0.05). Twenty‐eight T 2 ‐w Haralick features and all four geometrical features were significantly associated with biochemical recurrence ( P < 0.05). The most relevant features were Haralick features T 2 ‐w contrast, T 2 ‐w difference variance, ADC median, along with tumor volume and tumor area (C‐index from 0.76 to 0.82; P < 0.05). By combining these most powerful features in an RSF model, the obtained C‐index was 0.90. Conclusion: T 2 ‐w Haralick features appear to be strongly associated with biochemical recurrence following prostate cancer radiotherapy. Level of Evidence: 3 J. Magn. Reson. Imaging 2017;45:103–117.