• Zhao Zhang, Huazhi Xu, Yingnan Xue, Jiance Li, and Qiong Ye.
• Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, ZheJiang Province, P.R. China.
• J Magn Reson Imaging. 2019 Feb 1; 49 (2): 556-564.

BackgroundThe effectiveness of quantitative MRI and clinical information in the risk stratification of prostate cancer (PCa) patients was evaluated separately in previous research; however, the differentiation power of combining quantitative MRI and clinical information has yet to be investigated.PurposeTo investigate the power of combining histogram analysis of apparent diffusion coefficient (ADC) of tumor diffusion volume (tDv) with clinical information for the differentiation of low-grade (Gleason score [GS] ≤6) and high-grade (GS ≥7) PCa.Study TypeRetrospective.PopulationFifty-nine PCa patients who underwent preoperative diffusion-weighted imaging (DWI) (acquired with b = 0, 1000 mm2 /s) and followed by radical prostatectomy within 6 months.SequencesT2 -weighted, DWI, and ADC images at 3.0T.AssessmenttDv defined with different ADC thresholds were analyzed for each patient and combined with age and prostate-specific antigen (PSA) level. Binary logistic regression with backward feature selection was applied to determine the best discrimination and corresponding combination of parameters.Statistical TestsKolmogorov-Smirnov test; independent samples t-test; Mann-Whitney U-test; Spearman's rank correlation; receiver operating characteristic (ROC) analysis; binary logistical regression.ResultsPSA and the 10th percentile ADC value of tDv defined with different diffusion thresholds were significantly different between low-grade and high-grade PCa groups (P < 0.05 for all). Median ADC of tDv based on a threshold of 1.008 × 10-3 mm2 /s exhibited the best performance (AUC = 0.86, 95% confidence interval [CI]: 0.75-0.94), whereas binary logistic regression with backward feature selection achieved 97.20% accuracy with AUC = 0.978 (95% CI: 0.929-0.997).Data ConclusionThe discriminatory power of a single histogram variable of ADC in tDv was not significantly superior to that of a single clinical parameter. The combination of histogram analysis of ADC of tDv and clinical information using logistic regression might significantly improve the risk stratification of PCa and achieve reasonably high accuracy.Level Of Evidence4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:556-564.© 2018 International Society for Magnetic Resonance in Medicine.

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