Quantitative analysis of diffusion-weighted magnetic resonance images: differentiation between prostate cancer and normal tissue based on a computer-aided diagnosis system

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• 作者：Ge Gao ; Chengyan Wang ; Xiaodong Zhang ; Juan Hu ; Xuedong Yang…
• 关键词：prostate cancer ; magnetic resonance imaging ; DWI ; diagnosis ; computer ; assisted ; prostate imaging ; reporting and data system (PI ; RADS)
• 刊名：Science China Life Sciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：60
• 期：1
• 页码：37-43
• 全文大小：
• 刊物主题：Life Sciences, general;
• 出版者：Science China Press
• ISSN：1869-1889
• 卷排序：60

文摘

Diffusion-weighted imaging (DWI) is considered to be one of the dominant modalities used in prostate cancer (PCa) detection and the assessment of lesion aggressiveness, especially for peripheral zone (PZ) PCa. Computer-aided diagnosis (CAD), which is capable of automatically extracting and evaluating image features, can integrate multiple parameters and improve the detection of PCa. In this study, 13 quantitative image features were extracted from DWI by CAD, and diagnostic efficacy was analyzed in both the PZ and transition zone (TZ). The results demonstrated that there was a significant difference (P<0.05) between PCa and non-PCa for nine of the 13 features in the PZ and five of the 13 features in the TZ. Besides, the prediction outcome of CAD had a strong correlation with the DWI scores that were graded by experienced radiologists according to the Prostate Imaging-Reporting and Data System Version 2 (PI-RADS v2).