Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW 2006, Australia.
Centre for Medical Image Computing, University College London, London WC1E 6BT, UK.
Diagnostics (Basel). 2016 May 27;6(2):21. doi: 10.3390/diagnostics6020021.
Diffusion-weighted imaging (DWI) is the most effective component of the modern multi-parametric magnetic resonance imaging (mpMRI) scan for prostate pathology. DWI provides the strongest prediction of cancer volume, and the apparent diffusion coefficient (ADC) correlates moderately with Gleason grade. Notwithstanding the demonstrated cancer assessment value of DWI, the standard measurement and signal analysis methods are based on a model of water diffusion dynamics that is well known to be invalid in human tissue. This review describes the biophysical limitations of the DWI component of the current standard mpMRI protocol and the potential for significantly improved cancer assessment performance based on more sophisticated measurement and signal modeling techniques.
扩散加权成像(DWI)是现代多参数磁共振成像(mpMRI)扫描中用于前列腺病理的最有效组成部分。DWI 可对肿瘤体积进行最强预测,表观扩散系数(ADC)与 Gleason 分级有中度相关性。尽管 DWI 的癌症评估价值已得到证实,但标准的测量和信号分析方法基于众所周知在人体组织中无效的水扩散动力学模型。本综述描述了当前标准 mpMRI 方案中 DWI 成分的生物物理局限性,以及基于更复杂的测量和信号建模技术显著提高癌症评估性能的潜力。