Sen Snigdha, Valindria Vanya, Slator Paddy J, Pye Hayley, Grey Alistair, Freeman Alex, Moore Caroline, Whitaker Hayley, Punwani Shonit, Singh Saurabh, Panagiotaki Eleftheria
Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK.
Molecular Diagnostics and Therapeutics Group, University College London, London WC1E 6BT, UK.
Diagnostics (Basel). 2022 Jul 5;12(7):1631. doi: 10.3390/diagnostics12071631.
False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer—true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)—false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular−extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.
多参数磁共振成像(mp-MRI)的假阳性结果导致许多患有临床意义不显著疾病的男性接受了不必要的侵入性活检。本研究调查了定量扩散MRI是否能够非侵入性地区分假阳性、真阳性和正常组织。38名患者接受了mp-MRI和肿瘤细胞计数的血管、细胞外和受限扩散磁共振成像(VERDICT MRI),随后进行经会阴活检。活检后患者被分为两组:(1)显著癌症——真阳性,19例患者;(2)萎缩/炎症/高级别前列腺上皮内瘤变(PIN)——假阳性,19例患者。获取临床表观扩散系数(ADC)值,并通过深度学习拟合体素内不相干运动(IVIM)、扩散峰度成像(DKI)和VERDICT模型。在ADC、IVIM灌注分数(f)和扩散率(D)、DKI扩散率(DK)(p<0.0001)和峰度(K)以及VERDICT细胞内体积分数(fIC)、细胞外-血管外体积分数(fEES)和扩散率(dEES)值方面,真阳性和假阳性病变之间存在显著差异(p<0.05)。在VERDICT fIC(p = 0.004)和IVIM D方面,假阳性与正常组织之间存在显著差异。这些结果表明,基于模型的扩散MRI可以减少因前列腺病变假阳性导致的不必要活检,并对良性疾病显示出有前景的敏感性。