Ziayee Farid, Mueller-Lutz Anja, Gross Janina, Ullrich Tim, Quentin Michael, Arsov Christian, Antoch Gerald, Wittsack Hans-Jörg, Schimmöller Lars
Department of Diagnostic and Interventional Radiology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Department of Urology, University Dusseldorf, Faculty of Medicine, Dusseldorf, Germany.
Diagn Interv Radiol. 2022 Mar;28(2):108-114. doi: 10.5152/dir.2022.19512.
PURPOSE This study aims to analyze the ability of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to distinguish between prostate cancer (PCa) and benign lesions in transition zone (TZ) and peripheral zone (PZ) using different methods for arterial input function (AIF) determination. Study endpoints are identification of a standard AIF method and optimal quantitative perfusion parameters for PCa detection. METHODS DCE image data of 50 consecutive patients with PCa who underwent multiparametric MRI were analyzed retrospectively with three different methods of AIF acquisition. First, a region of interest was manually defined in an artery (AIFm); second, an automated algorithm was used (AIFa); and third, a population-based AIF (AIFp) was applied. Values of quantitative parameters after Tofts (Ktrans, ve, and kep) in PCa, PZ, and TZ in the three different AIFs were analyzed. RESULTS Ktrans and kep were significantly higher in PCa than in benign tissue independent from the AIF method. Whereas in PZ, Ktrans and kep could differentiate PCa (P < .001), in TZ only kep using AIFpdemonstrated a significant difference (P = .039). The correlations of the perfusion parameters that resulted from AIFm and AIFa were higher than those that resulted from AIFp, and the absolute values of Ktrans, kep, and ve were significantly lower when using AIFp. The values of quantitative perfusion parameters for PCa were similar regardless of whether PCa was located in PZ or TZ. CONCLUSION Ktrans and kep were able to differentiate PCa from benign PZ independent of the AIF method. AIFaseems to be the most feasible method of AIF determination in clinical routine. For TZ, none of the quantitative perfusion parameters provided satisfying results.
目的 本研究旨在分析定量动态对比增强磁共振成像(DCE-MRI)使用不同方法确定动脉输入函数(AIF)来区分前列腺癌(PCa)与移行区(TZ)和外周区(PZ)良性病变的能力。研究终点是确定用于PCa检测的标准AIF方法和最佳定量灌注参数。方法 回顾性分析50例接受多参数MRI检查的连续PCa患者的DCE图像数据,采用三种不同的AIF采集方法。首先,在动脉中手动定义感兴趣区域(AIFm);其次,使用自动算法(AIFa);第三,应用基于人群的AIF(AIFp)。分析三种不同AIF下PCa、PZ和TZ中Tofts模型(Ktrans、ve和kep)后的定量参数值。结果 无论采用何种AIF方法,PCa中的Ktrans和kep均显著高于良性组织。在PZ中,Ktrans和kep能够区分PCa(P <.001),而在TZ中,仅使用AIFp时kep显示出显著差异(P =.039)。AIFm和AIFa得出的灌注参数相关性高于AIFp得出的相关性,使用AIFp时Ktrans、kep和ve的绝对值显著更低。无论PCa位于PZ还是TZ,其定量灌注参数值相似。结论 无论采用何种AIF方法,Ktrans和kep均能将PCa与良性PZ区分开来。AIFa似乎是临床常规中最可行的AIF确定方法。对于TZ,没有一个定量灌注参数能提供令人满意的结果。