Huang Wei, Chen Yiyi, Fedorov Andriy, Li Xia, Jajamovich Guido H, Malyarenko Dariya I, Aryal Madhava P, LaViolette Peter S, Oborski Matthew J, O'Sullivan Finbarr, Abramson Richard G, Jafari-Khouzani Kourosh, Afzal Aneela, Tudorica Alina, Moloney Brendan, Gupta Sandeep N, Besa Cecilia, Kalpathy-Cramer Jayashree, Mountz James M, Laymon Charles M, Muzi Mark, Kinahan Paul E, Schmainda Kathleen, Cao Yue, Chenevert Thomas L, Taouli Bachir, Yankeelov Thomas E, Fennessy Fiona, Li Xin
Oregon Health and Science University, Portland, OR.
Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Tomography. 2019 Mar;5(1):99-109. doi: 10.18383/j.tom.2018.00027.
This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate K (volume transfer rate constant), v (extravascular, extracellular volume fraction), k (efflux rate constant), and τ (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for K, v, k, and τ, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in K and v (wCV = 0.50 and 0.10, respectively), but had smaller effects on k and τ (wCV = 0.39 and 0.22, respectively). k is less sensitive to AIF variation than K, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τ parameter may have advantages over the conventional PK parameters in a longitudinal study.
这项多中心研究使用快门速度模型（SSM）评估了动脉输入函数（AIF）测定的变化对动态对比增强磁共振成像（DCE-MRI）数据药代动力学（PK）分析的影响。从11名前列腺癌患者获取的数据在9个中心之间共享。每个中心使用特定于该站点的方法从每个数据集中测量个体AIF，并将结果提交给管理中心。管理中心使用这些AIF、其参考组织调整后的变体以及文献中的人群平均AIF进行SSM PK分析，以估计K（容积转移速率常数）、v（血管外细胞外容积分数）、k（流出速率常数）和τ（平均细胞内水寿命）。所有其他变量，包括感兴趣肿瘤区域的定义和对比前T值，均保持相同，以评估仅由AIF变化引起的参数变化。使用未调整的AIF时，观察到PK参数有相当大的变化，K、v、k和τ的受试者内变异系数（wCV）值分别为0.58、0.27、0.42和0.24。使用参考组织调整后的AIF减少了K和v的变化（wCV分别为0.50和0.10），但对k和τ的影响较小（wCV分别为0.39和0.22）。k对AIF变化的敏感性低于K，表明它可能是前列腺微血管更稳健的成像生物标志物。由于对AIF不确定性的敏感性较低，SSM特有的τ参数在纵向研究中可能比传统的PK参数具有优势。
