Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling.
Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling.
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DOI：
10.1016/j.jmr.2016.05.018
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发表时间：
2016-08
期刊：
影响因子：
--
通讯作者：
Springer CS Jr
中科院分区：
文献类型：
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作者：
Li X;Cai Y;Moloney B;Chen Y;Huang W;Woods M;Coakley FV;Rooney WD;Garzotto MG;Springer CS Jr
动态增强磁共振成像(DCE-MRI)已广泛应用于临床。对DCE-MRI数据进行药代动力学建模，提取定量造影剂/组织特异性模型参数是目前研究最多的方法。DCE-MRI数据药代动力学分析的主要挑战之一是准确可靠地测量动脉输入功能(AIF)，这是所有药物动力学背后的驱动力。由于流入和部分容量平均等影响，从单个动脉测量的AIF有时需要进行幅度缩放，以更好地表示血液造影剂(CR)浓度的时间进程。经验方法，如盲法AIF估计或参考组织AIF推导可能是有用和实用的，特别是当成像视野(FOV)内没有清晰可见的血管时。类似地，这些方法通常也需要对导出的AIF时间进程进行幅度缩放。即使使用相同的CR注射方案，AIF也因个体不同而不同，重建基本真实AIF的理想比例因子通常尚不清楚，因此，由于不同的AIF比例因子导致的估计药代动力学参数的变化特别令人感兴趣。在这项工作中，使用模拟和真实的前列腺癌DCE-MRI数据，我们检查了与AIF分级相关的参数变化。我们的结果表明，对于快速交换极限(FXL)Tofts模型和水交换敏化的快速交换状态(FXR)模型，通常拟合的CR传递常数(KTrans)和血管外、细胞外体积分数(Ve)与AIF成正比，而FXR特有的单向细胞水外流速率常数KIO和CR血管内速率常数Kep都对AIF不敏感。这表明，对于前列腺癌和可能的其他癌症的DCE-MRI，KIO和KEP可能是更适合跨平台、多中心应用的成像生物标志物。来自我们有限研究队列的数据显示，KIO与Gleason评分相关，这表明它可能是前列腺癌疾病进展监测的有用生物标记物。
Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (Ktrans) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging biomarkers for cross-platform, multicenter applications. Data from our limited study cohort show that kio correlates with Gleason scores, suggesting that it may be a useful biomarker for prostate cancer disease progression monitoring.