Dynamic contrast-enhanced MRI parametric mapping using high spatiotemporal resolution Golden-angle RAdial Sparse Parallel MRI and iterative joint estimation of the arterial input function and pharmacokinetic parameters.
Dynamic contrast-enhanced MRI parametric mapping using high spatiotemporal resolution Golden-angle RAdial Sparse Parallel MRI and iterative joint estimation of the arterial input function and pharmacokinetic parameters.
复制标题
使用高时空分辨率黄金角RAdial稀疏并行MRI和动脉输入函数和药代动力学参数的迭代联合估计进行动态对比增强MRI参数标测。
作者：
这项工作的目的是开发一种数据驱动的定量动态对比增强（DCE）MRI技术，使用具有高空间分辨率和高灵活时间分辨率的黄金角RAdial稀疏并行（GRASP）MRI和药物动力学（PK）分析，直接从每个患者获得的数据估计动脉输入函数（AIF）。DCE-MRI使用3-T MRI扫描仪对13例妇科恶性肿瘤患者进行了单次连续黄金角堆叠星采集和两种时间分辨率的图像重建，通过利用GRASP中的独特功能，以用户定义的时间分辨率重建采集的数据。采用在AIF和PK估计之间交替的迭代算法进行AIF（AIF形状和延迟）和PK参数的联合估计。进行计算机模拟以确定估计参数的准确度（表示为误差百分比[PE]）和精密度。使用群体平均和数据驱动AIF测量PK参数（体积转移常数[Ktranss]、血管外细胞外间隙体积分数[ve]和血浆体积分数[vp]）和肿瘤造影剂动力学数据拟合误差的归一化均方根误差[nRMSE]（%）。根据患者数据，进行Wilcoxon符号秩检验以比较nRMSE。模拟结果表明，GRASP图像重建的时间分辨率为1秒/帧的AIF估计和5秒/帧的PK分析导致的绝对PE小于5%的Ktranss和ve的估计，和小于11%的估计vp。双时间分辨率图像重建和数据驱动AIF的nRMSE（平均值± SD）为0.16 ± 0.04，而使用群体平均AIF的1 s/帧为0.27 ± 0.10（p < 0.001），使用群体平均AIF的5 s/帧为0.23 ± 0.07（p < 0.001）。我们的结论是，DCE-MRI数据采集和重建的GRASP技术在双时间分辨率可以成功地应用于联合估计AIF和PK参数从一个单一的采集数据驱动的AIF和voxelwise PK参数图。
The aim of this work is to develop a data-driven quantitative dynamic contrast-enhanced (DCE) MRI technique using Golden-angle RAdial Sparse Parallel (GRASP) MRI with high spatial resolution and high flexible temporal resolution and pharmaco-kinetic (PK) analysis with an arterial input function (AIF) estimated directly from the data obtained from each patient. DCE-MRI was performed on 13 patients with gynecological malignancy using a 3-T MRI scanner with a single continuous golden-angle stack-of-stars acquisition and image reconstruction with two temporal resolutions, by exploiting a unique feature in GRASP that reconstructs acquired data with user-defined temporal resolution. Joint estimation of the AIF (both AIF shape and delay) and PK parameters was performed with an iterative algorithm that alternates between AIF and PK estimation. Computer simulations were performed to determine the accuracy (expressed as percentage error [PE]) and precision of the estimated parameters. PK parameters (volume transfer constant [Ktrans], fractional volume of the extravascular extracellular space [ve], and blood plasma volume fraction [vp]) and normalized root-mean-square error [nRMSE] (%) of the fitting errors for the tumor contrast kinetic data were measured both with population-averaged and data-driven AIFs. On patient data, the Wilcoxon signed-rank test was performed to compare nRMSE. Simulations demonstrated that GRASP image reconstruction with a temporal resolution of 1 s/frame for AIF estimation and 5 s/frame for PK analysis resulted in an absolute PE of less than 5% in the estimation of Ktrans and ve, and less than 11% in the estimation of vp. The nRMSE (mean ± SD) for the dual temporal resolution image reconstruction and data-driven AIF was 0.16 ± 0.04 compared with 0.27 ± 0.10 (p < 0.001) with 1 s/frame using population-averaged AIF, and 0.23 ± 0.07 with 5 s/frame using population-averaged AIF (p < 0.001). We conclude that DCE-MRI data acquired and reconstructed with the GRASP technique at dual temporal resolution can successfully be applied to jointly estimate the AIF and PK parameters from a single acquisition resulting in data-driven AIFs and voxelwise PK parametric maps.
登录
查看更多内容
影响因子：
3.3
作者：
Feng, Li;Grimm, Robert;Block, Kai Tobias;Chandarana, Hersh;Kim, Sungheon;Xu, Jian;Axel, Leon;Sodickson, Daniel K.;Otazo, Ricardo
通讯作者：
Otazo, Ricardo
影响因子：
6.7
作者：
Chandarana H;Block TK;Ream J;Mikheev A;Sigal SH;Otazo R;Rusinek H
通讯作者：
Rusinek H
影响因子：
4.4
作者：
Planey, Catherine R.;Welch, E. Brian;Xu, Lei;Chakravarthy, A. Bapsi;Gatenby, J. Christopher;Freehardt, Darla;Mayer, Ingrid;Meszeoly, Ingrid;Kelley, Mark;Means-Powell, Julie;Gore, John C.;Yankeelov, Thomas E.
通讯作者：
Yankeelov, Thomas E.
影响因子：
3.3
作者：
Buckley, David L.;Kershaw, Lucy E.;Stanisz, Greg J.
通讯作者：
Stanisz, Greg J.
影响因子：
2.6
作者：
Jackson, A. S. N.;Reinsberg, S. A.;Dearnaley, D. P.
通讯作者：
Dearnaley, D. P.