Yoruk Umit, Saranathan Manojkumar, Loening Andreas M, Hargreaves Brian A, Vasanawala Shreyas S
Department of Radiology, Stanford University, California, USA.
Department of Electrical Engineering, Stanford University, California, USA.
Magn Reson Med. 2016 Mar;75(3):1301-11. doi: 10.1002/mrm.25731. Epub 2015 May 6.
To introduce a respiratory-gated high-spatiotemporal-resolution dynamic-contrast-enhanced MRI technique and a high-temporal-resolution aortic input function (HTR-AIF) estimation method for glomerular filtration rate (GFR) assessment in children.
A high-spatiotemporal-resolution DCE-MRI method with view-shared reconstruction was modified to incorporate respiratory gating, and an AIF estimation method that uses a fraction of the k-space data from each respiratory period was developed (HTR-AIF). The method was validated using realistic digital phantom simulations and demonstrated on clinical subjects. The GFR estimates using HTR-AIF were compared with estimates obtained by using an AIF derived directly from the view-shared images.
Digital phantom simulations showed that using the HTR-AIF technique gives more accurate AIF estimates (RMSE = 0.0932) compared with the existing estimation method (RMSE = 0.2059) that used view-sharing (VS). For simulated GFR > 27 mL/min, GFR estimation error was between 32% and 17% using view-shared AIF, whereas estimation error was less than 10% using HTR-AIF. In all clinical subjects, the HTR-AIF method resulted in higher GFR estimations than the view-shared method.
The HTR-AIF method improves the accuracy of both the AIF and GFR estimates derived from the respiratory-gated acquisitions, and makes GFR estimation feasible in free-breathing pediatric subjects.
介绍一种呼吸门控的高时空分辨率动态对比增强磁共振成像（MRI）技术以及一种用于评估儿童肾小球滤过率（GFR）的高时间分辨率主动脉输入函数（HTR-AIF）估计方法。
对采用视图共享重建的高时空分辨率动态对比增强MRI方法进行修改以纳入呼吸门控，并开发了一种使用每个呼吸周期一部分k空间数据的主动脉输入函数估计方法（HTR-AIF）。该方法通过逼真的数字体模模拟进行验证，并在临床受试者中进行展示。将使用HTR-AIF获得的GFR估计值与通过直接从视图共享图像得出的主动脉输入函数获得的估计值进行比较。
数字体模模拟表明，与使用视图共享（VS）的现有估计方法（均方根误差[RMSE]=0.2059）相比，使用HTR-AIF技术可得出更准确的主动脉输入函数估计值（RMSE=0.0932）。对于模拟的GFR>27 mL/min，使用视图共享主动脉输入函数时GFR估计误差在32%至17%之间，而使用HTR-AIF时估计误差小于10%。在所有临床受试者中，HTR-AIF方法得出的GFR估计值高于视图共享方法。
HTR-AIF方法提高了从呼吸门控采集中得出的主动脉输入函数和GFR估计值的准确性，并使在自由呼吸的儿科受试者中进行GFR估计成为可能。
