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

威尔科克森符号秩检验 动态增强MRI 计算机科学 时间分辨率 图像分辨率 迭代重建 人工智能 参数统计 数学 计算机视觉 算法 核医学 磁共振成像 统计 物理 放射科 光学 医学 曼惠特尼U检验
作者
Yousef Mazaheri,Nathanael Kim,Yulia Lakhman,Ramin Jafari,Alberto Vargas,Ricardo Otazo
出处
期刊:NMR in Biomedicine [Wiley]
卷期号:35 (7) 被引量:1
标识
DOI:10.1002/nbm.4718
摘要

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 pharmacokinetic (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 [ K trans ], fractional volume of the extravascular extracellular space [ v e ], and blood plasma volume fraction [ v p ]) 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 K trans and v e , and less than 11% in the estimation of v p . 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.
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