Rapid automated liver quantitative susceptibility mapping
Rapid automated liver quantitative susceptibility mapping
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DOI：
10.1002/jmri.26632
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发表时间：
2019-09-01
影响因子：
4.4
通讯作者：
Wang, Yi
中科院分区：
文献类型：
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作者：
Jafari, Ramin;Sheth, Sujit;Wang, Yi
背景：需要准确测量肝脏铁浓度（LIC），以指导铁螯合治疗输血性铁超载患者。在这项工作中，我们研究的可行性，自动化定量易感性映射（QSM）来衡量LIC。目的建立一种快速、可靠、自动化的肝脏定量分析方法。研究类型前瞻性。人群13例健康受试者和22例患者。场强/序列1.5 T和3 T/3D多回波梯度回波（GRE）序列。使用3D GRE序列采集评估数据，回波间隔彼此异相。在执行QSM之前，使用所有同相（IP）的奇数回波来初始化脂肪-水分离和场估计（T-2*-IDEAL）。肝脏QSM通过自动化管道生成，无需手动干预。在健康受试者（n = 5）中，将这种基于IP回波的初始化方法与现有的图形切割初始化方法（同时相位展开和化学位移去除，SPURS）进行了比较。使用健康受试者（n = 8），在两个制造商的两种场强下，在四台扫描仪上评估生殖能力。在患者（n = 22）中评价了临床可行性。使用配对t检验和线性回归分析比较健康受试者和患者的IP和SPURS初始化方法，以评估处理时间和感兴趣区域（ROI）测量值。使用线性回归、Bland-Altman分析和组内相关系数（ICC）评估四种不同扫描仪之间QSM、R-2* 和质子密度脂肪分数（PDFF）的再现性。结果使用IP方法的肝脏QSM在初始化T-2*-IDEAL时比SPURS快约5.5倍（P < 0.05），且输出相似。在所有四台扫描仪中可重复生成使用IP方法的肝脏QSM（平均决定系数0.95，平均斜率0.90，平均偏倚0.002 ppm，95%一致性限值在-0.06至0.07 ppm之间，ICC 0.97）。数据结论使用基于IP回波的初始化能够实现稳健的水/脂肪分离和场估计，用于临床应用的自动化、快速和可再现的肝脏QSM。技术功效：第2阶段J. Magn. Reson。Imaging 2019;50：725-732.
Background Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC. Purpose To develop a rapid, robust, and automated liver QSM for clinical practice. Study Type Prospective. Population 13 healthy subjects and 22 patients. Field Strength/Sequences 1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence. Assessment Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T-2*-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22). Statistical Tests IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R-2*, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC). Results Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T-2*-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97). Data Conclusion Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications. Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.