使用 3.0T MR 成像估计肝质子密度脂肪分数。
Estimation of hepatic proton-density fat fraction by using MR imaging at 3.0 T.
机构信息
Department of Radiology, University of California at San Diego, 408 Dickinson St, San Diego, CA 92103-8592, USA.
出版信息
Radiology. 2011 Mar;258(3):749-59. doi: 10.1148/radiol.10100659. Epub 2011 Jan 6.
PURPOSE
To compare the accuracy of several magnetic resonance (MR) imaging-based methods for hepatic proton-density fat fraction (FF) estimation at 3.0 T, with spectroscopy as the reference technique.
MATERIALS AND METHODS
This prospective study was institutional review board approved and HIPAA compliant. Informed consent was obtained. One hundred sixty-three subjects (39 with known hepatic steatosis, 110 with steatosis risk factors, 14 without risk factors) underwent proton MR spectroscopy and non-T1-weighted gradient-echo MR imaging of the liver. At spectroscopy, the reference FF was determined from frequency-selective measurements of fat and water proton densities. At imaging, FF was calculated by using two-, three-, or six-echo methods, with single-frequency and multifrequency fat signal modeling. The three- and six-echo methods corrected for T2*; the two-echo methods did not. For each imaging method, the fat estimation accuracy was assessed by using linear regression between the imaging FF and spectroscopic FF. Binary classification accuracy of imaging was assessed at four reference spectroscopic thresholds (0.04, 0.06, 0.08, and 0.10 FF).
RESULTS
Regression intercept of two-, three-, and six-echo methods were -0.0211, 0.0087, and -0.0062 (P <.001 for all three) without multifrequency modeling and -0.0237 (P <.001), 0.0022, and -0.0007 with multifrequency modeling, respectively. Regression slope of two-, three-, and six-echo methods were 0.8522, 0.8528, and 0.7544 (P <.001 for all three) without multifrequency modeling and 0.9994, 0.9775, and 0.9821 with multifrequency modeling, respectively. Significant deviation of intercept and slope from 0 and 1, respectively, indicated systematic error. Classification accuracy was 82.2%-90.1%, 93.9%-96.3%, and 83.4%-89.6% for two-, three-, and six-echo methods without multifrequency modeling and 88.3%-92.0%, 95.1%-96.3%, and 94.5%-96.3% with multifrequency modeling, respectively, depending on the FF threshold. T2*-corrected (three- and six-echo) multifrequency imaging methods had the overall highest FF estimation and classification accuracy. Among methods without multifrequency modeling, the T2-corrected three-echo method had the highest accuracy.
CONCLUSION
Non-T1-weighted MR imaging with T2 correction and multifrequency modeling helps accurately estimate hepatic proton-density FF at 3.0 T.
目的
比较几种基于磁共振（MR）的方法在 3.0T 下测量肝脏质子密度脂肪分数（FF）的准确性，以波谱法作为参考技术。
材料与方法
本前瞻性研究经机构审查委员会批准并符合 HIPAA 规定。获得了知情同意。163 例患者（39 例已知有肝脂肪变性，110 例有脂肪变性危险因素，14 例无危险因素）接受了质子 MR 波谱和肝脏非 T1 加权梯度回波 MR 成像检查。在波谱法中，参考 FF 是通过对脂肪和水质子密度的频率选择测量来确定的。在成像中，通过使用双、三或六回波方法，以及单频和多频脂肪信号建模来计算 FF。三回波和六回波方法校正了 T2*；而双回波方法没有校正。对于每种成像方法，通过线性回归评估成像 FF 与波谱 FF 之间的脂肪估计准确性。在四个参考波谱阈值（0.04、0.06、0.08 和 0.10 FF）下评估成像的二分类准确性。
结果
无多频建模时，双、三、六回波方法的回归截距分别为-0.0211、0.0087 和-0.0062（均<0.001），有模型时分别为-0.0237（<0.001）、0.0022 和-0.0007。无多频建模时，双、三、六回波方法的回归斜率分别为 0.8522、0.8528 和 0.7544（均<0.001），有模型时分别为 0.9994、0.9775 和 0.9821。无多频建模时，双、三、六回波方法的截距和斜率均显著偏离 0 和 1，表明存在系统误差。二分类准确性分别为无多频建模时双、三、六回波方法的 82.2%-90.1%、93.9%-96.3%和 83.4%-89.6%，有模型时分别为 88.3%-92.0%、95.1%-96.3%和 94.5%-96.3%，取决于 FF 阈值。T2*-校正（三、六回波）多频成像方法具有总体上最高的 FF 估计和分类准确性。在无多频建模的方法中，T2 校正的三回波方法具有最高的准确性。
结论
3.0T 时，非 T1 加权 MR 成像结合 T2 校正和多频建模有助于准确测量肝脏质子密度 FF。
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