Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Radiology, Duke University Medical Center, Durham, North Carolina.
Magn Reson Med. 2019 Apr;81(4):2330-2346. doi: 10.1002/mrm.27557. Epub 2018 Oct 28.
To develop a bipolar multi-echo MRI method for the accurate estimation of the adipose tissue fatty acid composition (FAC) using clinically relevant protocols at clinical field strength.
The proposed technique jointly estimates confounding factors (field map, , eddy-current phase) and triglyceride saturation state parameters by fitting multi-echo gradient echo acquisitions to a complex signal model. The noise propagation behavior was improved by applying a low-rank enforcing denoising technique and by addressing eddy-current-induced phase discrepancies analytically. The impact of the total echo train duration on the FAC parameter map accuracy was analyzed in an oil phantom at 3T. Accuracy and reproducibility assessment was based on in vitro oil phantom measurements at two field strengths (3T and 1.5T) and with two different protocols. Repeatability was assessed in vivo in patients (n = 8) with suspected fatty liver disease using test-retest acquisitions in the abdominal subcutaneous, perirenal and mesenteric fat depots.
Echo train readout durations of at least five times the conventional in-phase time were required for accurate FAC estimation in areas of high fat content. In vitro, linear regression and Bland-Altman analyses demonstrated strong (r > 0.94) and significant (P ≪ 0.01) correlations between measured and reference FACs for all acquisitions, with smaller overall intercepts and biases at 3T compared to 1.5T. In vivo, reported mean absolute differences between test and retest were 1.54%, 3.31%, and 2.63% for the saturated, mono-unsaturated, and poly-unsaturated fat component, respectively.
Accurate and reproducible MRI-based FAC quantification within a breath-hold is possible at clinical field strengths.
开发一种双极多回波 MRI 方法，以便在临床场强下使用临床相关方案准确估计脂肪组织脂肪酸组成 (FAC)。
该方法通过将多回波梯度回波采集拟合到复杂信号模型，联合估计混杂因素（场图、、涡流相位）和甘油三酯饱和度状态参数。通过应用低秩增强降噪技术和分析涡流引起的相位差异，改善了噪声传播行为。在 3T 油体模中分析了总回波列车持续时间对 FAC 参数图准确性的影响。在两个场强（3T 和 1.5T）和两个不同方案下的体外油体模测量中进行了准确性和可重复性评估。在 8 例疑似脂肪肝患者中进行了体内重复性评估，使用腹部皮下、肾周和肠系膜脂肪沉积的测试-再测试采集。
在高脂肪含量区域进行准确的 FAC 估计，需要至少五倍常规同相时间的回波列车读出时间。在体外，线性回归和 Bland-Altman 分析表明，所有采集的测量和参考 FAC 之间具有很强的相关性（r > 0.94）和显著相关性（P < 0.01），与 1.5T 相比，3T 的总体截距和偏差较小。在体内，测试和再测试之间报告的平均绝对差异分别为饱和脂肪、单不饱和脂肪和多不饱和脂肪成分的 1.54%、3.31%和 2.63%。
在临床场强下，基于 MRI 的 FAC 定量在屏气期间是准确且可重复的。
