Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.
Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.
Magn Reson Imaging. 2021 Jun;79:103-111. doi: 10.1016/j.mri.2021.03.013. Epub 2021 Mar 20.
T-weighted, two-point Dixon fast-spin-echo (FSE) is an effective technique for magnetic resonance neurography (MRN) that can provide quantitative assessment of muscle denervation. Low signal-to-noise ratio and inadequate fat suppression, however, can impede accurate interpretation.
To quantify effects of principal component analysis (PCA) denoising on tissue signal intensities and fat fraction (FF) and to determine qualitative image quality improvements from both denoising and water-weighting (WW) algorithms to improve nerve conspicuity and fat suppression.
Prospective.
Twenty-one subjects undergoing MR neurography evaluation (11/10 male/female, mean age = 46.3±13.7 years) with 60 image volumes. Twelve subjects (23 image volumes) were determined to have muscle denervation based on diffusely elevated T signal intensity.
FIELD STRENGTH/SEQUENCE: 3 T, 2D, two-point Dixon FSE.
Qualitative assessment included overall image quality, nerve conspicuity, fat suppression, pulsation and ringing artifacts by 3 radiologists separately on a three-point scale (1 = poor, 2 = average, 3 = excellent). Quantitative measurements for FF and signal intensity relative to normal muscle were made for nerve, abnormal muscle and subcutaneous fat.
Linear and ordinal regression models were used for quantitative and qualitative comparisons, respectively; 95% confidence intervals (CIs) and p-values for pairwise comparisons were adjusted using the Holm-Bonferroni method. Inter-rater agreement was assessed using Gwet's agreement coefficient (AC).
Simulations showed PCA-denoising reduced FF error from 2.0% to 1.0%, and from 7.6% to 3.1% at noise levels of 10% and 30%, respectively. In human subjects, PCA-denoising did not change signal levels and FF quantitatively. WW decreased fat signal significantly (-83.6%, p < 0.001). Nerve conspicuity was improved by WW (odds ratio, OR = 5.8, p < 0.001). Fat suppression was improved by both PCA (OR = 3.6, p < 0.001) and WW (OR = 2.2, p < 0.001). Overall image quality was improved by PCA + WW (OR = 1.7, p = 0.04).
WW and PCA-denoising improved nerve conspicuity and fat suppression in MR neurography. Denoising can potentially provide improved accuracy of FF maps for assessing fat-infiltrated muscle.
T 加权、两点 Dixon 快速自旋回波（FSE）是一种用于磁共振神经成像（MRN）的有效技术，可提供肌肉失神经支配的定量评估。然而，低信噪比和脂肪抑制不足会阻碍准确的解释。
定量分析主成分分析（PCA）去噪对组织信号强度和脂肪分数（FF）的影响，并确定去噪和水加权（WW）算法对提高神经显影和脂肪抑制的定性图像质量的改善。
前瞻性。
21 名接受 MR 神经成像评估的受试者（11/10 名男性/女性，平均年龄 46.3±13.7 岁），共 60 个图像容积。根据弥漫性升高的 T 信号强度，12 名受试者（23 个图像容积）被确定为肌肉失神经支配。
磁场强度/序列：3T、2D、两点 Dixon FSE。
定性评估包括三位放射科医生分别对整体图像质量、神经显影、脂肪抑制、搏动和振铃伪影进行的三分制评估（1=差，2=一般，3=优）。对神经、异常肌肉和皮下脂肪进行 FF 和相对于正常肌肉的信号强度的定量测量。
分别使用线性和有序回归模型进行定量和定性比较；使用 Holm-Bonferroni 方法调整 95%置信区间（CI）和两两比较的 p 值。使用 Gwet 的一致性系数（AC）评估组内一致性。
模拟显示 PCA 去噪将 FF 误差从 2.0%降低到 1.0%，从 7.6%降低到 3.1%，噪声水平分别为 10%和 30%。在人体受试者中，PCA 去噪对信号水平和 FF 无明显影响。WW 显著降低脂肪信号（-83.6%，p<0.001）。WW 提高了神经显影（比值比，OR=5.8，p<0.001）。PCA（OR=3.6，p<0.001）和 WW（OR=2.2，p<0.001）都改善了脂肪抑制。PCA+WW 提高了整体图像质量（OR=1.7，p=0.04）。
WW 和 PCA 去噪提高了 MR 神经成像中的神经显影和脂肪抑制。去噪可能会提高评估脂肪浸润肌肉的 FF 图的准确性。
