Use of the NESMA Filter to Improve Myelin Water Fraction Mapping with Brain MRI.
Use of the NESMA Filter to Improve Myelin Water Fraction Mapping with Brain MRI.
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DOI：
10.1111/jon.12537
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发表时间：
2018-11
期刊：
影响因子：
--
通讯作者：
Spencer RG
中科院分区：
文献类型：
--
作者：
Bouhrara M;Reiter DA;Maring MC;Bonny JM;Spencer RG
髓磷脂水分数 (MWF) 绘图可以直接可视化发育中的大脑和疾病中的髓鞘形成模式。 MWF 通常通过多指数 T2 分析来测量，该分析对噪声非常敏感，导致导出的 MWF 估计值不准确。虽然在后处理过程中可以应用降噪滤波器，但传统的滤波可能会引入偏差并模糊小结构和边缘。先进的非模糊滤波器虽然有效，但表现出很高的复杂性，并且需要监督实施才能获得最佳性能。本文的目的是证明最近引入的多光谱幅度非局部估计 (NESMA) 滤波器能够极大地改进根据梯度和自旋回波 (GRASE) 成像数据确定 MWF 参数估计的能力。我们根据人脑临床 GRASE 成像数据评估了 NESMA 过滤器用于 MWF 映射的性能，并将结果与根据未过滤图像计算的结果进行了比较。对代表不同年龄的三名受试者的大脑进行了数值和体内分析。我们的结果证明了 NESMA 过滤器实现高质量体内 MWF 绘图的潜力。事实上，NESMA 允许大幅减少导出的 MWF 估计中的随机变化，同时保留细节。通过使用 NESMA 滤波器，根据 GRASE 成像数据对人脑中 MWF 的体内估计得到了显着改善。 NESMA 的使用可能有助于在临床可行的成像时间内实现高质量 MWF 绘图的目标。
Myelin water fraction (MWF) mapping permits direct visualization of myelination patterns in the developing brain and in disease. MWF is conventionally measured through multiexponential T2 analysis which is very sensitive to noise, leading to inaccuracies in derived MWF estimates. While noise reduction filters may be applied during post-processing, conventional filtering can introduce bias and obscure small structures and edges. Advanced non-blurring filters, while effective, exhibit a high level of complexity and the requirement for supervised implementation for optimal performance. The purpose of this paper is to demonstrate the ability of the recently introduced nonlocal estimation of multispectral magnitudes (NESMA) filter to greatly improve determination of MWF parameter estimates from gradient and spin echo (GRASE) imaging data. We evaluated the performance of the NESMA filter for MWF mapping from clinical GRASE imaging data of human brain, and compared the results to those calculated from unfiltered images. Numerical and in vivo analyses of the brains of three subjects, representing different ages, were conducted. Our results demonstrate the potential of the NESMA filter to permit high quality in vivo MWF mapping. Indeed, NESMA permits substantial reduction of random variation in derived MWF estimates while preserving detail. In vivo estimation of MWF in the human brain from GRASE imaging data was markedly improved through use of the NESMA filter. The use of NESMA may contribute to the goal of high quality MWF mapping in clinically feasible imaging times.
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