School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.
Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.
Magn Reson Med. 2019 May;81(5):3292-3303. doi: 10.1002/mrm.27600. Epub 2018 Nov 16.
In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T relaxation is a powerful and widely applied method for the quantification of the myelin water fraction (MWF). In recent literature, the MWF is most commonly estimated using a regularized nonnegative least squares algorithm.
The orthogonal matching pursuit algorithm is proposed as an alternative method for the estimation of the MWF. The orthogonal matching pursuit is a greedy sparse reconstruction algorithm with a low computation complexity. For validation, both methods are compared to a ground truth using numerical simulations and a phantom model using comparable computation times. The numerical simulations were used to measure the theoretical errors, as well as the effects of varying the SNR, strength of the regularization, and resolution of the basis set. Additionally, a phantom model was used to estimate the performance of the 2 methods while including errors occurring due to the MR measurement. Lastly, 4 healthy subjects were scanned to evaluate the in vivo performance.
The results in simulations and phantoms demonstrate that the MWFs determined with the orthogonal matching pursuit are 1.7 times more accurate as compared to the nonnegative least squares, with a comparable precision. The remaining bias of the MWF is shown to be related to the regularization of the nonnegative least squares algorithm and the Rician noise present in magnitude MR images.
The orthogonal matching pursuit algorithm provides a more accurate alternative for T relaxometry myelin water quantification.
体内髓鞘定量可以提供有价值的关于神经元成熟和发育的非侵入性信息,并深入了解神经退行性疾病。多回波 T 弛豫的多指数分析是一种强大且广泛应用的方法,可用于量化髓鞘水分数(MWF)。在最近的文献中,MWF 最常使用正则化非负最小二乘算法进行估计。
提出正交匹配追踪算法作为估计 MWF 的替代方法。正交匹配追踪是一种具有低计算复杂度的贪婪稀疏重建算法。为了验证,两种方法都与数值模拟和使用可比计算时间的体模模型的真实值进行了比较。数值模拟用于测量理论误差,以及变化 SNR、正则化强度和基集分辨率的影响。此外,还使用体模模型来评估在包括由于 MR 测量而产生的误差的情况下,这两种方法的性能。最后,对 4 名健康受试者进行扫描,以评估体内性能。
模拟和体模的结果表明,与非负最小二乘法相比,正交匹配追踪确定的 MWF 精度提高了 1.7 倍,且具有可比性的精度。MWF 的剩余偏差被证明与非负最小二乘法的正则化和幅度 MR 图像中的瑞利噪声有关。
正交匹配追踪算法为 T 弛豫度髓鞘水定量提供了更准确的替代方法。