Biomedical Imaging Research and Development Laboratory, and Department of Biomedical Device Technologies, Acıbadem Mehmet Ali Aydınlar University, Kayışdağı, Cad., No:32, 34752, Ataşehir, İstanbul, Turkey.
Magn Reson Imaging. 2019 Oct;62:209-213. doi: 10.1016/j.mri.2019.06.015. Epub 2019 Jul 6.
Tissue microstructure has significance as a biomarker, however its accurate inference with diffusion magnetic resonance (MR) is still an open problem. With few exceptions, diffusion weighted (DW) MR models either process diffusion MR data using signal magnitude, whereby microstructural information is forcefully confined to symmetry due to Fourier transform properties, or directly use symmetric basis expansions. Herein, information loss from magnitude utilization is demonstrated by numerically simulating particles undergoing diffusion near a fully reflective infinite wall and an orthogonal corner. Simulation results show that the loss of the Hermitian property when using signal magnitude impedes DW-MR from accurately inferring microstructural information in both of the geometries.
组织微观结构作为一种生物标志物具有重要意义，但其与扩散磁共振（MR）的准确推断仍然是一个未解决的问题。除了少数例外，扩散加权（DW）MR 模型要么使用信号幅度处理扩散 MR 数据，由于傅里叶变换特性，这种方法将微观结构信息强制限制在对称范围内，要么直接使用对称基扩展。本文通过数值模拟在全反射无限壁和正交角附近扩散的粒子，展示了使用信号幅度时的信息丢失。模拟结果表明，在使用信号幅度时丧失厄米性会阻碍 DW-MR 在这两种几何形状中准确推断微观结构信息。
