Zlotzover Sharon, Omer Noam, Radunsky Dvir, Stern Neta, Blumenfeld-Katzir Tamar, Reichman Dominique Ben-Ami, Shrot Shai, Hoffmann Chen, Ben-Eliezer Noam
Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.
Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel.
Imaging Neurosci (Camb). 2024 Jul 31;2. doi: 10.1162/imag_a_00254. eCollection 2024.
The predominant technique for quantifying myelin content in the white matter is multicompartment analysis of MRI's Trelaxation times ( analysis). The process of resolving the Tspectrum at each voxel, however, is highly ill-posed and remarkably susceptible to noise and to inhomogeneities of the transmit field ( ). To address these challenges, we employ a preprocessing stage wherein a spatially global data-driven analysis of the tissue is performed to identify a set of mcTconfigurations () that best describe the tissue under investigation, followed by using this basis set to analyze the signal in each voxel. This procedure is complemented by a new algorithm for correcting B inhomogeneities, lending the overall fitting process with improved robustness and reproducibility. Successful validations are presented using numerical and physical phantoms vs. ground truth, showcasing superior fitting accuracy and precision compared with conventional (non-data-driven) fitting.application of the technique is presented on 26 healthy subjects and 29 people living with multiple sclerosis (), revealing substantial reduction in myelin content within normal-appearing white matter regions of people with MS (i.e., outside obvious lesions), and confirming the potential of data-driven myelin values as a radiological biomarker for MS.
在白质中量化髓磷脂含量的主要技术是对MRI的T弛豫时间进行多室分析。然而，在每个体素处解析T谱的过程是高度不适定的，并且极易受到噪声和发射场不均匀性的影响。为应对这些挑战，我们采用了一个预处理阶段，其中对组织进行空间全局数据驱动分析，以识别一组最能描述所研究组织的mcT配置，然后使用该基集分析每个体素中的信号。此过程辅以一种校正B不均匀性的新算法，使整个拟合过程具有更高的稳健性和可重复性。使用数值和物理体模与真实情况进行了成功验证，与传统（非数据驱动）拟合相比，展示了卓越的拟合精度和准确性。该技术在26名健康受试者和29名多发性硬化症患者身上进行了应用，揭示了MS患者正常外观白质区域（即明显病变之外）的髓磷脂含量大幅降低，并证实了数据驱动的髓磷脂值作为MS放射学生物标志物的潜力。
