Clinical feasibility of brain quantitative susceptibility mapping

Magnetic Resonance Imaging(2019)

引用 0|浏览0
暂无评分
摘要
PURPOSE:To evaluate the quality of brain quantitative susceptibility mapping (QSM) that is fully automatically reconstructed in clinical MRI of various neurological diseases. METHODS:393 consecutive patients in one month were recruited for this evaluation study. QSM was reconstructed using Morphology Enabled Dipole Inversion without zero reference regularization (MEDI) and using MEDI with cerebrospinal fluid automatic zero-reference regularization to generate susceptibility values (MEDI+0). Two neuroradiologists independently assessed the image quality of MEDI+0 and MEDI and image concordance between them. Lesion susceptibility values were measured in 20 cases of glioma, 21 cases of ischemic stroke and 43 multiple sclerosis (MS) cases on both MEDI+0 and MEDI images. RESULTS:The two neuroradiologists rated the MEDI+0 image qualities of the 393 cases as 351 (89.3%) and 362 (92.1%) excellent, 29 (7.4%) and 24 (6.1%) diagnostic, and 13 (3.3%) and 7 (1.8%) poor, and scored the concordances between MEDI+0 and MEDI as 364 (92.6%) and 351 (89.3%) excellent, 13 (3.3%) and 31 (7.9%) good, 14 (3.6%) and 9 (2.3%) intermediate, 2 (0.5%) and 2 (0.5%) poor, and 0 (0%) and 0 (0%) none. There was good correlation between MEDI+0 and MEDI in lesion susceptibility contrast of glioma, ischemic stroke, and MS cases (all p < 0.05). The MS lesion susceptibility time course from this patient cohort was found to be similar to the reported pattern: isointense initially for acute enhancing lesions, and hyperintense over the following years for active chronic lesions. CONCLUSION:Brain QSM images of various neurological diseases have reliable diagnostic quality in clinical MRI, with MEDI+0 providing susceptibility values automatically referenced to CSF in longitudinal and cross-center studies.
更多
查看译文
关键词
Quantitative susceptibility mapping,Zero reference,Cerebrospinal fluid,Morphology enabled dipole inversion,Multiple sclerosis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要