Shiroishi Mark S, Cen Steven Y, Tamrazi Benita, D'Amore Francesco, Lerner Alexander, King Kevin S, Kim Paul E, Law Meng, Hwang Darryl H, Boyko Orest B, Liu Chia-Shang J
Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Neurosurg Clin N Am. 2016 Apr;27(2):145-54. doi: 10.1016/j.nec.2015.11.007. Epub 2016 Feb 18.
This article provides an overview of the neuroimaging literature focused on preoperative prediction of meningioma consistency. A validated, noninvasive neuroimaging method to predict tumor consistency can provide valuable information regarding neurosurgical planning and patient counseling. Most of the neuroimaging literature indicates conventional MRI using T2-weighted imaging may be helpful to predict meningioma consistency; however, further rigorous validation is necessary. Much less is known about advanced MRI techniques, such as diffusion MRI, MR elastography (MRE), and MR spectroscopy. Of these methods, MRE and diffusion tensor imaging appear particularly promising.
本文概述了专注于脑膜瘤质地术前预测的神经影像学文献。一种经过验证的、非侵入性的预测肿瘤质地的神经影像学方法可为神经外科手术规划和患者咨询提供有价值的信息。大多数神经影像学文献表明，使用T2加权成像的传统MRI可能有助于预测脑膜瘤质地；然而，还需要进一步严格验证。对于先进的MRI技术，如扩散MRI、磁共振弹性成像（MRE）和磁共振波谱，了解则少得多。在这些方法中，MRE和扩散张量成像似乎特别有前景。
