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脑转移瘤:神经影像学

Brain metastases: neuroimaging.

作者信息

Pope Whitney B

机构信息

Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.

出版信息

Handb Clin Neurol. 2018;149:89-112. doi: 10.1016/B978-0-12-811161-1.00007-4.

Abstract

Magnetic resonance imaging (MRI) is the cornerstone for evaluating patients with brain masses such as primary and metastatic tumors. Important challenges in effectively detecting and diagnosing brain metastases and in accurately characterizing their subsequent response to treatment remain. These difficulties include discriminating metastases from potential mimics such as primary brain tumors and infection, detecting small metastases, and differentiating treatment response from tumor recurrence and progression. Optimal patient management could be benefited by improved and well-validated prognostic and predictive imaging markers, as well as early response markers to identify successful treatment prior to changes in tumor size. To address these fundamental needs, newer MRI techniques including diffusion and perfusion imaging, MR spectroscopy, and positron emission tomography (PET) tracers beyond traditionally used 18-fluorodeoxyglucose are the subject of extensive ongoing investigations, with several promising avenues of added value already identified. These newer techniques provide a wealth of physiologic and metabolic information that may supplement standard MR evaluation, by providing the ability to monitor and characterize cellularity, angiogenesis, perfusion, pH, hypoxia, metabolite concentrations, and other critical features of malignancy. This chapter reviews standard and advanced imaging of brain metastases provided by computed tomography, MRI, and amino acid PET, focusing on potential biomarkers that can serve as problem-solving tools in the clinical management of patients with brain metastases.

摘要

磁共振成像(MRI)是评估患有脑肿瘤(如原发性和转移性肿瘤)患者的基石。在有效检测和诊断脑转移瘤以及准确表征其对治疗的后续反应方面,仍然存在重大挑战。这些困难包括将转移瘤与原发性脑肿瘤和感染等潜在的相似病变区分开来,检测小的转移瘤,以及将治疗反应与肿瘤复发和进展区分开来。改进且经过充分验证的预后和预测性成像标志物,以及在肿瘤大小改变之前识别成功治疗的早期反应标志物,有助于实现最佳的患者管理。为满足这些基本需求,除了传统使用的18-氟脱氧葡萄糖之外,包括扩散和灌注成像、磁共振波谱以及正电子发射断层扫描(PET)示踪剂在内的更新的MRI技术正在广泛研究中,并且已经确定了几个有前景的附加价值途径。这些更新的技术提供了丰富的生理和代谢信息,通过提供监测和表征细胞密度、血管生成、灌注、pH值、缺氧、代谢物浓度以及恶性肿瘤其他关键特征的能力,可能补充标准的MR评估。本章回顾了计算机断层扫描、MRI和氨基酸PET提供的脑转移瘤的标准和先进成像,重点关注可作为脑转移瘤患者临床管理中解决问题工具的潜在生物标志物。

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Clin Cancer Res. 2017 Jul 15;23(14):3667-3675. doi: 10.1158/1078-0432.CCR-16-2265. Epub 2017 Jan 17.
2
Gadolinium-based contrast agents: A comprehensive risk assessment.
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4
Leptomeningeal metastases: a RANO proposal for response criteria.
Neuro Oncol. 2017 Apr 1;19(4):484-492. doi: 10.1093/neuonc/now183.
7
The evaluation of MRI diffusion values of active demyelinating lesions in multiple sclerosis.
Mult Scler Relat Disord. 2016 Nov;10:97-102. doi: 10.1016/j.msard.2016.09.006. Epub 2016 Sep 28.
8
Can morphological MRI differentiate between primary central nervous system lymphoma and glioblastoma?
Cancer Imaging. 2016 Nov 29;16(1):40. doi: 10.1186/s40644-016-0098-9.
9
Differentiation of Glioblastoma from Brain Metastasis: Qualitative and Quantitative Analysis Using Arterial Spin Labeling MR Imaging.
PLoS One. 2016 Nov 18;11(11):e0166662. doi: 10.1371/journal.pone.0166662. eCollection 2016.

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