Advanced magnetic resonance imaging in glioblastoma: a review

医学 流体衰减反转恢复 磁共振成像 体内磁共振波谱 磁共振弥散成像 胶质母细胞瘤 模式 放射科 社会科学 社会学 癌症研究
作者
Gaurav Shukla,Gregory S. Alexander,Spyridon Bakas,Rahul Nikam,Kiran Talekar,Joshua D. Palmer,Wenyin Shi
出处
期刊:Chinese clinical oncology [AME Publishing Company]
卷期号:6 (4): 40-40 被引量:163
标识
DOI:10.21037/cco.2017.06.28
摘要

Abstract: Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
隐形曼青应助清故采纳,获得10
2秒前
2秒前
Silvermonique发布了新的文献求助10
3秒前
4秒前
4秒前
zhourenpeng完成签到,获得积分10
4秒前
5秒前
lesser发布了新的文献求助10
6秒前
6秒前
Maria发布了新的文献求助10
6秒前
7秒前
Yusheng完成签到,获得积分10
7秒前
徐双凯发布了新的文献求助10
9秒前
大圣发布了新的文献求助10
9秒前
林林爱学医应助彩色蚂蚁采纳,获得10
10秒前
10秒前
菌根发布了新的文献求助10
10秒前
10秒前
无花果应助阿东采纳,获得10
10秒前
syt发布了新的文献求助10
11秒前
英俊的铭应助柚子采纳,获得30
12秒前
谦让的贞完成签到,获得积分10
13秒前
14秒前
14秒前
14秒前
Freiheit发布了新的文献求助10
15秒前
15秒前
Lynn完成签到,获得积分10
16秒前
科研通AI6.2应助喜悦的厉采纳,获得10
17秒前
g123发布了新的文献求助10
17秒前
无花果应助柠栀采纳,获得10
18秒前
18秒前
21秒前
21秒前
22秒前
科研通AI6.4应助哈哈采纳,获得10
23秒前
23秒前
Lynn发布了新的文献求助30
23秒前
隐形曼青应助娴娴超爱笑采纳,获得10
24秒前
26秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7220412
求助须知:如何正确求助?哪些是违规求助? 8850451
关于积分的说明 18676809
捐赠科研通 6878281
什么是DOI,文献DOI怎么找? 3186689
关于科研通互助平台的介绍 2350256
邀请新用户注册赠送积分活动 2160878