神经肿瘤学中基于模板的神经成像工具综述:新的见解

Onco Pub Date : 2022-12-23 DOI:10.3390/onco3010001
J. Germann, Andrew Yang, Clement Chow, Brendan Santyr, N. Samuel, Artur Vetkas, C. Sarica, G. Elias, M. Voisin, W. Kucharczyk, G. Zadeh, A. Lozano, A. Boutet
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引用次数: 0

摘要

背景:一个通用的MRI参考空间可以方便地交流研究结果,并在神经科学中产生了高影响力的发现。有肿块病变或手术腔的神经肿瘤患者的脑MRI现在可以准确地转换到参考空间,从而在患者之间进行可靠的比较。尽管如此,它目前很少用于神经肿瘤学,分析工具尚未开发。本研究的目的是利用参考空间系统地回顾神经肿瘤学文献。方法:根据PRISMA声明指南对神经肿瘤学出版物进行系统综述。包括专门报告蒙特利尔神经研究所(MNI)参考空间使用情况的研究。研究根据其输入数据的类型及其对该领域的贡献进行了分类。还包括一个侧重于连接组学和转录组学的子分析。结果:我们只发现了101篇在神经肿瘤学研究中使用MNI大脑的文章。肿瘤位置(n=77)和直接皮层电刺激(n=19)是最常见的数据来源。大多数研究(n=51)提供了关于肿瘤亚型、生长进展和预后等临床因素的见解。一小群研究(n=21)使用了新的连接组学和转录组学工具。结论:神经肿瘤患者的脑MRI可以准确地转换到MNI空间。这有助于增强我们对从肿瘤分型到症状图谱等各种临床问题的理解。许多先进的工具,如连接组学和转录组学,仍然相对未开发,从而阻碍了我们对神经肿瘤学的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of Template-Based Neuroimaging Tools in Neuro-Oncology: Novel Insights
Background: A common MRI reference space allows for easy communication of findings, and has led to high-impact discoveries in neuroscience. Brain MRI of neuro-oncology patients with mass lesions or surgical cavities can now be accurately transformed into reference space, allowing for a reliable comparison across patients. Despite this, it is currently seldom used in neuro-oncology, leaving analytic tools untapped. The aim of this study was to systematically review the neuro-oncology literature utilizing reference space. Methods: A systematic review of the neuro-oncology publications was conducted according to PRISMA statement guidelines. Studies specially reporting the use of the Montreal Neurological Institute (MNI) reference space were included. Studies were categorized according to their type of input data and their contributions to the field. A sub-analysis focusing on connectomics and transcriptomics was also included. Results: We identified only 101 articles that utilized the MNI brain in neuro-oncology research. Tumor locations (n = 77) and direct electrocortical stimulation (n = 19) were the most common source of data. A majority of studies (n = 51) provided insights on clinical factors such as tumor subtype, growth progression, and prognosis. A small group of studies (n = 21) have used the novel connectomic and transcriptomic tools. Conclusions: Brain MRI of neuro-oncology patients can be accurately transformed to MNI space. This has contributed to enhance our understanding of a wide variety of clinical questions ranging from tumor subtyping to symptom mapping. Many advanced tools such as connectomics and transcriptomics remain relatively untapped, thereby hindering our knowledge of neuro-oncology.
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