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脑肿瘤手术的术前定位技术:一项系统综述

Preoperative mapping techniques for brain tumor surgery: a systematic review.

作者信息

Leone Augusto, Carbone Francesco, Spetzger Uwe, Vajkoczy Peter, Raffa Giovanni, Angileri Flavio, Germanó Antonino, Engelhardt Melina, Picht Thomas, Colamaria Antonio, Rosenstock Tizian

机构信息

Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.

Department of Neurosurgery, Städtisches Klinikum Karlsruhe, Karlsruhe, Germany.

出版信息

Front Oncol. 2025 Jan 7;14:1481430. doi: 10.3389/fonc.2024.1481430. eCollection 2024.


DOI:10.3389/fonc.2024.1481430
PMID:39839770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11747149/
Abstract

Accurate preoperative mapping is crucial for maximizing tumor removal while minimizing damage to critical brain functions during brain tumor surgery. Navigated transcranial magnetic stimulation (nTMS), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) are established methods for assessing motor and language function. Following PRISMA guidelines, this systematic review analyzes the reliability, clinical utility, and accessibility of these techniques. A total of 128 studies (48 nTMS, 56 fMRI, 24 MEG) were identified from various databases. The analysis finds nTMS to be a safe, standardized method with high accuracy compared to direct cortical stimulation for preoperative motor mapping. Combining nTMS with tractography allows for preoperative assessment of short-term and long-term motor deficits, which may not be possible with fMRI. fMRI data interpretation requires careful consideration of co-activated, non-essential areas (potentially leading to false positives) and situations where neural activity and blood flow are uncoupled (potentially leading to false negatives). These limitations restrict fMRI's role in preoperative planning for both motor and language functions. While MEG offers high accuracy in motor mapping, its high cost and technical complexity contribute to the limited number of available studies. Studies comparing preoperative language mapping techniques with direct cortical stimulation show significant variability across all methods, highlighting the need for larger, multicenter studies for validation. Repetitive nTMS speech mapping offers valuable negative predictive value, allowing clinicians to evaluate whether a patient should undergo awake or asleep surgery. Language function monitoring heavily relies on the specific expertise and experience available at each center, making it challenging to establish general recommendations.

摘要

准确的术前功能定位对于在脑肿瘤手术中最大程度切除肿瘤并同时最小化对关键脑功能的损伤至关重要。导航经颅磁刺激(nTMS)、脑磁图(MEG)和功能磁共振成像(fMRI)是评估运动和语言功能的既定方法。遵循PRISMA指南,本系统评价分析了这些技术的可靠性、临床实用性和可及性。从各种数据库中总共识别出128项研究(48项nTMS、56项fMRI、24项MEG)。分析发现,与直接皮质刺激相比,nTMS是一种安全、标准化且准确性高的术前运动功能定位方法。将nTMS与神经纤维束成像相结合可对短期和长期运动功能缺损进行术前评估,而这用fMRI可能无法实现。fMRI数据解读需要仔细考虑共同激活的非必要区域(可能导致假阳性)以及神经活动与血流解偶联的情况(可能导致假阴性)。这些局限性限制了fMRI在运动和语言功能术前规划中的作用。虽然MEG在运动功能定位方面具有较高的准确性,但其高成本和技术复杂性导致可用研究数量有限。比较术前语言功能定位技术与直接皮质刺激的研究表明,所有方法之间存在显著差异,这突出表明需要开展更大规模的多中心研究进行验证。重复性nTMS言语功能定位具有重要的阴性预测价值,可让临床医生评估患者是否应接受清醒或睡眠手术。语言功能监测严重依赖于每个中心现有的专业知识和经验,因此很难制定通用的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/eb6ff284e4b1/fonc-14-1481430-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/ad965b02a093/fonc-14-1481430-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/87f926026908/fonc-14-1481430-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/b843792a5a45/fonc-14-1481430-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/eb6ff284e4b1/fonc-14-1481430-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/ad965b02a093/fonc-14-1481430-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/45a3e1809b21/fonc-14-1481430-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/87f926026908/fonc-14-1481430-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/e47b29942241/fonc-14-1481430-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/b843792a5a45/fonc-14-1481430-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b5f/11747149/eb6ff284e4b1/fonc-14-1481430-g006.jpg

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引用本文的文献

[1]
Real-Time Object Detector for Medical Diagnostics (RTMDet): A High-Performance Deep Learning Model for Brain Tumor Diagnosis.

Bioengineering (Basel). 2025-3-11

[2]
Virtual Biopsy for the Prediction of MGMT Promoter Methylation in Gliomas: A Comprehensive Review of Radiomics and Deep Learning Approaches Applied to MRI.

Diagnostics (Basel). 2025-1-22

本文引用的文献

[1]
MEG language mapping using a novel automatic ECD algorithm in comparison with MNE, dSPM, and DICS beamformer.

Front Neurosci. 2023-6-2

[2]
Comparison of anatomical-based vs. nTMS-based risk stratification model for predicting postoperative motor outcome and extent of resection in brain tumor surgery.

Neuroimage Clin. 2023

[3]
Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.

J Neurosurg. 2023-11-1

[4]
Tractography-based navigated TMS language mapping protocol.

Front Oncol. 2022-12-9

[5]
Neuroimaging in schizophrenia: A review article.

Front Neurosci. 2022-11-15

[6]
Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract.

Brain Commun. 2022-5-27

[7]
Fluorescence-Guided Surgery in Glioblastoma: 5-ALA, SF or Both? Differences between Fluorescent Dyes in 99 Consecutive Cases.

Brain Sci. 2022-4-26

[8]
Validation of Non-invasive Language Mapping Modalities for Eloquent Tumor Resection: A Pilot Study.

Front Neurosci. 2022-3-1

[9]
Predicting the Extent of Resection of Motor-Eloquent Gliomas Based on TMS-Guided Fiber Tracking.

Brain Sci. 2021-11-16

[10]
Bicentric validation of the navigated transcranial magnetic stimulation motor risk stratification model.

J Neurosurg. 2022-4-1

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