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.

Preoperative mapping techniques for brain tumor surgery: a systematic review

Angileri F.;
2024-01-01

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.
2024
brain mapping
brain tumor surgery
fMRI
language eloquent tumor
magnetoencephalography (MEG)
motor eloquent tumors
navigated transcranial magnetic stimulation (nTMS)
preoperative mapping
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11699/108880
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