Cortical Excitability and Connectivity in Patients With Brain Tumors

Abstract

Background: Brain tumors can cause different changes in excitation and inhibition at the neuronal network level. These changes can be generated from mechanical and cellular alterations, often manifesting clinically as seizures.Objective/Hypothesis: The effects of brain tumors on cortical excitability (CE) have not yet been well-evaluated. The aim of the current study was to further investigate cortical–cortical and cortical–spinal excitability in patients with brain tumors using a more extensive transcranial magnetic stimulation protocol.Methods: We evaluated CE on 12 consecutive patients with lesions within or close to the precentral gyrus, as well as in the subcortical white matter motor pathways. We assessed resting and active motor threshold, short-latency intracortical inhibition (SICI), intracortical facilitation (ICF), short-latency afferent inhibition (SAI), long-latency afferent inhibition, cortical silent period, and interhemispheric inhibition.Results: CE was reduced in patients with brain tumors than in healthy controls. In addition, SICI, ICF, and SAI were lower in the affected hemisphere compared to the unaffected and healthy controls.Conclusions: CE is abnormal in hemispheres affected by brain tumors. Further studies are needed to determine if CE is related with motor impairment.

Transcranial Magnetic Stimulation–Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas

“…nTMS motor mapping is a technique that can provide an accurate functional characterization of brain connectivity and alterations of CST excitability produced by brain tumors. 29-31 Our study shows that ML models on interhemispheric excitability differences based on nTMS preoperative motor mapping provide a robust prediction for high-grade motor-eloquent gliomas when compared with low-grade gliomas (LGGs). This applies not only when the iRMTr for the upper and lower limbs in isolation but also when combined with CES.…”

“…39,40 TMS-derived data have been proven to be hemisphere-specific with regard to tumorinduced changes or rely in interhemispheric differences but no further anatomic specification has been proven up to date. 18,30,31 Therefore, future ML models, such as Bayesian networks, 41 combining preoperative imaging characteristics and nTMS functional information could improve the accuracy of tumor grade predicting models based only on preoperative data.…”

Avaliação da relocação plástica motora em pacientes com gliomas de baixo grau utilizando mapeamento anatômico e funcional não invasivo do córtex cerebral por estimulação magnética transcraniana navegada

“…A intensidade do campo magnético necessária para atingir a despolarização varia em grande monta entre indivíduos, a determinação do valor referencial para cada paciente habitualmente é obtida com base no Limiar Motor (LM) (Chaieb et al, 2011;Cueva et al, 2016;Rizzo et al, 2021). O uso da resposta motora mesmo para estudos cognitivos se dá pelo fato de a contração muscular involuntária ser o efeito mais facilmente identificável de uma EMT adequada.…”

“…Outra dificuldade para a adequada mensuração da plasticidade é a consideração para além da função cortical local, incluindo os mecanismos de conectividade subcortical (Pascual- Leone et al, 2000;Sollmann et al, 2016;Bourdillon et al, 2017;Picart et al, 2019;Rizzo et al, 2021) e a possibilidade de mecanismos hodotopicos de áreas correlatas (Duffau, 2010;Bourdillon et al, 2017;Duffau, 2017), que são menos acessíveis à experimentação direta e observação intraoperatória. Adicionalmente, estas mudanças na conectividade cerebral e o recrutamento local e à distância de múltiplas áreas de integração cortical podem influenciar o desfecho de remodelamento após lesões de diferentes tipos e com tempos de evolução distintos (Herbet et al, 2016;Hillary e Grafman, 2017).…”