{"title":"Population-optimized electrode montage approximates individualized optimization in transcranial temporal interference stimulation","authors":"Kanata Yatsuda , Mariano Fernández-Corazza , Wenwei Yu , Jose Gomez-Tames","doi":"10.1016/j.compbiomed.2025.110223","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Effective transcranial temporal interference stimulation (tTIS) requires an optimized electrode configuration to target deep brain structures accurately. While individualized electric field analysis using high-resolution structural MRI enables precise electrode placement, its clinical practicality is limited by significant costs associated with imaging, specialized software, and navigation systems. Alternatively, standardized electrode montages optimized through population-based electric field analysis might overcome these limitations, although it remains unclear how accurately this approach approximates individualized optimization.</div></div><div><h3>Aim</h3><div>This study evaluates the feasibility of using group-level electric field analysis to optimize the tTIS montage. Specifically, it seeks to maximize the intracranial electric field using a population-proxy approach and compare its efficacy to individualized electric field optimization.</div></div><div><h3>Method</h3><div>We optimize the montage across various populations, balancing the trade-off between focality and electric field strength at deep brain targets. The method is compared to conventional individualized electric field-based optimization. Factors such as population size and age were analyzed for their impact on montage selection and effectiveness.</div></div><div><h3>Results</h3><div>Population-based electric field optimization demonstrated comparable focality and targeting accuracy to individualized analysis, with a difference of up to 17 %. Age mismatch between the population proxy and the target individual reduced the focality of up to 8.3 % compared to an age-matched population proxy. Also, insufficient population size led to inconsistencies in montage optimization, although these were negligible for populations larger than 40 individuals.</div></div><div><h3>Conclusion</h3><div>This study demonstrates the capability of population-based electric field analysis to achieve targeting effects comparable to individualized-level electric field analysis in terms of focality and intensity. By eliminating the need for patient-specific MRI scans, this approach significantly enhances the accessibility and practicality of tTIS in diverse research and clinical applications.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"192 ","pages":"Article 110223"},"PeriodicalIF":7.0000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in biology and medicine","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010482525005748","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Effective transcranial temporal interference stimulation (tTIS) requires an optimized electrode configuration to target deep brain structures accurately. While individualized electric field analysis using high-resolution structural MRI enables precise electrode placement, its clinical practicality is limited by significant costs associated with imaging, specialized software, and navigation systems. Alternatively, standardized electrode montages optimized through population-based electric field analysis might overcome these limitations, although it remains unclear how accurately this approach approximates individualized optimization.
Aim
This study evaluates the feasibility of using group-level electric field analysis to optimize the tTIS montage. Specifically, it seeks to maximize the intracranial electric field using a population-proxy approach and compare its efficacy to individualized electric field optimization.
Method
We optimize the montage across various populations, balancing the trade-off between focality and electric field strength at deep brain targets. The method is compared to conventional individualized electric field-based optimization. Factors such as population size and age were analyzed for their impact on montage selection and effectiveness.
Results
Population-based electric field optimization demonstrated comparable focality and targeting accuracy to individualized analysis, with a difference of up to 17 %. Age mismatch between the population proxy and the target individual reduced the focality of up to 8.3 % compared to an age-matched population proxy. Also, insufficient population size led to inconsistencies in montage optimization, although these were negligible for populations larger than 40 individuals.
Conclusion
This study demonstrates the capability of population-based electric field analysis to achieve targeting effects comparable to individualized-level electric field analysis in terms of focality and intensity. By eliminating the need for patient-specific MRI scans, this approach significantly enhances the accessibility and practicality of tTIS in diverse research and clinical applications.
期刊介绍:
Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.