{"doi":"10.1162/imag_a_00412","title":"Real-time computation of brain E-field for enhanced transcranial magnetic stimulation neuronavigation and optimization","abstract":"Abstract Transcranial Magnetic Stimulation (TMS) coil placement and pulse waveform current are often chosen to achieve a specified E-field dose on targeted brain regions. TMS neuronavigation could be improved by including real-time accurate distributions of the E-field dose on the cortex. We introduce a method and develop software for computing brain E-field distributions in real-time enabling easy integration into neuronavigation and with the same accuracy as 1st-order finite element method (FEM) solvers. Initially, a spanning basis set (<400) of E-fields generated by white noise magnetic currents on a surface separating the head and permissible coil placements are orthogonalized to generate the modes. Subsequently, Reciprocity and Huygens’ principles are utilized to compute fields induced by the modes on a surface separating the head and coil by FEM, which are used in conjunction with online (real-time) computed primary fields on the separating surface to evaluate the mode expansion. We conducted a comparative analysis of E-fields computed by FEM and in real-time for eight subjects, utilizing two head model types (SimNIBS’s ‘headreco’ and ‘mri2mesh’ pipeline), three coil types (circular, double-cone, and Figure-8), and 1000 coil placements (48,000 simulations). The real-time computation for any coil placement is within 4 milliseconds (ms), for 400 modes, and requires less than 4 GB of memory on a GPU. Our solver is capable of computing E-fields within 4 ms, making it a practical approach for integrating E-field information into the neuronavigation systems without imposing a significant overhead on frame generation. The software is available at https://github.com/NahianHasan/Real-Time-TMS.","journal":"Imaging Neuroscience","year":2024,"id":456895,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9548,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":268270,"name":"Moritz Dannhauer","orcid":"0000-0001-8747-1021","position":1,"is_corresponding":false},{"id":1030903,"name":"Dezhi Wang","orcid":"0000-0002-3113-7435","position":2,"is_corresponding":false},{"id":313432,"name":"Zhi‐De Deng","orcid":"0000-0001-8925-0871","position":3,"is_corresponding":false},{"id":268269,"name":"Luis J. Gomez","orcid":"0000-0002-7699-2160","position":4,"is_corresponding":false},{"id":1030904,"name":"Nahian I. Hasan","orcid":"0000-0003-1725-4683","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-19T02:03:32.516678Z","pmid":"40800850","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}