Autor(es):
Fernandes, Filipa Gracinda Silva ; Silva, Filipe Samuel ; Sousa, Nuno ; Carvalho, Óscar Samuel Novais ; Catarino, Susana Oliveira
Data: 2025
Identificador Persistente: https://hdl.handle.net/1822/94500
Origem: RepositóriUM - Universidade do Minho
Projeto/bolsa:
info:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEME-EME%2F1681%2F2021/PT;
Assunto(s): Transcranial photobiomodulation; Optical phantoms; Numerical simulation; Brain; Light propagation; Saúde de qualidade; Ciências Médicas::Biotecnologia Médica
Descrição
Transcranial photobiomodulation (tPBM) is an alternative therapy to conventional approaches, with clinical studies that show promising results for the treatment of several neurological pathologies, such as stroke and dementia related conditions. Despite its potential, the optimal light parameters and dosimetry for effective tPBM therapy remain uncertain, with most literature on this topic highlighting the need for establishing optimal stimulation parameters. The efficiency of tPBM therapy is related to the propagation of light through the head tissues, which in turn depends on the tissues' optical properties. Therefore, the most accurate way to define optimal parameters for treatments is to first define how light interacts with the tissues involved. To this end, we aim to improve the understanding of tPBM by characterizing the propagation of light through the head tissues and develop tools for customized treatments. We approached the problem both experimentally and in silico. Experimentally, we developed optical mimicking phantoms for each of the head’s tissues. Agarose was used as a base, to which titanium dioxide, India ink, organometallic compounds, and laser-ablated gold and zinc nanoparticles were individually added. In parallel, we developed an in silico model for light propagation on those tissues, using the transmittance spectra obtained from the phantoms. The numerical simulation was implemented in COMSOL Multiphysics software, using Finite Element Methods. In the future, by using imaging data, such as Magnetic Resonance Imaging, we can construct patient-specific models, both with the phantoms and the numerical simulation, to provide the physicians with patient-specific treatment protocols. These advancements will improve outcomes for patients and thus further proving that light, a bioinspired therapy, can be the future for neurological treatments.
This work was supported by the project PTDC/EME-EME/1681/2021—BrainStimMap, with DOI: 10.54499/PTDC/EME-EME/1681/2021
