Your browser doesn't support javascript.
loading
Determining ideal offsets of spatially offset Raman spectroscopy for transcutaneous measurements-A Monte Carlo study.
Chen, Keren; Sun, Mengya; Chen, Shuo.
Afiliação
  • Chen K; College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
  • Sun M; Foshan Graduate School of Innovation, Northeastern University, Foshan, China.
  • Chen S; College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
J Biophotonics ; 17(8): e202300564, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38887978
ABSTRACT
Spatially offset Raman spectroscopy (SORS) is valuable for noninvasive bone assessment but requires a clearer understanding of how offset distances influence detection depth. To address this, our study devised a forward-adjoint Monte Carlo multi-layer (MCML) model to simulate photon paths in SORS, aiming to determine optimal offsets for various tissue types. We examined photon migration at offsets between 0 and 15 mm against layered phantoms of differing thicknesses and compositions to optimize the signal-to-noise ratio for bone layers. The findings highlight that optimal offsets are contingent on tissue characteristics a metacarpal beneath 2.5 mm of tissue had an ideal offset of 6.7 mm, while a tibia with 5 mm of soft tissue required 10-11 mm. This precise calibration of SORS via MCML modeling promises substantial improvements in bone health diagnostics and potential for expansive medical applications.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise Espectral Raman / Método de Monte Carlo / Imagens de Fantasmas Limite: Humans Idioma: En Revista: J Biophotonics Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise Espectral Raman / Método de Monte Carlo / Imagens de Fantasmas Limite: Humans Idioma: En Revista: J Biophotonics Ano de publicação: 2024 Tipo de documento: Article