論文

査読有り
2017年5月

Modeling of light propagation in the human neck for diagnoses of thyroid cancers by diffuse optical tomography

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
  • H. Fujii
  • ,
  • Y. Yamada
  • ,
  • K. Kobayashi
  • ,
  • M. Watanabe
  • ,
  • Y. Hoshi

33
5
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1002/cnm.2826
出版者・発行元
WILEY

Diffuse optical tomography using near-infrared light in a wavelength range from 700 to 1000nm has the potential to enable non-invasive diagnoses of thyroid cancers; some of which are difficult to detect by conventional methods such as ultrasound tomography. Diffuse optical tomography needs to be based on a physically accurate model of light propagation in the neck, because it reconstructs tomographic images of the optical properties in the human neck by inverse analysis. Our objective here was to investigate the effects of three factors on light propagation in the neck using the 2D time-dependent radiative transfer equation: (1) the presence of the trachea, (2) the refractive-index mismatch at the trachea-tissue interface, and (3) the effect of neck organs other than the trachea (spine, spinal cord, and blood vessels). There was a significant influence of reflection and refraction at the trachea-tissue interface on the light intensities in the region between the trachea and the front of the neck surface. Organs other than the trachea showed little effect on the light intensities measured at the front of the neck surface although these organs affected the light intensities locally. These results indicated the necessity of modeling the refractive-index mismatch at the trachea-tissue interface and the possibility of modeling other neck organs simply as a homogeneous medium when the source and detectors were far from large blood vessels.

リンク情報
DOI
https://doi.org/10.1002/cnm.2826
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000400975000008&DestApp=WOS_CPL
ID情報
  • DOI : 10.1002/cnm.2826
  • ISSN : 2040-7939
  • eISSN : 2040-7947
  • Web of Science ID : WOS:000400975000008

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