Image reconstruction of effective Mie scattering parameters of breast tissue in vivo with near-infrared tomography

Research output: Contribution to journalArticle

Authors

  • Xin Wang
  • Brian W Pogue
  • Shudong Jiang
  • Xiaomei Song
  • Subhadra Srinivasan
  • Ben A Brooksby
  • Keith D Paulsen
  • Christine Kogel
  • Steven P Poplack
  • Wendy A Wells

Colleges, School and Institutes

Abstract

A method for image reconstruction of the effective size and number density of scattering particles is discussed within the context of interpreting near-infrared (NIR) tomography images of breast tissue. An approach to use Mie theory to estimate the effective scattering parameters is examined and applied, given some assumptions about the index of refraction change expected in lipid membrane-bound scatterers. When using a limited number of NIR wavelengths in the reduced scattering spectra, the parameter extraction technique is limited to representing a continuous distribution of scatterer sizes, which is modeled as a simple exponentially decreasing distribution function. In this paper, image formation of effective scatterer size and number density is presented based on the estimation method. The method was evaluated with Intralipid phantom studies to demonstrate particle size estimation to within 9% of the expected value. Then the method was used in NIR patient images, and it indicates that for a cancer tumor, the effective scatterer size is smaller than the background breast values and the effective number density is higher. In contrast, for benign tumor patients, there is not a significant difference in effective scatterer size or number density between tumor and normal tissues. The method was used to interpret magnetic resonance imaging-coupled NIR images of adipose and fibroglandular tissues, and it indicated that the fibroglandular tissue has smaller effective scatterer size and larger effective number density than the adipose tissue does.

Details

Original languageEnglish
Pages (from-to)041106
JournalJournal of Biomedical Optics
Volume11
Issue number4
Publication statusPublished - 13 Sep 2006

Keywords

  • Algorithms, Breast, Breast Neoplasms, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Infrared Rays, Phantoms, Imaging, Refractometry, Reproducibility of Results, Scattering, Radiation, Sensitivity and Specificity, Tomography, Optical