A method for estimating Mie theory scattering parameters from diffuse light tomography measurements in breast tissue is discussed. The approach provides an estimate of the mean particle size and number density given assumptions about the index of refraction change expected in lipid-membrane-bound scatterers. When using a sparse number of wavelengths in the reduced scattering spectra, the parameter extraction technique is limited to representing a continuous distribution of scatterer sizes that appears to be dominated by an exponential decrease with increasing particle size. The fitting method is tested on simulated data and then on Intralipid-based tissue-phantom data, giving a mean particle size of 93+/-17 nm, which is in excellent agreement with expectations. The approach is also applied retrospectively to breast tissue spectra acquired from normal healthy volunteers, where the average particle size and number density were found to be in the range of 20 to 1400 nm. Grouping of the data based on radiographic breast density, as a surrogate measure of tissue composition yielded values of 20 to 65, 25 to 200, 140 to 1200, and 150 to 1400 nm, respectively, for the four BI-RADS (American College of Radiology Breast Imaging Reporting and Data System) density classifications of extremely dense, heterogeneously dense, scattered, and fatty. These results are consistent with the microscopic characteristics of each breast type given the expected progression from predominantly collagenous connective tissue (extremely dense category) to increasing proportions of glandular epithelium and fat (intermediate density categories) to predominantly fat (fatty category).
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http://dx.doi.org/10.1117/1.2098607 | DOI Listing |
Front Toxicol
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Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan.
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National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery, East China University of Science and Technology, Shanghai, 200237, China. Electronic address:
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View Article and Find Full Text PDFSci Rep
January 2025
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