Wavelength optimization for quantitative spectral imaging of breast tumor margins.

Abstract

A wavelength selection method that combines an inverse Monte Carlo model of reflectance and a genetic algorithm for global optimization was developed for the application of spectral imaging of breast tumor margins. The selection of wavelengths impacts system design in cost, size, and accuracy of tissue quantitation. The minimum number of wavelengths required for the accurate quantitation of tissue optical properties is 8, with diminishing gains for additional wavelengths. The resulting wavelength choices for the specific probe geometry used for the breast tumor margin spectral imaging application were tested in an independent pathology-confirmed ex vivo breast tissue data set and in tissue-mimicking phantoms. In breast tissue, the optical endpoints (hemoglobin, β-carotene, and scattering) that provide the contrast between normal and malignant tissue specimens are extracted with the optimized 8-wavelength set with <9% error compared to the full spectrum (450-600 nm). A multi-absorber liquid phantom study was also performed to show the improved extraction accuracy with optimization and without optimization. This technique for selecting wavelengths can be used for designing spectral imaging systems for other clinical applications.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1371/journal.pone.0061767

Publication Info

Lo, Justin Y, J Quincy Brown, Sulochana Dhar, Bing Yu, Gregory M Palmer, Nan M Jokerst and Nirmala Ramanujam (2013). Wavelength optimization for quantitative spectral imaging of breast tumor margins. PloS one, 8(4). p. e61767. 10.1371/journal.pone.0061767 Retrieved from https://hdl.handle.net/10161/22463.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.