Autofluorescence and diffuse reflectance spectroscopy and spectral imaging for breast surgical margin analysis

Abstract

Fluorescence and reflectance spectroscopy could be a valuable tool for examining the superficial margin status of excised breast tumor specimens, particularly in the form of spectral imaging to examine entire margins in a single acquisition.

Evaluation of breast tissue with confocal strip-mosaicking microscopy: a test approach emulating pathology-like examination

“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] Confocal microscopy is an emerging technology for rapid imaging of freshly excised tissue without the need for frozen-or fixed-section processing. Initial studies have described the major findings of invasive breast cancers using fluorescence confocal microscopy.…”

Development of a spatially offset Raman spectroscopy probe for breast tumor surgical margin evaluation

“…Another optical approach for intraoperative margin evaluation is to image an entire margin (i.e., one of the six facets of the "cuboidal" excised specimen) at once with autofluorescence and/or diffuse reflectance modalities. While our group has published a small study on the topic, 13 it has been extensively researched in recent years by the Ramanujam group. [9][10][11][12] Using extracted optical properties of the tissue from visible diffuse reflectance, that group has achieved 79% sensitivity and 67% specificity for discriminating normal from positive or close (< 2 mm) margins for a set of 48 patients.…”

“…12 Keller et al used combined diffuse reflectance and autofluorescence spectroscopy to classify individual points from 32 patients on margins as negative versus positive with 85% sensitivity and 96% specificity, and also demonstrated the ability to perform autofluorescence spectral imaging of larger regions. 13 Nguyen et al used optical coherence tomography (OCT) images from 20 patients to classify the margin status with 100% sensitivity and 82% specificity. 14 In the one report of using Raman spectroscopy for a margin analysis tool, 15 measurements were made in vivo rather than on the excised specimen; the latter approach is the current standard practice in surgical pathology.…”

Automated classification of breast pathology using local measures of broadband reflectance

“…[25][26][27][28] Georgakoudi augmented LSS with diffuse reflectance spectroscopy and fluorescence spectroscopy (trimodal spectroscopy) to discriminate between dysplasia or cancerous and normal oral tissues, achieving a sensitivity and specificity of 96%. 28 Keller et al, 29 Breslin et al, 30 Palmer et al, 31 and Zhu et al, 32 combined diffuse reflectance with fluorescence spectroscopy to discriminate between benign and malignant breast tissues, achieving a sensitivity: specificity of 70.0%:91.7% and 78%:99%, respectively. More recently, Keller et al 29 developed a Monte Carlo inverse model to generate chromophore and scattering maps from visible-near-infrared diffuse reflectance spectra.…”

“…28 Keller et al, 29 Breslin et al, 30 Palmer et al, 31 and Zhu et al, 32 combined diffuse reflectance with fluorescence spectroscopy to discriminate between benign and malignant breast tissues, achieving a sensitivity: specificity of 70.0%:91.7% and 78%:99%, respectively. More recently, Keller et al 29 developed a Monte Carlo inverse model to generate chromophore and scattering maps from visible-near-infrared diffuse reflectance spectra. When applied to 55 surgical margins, a multivariate predictive model discriminated between positive and negative breast tissue margins up to 2 mm in depth, with a sensitivity and specificity of 79 and 67%, respectively.…”