Time‐Resolved Fluorescence and Diffuse Reflectance ( <scp>TRF</scp> ‐ <scp>DR</scp> ) Spectroscopy for Heterogeneous Breast Tissue Classification and Tumor Margin Assessment

Re-excision rates remain high for early-stage breast cancer patients due to challenges in margin delineation during surgery, such as poorly defined tumor boundaries. Our group has developed a time-resolved fluorescence and diffuse reflectance (TRF-DR) spectroscopy system to assess tumor boundaries where tissue composition is heterogeneous. This study assesses system feasibility for classifying tumor in heterogeneous regions using weighted logistic regression and principal component analysis (PCA). A total of 4818 measurements from 73 frozen patient ex vivo samples were evaluated. Tissue measurement areas (1 mm × 1 mm) were pathologist-assigned percentages of low (< 25%), medium (25%-< 75%), and high (≥ 75%) for tumor, fibroglandular, or adipose composition. The model trained with four principal components (PCs) achieved sensitivity of 77% and specificity of 68%, comparable to current clinical techniques while being fast, portable, and economical. The TRF-DR system with weighted logistic regression demonstrates potential as an intraoperative margin assessment tool.

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Publication Details

Journal
Journal of Biophotonics
Published
2026-02-01
DOI
https://doi.org/10.1002/jbio.70230
Primary Topic
Optical Imaging and Spectroscopy Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Time‐Resolved Fluorescence and Diffuse Reflectance ( TRF ‐ DR ) Spectroscopy for Heterogeneous Breast Tissue Classification and Tumor Margin Assessment

Gabriella Gohla, Michael J. Farquharson, Erica Dao, Peter Lovrics et al.
Journal of Biophotonics
Optical Imaging and Spectroscopy Techniques
article

Time‐Resolved Fluorescence and Diffuse Reflectance ( TRF ‐ DR ) Spectroscopy for Heterogeneous Breast Tissue Classification and Tumor Margin Assessment

Gabriella Gohla, Michael J. Farquharson, Erica Dao, Peter Lovrics, Qiyin Fang, Jigar Lad, Thomas J. Farrell
article en

Abstract

Re-excision rates remain high for early-stage breast cancer patients due to challenges in margin delineation during surgery, such as poorly defined tumor boundaries. Our group has developed a time-resolved fluorescence and diffuse reflectance (TRF-DR) spectroscopy system to assess tumor boundaries where tissue composition is heterogeneous. This study assesses system feasibility for classifying tumor in heterogeneous regions using weighted logistic regression and principal component analysis (PCA). A total of 4818 measurements from 73 frozen patient ex vivo samples were evaluated. Tissue measurement areas (1 mm × 1 mm) were pathologist-assigned percentages of low (< 25%), medium (25%-< 75%), and high (≥ 75%) for tumor, fibroglandular, or adipose composition. The model trained with four principal components (PCs) achieved sensitivity of 77% and specificity of 68%, comparable to current clinical techniques while being fast, portable, and economical. The TRF-DR system with weighted logistic regression demonstrates potential as an intraoperative margin assessment tool.

Journal of BiophotonicsVol. 19(2)
St. Joseph Hospital (US), St. Joseph's Hospital (CA), St. Joseph’s Healthcare Hamilton (CA), Hamilton Health Sciences (CA), McMaster University (CA)
Max-Planck-Institut für Chemie, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 71%
Optical Imaging and Spectroscopy Techniques
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