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

Journal of biophotonics 2026 Vol.19(2) p. e70230

Lad J, Dao E, Gohla G, Lovrics P, Fang Q, Farrell TJ, Farquharson MJ

📝 환자 설명용 한 줄

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.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • Sensitivity 77%
  • Specificity 68%

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BibTeX ↓ RIS ↓
APA Lad J, Dao E, et al. (2026). Time-Resolved Fluorescence and Diffuse Reflectance (TRF-DR) Spectroscopy for Heterogeneous Breast Tissue Classification and Tumor Margin Assessment.. Journal of biophotonics, 19(2), e70230. https://doi.org/10.1002/jbio.70230
MLA Lad J, et al.. "Time-Resolved Fluorescence and Diffuse Reflectance (TRF-DR) Spectroscopy for Heterogeneous Breast Tissue Classification and Tumor Margin Assessment.." Journal of biophotonics, vol. 19, no. 2, 2026, pp. e70230.
PMID 41622347
DOI 10.1002/jbio.70230

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.

MeSH Terms

Humans; Breast Neoplasms; Female; Margins of Excision; Time Factors; Spectrometry, Fluorescence; Breast; Principal Component Analysis; Middle Aged