Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery

Published

May 7, 2024

Author(s)

Jeeseong Hwang, Philip Cheney, Stephen Kanick, Hanh Le, David McClatchy, Helen Zhang, John Lu, Tae Joon Cho, Kimberly Briggman, David W. Allen, Wendy A. Wells, Brian Pogue

Abstract

Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful classification of various tissue types, including the detection of carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries. Performance of the HSDFM is evaluated by comparing the backscattering intensity spectra of polystyrene microbead solutions with the Monte Carlo simulation of the experimental data. For classification algorithms, two approaches, a supervised technique based on the spectral angle mapper (SAM) algorithm and an unsupervised K-means algorithm, are used. The manually extracted endmembers of known tissue types were determined by the histopathology reading of the hematoxylin and eosin (H&E)-stained slides. Their associated threshold spectral correlation angles from the SAM algorithm for supervised classification make a good reference library that validates endmembers from the unsupervised algorithm. For the unsupervised classification, a K-means algorithm, with no a priori information, produces abundance maps with dominant endmembers of various tissue types present, including carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma. The two carcinomas' unique endmembers used by the two methods agree with each other within less than 2% residual error margin. The unsupervised method enables spectral unmixing of various tissue types from a single pixel spectrum, demonstrating the potential for tumor margin detection at a single cell level. Ongoing work includes analysis of other carcinoma subtypes such as invasive lobular carcinoma and phyllodes.

Citation

Journal of Biomedical Optics

Volume

29

Issue

9

Pub Type

Journals

Download Paper

https://doi.org/10.1117/1.JBO.29.9.093503

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Keywords

breast tissue imaging, hyperspectral imaging, tumor margin detection, dark field microscopy, optical biopsy

Citation

Hwang, J. , Cheney, P. , Kanick, S. , Le, H. , McClatchy, D. , Zhang, H. , Lu, J. , Cho, T. , Briggman, K. , Allen, D. , Wells, W. and Pogue, B. (2024), Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery, Journal of Biomedical Optics, [online], https://doi.org/10.1117/1.JBO.29.9.093503 , https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957169 (Accessed March 3, 2025)