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. 2020 Aug;14(4):879-888.
doi: 10.1109/TBCAS.2020.3005971. Epub 2020 Jun 30.

Towards a Portable Platform Integrated With Multispectral Noncontact Probes for Delineating Normal and Breast Cancer Tissue Based on Near-Infrared Spectroscopy

Towards a Portable Platform Integrated With Multispectral Noncontact Probes for Delineating Normal and Breast Cancer Tissue Based on Near-Infrared Spectroscopy

Uttam M Pal et al. IEEE Trans Biomed Circuits Syst. 2020 Aug.

Abstract

Currently, the confirmation of diagnosis of breast cancer is made by microscopic examination of an ultra-thin slice of a needle biopsy specimen. This slice is conventionally formalin-fixed and stained with hematoxylin-eosin and visually examined under a light microscope. This process is labor-intensive and requires highly skilled doctors (pathologists). In this paper, we report a novel tool based on near-infrared spectroscopy (Spectral-IRDx) which is a portable, non-contact, and cost-effective system and could provide a rapid and accurate diagnosis of cancer. The Spectral-IRDx tool performs absorption spectroscopy at near-infrared (NIR) wavelengths of 850, 935, and 1060 nm. We measure normalized detected voltage (Vdn) with the tool in 10 deparaffinized breast biopsy tissue samples, 5 of which were cancer (C) and 5 were normal (N) tissues. The difference in Vdn at 935 nm and 1060 nm between cancer and normal tissues is statistically significant with p-values of 0.0038 and 0.0022 respectively. Absorption contrast factor (N/C) of 1.303, 1.551, and 1.45 are observed for 850, 935, and 1060 nm respectively. The volume fraction contrast (N/C) of lipids and collagens are reported as 1.28 and 1.10 respectively. Higher absorption contrast factor (N/C) and volume fraction contrast (N/C) signifies higher concentration of lipids in normal tissues as compared to cancerous tissues, a basis for delineation. These preliminary results support the envisioned concept for noninvasive and noncarcinogenic NIR-based breast cancer diagnostic platform, which will be tested using a larger number of samples.

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