Abstract

Most tissue optical spectroscopy platforms use a fiber probe for light delivery and collection, while the inconsistent probe-sample contact could induce significant distortions in the measured optical signals, which consequently bring analysis errors. Moreover, it will be practically difficult to use a fiber probe for measurements in some cases such as oral cancer investigations using small animal models. To address the critical challenge, we report a portable, lens-based, optical spectroscopy device capable of quantifying key vascular and metabolic parameters in vivo without probe-sample contact. We combined lenses based diffuse reflectance and fluorescence spectroscopy into one portable platform to enable multi-parametric functional characterizations of orthotopic tongue cancer models in vivo. We also implemented easy-to-use spectroscopic algorithms with the system for rapid quantification of the key metabolic and vascular parameters on biological tissue models. We then demonstrated our non-contact optical spectroscopy on tissue-mimicking phantoms and in vivo mouse tongue tumor models. Our phantom and in vivo animal studies showed that our non-contact optical spectroscopy, along with spectroscopic algorithms, could quantify the major metabolic and vascular parameters on in vivo tongue tumors with high accuracy. We also captured the diverse metabolic and vascular phenotypes of tongue tumors with different radiation sensitivity. Our new optical spectroscopy implemented with easy-to-use spectroscopic algorithms will provide a non-contact way for rapid and systematic characterizations of biological tissue metabolism and vascular microenvironment in vivo, which may significantly advance head and neck cancer research in the future.

Document Type

Article

Publication Date

2026

Notes/Citation Information

1077-260X © 2025 IEEE. All rights reserved, including rights for text and data mining, and training of artificial intelligence and similar technologies. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

Digital Object Identifier (DOI)

https://doi.org/10.1109/JSTQE.2025.3635031

Funding Information

This work was supported in part by NIDRC under Grant R01DE031998 and in part by NIGMS under Grant R01DE031998.

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