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Thermal product sensing: simulations and experiments of a novel biosensor for quantitative thermal property measurement of biological tissues

Abstract:

Skin cancer represents a critical global health challenge, with incidence rates rising dramatically over recent decades. In the UK, the incidence of malignant melanoma has increased from 837 per year to 6963 per year in males and 1609 per year to 6952 per year in females between 1981 and 2018. Current diagnostic methods rely on time-consuming biopsy and histopathological analysis, which can delay critical intervention. This study uses a Thermal Product Sensor (TPS), a technology proven in aerospace engineering applications, now transferred to biomedical applications. This new and innovative biosensor is designed to provide rapid, quantitative assessment of biological tissue thermal properties. The Thermal Product sensor employs a measurement technique utilizing platinum thin-film gauges on a Macor substrate to directly measure thermal transfer characteristics. Through detailed mathematical modeling and experimental validation, the sensor's capability to distinguish between different biological tissue types with high precision is demonstrated. The sensor's working principle is grounded in fundamental heat transfer principles, specifically leveraging the relationship between thermal conductivity, density, and specific heat capacity.

Experimental validation using porcine tissue samples revealed the sensor's ability to differentiate between skin, fat, and muscle tissues with 99.9% confidence. Furthermore, the study investigated the impact of medical films on thermal measurements, showing minimal interference for skin tissues and providing crucial insights for potential clinical applications. A numerical heat transfer model was developed - utilising both the one-dimensional heat diffusion equation and Pennes’ bioheat equation - to increase understanding of the detrimental effect on sensitivity of a plastic medical film and to aid in future design optimisation. Thermal responses to cancerous and non-cancerous tissue were investigated, exploring the sensors potential as a diagnostic tool.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.5281/zenodo.15602993

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Anne's College
Role:
Author


Publisher:
Mega Journal of Case Reports
Journal:
Mega Journal of Case Reports More from this journal
Volume:
8
Issue:
6
Pages:
2001-2019
Publication date:
2025-06-06
Acceptance date:
2025-06-04
DOI:
ISSN:
2995-8458

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