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Combining scanning haptic microscopy and fibre optic Raman spectroscopy for tissue characterisation
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Umeå University, Umeå, Sweden; Signals and Systems, Chalmers University of Technology, 412 96, Gothenburg, Sweden; MedTech West, Sahlgrenska University Hospital, Blå Stråket 7, 413 45, Gothenburg, Sweden.
Umeå University, Umeå, Sweden; Department of Electrical and Electronics Engineering, College of Engineering, Nihon University, Fukushima, Japan.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Umeå University, Umeå, Sweden.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Umeå University, Umeå, Sweden.ORCID iD: 0000-0003-3191-8335
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2012 (English)In: Journal of Medical Engineering & Technology, ISSN 0309-1902, E-ISSN 1464-522X, Vol. 36, no 6, p. 319-327Article in journal (Refereed) Published
Abstract [en]

The tactile resonance method (TRM) and Raman spectroscopy (RS) are promising for tissue characterisation in vivo. Our goal is to combine these techniques into one instrument, to use TRM for swift scanning, and RS for increasing the diagnostic power. The aim of this study was to determine the classification accuracy, using support vector machines, for measurements on porcine tissue and also produce preliminary data on human prostate tissue. This was done by developing a new experimental setup combining micro-scale TRM — scanning haptic microscopy (SHM) — for assessing stiffness on a micro-scale, with fibre optic RS measurements for assessing biochemical content. We compared the accuracy for using SHM alone versus SHM combined with RS, for different degrees of tissue homogeneity. The cross-validation classification accuracy for healthy porcine tissue types using SHM alone was 65–81%, and when RS was added it was increased to 81–87%. The accuracy for healthy and cancerous human tissue was 67–70% when only SHM was used, and increased to 72–77% for the combined measurements. This shows that the potential for swift and accurate classification of healthy and cancerous prostate tissue is high. This is promising for developing a tool for probing the surgical margins during prostate cancer surgery.

Place, publisher, year, edition, pages
2012. Vol. 36, no 6, p. 319-327
National Category
Other Medical Engineering
Research subject
Medical Engineering for Healthcare; Centre - Centre for Biomedical Engineering and Physics (CMTF)
Identifiers
URN: urn:nbn:se:ltu:diva-2815DOI: 10.3109/03091902.2012.687035PubMedID: 22762445Scopus ID: 2-s2.0-84864242193Local ID: 083ed69f-9222-4f86-af6c-8d1e25131a0eOAI: oai:DiVA.org:ltu-2815DiVA, id: diva2:975668
Note

Validerad; 2012; 20120417 (qwazi)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2024-05-08Bibliographically approved

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Candefjord, StefanNyberg, MorganHallberg, JosefRamser, KerstinLindahl, Olof

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