Presentation
9 March 2020 Spatially offset Raman spectroscopy for in vivo bone strength prediction with minimized soft tissue influence (Conference Presentation)
Author Affiliations +
Abstract
Using transcutaneous spatially offset Raman spectroscopy (SORS) and partial least squares regression (PLSR), we recently predicted the areal bone mineral density (aBMD), volumetric bone mineralization density (vBMD) and maximum torque (MT) of tibiae in living mice. Despite the spatial offset geometry, the accuracy of the predictions was still affected by the signal from the overlying soft tissue that, like bone, contains large amounts of Type I collagen. Here we report a way to use SOLD (simultaneous, overconstrained, library-based decomposition) to improve the PLSR accuracy. The SOLD processing generates one bone spectrum estimate, one soft tissue spectrum estimate, and a residual. We combine the bone and residual spectra together for submission to PLSR, discarding only the soft tissue contribution. With the implementation of this soft-tissue-subtracted SOLD processing, we demonstrate that we can predict vBMD and MT more accurately than our previous transcutaneous measurements.
Conference Presentation
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Keren Chen, Christine M. Massie, and Andrew J. Berger "Spatially offset Raman spectroscopy for in vivo bone strength prediction with minimized soft tissue influence (Conference Presentation)", Proc. SPIE 11236, Biomedical Vibrational Spectroscopy 2020: Advances in Research and Industry, 112360J (9 March 2020); https://doi.org/10.1117/12.2545993
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KEYWORDS
Bone

Raman spectroscopy

In vivo imaging

Tissue optics

Tissues

Collagen

Minerals

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