Overconstrained library-based fitting method reveals age- and disease-related differences in transcutaneous Raman spectra of murine bones

Abstract

Abstract. Clinical diagnoses of bone health and fracture risk typically rely on measurements of bone density or structure, but the strength of a bone is also dependent on its chemical composition. Raman spectroscopy has been used extensively in ex vivo studies to measure the chemical composition of bone. Recently, spatially offset Raman spectroscopy (SORS) has been utilized to measure bone transcutaneously. Although the results are promising, further advancements are necessary to make noninvasive, in vivo measurements of bone with SORS that are of sufficient quality to generate accurate predictions of fracture risk. In order to separate the signals from bone and soft tissue that contribute to a transcutaneous measurement, we developed an overconstrained extraction algorithm that is based on fitting with spectral libraries. This approach allows for accurate spectral unmixing despite the fact that similar chemical components (e.g., type I collagen) are present in both bone and soft tissue. The algorithm was utilized to transcutaneously detect biochemical differences in the tibiae of wild-type mice between 1 and 7 months of age and between the tibiae of wild-type mice and a mouse model of osteogenesis imperfecta. These results represent the first diagnostically sensitive, transcutaneous measurements of bone using SORS. © The Authors.Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Raman spectroscopy: techniques and applications in the life sciences

“…Such advances should also benefit biomedical applications of TRS and micro-SORS. Separation of the layers by library-based modeling could also be promising for extracting more specific information such as mineral to matrix ratios in bone/tissue layers [415].…”

Decomposition of in vivo spatially offset Raman spectroscopy data using multivariate analysis techniques

“…For these systems, more sophisticated methods, such as library-based fitting, need to be employed. [20] Another approach is to use multivariate analysis; band-target entropy minimization (BTEM), [21][22][23] coupled with SORS, has been used to measure the carbonate-to-phosphate ratio of rat tibia through 1 mm of skin (with an error of 2.3%), [12] of chicken tibia through 4 mm of skin/soft tissue (with an error of 8%) [12] and of porcine bone through~1 mm of soft tissue. [19] In the latter study, a second spectral decomposition method, parallel factor analysis (PARAFAC) [24] , was also used to retrieve the bone spectrum.…”

Sensitivity of coded aperture Raman spectroscopy to analytes beneath turbid biological tissue and tissue-simulating phantoms

“…Various computational algorithms can then be used to extract spectra of analytes present at different depths. 26 This study reports the generalizable relationship between relative analyte signal and the transport MFPs of an overlying scattering medium. It should be noted, however, that the ability to accurately quantify analyte concentrations or biochemical tissue properties depends not upon absolute signal levels, but rather on signal-to-background ratios (SBRs) and SNRs.…”

“…In the subfield of biomedical Raman spectroscopy, these include transcutaneous measurements of blood glucose levels, 24 breast tumor tissue, 25 bone, 26 and the pharmacokinetics of various topically applied drugs. 27 Our laboratory is particularly interested in validating pharmacokinetic models of topically applied drugs used for prophylaxis against human immunodeficiency virus.…”