Abstract
Spatially offset Raman spectroscopy (SORS) is valuable for noninvasive bone assessment but requires a clearer understanding of how offset distances influence detection depth. To address this, our study devised a forward-adjoint Monte Carlo multi-layer (MCML) model to simulate photon paths in SORS, aiming to determine optimal offsets for various tissue types. We examined photon migration at offsets between 0 and 15 mm against layered phantoms of differing thicknesses and compositions to optimize the signal-to-noise ratio for bone layers. The findings highlight that optimal offsets are contingent on tissue characteristics: a metacarpal beneath 2.5 mm of tissue had an ideal offset of 6.7 mm, while a tibia with 5 mm of soft tissue required 10-11 mm. This precise calibration of SORS via MCML modeling promises substantial improvements in bone health diagnostics and potential for expansive medical applications.
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