Light can be coupled into imaging spectrographs through the use of fiber-optic bundles. Ideally, the collected
spectra from adjacent optical fibers should be resolved and independent. However, this assumption breaks down if a
partial overlap of adjacent fibers on the detector CCD results from either diffraction or uncorrected monochromatic
aberrations. In addition, spectral mixing can be caused by optical cross-talk among tightly packed fibers, particularly if
the fiber-optic buffer has been removed in order to use the CCD area more efficiently and increase the linear fiber
packing density. These coupling effects can become sources of systematic error, especially when fiber bundles are used
for imaging or when branches of a multi-leg fiber array are interrogating different samples. Coupling errors can mix
spectra from different spatial regions of the sample. In this paper, the mixing in fiber bundles will be assessed, and
mathematical methods to resolve overlapped signals and correct for signal mixing will be discussed. Using data
processing to correct for optical coupling errors, instead of physically changing the spacing between fibers in the bundle,
allows for the efficient use of the limited spectrograph detector area by having a larger number of fibers.
Stress differences via spectral shifts that arise among failed, strained, and undamaged regions of bone can be determined using Raman spectroscopy and double-notch specimens. A double-notch specimen is a model in which the early stages of fracture can be examined. At four-point bending, fracture occurs at one of the notches. Tissue near each notch is representative of bone in a state either directly before or after bone failure. Raman images are acquired among three regions: control, strained (root of unbroken notch), and failed (root of fractured notch). The center of gravities (CGs), a way to monitor wavenumber shifts, of the phosphate v1 band are calculated. A PO v1 band shift most likely corresponds to a change in spacing between phosphate cations and anions. This spectral shift is converted into stress values using the dv/dP coefficient, determined by applying known pressures/stresses and measuring the change in position of the PO v1 band. In comparison to control regions, the residual stress in strained and failed regions is significantly higher (p=0.0425 and p=0.0169, respectively). In strained regions, residual stress is concentrated near the corners of the unbroken notch, whereas in failed regions the high stresses are confined near the edge of the fracture.
Light-scattering spectroscopy has the potential to provide information about bone composition via a fiber-optic probe
placed on the skin. In order to design efficient probes, one must understand the effect of all tissue layers on photon
transport. To quantitatively understand the effect of overlying tissue layers on the detected bone Raman signal, a layered
Monte Carlo model was modified for Raman scattering. The model incorporated the absorption and scattering properties
of three overlying tissue layers (dermis, subdermis, muscle), as well as the underlying bone tissue. The attenuation of the
collected bone Raman signal, predominantly due to elastic light scattering in the overlying tissue layers, affected the
carbonate/phosphate (C/P) ratio by increasing the standard deviation of the computational result. Furthermore, the mean
C/P ratio varied when the relative thicknesses of the layers were varied and the elastic scattering coefficient at the
Raman scattering wavelength of carbonate was modeled to be different from that at the Raman scattering wavelength of
phosphate. These results represent the first portion of a computational study designed to predict optimal probe geometry
and help to analyze detected signal for Raman scattering experiments involving bone.
Raman spectroscopic diffuse tomographic imaging has been demonstrated for the first time. It provides a noninvasive, label-free modality to image the chemical composition of human and animal tissue and other turbid media. This technique has been applied to image the composition of bone tissue within an intact section of a canine limb. Spatially distributed 785-nm laser excitation was employed to prevent thermal damage to the tissue. Diffuse emission tomography reconstruction was used, and the location that was recovered has been confirmed by micro-computed tomography (micro-CT) images.
The effect of optical clearing with glycerol on the Raman spectra of bone tissue acquired transcutaneously on right and left tibiae from four mice is studied. Multiple transcutaneous measurements are obtained from each limb; glycerol is then applied as an optical clearing agent, and additional transcutaneous measurements are taken. Glycerol reduces the noise in the raw spectra (p=0.0037) and significantly improves the cross-correlation between the recovered bone factor and the exposed bone measurement in a low signal-to-noise region of the bone spectra (p=0.0245).
We report tomographic reconstruction of objects located several millimeters below the surface of highly scattering
media. For this purpose we adapted proven software developed for fluorescence tomography with and without the use of
spatial priors1. For this first demonstration we acquired Raman spectra using an existing ring/disk fiber optic probe with
fifty collection fibers2. Several illumination ring diameters were employed to generate multiple angles of incidence.
Tomographic reconstruction from Raman scatter was tested using a 9.5 mm diameter Teflon® sphere embedded in a gel
of agarose and 1% Intralipid. Blind reconstruction of the sphere using the 732 cm-1 C-F stretch yielded an accurate shape
but an inaccurate depth. Using the known shape and position of the object as spatial priors, a more accurate
reconstruction was obtained. We also demonstrated a reconstruction of the tibial diaphysis of an intact canine hind limb
using spatial priors generated from micro-computed tomography. In this first demonstration of Raman tomography in
animal tissue, the P-O stretch of the bone mineral at 958 cm-1 was used for the reconstruction. An accurate shape and
depth were recovered.
Understanding compositional changes that occur when bone fails may help predict fracture risk. Compositional
differences that arise among failed, strained, and undamaged regions of bone can be determined using Raman
spectroscopy and double-notch specimens. A double-notch specimen is a rectangular bone beam that has identical,
rounded notches milled equidistant from each end. When subjected to a four-point bend test, maximum strains occur at
the roots of the notches, and eventually the bone fractures at one of the notches. Because both notches experience the
same force, when one notch breaks, the other is 'frozen' in the state directly preceding fracture. Spectra taken at the
roots of both the unbroken and fractured notches can measure changes in tissue that occur prior to and after bone failure,
respectively. Phosphate center of gravities (CGs) were calculated and compared among three regions: control, strained
(root of unbroken notch), and failed (root of fractured notch). In comparison to control regions, the phosphate CGs near
the unbroken notch showed a shift toward higher wavenumbers ( > 0.5 cm-1), with the shift being concentrated at the
corners of the notch. The tissue in the failed region appears to have relaxed, and showed a shift toward higher
wavenumbers ( > 0.5 cm-1) only near the edge of the fracture.
Transcutaneous bone Raman spectroscopy with an exciting annulus of 785-nm laser light surrounding the field of view of a circular array of collection fibers is demonstrated. The configuration provides distributed laser light. The annulus is located 2 to 3 mm beyond the edge of the field of view of the collection fibers to reject contributions from skin and other overlying tissues. Data are presented for rat and chicken tissue. For rat tibia, the carbonate/phosphate ratio measured at a depth of 1 mm below the skin is in error by 2.3% at an integration time of 120 s and within 10% at a 30-s integration time. For chicken tibia 4 mm below the skin surface, the error is less than 8% with a 120-s integration time.
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