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- Häggblad, Erik, 1972-
(författare)
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In Vivo Diffuse Reflectance Spectroscopy of Human Tissue : From Point Measurements to Imaging
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis presents the non-invasive use of diffuse reflectance spectroscopy (DRS) to provide information about the biochemical composition of living tissue. During DRS measurements, the incident, visible light is partially absorbed by chromophores but also scattered in the tissue before being remitted.Human skin and heart, the main tissue objects in this thesis, are dependent on a sufficient inflow of oxygenized blood, and outflow of metabolic byproducts. This process could be monitored by DRS using the spectral fingerprints of the most important tissue chromophores, oxyhemoglobin and deoxyhemoglobin.The Beer-Lambert law was used to produce models for the DRS and has thus been a foundation for the analyses throughout this work. Decomposition into the different chromophores was performed using least square fitting and tabulated data for chromophore absorptivity.These techniques were used to study skin tissue erythema induced by a provocation of an applied heat load on EMLA-treated skin. The absorbance differences, attributed to changes in the hemoglobin concentrations, were examined and found to be related to, foremost, an increase in oxyhemoglobin.To estimate UV-induced border zones between provoked and nonprovoked tissue a modified Beer-Lambert model, approximating the scattering effects, was used. An increase of chromophore content of more than two standard deviations above mean indicated responsive tissue. The analysis revealed an edge with a rather diffuse border, contradictory to the irradiation pattern.Measuring in the operating theater, on the heart, it was necessary to calculate absolute chromophore values in order to assess the state of the myocardium. Therefore, a light transport model accounting for the optical properties, and a calibrated probe, was adopted and used. The absolute values and fractions of the chromophores could then be compared between sites and individuals, despite any difference of the optical properties in the tissue.A hyperspectral imaging system was developed to visualize the spatial distribution of chromophores related to UV-provocations. A modified Beer-Lambert approximation was used including the chromophores and a baseline as an approximate scattering effect. The increase in chromophore content was estimated and evaluated over 336 hours.In conclusion, advancing from a restricted Beer-Lambert model, into a model estimating the tissue optical properties, chromophore estimation algorithms have been refined progressively. This has allowed advancement from relative chromophore analysis to absolute values, enabling precise comparisons and good prediction of physiological conditions.
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| 2. |
- Ewerlöf, Maria, 1987-
(författare)
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Multispectral imaging of hemoglobin oxygen saturation in skin microcirculation
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The ability to measure microcirculatory parameters such as hemoglobin oxygen saturation is important since it mirrors the microcirculatory state of the body. The microcirculation delivers oxygen and nutrients to the cells of the body and, if impaired, may be a sign of circulatory failure. Human skin microcirculation can be accessed non-invasively with bio-optical technologies, where skin acts as a diagnostic window. Diffuse reflectance spectroscopy (DRS) is a technique that access skin microcirculatory parameters, especially hemoglobin oxygen saturation. Basic systems are fiber optic probebased and measure in one point, often in firm contact with the skin. Multispectral diffuse reflectance imaging (MSI) enables spatially resolved DRS, imaging skin optical parameters from spectrally resolved backscattered intensities. Spectral information detected by MSI systems contain information on, e.g., hemoglobin oxygen saturation and optical properties of the tissue. Both spatial and temporal resolved information of hemoglobin oxygen saturation is beneficial for better diagnostics in most clinical applications, e.g., to monitor progression of wound healing processes, or other microcirculatory diseases reflected in hemoglobin spectral changes. Analysis of acquired MSI multispectral data cubes to access information on tissue parameters with high contrast to these variations can be performed in several ways using models and simulations. Time resolved continuous measurements that are spectrally and spatially resolved generate large amounts of data, requiring both storage space and fast analysis. Reducing the number of wavelengths is one way to limit the amount of data, if it does not reduce the quality of interpreted results. Therefore, in my work, I investigated theoretically how to reduce the number of wavelengths, and later implemented my findings using a snapshot MSI camera. Monte Carlo (MC) simulations were used to estimate hemoglobin oxygen saturation from captured MSI data. I also performed temporally resolved in vivo measurements on healthy test subjects during vascular occlusion provocations with a 16-channel snapshot MSI system. The acquired data were analyzed using two different methods: inverse MC and trained artificial neural networks (ANNs). For inverse MC, the acquired spectrum was iteratively compared to simulated spectra, where different optical properties were used for the simulation, trying to find the best fit. ANNs were trained to intensity data measured with the MSI system, using concurrently measured hemoglobin oxygen saturation values from a validated probe-based system as target data. The results and outcome of this thesis indicate good possibility to accurately estimate hemoglobin oxygen saturation with as few as four wavelengths. Estimated hemoglobin oxygen saturation values from analysis of in vivo measurements from the 16-channel snapshot MSI camera show high conformance to values measured by the validated probe-based system. Using the ANN-approach reduces time for analysis of a 512 × 270-pixel image to 0.056 s, compared to 1 h 58 min required by the inverse MC algorithm to analyze the same data. The method enables real-time analysis, and is, consequently, preferable in many clinical situations.
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