Tissue fraction red blood cells and oxygen saturation
Hemoglobin, the oxygen carrying protein found in red blood cells, absorbs light in a characteristic manner. Its absorption spectra, i.e. how much light that it absorbs dependent on wavelength, is different dependent on if it carries oxygen (saturated hemoglobin) compared to if it does not (reduced hemoglobin), see Figure. By illuminating tissue with white light, i.e. light that contains “all” wavelengths, and studying how much light that is detected at each wavelength, conclusions about the amount of hemoglobin (or red blood cells) that is present in the sampling volume, as well as its oxygen saturation, can be drawn, see figure. By illuminating tissue with white light, i.e. light that contains “all” wavelengths, and studying how much light that is detected at each wavelength, conclusions about the amount of hemoglobin (or red blood cells) that is present in the sampling volume, as well as its oxygen saturation, can be drawn.
It is the same principle that is used in a pulse oximeter, but with the important difference that we analyze all backscattered light, not only the pulsative part in light that has been transmitted through for example a finger as in pulse oximetry. As a consequence, this technique (diffuse reflectance spectroscopy, DRS) reveals information about the oxygen saturation in all blood in the sampling volume, not only about the blood in the arteries. A typical value of the oxygen saturation in skin is slightly less than 50 % with our technique, whereas it should be close to 100 % when measuring with a pulse oximeter. A low oxygen saturation indicates that the oxygen has left the blood, which is often positive, dependent on the situation.
Applications
By combining DRS and LDF, simultaneous information about the tissue fraction of red blood cells, its oxygen saturation and speed resolved perfusion can be retrieved in the same point. We are convinced that this combined information gives a benefit compared with measuring the parameters separately. It will lead to new insights within the area of microcirculation, which until now has been an inaccessible part of the physiology to study. In addition, it can give valuable diagnostic information related to a number of diseases, including diabetes mellitus and cardiovascular disease. By making certain assumptions, the measures can be used to assess the local tissue metabolism.
We have used EPOS in a study on healthy subjects [ref 4] where we have studied the normal response during heat and occlusion provocations. We have also used the technique in a study including persons with diabetes type II [ref 1 och 9]. We have recently finished the data collection in the Swedish Heart-Lung Foundation’s national study SCAPIS, where we used EPOS to characterize the microcirculation in a local add-on called SCAPIS-MICRO. We collected data from more than 4000 persons 50-64 years old. The long-term aim of that study is to find early signs of impaired microcirculation in persons developing cardiovascular disease.
Model-based analysis
A tissue model, consisting of a number of adaptive parameters, is the core of the model-based analysis of the detected signals in EPOS. Using a specific set of parameter values, spectra (DRS and LDF spectra) are calculated and compared to measured spectra. The model parameters are iteratively updated until calculated and measured spectra match. When a good match is achieved, it is assumed that the tissue model reflects the tissue. Output data, i.e. tissue fraction red blood cells, their oxygen saturation and speed resolved perfusion, are then calculated from the adapted tissue model, rather than directly from the measured signals.
This is a computational demanding procedure, but by utilizing the GPU (graphic processing unit) and hyper-parallel GPU programming, the computations can be performed in real-time with multiple measurements per second. The model-based analysis enables new possibilities to extract more and new information from the measured signals. Both techniques gain from the integration via the joint tissue model. The information from DRS is for example used to estimate the scattering properties that can then be compensated for when the Doppler spectra are analyzed. The method is thoroughly described in [ref 6].
Instrument
The technique is now available as an instrument via Perimed AB,
Periflux 6000 EPOS System. The instrument uses a fiber-based probe for delivery of laser light and white light to the tissue, and for detecting backscattered light using closely located fibers. The instrument contains dedicated software for analysis of the detected signals and for measuring and performing various types of provocations, such as local heating and occlusion. The instrument is a special configuration of Perimed’s modular system Periflux 6000, and consists of at least a PF 6010 LDF module and a PF 6060 spectroscopy module, but can also include a PF 6040 tcpO2 module and a PF 6050 pressure unit.
Financing
This project has received grants from Sweden’s innovation agency VINNOVA several times, most recently via MedTech4Health, d.no. 2016-02211.
Publications
Bergstrand S, Morales M-A, Coppini G, Larsson M, Strömberg T., The relationship between forearm skin speed-resolved perfusion and oxygen saturation, and finger arterial pulsation amplitudes, as indirect measures of endothelial function. Microcirculation. 25(2), 2018.
Jonasson H, Fredriksson I, Bergstrand S, Östgren CJ, Larsson M, Strömberg T. In vivo characterization of light scattering properties of human skin in the 475- to 850-nm wavelength range in a Swedish cohort. Journal of Biomedical Optics. 23(12), 2018.
Strömberg T, Sjöberg F, Bergstrand S. Temporal and spatiotemporal variability in comprehensive forearm skin microcirculation assessment during occlusion protocols.Microvascular Research. 113, 2017.
Jonasson, H., et al., Skin microvascular endothelial dysfunction is associated with type 2 diabetes independently of microalbuminuria and arterial stiffness. Diabetes and Vascular Disease Research, 2017: p. 1479164117707706.
Fredriksson, I., Saager, R.B., Durkin, A.J., and Strömberg, T. Evaluation of a multi-layer diffuse reflectance spectroscopy system using optical phantoms. in Proc. SPIE. 2017.
Jonasson, H, Model-based quantitative assessment of skin microcirculatory blood flow and oxygen saturation, 2016 Doktorsavhandling
Jonasson, H., Fredriksson, I., Pettersson, A., Larsson, M., and Strömberg, T., Oxygen saturation, red blood cell tissue fraction and speed resolved perfusion - A new optical method for microcirculatory assessment. Microvasc Res, 2015. 102: p. 70-77.
Fredriksson, I., Larsson, M., and Strömberg, T., Model-Based Quantification of Skin Microcirculatory Perfusion, in Computational Biophysics of the Skin, B. Querleux, Editor. 2014, Pan Stanford Publishing: Singapore. p. 395–418.
Fredriksson, I., Burdakov, O., Larsson, M., and Strömberg, T., Inverse Monte Carlo in a multilayered tissue model: merging diffuse reflectance spectroscopy and laser Doppler flowmetry. Journal of Biomedical Optics, 2013. 18(12): p. 127004-127004.
Fredriksson, I., Larsson, M., and Strömberg, T., Inverse Monte Carlo method in a multilayered tissue model for diffuse reflectance spectroscopy. Journal of Biomedical Optics, 2012. 17(4): p. 047004-12.
Fredriksson, I., Larsson, M., and Strömberg, T., Model-based quantitative laser Doppler flowmetry in skin. Journal of Biomedical Optics, 2010. 15(5): p. 057002.
Fredriksson, I., et al., Reduced Arteriovenous Shunting Capacity After Local Heating and Redistribution of Baseline Skin Blood Flow in Type 2 Diabetes Assessed With Velocity-Resolved Quantitative Laser Doppler Flowmetry. Diabetes, 2010. 59(7): p. 1578-1584.
Fredriksson, I., Quantitative laser doppler flowmetry. 2009, Doktorsavhandling
Fredriksson, I., Larsson, M., and Strömberg, T., Optical microcirculatory skin model: assessed by Monte Carlo simulations paired with in vivo laser Doppler flowmetry. Journal of Biomedical Optics, 2008. 13(1): p. 014015.
Fredriksson, I., Larsson, M., and Strömberg, T. Absolute flow velocity components in laser Doppler flowmetry. in Proc. SPIE. 2006. San Jose, CA, USA.
Larsson, M. and Strömberg, T., Towards a velocity-resolved microvascular blood flow measure by decomposition of the laser Doppler spectrum. Journal of Biomedical Engineering, 2006. 11(1): p. 014024.
