Measuring collagen injury depth for burn severity determination using polarization sensitive optical coherence tomography

Dynamic optical coherence elastography for skin burn assessment: A preliminary study on mice model

Skin burns that include tissue coagulation necrosis imply variations in stiffness. Dynamic phase-sensitive optical coherence elastography (OCE) is used to evaluate the stiffness of burned skin nondestructively in this paper. The homemade dynamic OCE was initially verified through tissue-mimicking phantom experiments regarding Rayleigh wave speed. After being burned with a series of temperatures and durations, the corresponding structure and stiffness variations of mice skin were demonstrated by histological images, optical coherence tomography B-scans, and OCE elastic wave speed maps. The results clearly displayed the variation in elastic properties and stiffness of the scab edge extending in the lateral direction. Statistical analysis revealed that murine skin burned at temperatures exceeding 100°C typically exhibited greater stiffness than skin burned at temperatures below 100°C. The dynamic OCE technique shows potential application for incorporating elasticity properties as a biomechanical extension module to diagnose skin burn injuries.

Effect of femtosecond laser process parameters on the thermal denaturation degree of skin tissue

The influence of femtosecond laser parameters on the degree of thermal denaturation was studied experimentally. The relationship between the degree of thermal denaturation and the characteristic parameters of skin microstructure and the secondary structure of skin tissue proteins in characterizing the degree of thermal damage was analyzed. The results showed the interaction of laser power, laser power, and scanning speed had a significant effect on the degree of thermal denaturation; greater degrees of thermal denaturation were associated with larger second-order moments of the texture angle of the skin microtissue and smaller entropy values and contrast, indicating a greater degree of thermal damage; and higher peak temperature, the lower peak intensity of Raman spectra, decrease in the percentage area of α-helix fitted curves and increase in the percentage area of β-sheet and β-turn fitted curves indicate that the protein is denatured to a large extent that means thermal damage is large.

Mapping optical scattering properties to physical particle information in singly and multiply scattering samples

Optical coherence tomography (OCT) leverages light scattering by biological tissues as endogenous contrast to form structural images. Light scattering behavior is dictated by the optical properties of the tissue, which depend on microstructural details at the cellular or sub-cellular level. Methods to measure these properties from OCT intensity data have been explored in the context of a number of biomedical applications seeking to access this sub-resolution tissue microstructure and thereby increase the diagnostic impact of OCT. Most commonly, the optical attenuation coefficient, an analogue of the scattering coefficient, has been used as a surrogate metric linking OCT intensity to subcellular particle characteristics. To record attenuation coefficient data that is accurately representative of the underlying physical properties of a given sample, it is necessary to account for the impact of the OCT imaging system itself on the distribution of light intensity in the sample, including the numerical aperture (NA) of the system and the location of the focal plane with respect to the sample surface, as well as the potential contribution of multiple scattering to the reconstructed intensity signal. Although these considerations complicate attenuation coefficient measurement and interpretation, a suitably calibrated system may potentiate a powerful strategy for gaining additional information about the scattering behavior and microstructure of samples. In this work, we experimentally show that altering the OCT system geometry minimally impacts measured attenuation coefficients in samples presumed to be singly scattering, but changes these measurements in more highly scattering samples. Using both depth-resolved attenuation coefficient data and layer-resolved backscattering coefficients, we demonstrate the retrieval of scattering particle diameter and concentration in tissue-mimicking phantoms, and the impact of presumed multiple scattering on these calculations. We further extend our approach to characterize a murine brain tissue sample and highlight a tumor-bearing region based on increased scattering particle density. Through these methods, we not only enhance conventional OCT attenuation coefficient analysis by decoupling the independent effects of particle size and concentration, but also discriminate areas of strong multiple scattering through minor changes to system topology to provide a framework for assessing the accuracy of these measurements.

Advances in non-invasive biosensing measures to monitor wound healing progression

Impaired wound healing is a significant financial and medical burden. The synthesis and deposition of extracellular matrix (ECM) in a new wound is a dynamic process that is constantly changing and adapting to the biochemical and biomechanical signaling from the extracellular microenvironments of the wound. This drives either a regenerative or fibrotic and scar-forming healing outcome. Disruptions in ECM deposition, structure, and composition lead to impaired healing in diseased states, such as in diabetes. Valid measures of the principal determinants of successful ECM deposition and wound healing include lack of bacterial contamination, good tissue perfusion, and reduced mechanical injury and strain. These measures are used by wound-care providers to intervene upon the healing wound to steer healing toward a more functional phenotype with improved structural integrity and healing outcomes and to prevent adverse wound developments. In this review, we discuss bioengineering advances in 1) non-invasive detection of biologic and physiologic factors of the healing wound, 2) visualizing and modeling the ECM, and 3) computational tools that efficiently evaluate the complex data acquired from the wounds based on basic science, preclinical, translational and clinical studies, that would allow us to prognosticate healing outcomes and intervene effectively. We focus on bioelectronics and biologic interfaces of the sensors and actuators for real time biosensing and actuation of the tissues. We also discuss high-resolution, advanced imaging techniques, which go beyond traditional confocal and fluorescence microscopy to visualize microscopic details of the composition of the wound matrix, linearity of collagen, and live tracking of components within the wound microenvironment. Computational modeling of the wound matrix, including partial differential equation datasets as well as machine learning models that can serve as powerful tools for physicians to guide their decision-making process are discussed.