Auto-detection of cervical collagen and elastin in Mueller matrix polarimetry microscopic images using K-NN and semantic segmentation classification.

We propose an approach for discriminating fibrillar collagen fibers from elastic fibers in the mouse cervix in Mueller matrix microscopy using convolutional neural networks (CNN) and K-nearest neighbor (K-NN) for classification. Second harmonic generation (SHG), two-photon excitation fluorescence (TPEF), and Mueller matrix polarimetry images of the mice cervix were collected with a self-validating Mueller matrix micro-mesoscope (SAMMM) system. The components and decompositions of each Mueller matrix were arranged as individual channels of information, forming one 3-D voxel per cervical slice. The classification algorithms analyzed each voxel and determined the amount of collagen and elastin, pixel by pixel, on each slice. SHG and TPEF were used as ground truths. To assess the accuracy of the results, mean-square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were used. Although the training and testing is limited to 11 and 5 cervical slices, respectively, MSE accuracy was above 85%, SNR was greater than 40 dB, and SSIM was larger than 90%.

Monte Carlo analysis of optical heart rate sensors in commercial wearables: the effect of skin tone and obesity on the photoplethysmography (PPG) signal.

Commercially available wearable devices have been used for fitness and health management and their demand has increased over the last ten years. These "general wellness" and heart-rate monitoring devices have been cleared by the Food and Drug Administration for over-the-counter use, yet anecdotal and more systematic reports seem to indicate that their error is higher when used by individuals with elevated skin tone and high body mass index (BMI). In this work, we used Monte Carlo modeling of a photoplethysmography (PPG) signal to study the theoretical limits of three different wearable devices (Apple Watch series 5, Fitbit Versa 2 and Polar M600) when used by individuals with a BMI range of 20 to 45 and a Fitzpatrick skin scale 1 to 6. Our work shows that increased BMI and skin tone can induce a relative loss of signal of up to 61.2% in Fitbit versa 2, 32% in Apple S5 and 32.9% in Polar M600 when considering the closest source-detector pair configuration in these devices.

Depth-resolved Mueller matrix polarimetry microscopy of the rat cornea.

Mueller matrix polarimetry (MMP) is a promising linear imaging modality that can enable visualization and measurement of the polarization properties of the cornea. Although the distribution of corneal birefringence has been reported, depth resolved MMP imaging of the cornea has not been archived and remains challenging. In this work, we perform depth-resolved imaging of the cornea using an improved system that combines Mueller matrix reflectance and transmission microscopy together with nonlinear microscopy utilizing second harmonic generation (SHG) and two photon excitation fluorescence (TPEF). We show that TPEF can reveal corneal epithelial cellular network while SHG can highlight the presence of corneal stromal lamellae. We then demonstrate that, in confocal reflectance measurement, as depth increases from 0 to 80 µm both corneal depolarization and retardation increase. Furthermore, it is shown that the spatial distribution of corneal depolarization and retardation displays similar complexity in both reflectance (confocal and non-confocal) and transmission measurement, likely due to the strong degree of heterogeneity in the stromal lamellae.

Beyond diffuse correlations: deciphering random flow in time-of-flight resolved light dynamics.

Diffusing wave spectroscopy (DWS) and diffuse correlation spectroscopy (DCS) can assess blood flow index (BFI) of biological tissue with multiply scattered light. Though the main biological function of red blood cells (RBCs) is advection, in DWS/DCS, RBCs are assumed to undergo Brownian motion. To explain this discrepancy, we critically examine the cumulant approximation, a major assumption in DWS/DCS. We present a precise criterion for validity of the cumulant approximation, and in realistic tissue models, identify conditions that invalidate it. We show that, in physiologically relevant scenarios, the first cumulant term for random flow and second cumulant term for Brownian motion alone can cancel each other. In such circumstances, assuming pure Brownian motion of RBCs and the first cumulant approximation, a routine practice in DWS/DCS of BFI, can yield good agreement with data, but only because errors due to two incorrect assumptions cancel out. We conclude that correctly assessing random flow from scattered light dynamics requires going beyond the cumulant approximation and propose a more accurate model to do so.

Time-of-flight resolved light field fluctuations reveal deep human tissue physiology.

Red blood cells (RBCs) transport oxygen to tissues and remove carbon dioxide. Diffuse optical flowmetry (DOF) assesses deep tissue RBC dynamics by measuring coherent fluctuations of multiply scattered near-infrared light intensity. While classical DOF measurements empirically correlate with blood flow, they remain far-removed from light scattering physics and difficult to interpret in layered media. To advance DOF measurements closer to the physics, here we introduce an interferometric technique, surmounting challenges of bulk motion to apply it in awake humans. We reveal two measurement dimensions: optical phase, and time-of-flight (TOF), the latter with 22 picosecond resolution. With this multidimensional data, we directly confirm the unordered, or Brownian, nature of optically probed RBC dynamics typically assumed in classical DOF. We illustrate how incorrect absorption assumptions, anisotropic RBC scattering, and layered tissues may confound classical DOF. By comparison, our direct method enables accurate and comprehensive assessment of blood flow dynamics in humans.

Vascular contrast in narrow-band and white light imaging.

Narrow-band imaging (NBI) is a spectrally selective reflectance imaging technique that is used clinically for enhancing visualization of superficial vasculature and has shown promise for applications such as early endoscopic detection of gastrointestinal neoplasia. We have studied the effect of vessel geometry and illumination wavelength on vascular contrast using idealized geometries in order to more quantitatively understand NBI and broadband or white light imaging of mucosal tissue. Simulations were performed using a three-dimensional, voxel-based Monte Carlo model incorporating discrete vessels. In all cases, either 415 or 540 nm illumination produced higher contrast than white light, yet white light did not always produce the lowest contrast. White light produced the lowest contrast for small vessels and intermediate contrast for large vessels (diameter≥100 µm) at deep regions (vessel depth≥200 µm). The results show that 415 nm illuminations provided superior contrast for smaller vessels at shallow depths while 540 nm provided superior contrast for larger vessels in deep regions. Besides 540 nm, our studies also indicate the potential of other wavelengths to achieve high contrast of large vessels at deep regions. Simulation results indicate the importance of three key mechanisms in determining spectral variations in contrast: intravascular hemoglobin (Hb) absorption in the vessel of interest, diffuse Hb absorption from collateral vasculature, and bulk tissue scattering. Measurements of NBI contrast in turbid phantoms incorporating 0.1-mm-diameter hemoglobin-filled capillary tubes indicated good agreement with modeling results. These results provide quantitative insights into light-tissue interactions and the effect of device and tissue properties on NBI performance.