Doppler Optical Coherence Tomography for Otology Applications: From Phantom Simulation to In Vivo Experiment

Synthetic polarization-sensitive optical coherence tomography using contrastive unpaired translation

Polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization state of backscattered light from tissues and provides valuable insights into the birefringence properties of biological tissues. Contrastive unpaired translation (CUT) was used in this study to generate a synthetic PS-OCT image from a single OCT image. The challenges related to extensive data requirements relying on labeled datasets using only pixel-wise correlations that make it difficult to efficiently regenerate the periodic patterns observed in PS-OCT images were addressed. The CUT model captures birefringence patterns by leveraging patch-wise correlations from unpaired data, which allows learning of the underlying structural features of biological tissues responsible for birefringence. To demonstrate the performance of the proposed approach, three generative models (Pix2pix, CycleGAN, and CUT) were compared on an in vivo dataset of injured mouse tendons over a six-week healing period. CUT outperformed Pix2pix and CycleGAN by producing high-fidelity synthetic PS-OCT images that closely matched the original PS-OCT images. Pearson correlation and two-way ANOVA tests confirmed the superior performance of CUT (p-value < 0.0001) over the comparison models. Additionally, a ResNet-152 classification model was used to assess tissue damage, which achieved an accuracy of up to 90.13% compared to the original PS-OCT images. This research demonstrates that CUT is superior to conventional methods for generating high-quality synthetic PS-OCT images and offers better improvements in most scenarios, in terms of efficiency and image fidelity.

Imaging of the vascular distribution of the outer ear using optical coherence tomography angiography for highly accurate positioning of a hearable sensor

Novel hearable technology is securely and comfortably positioned within the ear canal minimizing inaccuracies caused by accessory movements during activities. Despite extensive research on hearable technologies within the outer ear, there is a lack of research in the field of vascular imaging and quantitative analysis in the outer ear in vivo, which is one of the crucial factors to select the appropriate sensor position. Therefore, in this paper, we introduced optical coherence tomography angiography (OCTA)-based qualitative and quantitative analyses to visualize the inner vasculature of the outer ear to acquire vascular maps for microvascular assessments in vivo. By generating maximum amplitude projection images from three-dimensional blood vascular volume, we identified variations of blood vessel signal caused by the different biological characteristics and curvature of the ear among individuals. The performance of micro-vascular mapping using the proposed method was validated through the comparison and analysis of individual vascular parameters using extracted 20 vascular-related variables. In addition, we extracted pulsatile blood flow signals, demonstrating its potential to provide photoplethysmographic signals and ear blood maps simultaneously. Therefore, our proposed OCTA-based method for ear vascular mapping successfully provides quantitative information about ear vasculature, which is potentially used for determining the position of system-on-chip sensors for health monitoring in hearable devices.

Skin pore imaging using spectral-domain optical coherence tomography: a case report

Sebum is an important component of the skin that has attracted attention in many fields, including dermatology and cosmetics. Pore expansion due to sebum on the skin can lead to various problems. Therefore, it is necessary to analyze the morphological characteristics of sebum. In this study, we used optical coherence tomography (OCT) to evaluate facial sebum areas. We obtained the OCT maximum amplitude projection (MAP) image and a cross-sectional image of skin pores in the facial area. Subsequently, we detected the sebum in skin pores using the detection algorithm of the ImageJ software to quantitatively determine the size of randomly selected pores in the proposed MAP images. Additionally, the pore size was analyzed by acquiring images before and after facial sebum extraction. According to our research, facial sebum can be morphologically described using the OCT system. Since OCT imaging enables specific analysis of skin parameters, including pores and sebum, skin analysis employing OCT could be an effective method for further research.