Quantification of smooth muscle in human airways by polarization-sensitive optical coherence tomography requires correction for perichondrium.

Quantifying airway smooth muscle (ASM) in patients with asthma raises the possibility of improved and personalized disease management. Endobronchial polarization-sensitive optical coherence tomography (PS-OCT) is a promising quantitative imaging approach that is in the early stages of clinical translation. To date, only animal tissues have been used to assess the accuracy of PS-OCT to quantify absolute (rather than relative) ASM in cross sections with directly matched histological cross sections as validation. We report the use of whole fresh human and pig airways to perform a detailed side-by-side qualitative and quantitative validation of PS-OCT against gold-standard histology. We matched and quantified 120 sections from five human and seven pig (small and large) airways and linked PS-OCT signatures of ASM to the tissue structural appearance in histology. Notably, we found that human cartilage perichondrium can share with ASM the properties of birefringence and circumferential alignment of fibers, making it a significant confounder for ASM detection. Measurements not corrected for perichondrium overestimated ASM content several-fold (P < 0.001, paired t test). After careful exclusion of perichondrium, we found a strong positive correlation (r = 0.96, P < 0.00001) of ASM area measured by PS-OCT and histology, supporting the method's application in human subjects. Matching human histology further indicated that PS-OCT allows conclusions on the intralayer composition and in turn potential contractile capacity of ASM bands. Together these results form a reliable basis for future clinical studies.NEW & NOTEWORTHY Polarization-sensitive optical coherence tomography (PS-OCT) may facilitate in vivo measurement of airway smooth muscle (ASM). We present a quantitative validation correlating absolute ASM area from PS-OCT to directly matched histological cross sections using human tissue. A major confounder for ASM quantification was observed and resolved: fibrous perichondrium surrounding hyaline cartilage in human airways presents a PS-OCT signature similar to ASM for birefringence and optic axis orientation. Findings impact the development of automated methods for ASM segmentation.

Deep learning-based label-free imaging of lymphatics and aqueous veins in the eye using optical coherence tomography.

We demonstrate an adaptation of deep learning for label-free imaging of the micro-scale lymphatic vessels and aqueous veins in the eye using optical coherence tomography (OCT). The proposed deep learning-based OCT lymphangiography (DL-OCTL) method was trained, validated and tested, using OCT scans (23 volumetric scans comprising 19,736 B-scans) from 11 fresh ex vivo porcine eyes with the corresponding vessel labels generated by a conventional OCT lymphangiography (OCTL) method based on thresholding with attenuation compensation. Compared to conventional OCTL, the DL-OCTL method demonstrates comparable results for imaging lymphatics and aqueous veins in the eye, with an Intersection over Union value of 0.79 ± 0.071 (mean ± standard deviation). In addition, DL-OCTL mitigates the imaging artifacts in conventional OCTL where the OCT signal modelling was corrupted by the tissue heterogeneity, provides ~ 10 times faster processing based on a rough comparison and does not require OCT-related knowledge for correct implementation as in conventional OCTL. With these favorable features, DL-OCTL promises to improve the practicality of OCTL for label-free imaging of lymphatics and aqueous veins for preclinical and clinical imaging applications.