Visualization of ex vivo rabbit olfactory mucosa and foramina with three-dimensional optical coherence tomography.

There is increasing interest in developing a minimally invasive imaging modality to safely evaluate dynamic microscopic changes of the olfactory mucosa and cribriform foramina. Herein, we utilized three-dimensional (3D) optical coherence tomography (OCT) to characterize the ex vivo stratified substructure of olfactory mucosa in rabbits and create 3D reconstructed images of olfactory foramina. Olfactory mucosa and cribriform plates from four New Zealand White rabbits were dissected and imaged using two swept-source OCT systems: (1) 1.3-µm (µm) center wavelength, 100-nm bandwidth, 200-kHz sweep rate, and (2) 1.7-µm center wavelength, 120-nm bandwidth, 90-kHz sweep rate. Volumetric OCT images were compiled to create a 3D reconstruction of the cribriform plate. The ability of OCT to distinguish the olfactory mucosa substructure and foramina was compared to histology. To estimate imaging penetration depth of each system, the first-order exponential decays of depth-resolved intensity were calculated and compared using a paired t-test. Three-dimensional OCT depicted the stratified layered structures within the olfactory mucosa correlating with histology. The epithelium and lamina propria were measured to be 32 µm and 107 µm in 1.3-µm OCT compared to 30 µm and 105 µm in histology. Olfactory foramina were visualized via 3D reconstruction. The 1.7-µm system provided greater depth penetration compared to the 1.3-µm system, allowing for improved foramina visualization. We have shown that OCT can be used to image non-pathologic olfactory mucosa and foramina. Implications for this work include diagnostic and therapeutic potentials for neurorhinological and neurodegenerative diseases.

Monitoring Response to Platelet-Rich Plasma in Patients with Alopecia Areata with Optical Coherence Tomography: A Case Series.

Alopecia areata (AA) is an autoimmune hair loss condition that is difficult to treat and frequently disruptive to the psychosocial well-being of patients. Platelet-rich plasma (PRP) is an innovative therapy that provides concentrated GFs that impart anti-inflammatory effects. Optical coherence tomography (OCT) is a noninvasive imaging modality with the potential for providing quantitative monitoring of AA response to PRP. Our objective is to share our experience using OCT to monitor the therapeutic progress of patients with AA treated with PRP. Two patients with patchy AA and one with alopecia universalis were treated with PRP three times at 6-week intervals as part of a larger clinical trial. Patients were followed from baseline to week 24 with OCT imaging. OCT demonstrates an increase in hair density associated with improvement in inflammation at week 24. Conversely, the patient with alopecia universalis did not experience any significant change in follicular activity. This case series exemplifies the potential of PRP in inflammatory regulation as well as hair regrowth in patchy AA, whereas there is no notable advantage in alopecia universalis. Our findings add evidence on the possible value of OCT in quantitatively assessing hair growth progress throughout a treatment course.

Validation of a Point-of-Care Optical Coherence Tomography Device with Machine Learning Algorithm for Detection of Oral Potentially Malignant and Malignant Lesions.

Non-invasive strategies that can identify oral malignant and dysplastic oral potentially-malignant lesions (OPML) are necessary in cancer screening and long-term surveillance. Optical coherence tomography (OCT) can be a rapid, real time and non-invasive imaging method for frequent patient surveillance. Here, we report the validation of a portable, robust OCT device in 232 patients (lesions: 347) in different clinical settings. The device deployed with algorithm-based automated diagnosis, showed efficacy in delineation of oral benign and normal (n = 151), OPML (n = 121), and malignant lesions (n = 75) in community and tertiary care settings. This study showed that OCT images analyzed by automated image processing algorithm could distinguish the dysplastic-OPML and malignant lesions with a sensitivity of 95% and 93%, respectively. Furthermore, we explored the ability of multiple (n = 14) artificial neural network (ANN) based feature extraction techniques for delineation high grade-OPML (moderate/severe dysplasia). The support vector machine (SVM) model built over ANN, delineated high-grade dysplasia with sensitivity of 83%, which in turn, can be employed to triage patients for tertiary care. The study provides evidence towards the utility of the robust and low-cost OCT instrument as a point-of-care device in resource-constrained settings and the potential clinical application of device in screening and surveillance of oral cancer.