Comparison of the Meibomian Gland Openings by Optical Coherence Tomography in Obstructive Meibomian Gland Dysfunction and Normal Patients

Advances in artificial intelligence for meibomian gland evaluation: A comprehensive review

Meibomian gland dysfunction (MGD) is increasingly recognized as a critical contributor to evaporative dry eye, significantly impacting visual quality. With a global prevalence estimated at 35.8 %, it presents substantial challenges for clinicians. Conventional manual evaluation techniques for MGD face limitations characterized by inefficiencies, high subjectivity, limited big data processing capabilities, and a dearth of quantitative analytical tools. With rapidly advancing artificial intelligence (AI) techniques revolutionizing ophthalmology, studies are now leveraging sophisticated AI methodologies--including computer vision, unsupervised learning, and supervised learning--to facilitate comprehensive analyses of meibomian gland (MG) evaluations. These evaluations employ various techniques, including slit lamp examination, infrared imaging, confocal microscopy, and optical coherence tomography. This paradigm shift promises enhanced accuracy and consistency in disease evaluation and severity classification. While AI has achieved preliminary strides in meibomian gland evaluation, ongoing advancements in system development and clinical validation are imperative. We review the evolution of MG evaluation, juxtapose AI-driven methods with traditional approaches, elucidate the specific roles of diverse AI technologies, and explore their practical applications using various evaluation techniques. Moreover, we delve into critical considerations for the clinical deployment of AI technologies and envisages future prospects, providing novel insights into MG evaluation and fostering technological and clinical progress in this arena.

Modeling meibum secretion: Alternatives for obstructive Meibomian Gland Dysfunction (MGD)

PURPOSE

While changes in meibum quality are correlated with severity of meibomian gland dysfunction (MGD) and dry eye disease, little is known regarding the mechanics of meibum secretion. The purpose of this study was to develop a finite element model of meibum secretion and evaluate the effect of various factors that might impact meibum delivery to the ocular surface.

METHODS

A finite element analysis in COMSOL 6.0 was used to simulate the flow of meibum within the gland's terminal excretory duct. Historical normal human meibum rheology data taken over the meibum melting range from fluid (35-40 °C) to solid (25-30 °C) were then used to calculate the minimum yield stress and plastic viscosity of meibum. The effects of meibum melting state, eyelid pressure and terminal duct diameter on meibum flow rates were then systematically investigated.

RESULTS

The melting state of meibum from liquid to solid was associated with an increase in the minimum yield stress and plastic viscosity that caused an exponential decrease in meibum flow. Modeling also established that there was a linear correlation between meibum flow rate and eyelid pressure needed to express meibum and the 4th power of the terminal duct radius.

CONCLUSIONS

Our results suggest that changes in the melting state of meibum from fluid to solid, as well as changes in the radius of the terminal excretory duct and the force exerted by the eyelid can lead to dramatic decreases in the flow of meibum. Together these findings suggest alternative mechanisms for meibomian gland obstruction.

Dry Eye Disease Associated with Meibomian Gland Dysfunction: Focus on Tear Film Characteristics and the Therapeutic Landscape

Meibomian gland dysfunction (MGD) is highly prevalent and is the leading cause of evaporative dry eye disease (DED). MGD is characterized by a reduction in meibum secretion and/or a change in meibum composition that results in the disruption of the tear film lipid layer and an increase in the tear film evaporation rate. Excessive evaporation causes tear film instability, desiccation, tear hyperosmolarity, inflammation, and apoptosis of ocular surface cells, resulting in a continuous cycle of DED. The primary treatment goal for DED associated with MGD is to restore the tear film lipid layer and decrease evaporation, thereby reducing ocular signs and symptoms. The management of MGD includes home care options (eyelid hygiene, warming eye masks, ocular lubricants) and office-based treatments (manual expression, microblepharoexfoliation, thermal pulsation, intense pulsed light, intraductal probing). Topical ophthalmic prescription medications attempt to alter various factors that may contribute to DED (e.g., inflammation, bacterial growth, inadequate tear production). In this review, clinical evidence regarding available treatments and emerging therapies from randomized studies in patients with DED associated with MGD is summarized. Although some treatment modalities have been evaluated specifically for DED patients with MGD, large-scale randomized controlled trials are needed to confirm efficacy and safety in this patient population. Currently, there are no approved prescription pharmacologic treatments specifically indicated for DED associated with MGD, and those medications approved for the treatment of DED do not target the key driver of the disease (i.e., excessive evaporation). NOV03 (perfluorohexyloctane; under review with the US Food and Drug Administration) is the most advanced emerging therapy for DED associated with MGD and has demonstrated statistically significant improvements in both signs and symptoms in randomized controlled trials. Development of novel pharmacotherapies will improve therapeutic options and allow for a more individualized approach for patients with DED associated with MGD.

Development of Artefact-Free Imaging System for Accurate Meibomian Gland Reflectivity Assessment

Purpose

To develop and evaluate a custom imaging system to provide high-resolution, wide depth-of-field, reflection-free, multispectral infrared (IR) imaging of the Meibomian glands.

Methods

Lower eyelids of 15 volunteers were everted to obtain multispectral images of the Meibomian glands with custom imaging setup. Photographs were captured at 10 different ISO settings (from underexposure to overexposure) and using nine IR imaging filters (ranging from 600 nm to 1000 nm in 50-nm steps). Meibomian gland contrast (simple and Michelson) was calculated for the images to choose an optimal wavelength for Meibomian gland imaging and to determine differences in contrast across individuals.

Results

The overall linear regression model showed a significant effect of wavelength on Meibomian gland contrast (Simple contrast: F = 7.24, P < 0.0001; Michelson contrast: F = 7.19, P < 0.0001). There was a significant negative correlation between Meibomian gland contrast and Meibomian gland depth for 750-nm IR filter (ρs= -0.579; P = 0.026).

Conclusions

Meibomian gland contrast varies across individuals and depends on Meibomian gland depth. IR filter of 750 nm is the optimal choice for Meibomian gland imaging because it provides images of greatest contrast.

Translational Relevance

This study adds to our understanding of Meibomian gland imaging. It has successfully demonstrated that Meibomian glands that are deeper in the tarsal plate require longer wavelengths for imaging.

Anwendungsmöglichkeiten der optischen Kohärenztomographie beim trockenen Auge

Durch die stetige Weiterentwicklung und Verbesserung der Technik hat die optische Kohärenztomographie (OCT) in den letzten Jahren neue Möglichkeiten zur Beurteilung der Strukturen des vorderen Augenabschnittes eröffnet. Aufgrund der Darstellung kleinster Strukturen, wie beispielsweise des Tränenfilms, nimmt die OCT in der Diagnostik und Verlaufsbeurteilung des trockenen Auges eine immer wichtigere Rolle ein. Der vorliegende Beitrag gibt einen Überblick über die derzeitigen Einsatzmöglichkeiten der OCT beim trockenen Auge.