Grading and baseline characteristics of meibomian glands in meibography images and their clinical associations in the Dry Eye Assessment and Management (DREAM) study

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.

Meibomian gland dropout of upper eyelids as a novel biomarker for early diagnosis of primary Sjögren's syndrome: a pilot study

Background

Early diagnosis of primary Sjögren's syndrome (pSS) remains difficult due to its insidious onset.

Objectives

To identify whether meibomian gland dropout (MGD) is a sensitive and noninvasive predictor of pSS by studying its association with histopathology in labial salivary gland biopsy in patients with clinically suspected pSS.

Design

Prospective, randomized, multicenter, comparative effectiveness study.

Methods

The study was conducted from July 2022 to July 2023. In all, 56 eligible participants with clinically suspected pSS were recruited from three combined ophthalmology medicine/rheumatology SS clinics. All participants with suspected pSS were evaluated and diagnosed by ophthalmology and rheumatology consultants and underwent infrared imaging of the meibomian glands using Keratograph 5M and histopathological evaluation of labial salivary gland biopsies. The length, width, and tortuosity of the meibomian glands were measured; the dropout rate in the nasal, temporal, and total eyelids was analyzed; and the dropout score was calculated using meibography grading scales.

Results

Among the 56 participants, 34 were identified with pSS, and 22 were diagnosed with non-SS dry eye (NSSDE) and served as the control group. We recorded significant differences in the temporal and total MGD rates of the upper eyelids between the pSS and NSSDE groups (all p < 0.01). Improved prediction accuracy was achieved with the temporal and total MGD rates in the upper eyelids, with area under the curve values of 0.94 and 0.91, and optimal cutoff points of 0.78 and 0.75, respectively.

Conclusion

MGD in the upper eyelids, especially in the temporal portion, is strongly associated with the histopathological outcome of labial salivary gland biopsy in pSS and is proposed as a highly predictive and noninvasive biomarker for the early diagnosis of pSS.

Trial registration

ClinicalTrials.gov identifier: ChiCTR2000038911.

Meibography signal intensity as a novel image biomarker for meibomian gland function: evidence from cross-sectional and longitudinal analyses

Background

Meibomian gland dysfunction (MGD), one of the most common ocular surface diseases, can induce dry eye and reduce patients' quality of life. Methodological limitations have resulted in contradictory interpretations of gland function. This study sought to investigate the correlation between meibography signal intensity (SI) and meibomian gland (MG) function and to validate an MGD classification strategy based on different levels of SI.

Methods

A multicenter, cross-sectional analysis was conducted on 817 eyes from 361 patients with MGD and 52 healthy controls. Additionally, 78 eyes from 39 patients with MGD who had undergone LipiFlow treatment were recruited for longitudinal analyses. The SI value was obtained via meibography using an automated analyzer, and all participants underwent ocular surface examinations. A cross-sectional analysis was performed to determine SI distribution and its relationship to clinical characteristics via a generalized estimating equation model. Longitudinal analyses were conducted on the treatment cohort using a mixed-effects model to explore the outcome in different SI levels.

Results

Regression analysis revealed significant correlations between SI and lipid layer thickness (β=0.016), meibum expressibility (β=-0.676), meibum quality (β=-0.251), and fluorescein-stained tear-film break-up time (FBUT) (β=0.064) (all P values <0.001 for the above associations). Low-level SI MGD cases exhibited the most severe clinical signs, including the worst meibum expressibility (16% for level 3) and quality scores (19% for level 3), the shortest FBUT (3.82±0.13 s), and the thinnest lipid layer (65.68±2.58 nm), (all P values <0.05, respectively). Patients with medium SI showed the lowest ocular surface disease index (OSDI) value (26.64±1.06), the longest FBUT (4.56±0.08 s), and the thickest lipid layer (80.20±2.90 nm). After treatment, the high SI values reduced significantly at each follow-up point compared to baseline (all P values <0.05). The medium SI group demonstrated the greatest improvement in symptoms and signs, followed by the high SI group, and the low SI group.

Conclusions

Automated measurements of SI can effectively reflect MG secretory activity. The proposed low, medium, and high SI classifications represent different functional subtypes of MGD.

Evaluation of Meibomian Gland Structure and Function in Patients with Vernal Keratoconjunctivitis Using Non Contact Meibography and Lipid Layer Interferometry

PURPOSE

This study evaluated the structural and functional impact of vernal keratoconjunctivitis (VKC) on meibomian glands (MGs) using a combination of noncontact meibography and lipid layer interferometry.

METHODS

In this observational study 50 patients with moderate persistent or severe VKC and 50 age-matched controls underwent MG imaging and lipid layer thickness (LLT) measurements with Lipiview II. Image J software was used to assess MG loss (meibograde) in both lids. All patients underwent dry eye evaluation comprising tear break-up time (TBUT), ocular surface staining (OSS), Schirmer I scoring, and meiboscoring (expressibility and quality of meibum secreted).

RESULTS

Meibograde, OSS score, and meiboscore was higher in cases (2.68 ± 0.96, 0.580 ± 1.07, and 0.56 ± 0.95 respectively) than controls (1.80 ± 0.67, 0.00 ± 0.00, 0.22 ± 0.47 respectively) (p < 0.001, 0.001, 0.025 respectively). LLT and TBUT was lower in cases (54.58 ± 9.43 nm and 4.92 ± 3.09 sec respectively) than controls (70.14 ± 22.50 nm and 12.02 ± 2.73 sec respectively) (both p's = 0.001). Both groups had comparable Schirmer I scores.

CONCLUSION

Children with VKC have significant MG dropouts, deterioration in meibum quality and a thinner and less stable tear film. VKC patients are thus prone to a vicious cycle of inflammation attributable both to the allergic component and to deterioration in MG structure and function. Co-management of MG dysfunction warrants as much attention as the allergic component itself.

Meibomian Gland Shortening Is Associated With Altered Meibum Composition

Purpose

The purpose of this study was to investigate differences in the composition of meibum extracted from human meibomian glands displaying different morphological characteristics.

Methods

Adult participants with evidence of meibomian gland shortening were enrolled. Glands were observed using infrared meibography, and meibum was collected from one short and one long gland from the lower eyelid of the same eye. Total protein concentration was evaluated using the detergent compatible (DC) protein assay and lipid analysis was performed using liquid chromatography mass spectrometry.

Results

Fifteen participants (8 women and 7 men) completed the study (mean age = 34.7 ± 7.7 years). The average volume of meibum collected from the short and long glands was 0.02 ± 0.01 and 0.05 ± 0.03 µL, respectively (P = 0.01). Average protein concentration in the short glands was significantly higher compared to the long glands (0.10 ± 0.03 vs. 0.08 ± 0.02 mg/mL, P = 0.01). Among the non-polar lipids, the mole percent of cholesterol esters (CEs; P = 0.02), triacylglycerols (TAGs; P = 0.04), and ceramide (Cer; P = 0.03) was significantly lower in short glands compared with long glands. Among the polar lipids, the mole percent of (O-acyl)-ω-hydroxy fatty acid (OAHFA; P = 0.01) was significantly lower in short glands, whereas phosphatidylcholine (PC; P = 0.02) and sphingomyelin (SM; P = 0.01) were significantly higher in short glands than long glands.

Conclusions

Meibum composition differed between short and long glands. The lower mole percent of CE, TAG, OAHFA, and Cer and a higher mole percent of PC and SM among short glands may indicate disease activity. This information may clarify the natural history of meibomian gland dysfunction and future targets for therapy.

Factors affecting long-term changes of meibomian gland in MGD patients

PURPOSE

To explore the long-term course of patients with meibomian gland dysfunction (MGD), and to analyse potential factors affecting the recovery of meibomian gland (MG) dropout.

METHODS

Seventy-nine MGD patients (79 eyes) aged 36.03±15.78 years old who underwent more than one year of follow-up were enrolled in this retrospective study. Corneal fluorescein staining (CFS), tear meniscus height (TMH), noninvasive breakup time (NIBUT), and noncontact meibography at baseline and last visit were collected and analysed. Then an automatic MG analyzer was used to measure the morphological and functional parameters of MGs, including their area ratio (AR), tortuosity index (TI), and signal index (SI). The patients whose AR increased by more than 5% were defined as MG improvement, and AR decreased by more than 5% was MG worsening.

RESULTS

A total of 79 patients (79 eyes) were assessed with at least 1-year of follow-up. More than 1/3 of MGD patients (27 eyes, 34.2%) underwent MG improvement, and 30.4% of MGs became worsened. Age (P=0.002), gender (P<0.001), IPL treatment (P=0.013), the change of CFS (P=0.0015), and the recovery of SI (P=0.035) showed significant differences among different recovery groups. Age(P<0.001), female sex (P=0.003), ΔCFS (P<0.001), AR at baseline (P<0.001) were negative correlation with AR recovery, and the change of SI (P=0.003) and IPL treatment (P=0.003) had a positive correlation with it. Among them, age (P=0.038), the change of CFS (P=0.004), and AR at baseline (P=0.007) were confirmed as negatively correlated factors predicting the long-term change of the MG.

CONCLUSION

Although the MGD treatment has continued for more than 1 year, only 34.2% of MGD patients were observed to undergo MG improvement. Younger patients and patients with better CFS recovery seem to have more opportunities to improve their MGs.

A Deep Learning Approach for Meibomian Gland Appearance Evaluation

Purpose

To develop and evaluate a deep learning algorithm for Meibomian gland characteristics calculation.

Design

Evaluation of diagnostic technology.

Subjects

A total of 1616 meibography images of both the upper (697) and lower (919) eyelids from a total of 282 individuals.

Methods

Images were collected using the LipiView II device. All the provided data were split into 3 sets: the training, validation, and test sets. Data partitions used proportions of 70/10/20% and included data from 2 optometry settings. Each set was separately partitioned with these proportions, resulting in a balanced distribution of data from both settings. The images were divided based on patient identifiers, such that all images collected for one participant could end up only in one set. The labeled images were used to train a deep learning model, which was subsequently used for Meibomian gland segmentation. The model was then applied to calculate individual Meibomian gland metrics. Interreader agreement and agreement between manual and automated methods for Meibomian gland segmentation were also carried out to assess the accuracy of the automated approach.

Main Outcome Measures

Meibomian gland metrics, including length ratio, area, tortuosity, intensity, and width, were measured. Additionally, the performance of the automated algorithms was evaluated using the aggregated Jaccard index.

Results

The proposed semantic segmentation-based approach achieved average aggregated Jaccard index of mean 0.4718 (95% confidence interval [CI], 0.4680-0.4771) for the 'gland' class and a mean of 0.8470 (95% CI, 0.8432-0.8508) for the 'eyelid' class. The result for object detection-based approach was a mean of 0.4476 (95% CI, 0.4426-0.4533). Both artificial intelligence-based algorithms underestimated area, length ratio, tortuosity, widthmean, widthmedian, width10th, and width90th. Meibomian gland intensity was overestimated by both algorithms compared with the manual approach. The object detection-based algorithm seems to be as reliable as the manual approach only for Meibomian gland width10th calculation.

Conclusions

The proposed approach can successfully segment Meibomian glands; however, to overcome problems with gland overlap and lack of image sharpness, the proposed method requires further development. The study presents another approach to utilizing automated, artificial intelligence-based methods in Meibomian gland health assessment that may assist clinicians in the diagnosis, treatment, and management of Meibomian gland dysfunction.

Financial Disclosures

The authors have no proprietary or commercial interest in any materials discussed in this article.

Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features

Purpose

This study aimed to establish an image-based classification that can reveal the clinical characteristics of patients with dry eye using unsupervised learning methods.

Methods

In this study, we analyzed 82,236 meibography images from 20,559 subjects. Using the SimCLR neural network, the images were categorized. Data for each patient were averaged and subjected to mini-batch k-means clustering, and validated through consensus clustering. Statistical metrics determined optimal category numbers. Using a UNet model, images were segmented to identify meibomian gland (MG) areas. Clinical features were assessed, including tear breakup time (BUT), tear meniscus height (TMH), and gland atrophy. A thorough ocular surface evaluation was conducted on 280 cooperative patients.

Results

SimCLR neural network achieved clustering patients with dry eye into six image-based subtypes. Patients in different subtypes harbored significantly different noninvasive BUT, significantly correlated with TMH. Subtypes 1 and 5 had the most severe MG atrophy. Subtype 2 had the highest corneal fluorescent staining (CFS). Subtype 4 had the lowest TMH, whereas subtype 5 had the highest. Subtypes 3 and 6 had the largest MG areas, and the upper MG areas of a person's bilateral eyes were highly correlated. Image-based subtypes are related to meibum quality, CFS, and morphological characteristics of MG.

Conclusions

In this study, we developed an unsupervised neural network model to cluster patients with dry eye into image-based subtypes using meibography images. We annotated these subtypes with functional and morphological clinical characteristics.

Morphologic variants of Meibomian glands: age-wise distribution and differences between upper and lower eyelids

Purpose

To evaluate the distribution of various Meibomian gland morphologies across different age groups in healthy individuals.

Methods

The infrared meibographic morphologies of the Meibomian glands from the upper and lower eyelids of 236 healthy individuals (472 eyes; mean age 38.4 ± 17.5 years; 80 female participants: 156 male participants) were evaluated for their prevalence and differences across six decades of life, from 10 to 80 years. A linear mixed-effects modeling test was performed for statistical analysis.

Results

Of 14,452 glands, 8,830 (61%) glands were located in the upper eyelid. No significant differences in frequency were noted between different age groups for distorted, tortuous, hooked, overlapping, abnormal gap, fluffy areas, dropout (except for 51-60 vs. 10-20 years, P = 0.023), and thick and thin morphologies. Short glands were significantly more common in individuals aged over 30 years (P = 0.015), whereas moderately short and severely short glands were more common in the upper eyelids of individuals older than 50 years compared to those aged 10-20 years (P = 0.035). The frequency of distorted, hooked, tortuous, overlapping, and tadpole-shaped Meibomian glands was significantly higher in the upper eyelids than in the lower eyelids for all age groups. Dropout glands were more common in the lower eyelids of individuals younger than 50 years, but no difference was observed in the upper and lower eyelids of individuals over 50 years. Dropout (P = 0.006) and severely short glands (0.026) of the lower eyelid were associated with low non-invasive tear break-up time (NIBUT) values.

Conclusion

Various morphologic characteristics of the Meibomian glands that are considered abnormal can be present in healthy individuals, and only moderate to severely short glands display an increase in abnormal morphologic characteristics of the Meibomian glands with age.

Impacts of gender and age on meibomian gland in aged people using artificial intelligence

Purpose: To evaluate the effects of age and gender on meibomian gland (MG) parameters and the associations among MG parameters in aged people using a deep-learning based artificial intelligence (AI). Methods: A total of 119 subjects aged ≥60 were enrolled. Subjects completed an ocular surface disease index (OSDI) questionnaire, received ocular surface examinations including Meibography images captured by Keratograph 5M, diagnosis of meibomian gland dysfunction (MGD) and assessment of lid margin and meibum. Images were analyzed using an AI system to evaluate the MG area, density, number, height, width and tortuosity. Results: The mean age of the subjects was 71.61 ± 7.36 years. The prevalence of severe MGD and meibomian gland loss (MGL) increased with age, as well as the lid margin abnormities. Gender differences of MG morphological parameters were most significant in subjects less than 70 years old. The MG morphological parameters detected by AI system had strong relationship with the traditional manual evaluation of MGL and lid margin parameters. Lid margin abnormities were significantly correlated with MG height and MGL. OSDI was related to MGL, MG area, MG height, plugging and lipid extrusion test (LET). Male subjects, especially the ones who smoke or drink, had severe lid margin abnormities, and significantly decreased MG number, height, and area than the females. Conclusion: The AI system is a reliable and high-efficient method for evaluating MG morphology and function. MG morphological abnormities developed with age and were worse in the aging males, and smoking and drinking were risk factors.

Association of meibomian gland morphology with orifice plugging and lid margin thickening in meibomian gland dysfunction patients

PURPOSE

We sought to investigate the association of meibomian gland morphology with lid margin abnormalities in patients with meibomian gland dysfunction.

METHODS

This retrospective study included 368 eyes of 184 patients. Meibography was used to evaluate meibomian gland (MG) morphological features, such as dropout, distortion, thickened ratio and thinned ratio. Lid margin photography was used to evaluate lid margin abnormalities including orifice plugging, vascularity, irregularity and thickening. The association between MG morphological features and lid margin abnormalities was analyzed using a mixed linear model.

RESULTS

The study found a positive correlation between plugging of gland orifices grade and MG dropout grade in both the upper lids (B = 0.40, p = 0.007) and the lower lids (B = 0.55, p = 0.001). Plugging of gland orifices grade was also positively correlated to MG distortion grade in the upper lids (B = 0.75, p = 0.006). In the upper lids, MG thickened ratio increased first (B = 0.21, p = 0.003) and then decreased (B = - 0.14, p = 0.010) with a higher lid margin thickening grade. MG thinned ratio was negatively correlated with lid margin thickening (B = - 0.14, p = 0.002, B = - 0.13, p = 0.007). MG distortion grade decreased with lid margin thickening (B = - 0.61, p = 0.012).

CONCLUSION

Orifice plugging was correlated to meibomian gland distortion and dropout. Lid margin thickening was associated with meibomian gland thickened ratio, thinned ratio, and distortion. The study also suggested that distorted and thinned glands may be transitional phases between thickened glands and glands dropout.

Repeatability and reproducibility of Cobra HD fundus camera meibography in young adults with and without symptoms of dry eye

PURPOSE

The inter-session repeatability (ISR), inter-examiner reproducibility (IER) and within-subject variability (WSV) of the Cobra HD fundus camera meibographer were examined in participants with and without dry eye symptoms.

METHODS

Symptoms were determined based on Ocular Surface Disease Index scores (≥13 being considered symptomatic), and subgroups were compared using the Mann-Whitney U-test. Images of meibomian glands (MGs) from the upper and lower right eyelids were captured by two examiners on the same day (S1) to determine IER. One examiner repeated the measurements on a second day (S2) to obtain the ISR. ISR, IER and WSV were calculated using Friedman, correlation tests and Bland and Altman analyses with mean differences (md) and 95% confidence intervals (CIs), within-subject standard deviations (Sw) and intra-class correlation coefficients (ICC).

RESULTS

The ISR experiment included 72 participants (mean age: 23 ± 5 years, range: 19-43, 36 symptomatic). Mean MG loss of the upper (S1: 13.5 ± 9.5%, S2: 12.8 ± 8.5%) and lower eyelids (S1: 7.5 ± 6.9%, S2: 7.3 ± 6.3%) was not significantly different between sessions for all participants, symptomatic and asymptomatic subgroups for both eyelids. The ISR Sw for the upper and lower eyelids was 1.3% and 1.0%; md was 0.7 ± 3.5% (CI:-6.25% to 7.62%) and 0.1 ± 2.1% (CI: -3.94% to 4.17%), respectively. The IER experiment included 74 participants (mean age: 23 ± 5 years, range: 19-43, 37 symptomatic). Mean MG loss of the upper (Examiner 1: 12.7 ± 8.2%, Examiner 2: 13.1 ± 8.0%) and lower eyelids (Examiner 1: 7.0 ± 6.2%, Examiner 2: 7.4 ± 6.2%) was not significantly different between examiners for all participants, symptomatic and asymptomatic subgroups for both eyelids. The IER ICC values were >0.86 for all conditions, Sw was 1.3% and 1.2%, with a md of -0.4 ± 3.2% (CI: -6.65% to 5.90%) and -0.4 ± 2.9% (CI: -6.15% to 5.31%), respectively. The WSV Sw values were <1.4%, and ICC values were >0.89 for both eyelids, examiners and experimental sessions.

CONCLUSIONS

The Cobra HD fundus camera demonstrates good repeatability, reproducibility and low WSV, and is a reliable clinical instrument for meibography.

Morphological variants of meibomian glands: correlation of meibography features with histopathology findings

PURPOSE

This study describes the histopathological features of different morphological variants of human meibomian glands (MGs) seen on infrared imaging.

METHODS

Tarsal plates dissected from seven cadaveric upper eyelids were imaged using infrared meibography, and then studied histopathologically using H&E, peroxisome proliferator-activated receptor gamma (PPARγ, meibocyte differentiation marker) and Ki-67 (cellular proliferation marker) antibody staining. The different morphological characteristics (varying size and shape) of MGs on meibography were correlated with histopathology findings using image analysis software.

RESULTS

Of the total 127 glands, the morphological variants observed on meibography based on size were: normal (n=62), short (n=18), severely short (n=6) and dropout (n=12) glands, and on shape were: hooked (n=2), tortuous (n=5), overlapping (n=1), thick (n=15) and fluffy (n=6) glands. Short, hooked, tortuous and overlapping glands had similar acinar and ductal histology as seen in normal glands whereas thick, and fluffy glands had increased acinar diameter. All glands except the severely short type demonstrated normal signs of holocrine secretory activity and normal nuclear and cytoplasmic PPARγ expression. Severely short glands had nil while short glands had reduced Ki-67 proliferation index (3%±1%) as compared with normal and other variants (8%±5.2%). Gland dropout areas showed no evidence of any glandular tissue on histology.

CONCLUSION

Hooked, tortuous and overlapping glands had completely normal glandular histology, whereas severely short glands showed atrophic changes with loss of meibocyte differentiation and cellular proliferation. Dropout areas showed total loss of glandular elements. Further studies are needed to validate and to explore the clinical implications of these findings.

The efficacy of ocular surface assessment approaches in evaluating dry eye treatment with artificial tears

This study evaluates the effectiveness of objective techniques in assessing dry eye disease (DED) treatment compared with the subjective assessment commonly used in clinical practice. Thirty subjects were recruited for two visits separated by 28(± 3) days of treatment with artificial tears. A buttery of common subjective assessment methods were accompanied by a set of objective techniques including measurement of noninvasive tear film break-up time (NIBUT), lipid layer thickness (LLT), and quantitative evaluation of tear film surface quality and dynamics (TFD). Additionally, meibography was performed. Two commercially available videokeratoscopes and a prototype of a lateral shearing interferometer were used for the measurements. Both subjective and objective techniques showed a positive effect of artificial tears in DED treatment. Statistically significant improvements were observed in subjective symptoms (from P < 0.001 for Ocular Surface Disease Index, OSDI to p = 0.019 for tearing), conjunctival redness (P = 0.022), ocular staining (P = 0.012), fluorescein tear film break-up time (P = 0.015), NIBUT (P = 0.037), LLT (P < 0.001), and TFD (P = 0.048). In general, weak or statistically insignificant correlations were observed between subjective and objective assessment methods. The apparent lack of correlation between these methods might indicate the complementary character of objective techniques that likely assess other characteristics of ocular surface health than those assessed subjectively.

Predicting demographics from meibography using deep learning

This study introduces a deep learning approach to predicting demographic features from meibography images. A total of 689 meibography images with corresponding subject demographic data were used to develop a deep learning model for predicting gland morphology and demographics from images. The model achieved on average 77%, 76%, and 86% accuracies for predicting Meibomian gland morphological features, subject age, and ethnicity, respectively. The model was further analyzed to identify the most highly weighted gland morphological features used by the algorithm to predict demographic characteristics. The two most important gland morphological features for predicting age were the percent area of gland atrophy and the percentage of ghost glands. The two most important morphological features for predicting ethnicity were gland density and the percentage of ghost glands. The approach offers an alternative to traditional associative modeling to identify relationships between Meibomian gland morphological features and subject demographic characteristics. This deep learning methodology can currently predict demographic features from de-identified meibography images with better than 75% accuracy, a number which is highly likely to improve in future models using larger training datasets, which has significant implications for patient privacy in biomedical imaging.

Latest developments in meibography: A review

Meibography is a visualisation technique that has been used for over 40 years. There have been significant improvements in image quality, examination technique and image interpretation over this period. Although meibography has received sporadic reviews in the past, an updated review is timely due to the rapid recent rise of relevant technology and advances in both image processing and artificial intelligence. The primary aim of this paper is to review recent research into Meibomian gland imaging and update the community about the most relevant technologies and approaches used in the field.

Correlation of meiboscale symptom score and sign score for primary meibomian gland dysfunction in Indian eyes - A cross-sectional study

Purpose:

To evaluate the correlation of Meiboscale with symptom score (Ocular Surface Disease Index [OSDI]) and meibomian gland dysfunction (MGD) sign score.

Methods:

We performed a cross-sectional hospital-based study of 53 patients of primary MGD who filled the OSDI questionnaire form and underwent complete ocular examination. The MGD sign score was calculated in both eyes using the sum of six grading systems proposed by Arita et al. in 2016. The participants underwent imaging of the upper and lower eyelids of both eyes (212 eyelids) by specular microscope. The area of meibomian gland loss (MGL) was visually assessed and scored using the Meiboscale photographic card. Correlation between these three values – OSDI score, sign score, and MGL score based on Meiboscale - was calculated using Spearman’s correlation analysis and Jonckheere–Terpstra (J–T) test. Correlation coefficient r_s > 0.5 was considered clinically significant.

Results:

Associations between MGL score and OSDI score, as well as between OSDI and sign score were statistically significant, but not clinically significant (r_s = 0.3684, P < 0.001 and r_s = 0.41179, P < 0.001, respectively). The association between MGL score and MGD sign score was statistically as well as clinically significant (r_s = 0.8392, P < 0.001). J–T test revealed large effect size (P < 0.001, r-effect = 0.93).

Conclusion:

The Meiboscale card had not been tested for utility in the Indian outpatient setting yet. Meiboscale can be used for reliable assessment and grading of MGD, and has clinical utility similar to the sum of six MGD sign scores. Additionally, assessment of symptoms using OSDI or a similar questionnaire is also recommended.

Global improvement in meibomian glands after chalazion surgery demonstrated by meibography

PURPOSE

To evaluate the use of meibography as an objective measure of the effects of incision & curettage (I&C) chalazion surgery on meibomian gland loss and morphology as well as dry eye syndrome.

METHODS

This prospective, interventional clinical study included adult patients with a primary chalazion which persisted despite conservative treatment. All patients underwent I&C surgery. The following parameters were compared both preoperatively and 21 days postoperatively: meibography, tear breakup time (TBUT), Schirmer test, meibum expression, tear meniscus height, meibomian gland dysfunction (MGD) grading, and the Ocular Surface Disease Index (OSDI).

RESULTS

Thirty eyelids were enrolled in the study. The mean age ± SD was 40.56 ± 13.94 years. Meibography demonstrated a significant decrease in meibomian gland loss (P = 0.00) and improvement in morphology. The most common meibomian gland pathology preoperatively noted was morphological signs of atrophy that included fluffy areas and tortuous glands. Both of these findings improved postoperatively (P = 0.04 and P = 0.02, respectively). There were a significant change in MGD grading and a significant decrease in meibum expression score postoperatively (P = 0.00). TBUT and tear meniscus height also improved significantly (P = 0.00 and P = 0.003, respectively). The OSDI score improved significantly as well (P = 0.00).

CONCLUSION

While incision and drainage surgery is a time-honored, standard treatment for chalazion, meibography now demonstrates a global improvement in the meibomian glands, not just the ones involved with the chalazion. In addition to the improvements in the clinical and dry eye syndrome parameters improvements, meibography findings demonstrate that early I&C surgery restores the meibomian glands architecture significantly.

Association Between Depression and Severity of Dry Eye Symptoms, Signs, and Inflammatory Markers in the DREAM Study

Importance

Depression is more prevalent in patients with dry eye disease (DED) than in the general population; however, the association between severity of DED and depression needs further evaluation.

Objective

To investigate the association between depression and severity of DED symptoms and signs, including inflammatory markers.

Design, Setting, and Participants

Secondary cross-sectional and longitudinal analysis performed in April to December 2020 of data from Dry Eye Assessment and Management (DREAM) study, a randomized clinical trial from October 2014 to July 2016 including patients with moderate to severe symptoms and signs of DED. Enrolled from 27 ophthalmology and optometry centers, both academic and private, in 17 US states, 535 patients were followed up for 1 year.

Exposure

Participants screened positive for depression if they scored 42 or less on the Mental Component Summary (MCS) of the 36-Item Short Form Health Survey.

Main Outcomes and Measures

Symptoms of DED were assessed by Ocular Surface Disease Index (OSDI) and Brief Ocular Discomfort Index (BODI) and signs assessed by tear film breakup time, Schirmer test, corneal and conjunctival staining, tear osmolarity, and meibomian gland dysfunction at baseline, 6 months, and 12 months. A composite severity sign score was calculated from all 6 signs. Inflammatory markers (cytokines in tears and HLA-DR expression by conjunctival surface cells) were measured for some trial participants. Features of DED were compared between participants with and without depression and adjusted for age, sex, race, visits, and baseline comorbidities.

Results

Among the 535 participants, mean (SD) age was 58 (13.2) years, 434 participants (81%) were women, and 398 (74.4%) were White. Participants who screened positive for depression had worse DED symptoms by OSDI (effect size = 0.45, P < .001) and BODI (effect size = 0.46, P < .001) and composite DED sign score (effect size = 0.21, P = .006). Lower MCS score (ie, worse depression) was correlated with higher OSDI score (ie, worse DED symptoms) at baseline (Spearman ρ = -0.09, P = .03), 6 months (ρ = -0.20, P < .001), and 12 months (ρ = -0.21, P < .001). Inflammatory markers did not differ by depression status.

Conclusions and Relevance

Depression was associated with more severe dry eye symptoms and overall signs, suggesting that among patients with moderate to severe DED, those with depression may be likely to have more severe DED. These findings support consideration of depression as a comorbidity when managing patients with DED. Further study is needed to elucidate the relationship.

Morphological and Functional Changes of Meibomian Glands in Pediatric and Adult Patients with Allergic Conjunctivitis

Allergic conjunctivitis (AC) is one of the most common ocular disorders in clinical practice and is associated with meibomian gland dysfunction. This study aimed to explore the morphological and functional changes of meibomian glands (MGs) in pediatric and adult patients with AC and to analyze their potential predictors. In our prospective, observational cohort study, a total of 59 patients with AC were enrolled, with 30 patients aged ≤16 years in the pediatric group and 29 patients in the adult group. All patients underwent examinations at baseline and last visit when the complete resolution of conjunctival papillae was identified. An automatic MG analyzer was used to measure the morphological and functional parameters of MGs, including their area ratio (GA), tortuosity index (TI), and signal index (SI). Two groups were comparable at baseline in terms of characteristics and MG parameters (p > 0.05). The morphological (length, square, and GA) and functional MG parameters (SI) of AC patients significantly improved in the pediatric group after treatment (all p < 0.05), but not in the adult group. The change in the GA correlated with age, sex, GA, TI, and SI at baseline (all p < 0.05). Age (p = 0.001) and GA (p < 0.001) at baseline were predictors of an improvement in the GA of MGs. The findings showed that the structure and function of MGs in pediatric patients with AC seem to improve after the conjunctival papillae disappear, but not in adult patients.

[Modern possibilities of studying the composition of meibomian glands secretion]

As the main source of various lipids, the meibomian glands are involved in the formation of lipid layer of the tear film and the maintenance of homeostasis of the ocular surface. This process is directly dependent on the chemical composition and thickness of the lipid layer. In addition to lipid components, the meibum also contains various proteins that affect the properties of the tear film. The introduction of various modifications of mass spectrometry into clinical practice is a new diagnostic approach that allows obtaining information about the composition of meibomian glands secretion and tears.

Ocular surface alterations and changes of meibomian glands with meibography in type 1 diabetic children

PURPOSE

To observe the changes of the ocular surface and meibomian glands by non-contact meibography in patients with type 1 diabetic children.

METHODS

A total of forty-three patients with type 1 diabetic children and 43 age-matched healthy subjects were included in the study. The ocular surface disease index (OSDI) questionnaire, invasive tear film break-up time (TF-BUT), fluorescein staining of the ocular surface and Schirmer II test were performed for all participants. Ocular surface and lid margins were evaluated by slit lamp. Non-contact meibography was performed with the Phoenix-Meibography module in Sirius corneal topographic device.

RESULTS

Both groups consisted of 25 (58.1%) female and 18 (41.9%) male children and the mean age was 14.4 ± 2.5 years. In the T1DM group, the mean disease duration was 6.8 ± 3.1 years. The mean TF-BUT (p = 0.002) and Schirmer II test (p = 0.007) measurements were lower in the diabetic group than those of in controls. Total eyelid score (p = 0.027) and meibomian gland (MG) secretion score (p = 0.007) were significantly high in diabetic children. MG area loss was also significantly high in both lower and upper eyelid (p < 0.001). In morphological analyses of meibomian glands thinning, shortening and presence of ghost areas (p = 0.05, p = 0.027 and p = 0.000, respectively) were more common in the diabetic group. There was no correlation between both lower and upper eyelid meiboscores and disease duration (p = 0.51 and p = 0.61), BMI (p = 0.08 and p = 0.51), serum HbA1c level (p = 0.06 and p = 0.49) and IGF-1 SDS (p = 0.38 and p = 0.68).

CONCLUSION

The study revealed that the MG loss area increases and morphological alterations of meibomian glands occur in type 1 diabetic children. Disease duration and metabolic control of diabetes do not affect meibography measurements.

CLINICAL TRIALS REGISTRATION

The study was organized in accordance with the ethical standards settled by the Ethics Committee of Faculty of Medicine, Afyonkarahisar Health Sciences University.

TRIAL REGISTRATION NUMBER

2011-KAEK-2, 2021/106.

TRIAL REGISTRATION DATE

02.05.2021.

Morphology of Meibomian Glands in a 65-Year-Old Norwegian Population without Dry Eye Disease

Analyses of meibography may help in the diagnosis, prevention, and management of meibomian gland dysfunction (MGD). However, there is currently a paucity of data regarding meibography analyses in the young elderly populations in the Nordic countries. In the current study, meibography of the upper and lower eyelids of 117 65-year-old residents in Oslo, Norway, who did not fulfil the diagnosis of dry eye disease (DED) were analysed. Meibomian gland (MG) dropout and tarsal areas were measured semi-automatically using ImageJ software. The relationship between morphological features of the MGs and clinical dry eye tests was examined. The median percent MG dropout was 26.1% and 40.7% in the upper and lower eyelids, respectively. There was no significant difference between males and females. None of the MG morphological parameters demonstrated significant values in discriminating abnormal dry eye symptom loads or MGD diagnosis from the normal loads. We therefore concluded that moderate MG atrophy was common among the Norwegian population of 65-year-olds without DED and showed no sexual differences. Meibography alone cannot discriminate MGD from non-MGD; thus, both morphological and functional MG tests are necessary when screening for MGD.

Artificial Intelligence to Detect Meibomian Gland Dysfunction From in-vivo Laser Confocal Microscopy

Background: In recent years, deep learning has been widely used in a variety of ophthalmic diseases. As a common ophthalmic disease, meibomian gland dysfunction (MGD) has a unique phenotype in in-vivo laser confocal microscope imaging (VLCMI). The purpose of our study was to investigate a deep learning algorithm to differentiate and classify obstructive MGD (OMGD), atrophic MGD (AMGD) and normal groups. Methods: In this study, a multi-layer deep convolution neural network (CNN) was trained using VLCMI from OMGD, AMGD and healthy subjects as verified by medical experts. The automatic differential diagnosis of OMGD, AMGD and healthy people was tested by comparing its image-based identification of each group with the medical expert diagnosis. The CNN was trained and validated with 4,985 and 1,663 VLCMI images, respectively. By using established enhancement techniques, 1,663 untrained VLCMI images were tested. Results: In this study, we included 2,766 healthy control VLCMIs, 2,744 from OMGD and 2,801 from AMGD. Of the three models, differential diagnostic accuracy of the DenseNet169 CNN was highest at over 97%. The sensitivity and specificity of the DenseNet169 model for OMGD were 88.8 and 95.4%, respectively; and for AMGD 89.4 and 98.4%, respectively. Conclusion: This study described a deep learning algorithm to automatically check and classify VLCMI images of MGD. By optimizing the algorithm, the classifier model displayed excellent accuracy. With further development, this model may become an effective tool for the differential diagnosis of MGD.

[Thermal pulsation system (LipiFlow®) for treatment of meibomian gland dysfunction (MGD) from the perspective of an ophthalmologist in private practice]

PURPOSE

Thermal pulsation (LipiFlow®, Johnson&Johnson, Santa Ana, CA, USA) has been advocated for meibomian gland dysfunction (MGD) treatment and was found to be useful in many studies. The aim of this study was to show the efficacy of the method and to compare it to a daily eyelid margin massage in a non-university institution.

METHODS

A non-blinded, single-center interventional study comparing thermal pulsation with eyelid margin massage for the treatment of MDD. In this study 30 patients were recruited during daily office hours. Symptoms (OSDI) and ocular surface (NIK-BUT, tear ferning test, tear meniscus height, LIPCO folds, meibography, meibomian gland evaluator) were assessed before treatment. A total of 15 patients (9 women) underwent thermal pulsation (single session), while 15 patients (8 women) performed eyelid margin massage (once daily) as instructed for 3 months.

RESULTS

Before the two treatment methods, there were no differences in the above parameters, gender and age were also normally distributed. After treatment, both subjective and objective criteria improved in the two groups but significantly more in the thermal pulsation arm. In particular, the limited compliance of 30% in the eyelid margin massage arm should be noted. Safety parameters, such as visual acuity and intraocular pressure (IOP) remained normal in all patients.

CONCLUSION

A single session of thermal pulsation showed significantly better results in the efficacy and safety profile after 3 months compared to eyelid margin massage once daily; however, the high costs for the patients due to the single use mode of the activators must be taken in account.

Alterations in meibomian glands in patients treated with intensity-modulated radiotherapy for head and neck cancer

Patients undergoing intensity-modulated radiotherapy (IMRT) for head and neck cancer may have increased incidence of dry eye disease and the exact mechanism is unclear. The present study aims to assess tear film and meibomian gland (MG) features in patients who received IMRT for head and neck cancer not involving the orbital area. Twenty-seven patients (64.7 ± 9.8 years) and 30 age-matched controls (61.4 ± 11.0 years) underwent a comprehensive dry eye work-up. Compared to the control group, the patients had more lid margin abnormalities, and worse meibum quality. The MG loss, calculated as (tarsal area-MG area)/tarsal area, was higher in the patient group in both the upper (53.0 ± 12.0% vs. 35.1 ± 10.3%, p < 0.001) and lower lids (69.5 ± 12.6% vs. 48.5 ± 12.5%, p < 0.001). In the patient group, more MG loss in the lower lids correlated with worse meibum quality (r = 0.445, p = 0.029). In contrast, there was no significant difference in aqueous tear production level, measured with Schirmer test. Patients treated with IMRT for head and neck cancer seemed to have comparable lacrimal gland function to the controls despite more dry eye symptoms. However, the patients had MG functional and morphological changes, which may present a higher risk for developing dry eye disease.

Comparative of meibomian gland morphology in patients with evaporative dry eye disease versus non-dry eye disease

Many recent studies have showed that morphological changes are one of the key signs of meibomian gland disease (MGD). These changes can be seen even before symptom onset, potentially underestimating the prevalence of MGD; however, until now, there is no conclusive information about the impact of meibomian gland (MG) morphology in tear film physiology and disease. This study aimed to investigate the prevalence of anatomical and morphological MG alterations between patients with evaporative dry eye disease (DED) and healthy controls. Retrospective chart review of seventy-five patients with evaporative DED and healthy individuals who had dry eye assessments included Ocular Surface Disease Index questionnaire, meibum quality, meibum expressibility, lid margin abnormality, ocular staining, non-invasive tear film break-up time, and meibography. We did not find significant differences in MG alterations in the upper lid between healthy and DED subjects. Patients with evaporative DED presented MG alterations in the lower lid more frequently than healthy subjects (54.8 vs. 30.3%; p = 0.03). The presence of shortened glands was the only MG alteration that was more prevalent in the lower lid in dry-eye patients than in healthy subjects (p < 0.05). Subjects with evaporative DED presented more alterations in the lower lid than healthy subjects.

Quantitative analysis of morphological and functional features in Meibography for Meibomian Gland Dysfunction: Diagnosis and Grading

BACKGROUND

To explore the performance of quantitative morphological and functional analysis in meibography images by an automatic meibomian glands (MGs) analyser in diagnosis and grading Meibomian Gland Dysfunction (MGD).

METHODS

A cross-sectional study collected 256 subjects with symptoms related to dry eye and 56 healthy volunteers who underwent complete ocular surface examination was conducted between January 1, 2019, and December 31, 2020. The 256 symptomatic subjects were classified into MGD group (n = 195) and symptomatic non-MGD group (n = 61). An automatic MGs analyser was used to obtained multi-parametric measurements in meibography images including the MGs area ratio (GA), MGs diameter deformation index (DI), MGs tortuosity index (TI), and MGs signal index (SI). Adjusted odds ratios (ORs) of the multi-parametric measurements of MGs for MGD, and the area under the receiver operating characteristic (AUC-ROC) curves of multi-parametric measurements for MGD diagnosing and grading were conducted.

FINDINGS

When consider age, sex, ocular surface condition together, the estimated ORs for DI was 1.62 (95% CI, 1.29-2.56), low-level SI was 24.34 (95% CI, 2.73-217.3), TI was 0.76(95% CI, 0.54-0.90), and GA was 0.86 (95% CI, 0.74-0.92) for MGD. The combination of DI-TI-GA-SI showed an AUC = 0.82 (P < 0.001) for discriminating MGD from symptomatic subjects. The DI had a higher AUC in identifying early-stage MGD (grade 1-2), while TI and GA had higher AUCs in moderate and advanced stages (grade 3-5). Merging DI-TI-GA showed the highest AUCs in distinguish MGD severities.

INTERPRETATION

The MGs area ratio, diameter deformation, tortuosity and signal intensity could be considered promising biomarkers for MGD diagnosis and objective grading.

FUNDING

This work was supported by the Key-Area Research and Development Program of Guangdong Province (No. 2019B010152001), the National Natural Science Foundation of China under Grant (81901788) and Guangzhou Science and Technology Program (202002030412).

Quantifying Meibomian Gland Morphology Using Artificial Intelligence

SIGNIFICANCE

Quantifying meibomian gland morphology from meibography images is used for the diagnosis, treatment, and management of meibomian gland dysfunction in clinics. A novel and automated method is described for quantifying meibomian gland morphology from meibography images.

PURPOSE

Meibomian gland morphological abnormality is a common clinical sign of meibomian gland dysfunction, yet there exist no automated methods that provide standard quantifications of morphological features for individual glands. This study introduces an automated artificial intelligence approach to segmenting individual meibomian gland regions in infrared meibography images and analyzing their morphological features.

METHODS

A total of 1443 meibography images were collected and annotated. The dataset was then divided into development and evaluation sets. The development set was used to train and tune deep learning models for segmenting glands and identifying ghost glands from images, whereas the evaluation set was used to evaluate the performance of the model. The gland segmentations were further used to analyze individual gland features, including gland local contrast, length, width, and tortuosity.

RESULTS

A total of 1039 meibography images (including 486 upper and 553 lower eyelids) were used for training and tuning the deep learning model, whereas the remaining 404 images (including 203 upper and 201 lower eyelids) were used for evaluations. The algorithm on average achieved 63% mean intersection over union in segmenting glands, and 84.4% sensitivity and 71.7% specificity in identifying ghost glands. Morphological features of each gland were also fed to a support vector machine for analyzing their associations with ghost glands. Analysis of model coefficients indicated that low gland local contrast was the primary indicator for ghost glands.

CONCLUSIONS

The proposed approach can automatically segment individual meibomian glands in infrared meibography images, identify ghost glands, and quantitatively analyze gland morphological features.

Evaluation of dry eye subtypes and characteristics using conventional assessments and dynamic tear interferometry

BACKGROUND/AIMS

To evaluate subtypes and characteristics of dry eye (DE) using conventional tests and dynamic tear interferometry, and to investigate determinants of disease severity in each DE subtype.

METHODS

309 patients diagnosed with DE and 69 healthy controls were prospectively enrolled. All eyes were evaluated using Ocular Surface Disease Index (OSDI), Schirmer's test I (ST1) and Meibomian gland dysfunction (MGD) grade were analysed. The tear interferometric pattern and lipid layer thickness were determined using DR-1α and LipiView II, respectively.

RESULTS

Dynamic interferometric analysis revealed 56.6% of patients with DE exhibited Jupiter patterns, indicative of aqueous-deficiency, while 43.4% exhibited crystal patterns, indicative of lipid deficiency. These findings were in accordance with classification based on ST1 scores and MGD grade. Conventional assessment indicated 286 patients exhibited evidence of evaporative DE (EDE) due to MGD, while only 11 exhibited signs of pure aqueous-deficient DE (pure ADDE, only ST1 ≤5 mm). Interestingly, of 286 patients with EDE, 144 were categorised into the mixed-ADDE/EDE group, in which ST1 was identified as a strong negative determinant of OSDI. In contrast, 72.2% of patients with mixed-ADDE/EDE exhibited Jupiter patterns (Jupiter mixed), while 27.8% exhibited crystal patterns (crystal mixed). OSDI values were significantly higher in the crystal-mixed group than in the Jupiter mixed, in which OSDI scores were independently associated with ST1 values only.

CONCLUSIONS

Our findings indicate that majority of EDE patients also exhibit aqueous deficiency, which can aggravate symptoms even in patients with lipid-deficient mixed-ADDE/EDE. Conventional assessments should be combined with interferometric tear analysis to determine the most appropriate treatment for each DE patient.

Comparative Study of Two Infrared Meibographers in Evaporative Dry Eye Versus Nondry Eye Patients

OBJECTIVE

To compare the measurement of the meibomian gland (MG) dropout between two infrared meibographers in patients with and without dry eye.

METHODS

The right eyelids of each patient were imaged using the Antares and Cobra meibography devices. All images were analyzed using Phoenix software to calculate the percentage of the MG dropout. Lipid layer thickness, eyelid margin characteristics, ocular surface staining, MG secretion, number of expressible glands, and noninvasive tear breakup time were also evaluated. A comparison between nondry eye and evaporative dry eye was performed.

RESULTS

Eighty participants (mean age, 36.93 years and 51.3% women) were included, of which 67.5% had nondry eye. A significant difference was observed in the dropout percentage of the superior eyelid between the Antares and Cobra devices (P=0.007) for all participants and when only the nondry eye patients were examined. In patients with dry eye, no significant differences were found in the dropout measurements of both eyelids.

CONCLUSIONS

Statistically significant differences in the MG dropout percentage in the upper eyelid of nondry eye patients were obtained from both meibographers. The measurements were similar in patients with dry eye, suggesting that the two instruments can be interchanged.

Intraductal meibomian gland probing and its efficacy in the treatment of meibomian gland dysfunction

Meibomian gland dysfunction (MGD) is a major cause of dry eye, affecting millions worldwide. Intraductal meibomian gland probing (MGP) aims to open obstructed meibomian glands using a small probe to promote meibum secretion. MGP has received increasing interest since 2010, and we critically evaluated the literature on the efficacy and safety of MGP. Despite positive results of MGP on dry eye symptoms in early single-group studies, MGP was not shown to consistently outperform controls in later controlled trials. Furthermore, MGP alone did not show improvement beyond placebo in the only placebo-controlled RCT conducted. Overall, the procedure appears safe. Self-limited intraoperative bleeding was frequent, but no major complications were reported. In conclusion, MGP has not yet been shown to be an effective treatment for MGD. Larger placebo-controlled trials need to be conducted to establish the potential effect of this novel treatment modality.

A Review of Imaging Biomarkers of the Ocular Surface

A biomarker is a "characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions." Recently, calls for biomarkers for ocular surface diseases have increased, and advancements in imaging technologies have aided in allowing imaging biomarkers to serve as a potential solution for this need. This review focuses on the state of imaging biomarkers for ocular surface diseases, specifically non-invasive tear break-up time (NIBUT), tear meniscus measurement and corneal epithelial thickness with anterior segment optical coherence tomography (OCT), meibomian gland morphology with infrared meibography and in vivo confocal microscopy (IVCM), ocular redness with grading scales, and cellular corneal immune cells and nerve assessment by IVCM. Extensive literature review was performed for analytical and clinical validation that currently exists for potential imaging biomarkers. Our summary suggests that the reported analytical and clinical validation state for potential imaging biomarkers is broad, with some having good to excellent intra- and intergrader agreement to date. Examples of these include NIBUT for dry eye disease, ocular redness grading scales, and detection of corneal immune cells by IVCM for grading and monitoring inflammation. Further examples are nerve assessment by IVCM for monitoring severity of diabetes mellitus and neurotrophic keratitis, and corneal epithelial thickness assessment with anterior segment OCT for the diagnosis of early keratoconus. However, additional analytical validation for these biomarkers is required before clinical application as a biomarker.

A review of meibography for a refractive surgeon

Refractive surgery has evolved from being a therapeutic correction of high refractive errors to a cosmetic correction. The expectations associated with such a surgery are enormous and one has to anticipate all possible complications and side-effects that come with the procedure and prepare accordingly. The most common amongst these is post-refractive surgery dry eye of which Meibomian gland dysfunction is a commonly associated cause. We present an understanding of various diagnostic imaging modalities that can be used for evaluating meibomian glands which can also serve as a visual aid for patient understanding. We also describe various common conditions which can silently cause changes in the gland architecture and function which are to be considered and evaluated for.

Effect of 3-Hydroxy-3-Methyl-Glutaryl-Coenzyme A Reductase Inhibitors on the Meibomian Gland Morphology in Patients with Dyslipidemia

PURPOSE

Previous studies have suggested an association between dyslipidemia and meibomian gland dysfunction (MGD). The aim of this prospective, nonrandomized clinical study is to evaluate the possible association of dyslipidemia and its treatment with meibomian gland (MG) morphologic changes by standardized meibography.

DESIGN

Prospective, nonrandomized clinical study.

METHODS

Two groups of participants were enrolled: group 1, comprised of patients under regular 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase inhibitor (statin) treatment for dyslipidemia, and group 2, those with newly diagnosed dyslipidemia who were under lifestyle interventions. Meibography was performed at baseline and at both the 6- and 12-month visits and were graded by meiboscores. Participants underwent slit lamp examination for signs of changes in meibum quality and MG lid morphologic features. The Ocular Surface Disease Index questionnaire was given to measure subjective symptoms of ocular surface disease. Dry eye parameters including tear meniscus height, noninvasive first and average tear film break-up time, and Schirmer test results were also recorded.

RESULTS

Ninety-eight participants completed this longitudinal study over 12 months. There were statistically significant changes in total meiboscores (P = .01) and upper eyelid meiboscores (P = .012), lid margin abnormality scores (P = .0059), and meibum quality (P = .0002) in the statin group during follow-up visits. Similar changes of upper eyelid meiboscores (P = .046) and meibum quality (P = .046) were noted in the nonstatin group.

CONCLUSION

Meibomian gland atrophy and deterioration of meibum quality continued in the long term among participants with dyslipidemia even under statin usage.

Latest evidences on meibomian gland dysfunction diagnosis and management

Meibomian gland dysfunction (MGD) can be considered the leading cause of dry eye disease (DED) and one of the most common ophthalmic disorders found in clinical practice. The growing body of literature provides a substantial amount of information on this condition, but more efforts are needed to better interpret research data and to properly apply them to daily clinical practice., In this article, we reviewed the most recent publications on MGD diagnosis and management, focusing on the highest available level of evidence, provided by well-designed and well-reported studies on humans., Latest evidences on MGD diagnosis are mainly focused on imaging techniques, including meibography, optical coherence tomography (OCT), and in vivo confocal microscopy. Meibographic parameters, such as drop-out and glands' distortion, show great diagnostic accuracy, which accounts for their widespread use in clinical practice and research., Recent randomized controlled clinical trials on MGD treatment provided data on the role of antibiotics, steroids, essential fatty acids, intraductal meibomian gland probing, electronic heating devices and intense pulsed light therapy.

Association of meibomian gland morphology with symptoms and signs of dry eye disease in the Dry Eye Assessment and Management (DREAM) study

PURPOSE

To describe associations between symptoms and signs of dry eye disease (DED) and meibomian gland (MG) morphology.

METHODS

Cross-sectional study utilizing data from the Dry Eye Assessment and Management (DREAM) Study. Readers graded MG features in the middle third of upper and lower lids on infrared meibography images. Associations with signs and symptoms of DED were evaluated with adjustment for age and sex.

RESULTS

Among 268 patients, no MG features were associated with symptom scores (p > 0.08). Among 394 upper eyelids, better tear break-up times (<2, >2- <3.2and ≥ 3.2 s) were associated with more tortuous glands (mean (SD) 0.58(0.95), 0.83(1.2) and 1.14 (1.4), p = 0.01) and with higher scores on a composite score of MG features (21.90 (9.76), 23.29 (9.50), 26.26 (10.27); p = 0.02). Longer Schirmer test wetting lengths (0-5, >5-10, and >10 mm) were associated with increasing composite scores (22.02 (9.29), 23.80 (10.34), 24.96 (9.96), p = 0.03). Patients with Sjogren syndrome compared to other patients had fewer distorted MGs (mean 3.4 (2.3) vs 4.3 (2.3), p = 0.03) and fewer ghost glands (mean 0.33 (0.88) vs 0.89 (1.8), p = 0.006) in the upper lid.

CONCLUSION

In the DREAM study, most MG morphologic features were not associated with the severity of DED symptoms or signs. Tortuous glands and a higher composite score for MG features were associated with longer tear break-up times and longer Schirmer test length in the upper eyelid only. Patients with Sjogren syndrome had fewer distorted and ghost glands.