Automatic assessment of tear film and tear meniscus parameters in healthy subjects using ultrahigh-resolution optical coherence tomography

Dynamic Aspects of Pre-Soft Contact Lens Tear Film and Their Relation to Dry Eye: Basic Science and Clinical Relevance

Soft contact lens (SCL) perturbs the intimate connection between the pre-lens tear film (PLTF) and the ocular surface in various ways, i.e., (i) decrease in tear meniscus radius and aqueous tear thickness, (ii) attenuation of tear film lipid layer spread, (iii) limited wettability of SCL surface, (iv) increased friction with eyelid wiper, etc. This often results in SCL-related dry eye (SCLRDE) manifested as PLTF instability and contact lens discomfort (CLD). In this review, the individual contributions of factors (i-iv) to PLTF breakup patterns (BUP) and CLD are considered via the tear film-oriented diagnosis framework adopted by the Asia Dry Eye Society from a clinical and basic science perspective. It is shown that SCLRDE (due to aqueous deficiency, increased evaporation, or decreased wettability) and BUP of PLTF classify within the same types as the ones observed for the precorneal tear film. The analysis of PLTF dynamics reveals that the inclusion of SCL enhances the manifestation of BUP associated with (i) decreased thickness of PLTF aqueous layer and (ii) limited SCL wettability as shown by the rapid expansion of BUP area. PLTF thinness and instability result in increased blink-related friction and lid wiper epitheliopathy as major contributor to CLD.

Measurement method of tear meniscus height based on deep learning

Tear meniscus height (TMH) is an important reference parameter in the diagnosis of dry eye disease. However, most traditional methods of measuring TMH are manual or semi-automatic, which causes the measurement of TMH to be prone to the influence of subjective factors, time consuming, and laborious. To solve these problems, a segmentation algorithm based on deep learning and image processing was proposed to realize the automatic measurement of TMH. To accurately segment the tear meniscus region, the segmentation algorithm designed in this study is based on the DeepLabv3 architecture and combines the partial structure of the ResNet50, GoogleNet, and FCN networks for further improvements. A total of 305 ocular surface images were used in this study, which were divided into training and testing sets. The training set was used to train the network model, and the testing set was used to evaluate the model performance. In the experiment, for tear meniscus segmentation, the average intersection over union was 0.896, the dice coefficient was 0.884, and the sensitivity was 0.877. For the central ring of corneal projection ring segmentation, the average intersection over union was 0.932, the dice coefficient was 0.926, and the sensitivity was 0.947. According to the evaluation index comparison, the segmentation model used in this study was superior to the existing model. Finally, the measurement outcome of TMH of the testing set using the proposed method was compared with manual measurement results. All measurement results were directly compared via linear regression; the regression line was y0.98x-0.02, and the overall correlation coefficient was r ²0.94. Thus, the proposed method for measuring TMH in this paper is highly consistent with manual measurement and can realize the automatic measurement of TMH and assist clinicians in the diagnosis of dry eye disease.

Automation of dry eye disease quantitative assessment: A review

Dry eye disease (DED) is a common eye condition worldwide and a primary reason for visits to the ophthalmologist. DED diagnosis is performed through a combination of tests, some of which are unfortunately invasive, non‐reproducible and lack accuracy. The following review describes methods that diagnose and measure the extent of eye dryness, enabling clinicians to quantify its severity. Our aim with this paper is to review classical methods as well as those that incorporate automation. For only four ways of quantifying DED, we take a deeper look into what main elements can benefit from automation and the different ways studies have incorporated it. Like numerous medical fields, Artificial Intelligence (AI) appears to be the path towards quality DED diagnosis. This review categorises diagnostic methods into the following: classical, semi‐automated and promising AI‐based automated methods.

The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques

The field of ophthalmic imaging has grown substantially over the last years. Massive improvements in image processing and computer hardware have allowed the emergence of multiple imaging techniques of the eye that can transform patient care. The purpose of this review is to describe the most recent advances in eye imaging and explain how new technologies and imaging methods can be utilized in a clinical setting. The introduction of optical coherence tomography (OCT) was a revolution in eye imaging and has since become the standard of care for a plethora of conditions. Its most recent iterations, OCT angiography, and visible light OCT, as well as imaging modalities, such as fluorescent lifetime imaging ophthalmoscopy, would allow a more thorough evaluation of patients and provide additional information on disease processes. Toward that goal, the application of adaptive optics (AO) and full-field scanning to a variety of eye imaging techniques has further allowed the histologic study of single cells in the retina and anterior segment. Toward the goal of remote eye care and more accessible eye imaging, methods such as handheld OCT devices and imaging through smartphones, have emerged. Finally, incorporating artificial intelligence (AI) in eye images has the potential to become a new milestone for eye imaging while also contributing in social aspects of eye care.

Dry eye disease, a prominent manifestation of systemic autoimmune disorders

OBJECTIVES

Dry eye disease (DED) is arguably the most frequent ocular disease encountered in ophthalmic clinical practice. DED is frequently an underestimated condition causing a significant impact on visual function and quality of life. Many systemic autoimmune diseases (SAIDs) are related to moderate to severe DED. The main objective of this review is to enhance the awareness among ophthalmologists of the potential association of an underlying SAID in a high-risk patient with DED.

METHODS

An exhaustive literature search was performed in the National Library of Medicine's Pubmed, Scopus, Web of Science, and Google Scholar databases for all English language articles published until November 2021. The main keywords included "dry eye disease" associated with autoimmune, connective tissue, endocrine, gastrointestinal, hematopoietic, vascular, and pulmonary diseases. Case reports, series, letters to the editor, reviews, and original articles were included.

RESULTS

Although DED is frequently associated with SAIDs, its diagnosis is commonly delayed or missed, producing significant complications, including corneal ulceration, melting, scleritis, uveitis, and optic neuritis resulting in severe complications detrimental to visual function and quality of life. SAID should be suspected in a woman, 30 to 60 years old with a family history of autoimmunity, presenting with DED symptoms and extraocular manifestations including arthralgias, dry mouth, unexplained weight and hair loss, chronic fatigue, heat or cold intolerance, insomnia, and mood disorders.

CONCLUSIONS

Establishing the correct diagnosis and treatment of DED associated with SAIDs is crucial to avoid its significant burden and severe ocular complications.

Objective assessment of eyelid position and tear meniscus in facial nerve palsy

PURPOSE

To evaluate lower lid position and tear meniscus in peripheral idiopathic facial nerve palsy (FNP).

METHODS

A prospective study enrolled patients with peripheral idiopathic FNP and epiphora. Data were collected on patient demographics, House-Brackmann (HB) scale, digital photographs of the face, and tear meniscus at the 1st, 30, and 90 day after onset of FNP. Marginal reflex distance to the upper (MRD1) and lower eyelid (MRD2) were evaluated using ImageJ software. Anterior segment optical coherence tomography (OCT) was performed to measure the tear menis- cus. P< .05 was considered statistically significant.

RESULTS

Sixteen patients were evaluated. The HB scale at presentation was grade III in six patients (37.5%). At 90 day, nine patients (56.25%) were grade I-normal. Three (18.7%) had upper lid retraction, three (18.7%) upper eyelid asymmetry and 7 (43.75%), lower eyelid retraction. The difference between MRD2-FNP with MRD2-healthy side was 0.51 ± 1.9 mm at the 1st visit, decreasing to 0.09 ± 1.47 mm at 90 days (P= .877). Tear meniscus measurements were significantly higher in FNP at the 1st visit (P= .001). The decrease in MRD2 was statistically correlated with the reduction of the tear meniscus area (TMA) (r = 0.67; P= .007) at 90 days. No correlation was found between HB and TMA. There is a difference in TMA between age groups at the 1st day(p= .009). Eldest group had higher HB scales.

CONCLUSION

Quantitative evaluation of eyelid position and tear meniscus are effective to document the evolution of FNP and can serve as a clue of orbicularis recovery.

Anterior Segment Optical Coherence Tomography of Tear Film and Cornea in Systemic Lupus Erythematosus Patients

Purpose

To study tear film and corneal thickness measurements in systemic lupus erythematosus (SLE) patients compared to age-matched controls using anterior segment optical coherence tomography (AS-OCT).

Methods

This was a cross-sectional study. Study participants were divided into 3 groups: Group A: SLE patients with clinical dry eye, Group B: SLE patients without clinical dry eye and Group C: healthy controls. The lower tear meniscus parameters measured using AS-OCT were tear meniscus height (TMH), tear meniscus depth (TMD) and tear meniscus area (TMA). The central corneal and corneal epithelial thickness were automatically calculated.

Results

The study included 40 eyes in Group A, 60 in Group B, and 100 in Group C. Mean age was 26.9±6.6 years for Group A, 27.6±7.3 years for Group B and 35.7±9.2 years for Group C (p= 0.06). All subjects were females except for 1 male patient in Group A. Mean TMH, TMA and TMD in Group C were 487.7±185.6 µm, 0.068±0.040 mm², and 341.2±99.1 µm, respectively, which was significantly higher compared to Group A (225.5±27.9 µm, 0.018±0.004 mm² and 171.9±26.0 µm, respectively, all p < 0.001) and Group B (395.4±118.8 µm, p < 0.001; 0.05±0.04 mm², p=0.016 and 280.6±93.4 µm, p < 0.001, respectively). Group B eyes also had significantly higher parameters compared to Group A (all p < 0.001). Mean corneal and epithelial thickness in Group C were 501.6±37.5 µm and 53.3±4.5 µm, respectively, which was significantly higher compared to Group A (496.1±24.1 µm, p=0.044 and 49.5±3.5 µm, p < 0.001, respectively) and Group B (504.2±22.03 µm, p=0.046 and 47.5±5.6 µm, p < 0.001, respectively). Group B eyes also had a significantly higher corneal thickness (p=0.031) and epithelial thickness (p=0.011) compared to Group A.

Conclusion

We demonstrated significant reduction of tear meniscus dimensions, central corneal thickness and epithelial thickness in SLE patients compared to age-matched controls using AS-OCT.

Influence of Sodium Hyaluronate Concentration in Tear Meniscus Height: 10-min Dynamic Profile After Single Instillation

PURPOSE

To assess the height, area, and density of tear meniscus throughout 10 min after instillation of sodium hyaluronate (SH) of equal molecular weight at two different concentrations.

METHODS

Thirty-four eyes from 17 patients were enrolled in this longitudinal, nonrandomized, interventional and contralateral eye study. Tear meniscus height (TMH), corneal meniscus junction (CMJ), lower-lid meniscus junction (LLMJ), and tear meniscus area (TMA) images were obtained with the anterior segment module of the deep range imaging ocular coherence tomography ([DRI-OCT] Triton Swept-Source). Tear meniscus density (TMD) was calculated using the image processing and analysis software by Java (ImageJ program). Sodium hyaluronate artificial tears at 0.1% and 0.2% concentrations were instilled into all right and left eyes, respectively.

RESULTS

Patients' mean age was 61.05±11.43 years. Tear meniscus height, CMJ, LLMJ, and TMA measured at 1-, 5-, 7- and 10-min postinstillation of 0.1% SH proved significant differences among them (P<0.05). Sodium hyaluronate 0.2% instillation obtained similar findings, although no significant differences were found between 1- and 3-min postinstillation measurements (P>0.05). Fewer differences were found in TMD 0.2% SH group due to a lower baseline densitometry compared to the 0.1% group.

CONCLUSION

0.2% sodium hyaluronate achieved better TMH and TMA in 1 and 3 min after instillation than 0.1% concentration. However, there were no statistically significant differences between 0.1% and 0.2% sodium hyaluronate throughout a ten-minute longitudinal profile measurement using DRI-OCT.

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.

Novel Approaches for Imaging-Based Diagnosis of Ocular Surface Disease

Imaging has become indispensable in the diagnosis and management of diseases in the posterior part of the eye. In recent years, imaging techniques for the anterior segment are also gaining importance and are nowadays routinely used in clinical practice. Ocular surface disease is often synonymous with dry eye disease, but also refers to other conditions of the ocular surface, such as Meibomian gland dysfunction or keratitis and conjunctivitis with different underlying causes, i.e., allergies or infections. Therefore, correct differential diagnosis and treatment of ocular surface diseases is crucial, for which imaging can be a helpful tool. A variety of imaging techniques have been introduced to study the ocular surface, such as anterior segment optical coherence tomography, in vivo confocal microscopy, or non-contact meibography. The present review provides an overview on how these techniques can be used in the diagnosis and management of ocular surface disease and compares them to clinical standard methods such as slit lamp examination or staining of the cornea or conjunctiva. Although being more cost-intensive in the short term, in the long term, the use of ocular imaging can lead to more individualized diagnoses and treatment decisions, which in turn are beneficial for affected patients as well as for the healthcare system. In addition, imaging is more objective and provides good documentation, leading to an improvement in patient follow-up and education.

New Technologies in Clinical Trials in Corneal Diseases and Limbal Stem Cell Deficiency: Review from the European Vision Institute Special Interest Focus Group Meeting

To discuss and evaluate new technologies for a better diagnosis of corneal diseases and limbal stem cell deficiency, the outcomes of a consensus process within the European Vision Institute (and of a workshop at the University of Cologne) are outlined. Various technologies are presented and analyzed for their potential clinical use also in defining new end points in clinical trials. The disease areas which are discussed comprise dry eye and ocular surface inflammation, imaging, and corneal neovascularization and corneal grafting/stem cell and cell transplantation. The unmet needs in the abovementioned disease areas are discussed, and realistically achievable new technologies for better diagnosis and use in clinical trials are outlined. To sum up, it can be said that there are several new technologies that can improve current diagnostics in the field of ophthalmology in the near future and will have impact on clinical trial end point design.

Deep learning segmentation for optical coherence tomography measurements of the lower tear meniscus

The tear meniscus contains most of the tear fluid and therefore is a good indicator for the state of the tear film. Previously, we used a custom-built optical coherence tomography (OCT) system to study the lower tear meniscus by automatically segmenting the image data with a thresholding-based segmentation algorithm (TBSA). In this report, we investigate whether the results of this image segmentation algorithm are suitable to train a neural network in order to obtain similar or better segmentation results with shorter processing times. Considering the class imbalance problem, we compare two approaches, one directly segmenting the tear meniscus (DSA), the other first localizing the region of interest and then segmenting within the higher resolution image section (LSA). A total of 6658 images labeled by the TBSA were used to train deep convolutional neural networks with supervised learning. Five-fold cross-validation reveals a sensitivity of 96.36% and 96.43%, a specificity of 99.98% and 99.86% and a Jaccard index of 93.24% and 93.16% for the DSA and LSA, respectively. Average segmentation times are up to 228 times faster than the TBSA. Additionally, we report the behavior of the DSA and LSA in cases challenging for the TBSA and further test the applicability to measurements acquired with a commercially available OCT system. The application of deep learning for the segmentation of the tear meniscus provides a powerful tool for the assessment of the tear film, supporting studies for the investigation of the pathophysiology of dry eye-related diseases.