Infrared Imaging of Meibomian Glands and Evaluation of the Lipid Layer in Sjogren's Syndrome Patients and Nondry Eye Controls

Menzies, K. L., Srinivasan, S., Prokopich, C. L., & Jones, L. (2015). Infrared Imaging of Meibomian Glands and Evaluation of the Lipid Layer in Sjogren’s Syndrome Patients and Nondry Eye Controls. Investigative Ophthalmology & Visual Science, 56(2), 836–841. https://doi.org/10.1167/iovs.14-13864Purpose.: The purpose of this study was to evaluate meibomian gland dropout and lipid layer thickness (LLT) in patients with and without Sjögren's syndrome dry eye (SS). Methods.: We recruited 11 participants with SS (males/females [M/F], 1:10; mean age = 56.0 ± 9.1 years) and 10 control subjects without dry eye (M/F, 3:7; mean age = 58.5 ± 4.7 years). All participants completed the Ocular Surface Disease Index (OSDI) questionnaire. The LLT was assessed using the Tearscope Plus based on the appearance of the lipid layer. Noninvasive tear break-up time (NITBUT) also was measured. The lower and upper lids were everted, and the meibomian glands were imaged using the infrared camera of the Keratograph 4. A meibomian gland dropout score due to gland loss was obtained. Statistical analysis was conducted using the Mann-Whitney U test and correlations were determined using Spearman rank correlations. Results.: Of the SS participants, 100% reported ocular and oral dryness symptoms in the AECC questionnaire. The SS group recorded a higher OSDI score (median = 48.00, interquartile range [IQR] 23.0–56.2 vs. 2.1, IQR 0.0–2.6; P < 0.001), reduced LLT (median [IQR] = 15.0 [15.0–15.0] vs. 60.0 [45.0–100.0] nm; P = 0.001), and lower NITBUT (median [IQR] = 3.7 [2.5–4.2] vs. 9.5 [6.4–17.6] sec; P < 0.001) compared to the controls. Digital meibomian gland dropout score (% dropout) was significantly higher for the SS group (16.0% [IQR 12.1–40.0%] vs. 6.7% [IQR 1.5–12.7%]; P = 0.01). Subjective meibomian gland dropout score (0–6 score) was significantly higher for the SS group (median [IQR] = 1.5 [1.0–4.0] vs. 1.0 [0.0–1.25]; P = 0.03). Conclusions.: Patients with SS showed higher meibomian gland dropout scores and reduced LLT and NITBUT, which likely contribute to the severe dry eye symptoms reported by SS subjects

A clinical utility assessment of the automatic measurement method of the quality of Meibomian glands

No outside funding was received for this study., This research was supported by grants from the Medical University of Silesia in Katowice, Grant No. KNW-1-023/N/6/0; the National Natural Science Foundation of China (31600758); Beijing Natural Science Foundation (7174287); the priming scientific research foundation for the junior researcher in Beijing Tongren Hospital, Capital Medical University (2015-YJJZZL- 008) and Beijing Key Laboratory of Ophthalmology and Visual Science (2016YKSJ02).Background: Meibomian gland dysfunction (MGD) is one of the most common diseases observed in clinics and is the leading cause of evaporative dry eye. Today, diagnostics of MGD is not fully automatic yet and is based on a qualitative assessment made by an ophthalmologist. Therefore, an automatic analysis method was developed to assess MGD quantiatively. Materials: The analysis made use of 228 images of 57 patients recorded by OCULUS Keratograph® 5 M with a resolution of 1024 × 1360 pixels concern 30 eyes of healthy individuals (14 women and 16 men) and 27 eyes of sick patients (10 women and 17 men). The diagnosis of dry eye was made according to the consensus of DED in China (2013). Methods: The presented method of analysis is a new, developed method enabling an automatic, reproducible and quantitative assessment of Meibomian glands. The analysis relates to employing the methods of analysis and image processing. The analysis was conducted in the Matlab environment Version 7.11.0.584, R2010b, Java VM Version: Java 1.6.0_17-b04 with Sun Microsystems Inc. with toolboxes: Statistical, Signal Processing and Image Processing. Results: The presented, new method of analysis of Meibomian glands is fully automatic, does not require operator's intervention, allows obtaining reproducible results and enables a quantitative assessment of Meibomian glands. Compared to the other known methods, particularly with the method described in literature it allows obtaining better sensitivity (98%) and specificity (100%) results by 2%.Medical University of Silesia in Katowice; National Natural Science Foundation of China; Natural Science Foundation of Beijing Municipalit

Meibomian Gland Morphology: The Influence of Structural Variations on Gland Function and Ocular Surface Parameters

Purpose: To objectively and quantitatively characterize meibomian gland morphology and to investigate the influence of morphological variations on gland function and ocular surface and tear film parameters. Methods: One hundred fifty subjects were enrolled. The examinations included tear osmolarity, tear meniscus height, bulbar conjunctival hyperemia, noninvasive tear film breakup time, lid margin thickness, foam secretion, meibomian gland expressibility, count of functioning glands, corneal and conjunctival staining, fluorescein breakup time, lid wiper epitheliopathy, and Schirmer test. Patient symptoms were assessed using the Ocular Surface Disease Index questionnaire. Images from noncontact meibography were analyzed using an automated method that objectively estimates dropout area, number of glands, gland length and width, and gland irregularity. Results: Gland irregularity highly correlated with dropout area (r = −0.4, P < 0.001) and showed significant partial correlations with fluorescein breakup time (r = 0.162, P = 0.049) and the Ocular Surface Disease Index questionnaire (r = −0.250, P = 0.002) Subjects with dropout area <32% were divided into 2 groups: high and low irregularity. Gland expressibility was statistically significantly different between the 2 groups (U = 319.5, P = 0.006). In the high irregularity group, gland irregularity correlated with the Schirmer test (r = 0.530, P = 0.001) and corneal fluorescein staining (r = −0.377, P = 0.021). Conclusions: Automated morphological analysis of meibomian gland structure provides additional quantitative and objective information regarding gland morphology. The link between dropout area and gland function is not clear. Assessment of gland irregularity might better predict gland function and its effects on ocular surface and tear film parameters

A Comprehensive Review on Dry Eye Disease: Diagnosis, Medical Management, Recent Developments, and Future Challenges

Dry eye syndrome (DES) or keratoconjunctivitis sicca (KCS) is a common disorder of the tear film caused by decreased tear production or increased evaporation and manifests with a wide variety of signs and symptoms. The present review from interpretation of the literature gives detailed information on the prevalence, definition, causes, diagnostic tests, and medical management of dry eye disease. A number of systems contribute to the physiological integrity of the ocular surface and disruption of system may or may not produce symptoms. Therefore accurate diagnosis of dry eyes with no or minimal disruption of physiological function is necessary. The paper also discusses different colloidal drug delivery systems and current challenges in the development of topical ophthalmic drug delivery systems for treatment of KCS. Due to the wide prevalence and number of factors involved, newer, more sensitive diagnostic techniques and novel therapeutic agents have been developed to provide ocular delivery systems with high therapeutic efficacy. The aim of this review is to provide awareness among the patients, health care professionals, and researchers about diagnosis and treatment of KCS and recent developments and future challenges in management of dry eye disease

Development of Novel Diagnostic Tools for Dry Eye Disease using Infrared Meibography and In Vivo Confocal Microscopy

Dry eye disease (DED) is a multifactorial disease of the ocular surface where tear film instability, hyperosmolarity, neurosensory abnormalities, meibomian gland dysfunction, ocular surface inflammation and damage play a dedicated etiological role. Estimated 5 to 50% of the world population in different demographic locations, age and gender are currently affected by DED. The risk and occurrence of DED increases at a significant rate with age, which makes dry eye a major growing public health issue. DED not only impacts the patient’s quality of vision and life, but also creates a socio-economic burden of millions of euros per year. DED diagnosis and monitoring can be a challenging task in clinical practice due to the multifactorial nature and the poor correlation between signs and symptoms. Key clinical diagnostic tests and techniques for DED diagnosis include tearfilm break up time, tear secretion – Schirmer’s test, ocular surface staining, measurement of osmolarity, conjunctival impression cytology. However, these clinical diagnostic techniques are subjective, selective, require contact, and are unpleasant for the patient’s eye. Currently, new advances in different state-of-the-art imaging modalities provide non-invasive, non- or semi-contact, and objective parameters that enable objective evaluation of DED diagnosis. Among the different and constantly evolving imaging modalities, some techniques are developed to assess morphology and function of meibomian glands, and microanatomy and alteration of the different ocular surface tissues such as corneal nerves, immune cells, microneuromas, and conjunctival blood vessels. These clinical parameters cannot be measured by conventional clinical assessment alone. The combination of these imaging modalities with clinical feedback provides unparalleled quantification information of the dynamic properties and functional parameters of different ocular surface tissues. Moreover, image-based biomarkers provide objective, specific, and non / marginal contact diagnosis, which is faster and less unpleasant to the patient’s eye than the clinical assessment techniques. The aim of this PhD thesis was to introduced deep learning-based novel computational methods to segment and quantify meibomian glands (both upper and lower eyelids), corneal nerves, and dendritic cells. The developed methods used raw images, directly export from the clinical devices without any image pre-processing to generate segmentation masks. Afterward, it provides fully automatic morphometric quantification parameters for more reliable disease diagnosis. Noteworthily, the developed methods provide complete segmentation and quantification information for faster disease characterization. Thus, the developed methods are the first methods (especially for meibomian gland and dendritic cells) to provide complete morphometric analysis. Taken together, we have developed deep learning based automatic system to segment and quantify different ocular surface tissues related to DED namely, meibomian gland, corneal nerves, and dendritic cells to provide reliable and faster disease characterization. The developed system overcomes the current limitations of subjective image analysis and enables precise, accurate, reliable, and reproducible ocular surface tissue analysis. These systems have the potential to make an impact clinically and in the research environment by specifying faster disease diagnosis, facilitating new drug development, and standardizing clinical trials. Moreover, it will allow both researcher and clinicians to analyze meibomian glands, corneal nerves, and dendritic cells more reliably while reducing the time needed to analyze patient images significantly. Finally, the methods developed in this research significantly increase the efficiency of evaluating clinical images, thereby supporting and potentially improving diagnosis and treatment of ocular surface disease

Evaluación de la estructura de las glándulas de meibomio mediante tecnología infrarroja

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Óptica y Optometría, Departamento de Optometría y Visión, leída el 26/06/2019Dry eye disease (DED) is a multifactorial disease of the ocular surface considered one of the most frequently encountered ocular conditions seen by eye care practitioners. Nowadays, DED is estimated to affect between 5 − 50% of the worldwide population. Furthermore, the prevalence of DED increases linearly with age which makes DED a growing public health concern as the global population of older people is expected to be more than double its current amount by 2050. According to DED classification, the aqueous deficient dry eye (ADDE) and evaporative dry eye (EDE) are the two major DED types and are considered to exist on a continuum rather than as separate entities. Despite this, according to the current DED understanding, an evaporative component is more common than an ADDE component. Currently, the Meibomian gland dysfunction (MGD) is considered the leading cause of EDE. This condition may result in alteration of the tear film, symptoms of eye irritation, clinically apparent inflammation and ocular surface disease. Therefore, any change that occurs in the morphology of the MG or in its secretion has an important clinical impact...El ojo seco o síndrome de ojo seco (SOS) es una enfermedad multifactorial de la superficie ocular considerada como una de las afecciones oculares más frecuentes observadas por los profesionales de la visión en la práctica clínica. Hoy en día, se estima que el SOS afecta al 5-50% de la población mundial. Además, su prevalencia aumenta linealmente con la edad, lo que hace que el SOS sea un problema de salud pública creciente, ya que se espera un aumento del doble de la población mundial de personas ancianas para 2050. Según la clasificación del SOS, se pueden distinguir principalmente dos tipos: el ojo seco acuodeficiente, caracterizado por un déficit en la capa acuosa de la película lagrimal y el ojo seco evaporativo, el cual se caracteriza por una alteración en la evaporación de esta. A pesar de esta diferenciación, recientemente se ha observado que ambos tipos de SOS pueden coexistir simultáneamente, aunque el componente evaporativo tiende a ser el más común. Actualmente, la disfunción de las glándulas de meibomio (DGM) se considera la causa principal de la SOS evaporativo. Esta condición puede provocar alteración de la película lagrimal, síntomas de irritación ocular, inflamación clínicamente aparente y enfermedad de la superficie ocular. Por lo tanto, cualquier cambio que se produzca en la morfología o en la secreción de las glándulas puede tener un impacto clínico importante...Zespół suchego oka (ZSO) jest wieloczynnikowym schorzeniem powierzchni ocznej i jedną z najczęściej obserwowanych w praktyce klinicznej dolegliwości okulistycznych. Obecnie szacuje się, że ZSO dotyka od 5 do 50% światowej populacji. Ponadto, zachorowalność na ZSO wzrasta liniowo z wiekiem. Szacuje się, iż populacja osób starszych ulegnie do 2050 roku podwojeniu, przez co ZSO może stać się znaczącym problem zdrowia publicznego. Zgodnie z przyjętą ogólnie klasyfikacją, podtyp ZSO związany z niedostatecznym wydzielaniem warstwy wodnej filmu łzowego (ang. aqueous deficient) oraz podtyp związany z nadmiernym jego parowaniem (ang. evaporative) są dwoma najbardziej powszechnymi rodzajami ZSO, które nierzadko są współistniejące. Badania naukowe pokazują, że ZSO spowodowane zwiększonym parowaniem łez występuje częściej niż pozostałe typy. Obecnie uważa się, że za ten podtyp odpowiada w dużej mierze dysfunkcja gruczołów Meiboma (ang. Meibomian gland dysfunction, MGD). Dysfunkcja ta powoduje zaburzenia filmu łzowego, podrażnienie, stan zapalny i chorobę powierzchni oka. Stąd też, każda zmiana zachodząca w morfologii gruczołów Meiboma lub w ich zdolności wydzielniczej ma duże znaczenie kliniczne...Fac. de Óptica y OptometríaTRUEunpu