Application of Keratograph and Fourier-Domain Optical Coherence Tomography in Measurements of Tear Meniscus Height

Application of optical coherence tomography and keratograph in the measurements of lower lid margin thickness

PURPOSE

This study aims to investigate the applicability of lower lid margin thickness (LLMT) measurements in adults with and without meibomian gland dysfunction (MGD) by optical coherence tomography (OCT) and keratograph.

METHODS

This is a cross-sectional, observational study. A hundred and eight volunteers aged 20 to 79, including 68 MGD patients and 40 normal subjects, were recruited. Using OCT and keratograph to measure the LLMT from the posterior lash line to anterior edge or outer edge of the tear meniscus was separately performed two times by the same person.

RESULTS

The mean age of normal and MGD subjects was 50.5 ± 14.2 years and 55.8 ± 15.5 years, respectively. The LLMT with OCT and keratograph in MGD patients was significantly greater than that in normal subjects (1.06 ± 0.27 and 1.03 ± 0.25 mm vs. 0.90 ± 0.20 and 0.86 ± 0.16 mm, respectively). In both normal and MGD subjects, the tear meniscus height and LLMT with OCT were both greater than that with keratograph (P < 0.05), and intraclass correlation coefficient (ICC) demonstrated a good agreement in the LLMT measurements between two devices (ICC = 0.83 and 0.79, respectively). Additionally, the LLMT in MGD patients was appeared to be positively correlated with meiboscore (rs = 0.37, P = 0.002).

CONCLUSIONS

The OCT and keratograph were two reliable tools in the LLMT measurements, which may have potential applications for diagnosis and evaluation of MGD. Furthermore, we found that the LLMT measured by OCT was greater than that measured by keratograph.

Promising High-Tech Devices in Dry Eye Disease Diagnosis

BACKGROUND

Dry eye disease (DED) is a common and debilitating condition that affects millions of people worldwide. Despite its prevalence, the diagnosis and management of DED can be challenging, as the condition is multifactorial and symptoms can be nonspecific. In recent years, there have been significant advancements in diagnostic technology for DED, including the development of several new devices.

METHODS

A literature review of articles on the dry eye syndrome and innovative diagnostic devices was carried out to provide an overview of some of the current high-tech diagnostic tools for DED, specifically focusing on the TearLab Osmolarity System, DEvice Hygrometer, IDRA, Tearcheck, Keratograph 5M, Cornea Dome Lens Imaging System, I-PEN Osmolarity System, LipiView II interferometer, LacryDiag Ocular Surface Analyzer, Tearscope-Plus, and Cobra HD Camera.

CONCLUSIONS

Despite the fact that consistent use of these tools in clinical settings could facilitate diagnosis, no diagnostic device can replace the TFOS algorithm.

Detecting dry eye from ocular surface videos based on deep learning

OBJECTIVE

To assess the performance of convolutional neural networks (CNNs) for automated diagnosis of dry eye (DE) in patients undergoing video keratoscopy based on single ocular surface video frames.

DESIGN

This retrospective cohort study included 244 ocular surface videos from 244 eyes of 244 subjects based on corneal topography. A total of 116 eyes were normal while 128 eyes had DE based on clinical evaluations.

METHODS

We developed a deep transfer learning model to directly identify DE from ocular surface videos. We evaluated the performance of the CNN model based on objective accuracy metrics. We assessed the clinical relevance of the findings by evaluating class activations maps.

MAIN OUTCOME MEASURE

Area under the receiver operating characteristics curve (AUC), accuracy, specificity, and sensitivity.

RESULTS

The AUC of the model for discriminating normal eyes from eyes with DE was 0.98. Network activation maps suggested that the lower paracentral cornea was the most important region for detection of DE by the CNN model.

CONCLUSIONS

Deep transfer learning achieved a high diagnostic accuracy in detecting DE based on non-invasive ocular surface videos at levels that may prove useful in clinical practice.

Agreement of Tear Break-up Time and Meniscus Height between Medmont E300 and Visionix VX120+

The goal of this study was to analyze the agreement between the Medmont E300 and the Visionix VX120+ systems in terms of non-invasive tear break-up time (NIBUT) and tear meniscus height (TMH) measurements. A total of 60 eyes (30 healthy subjects) were enrolled. NIBUT and TMH were evaluated with Medmont E300; first NIBUT, NIBUT50%, and TMH were evaluated with Visionix VX120+. Both evaluations were performed in a random order by the same clinician for right, left, and both eyes. The Medmont E300 provided significantly higher NIBUT than Visionix VX120+ for first NIBUT in right, left, and both eyes (p ≤ 0.003) and NIBUT50% in left and both eyes (p ≤ 0.042). The TMH measured with VX120+ was significantly higher than with Medmont E300 considering both eyes (p = 0.037). No significant correlations were found between both devices for either NIBUT (p ≥ 0.11) or TMH (p ≥ 0.09). Passing–Bablok regression analyses revealed poor agreement between devices for NIBUT and TMH outcomes. VX120+ is expected to provide substantial lower first NIBUT values than the NIBUT measured by Medmont E300. Clinicians should consider not using both instruments as interchangeable for dry eye diagnosis.