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Cornea. 2016 Nov;35 Suppl 1:S38-S48.

Noninvasive Dry Eye Assessment Using High-Technology Ophthalmic Examination Devices.

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1
*Department of Ophthalmology, Ehime Prefectural Central Hospital, Matsuyama, Ehime, Japan; †Department of Ophthalmology, Ehime University School of Medicine, Toon, Ehime, Japan; and ‡Hanamizuki Eye Clinic, Matsuyama, Ehime, Japan.

Abstract

Recently, the number of dry eye cases has dramatically increased. Thus, it is important that easy screening, exact diagnoses, and suitable treatments be available. We developed 3 original and noninvasive assessments for this disorder. First, a DR-1 dry eye monitor was used to determine the tear meniscus height quantitatively by capturing a tear meniscus digital image that was analyzed by Meniscus Processor software. The DR-1 meniscus height value significantly correlated with the fluorescein meniscus height (r = 0.06, Bland-Altman analysis). At a cutoff value of 0.22 mm, sensitivity of the dry eye diagnosis was 84.1% with 90.9% specificity. Second, the Tear Stability Analysis System was used to quantitatively measure tear film stability using a topographic modeling system corneal shape analysis device. Tear film stability was objectively and quantitatively evaluated every second during sustained eye openings. The Tear Stability Analysis System is currently installed in an RT-7000 autorefractometer and topographer to automate the diagnosis of dry eye. Third, the Ocular Surface Thermographer uses ophthalmic thermography for diagnosis. The decrease in ocular surface temperature in dry eyes was significantly greater than that in normal eyes (P < 0.001) at 10 seconds after eye opening. Decreased corneal temperature correlated significantly with the tear film breakup time (r = 0.572; P < 0.001). When changes in the ocular surface temperature of the cornea were used as indicators for dry eye, sensitivity was 0.83 and specificity was 0.80 after 10 seconds. This article describes the details and potential of these 3 noninvasive dry eye assessment systems.

PMID:
27661073
DOI:
10.1097/ICO.0000000000000993
[Indexed for MEDLINE]

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