Screening Evaporative Dry Eyes Severity Using an Infrared Image

Qing Zhang; Yi Wu; Yilin Song; Guanghao Qin; Lanting Yang; Sumeet Singh Talwar; Tiezhu Lin; Gagan Deep Singh Talwar; Hongda Zhang; Ling Xu; Jonathan E Moore; Emmanuel Eric Pazo; Wei He

doi:10.1155/2021/8396503

Screening Evaporative Dry Eyes Severity Using an Infrared Image

J Ophthalmol. 2021 Aug 24:2021:8396503. doi: 10.1155/2021/8396503. eCollection 2021.

Authors

Qing Zhang^{1

2}, Yi Wu^{1

2}, Yilin Song^{1

2}, Guanghao Qin^{1

2}, Lanting Yang^{1

2}, Sumeet Singh Talwar³, Tiezhu Lin^{1

4}, Gagan Deep Singh Talwar³, Hongda Zhang¹, Ling Xu¹, Jonathan E Moore⁵, Emmanuel Eric Pazo¹, Wei He¹

Affiliations

¹ He Eye Specialist Hospital, No. 128 North Huanghe Street, Shenyang, China.
² The Second Affiliated Hospital of Dalian Medical University, Dalian, China.
³ Tianjin Medical University, Tianjin, China.
⁴ Wenzhou Medical University, Jiaxing, China.
⁵ Cathedral Eye Clinic, 89-91 Academy Street, Belfast, UK.

Abstract

Background: Dry eye disease (DED) is a multifactorial and one of the most common problems treated in an ophthalmic outpatient clinic. Due to the variability in presentation, diagnosis of DED consists of a combination of subjective and objective clinical tests. The purpose of this study was to assess the effectiveness of a handheld smartphone-based infrared thermal (IRT) camera for screening symptomatic evaporative DED.

Methods: This observational sex-matched control study assessed IRT images of 184 right eyes (46 normal and 138 DED) of 184 participants. Evaporative DED was assessed using noninvasive tear breakup time, fluorescein staining, and the Chinese version of the ocular surface disease index (C-OSDI) questionnaire and categorized into their respective dry eye symptomology group (none, mild, moderate, or severe). The ocular surface temperature (OST) at 8 anatomical regions of interest (ROI) (nasal conjunctiva, nasal limbus, nasal cornea, central cornea, inferior cornea, temporal limbus, temporal cornea, and temporal conjunctiva) were measured and compared using a handheld smartphone-based IRT camera. The effectiveness of these 8 ROIs OST in detecting varying severity of DED was evaluated in terms of correlations with severity of DED and their area under the curve (AUC).

Results: OST at the 8 anatomical ROI was significantly higher in DED participants than in the non-DED group (p < 0.05) except for inferior cornea, temporal limbus, and temporal conjunctival regions (>0.05). Analyzing 8 anatomical ROIs revealed that the nasal limbus had the highest Pearson correlation with the severity of DED (0.64, p < 0.001). Additionally, the nasal limbus ROI achieved the highest AUC of 0.79 (CI: 0.73-0.85; p < 0.05), sensitivity, and specificity (0.96 and 0.91) when comparing its ability to discriminated DED vs. non-DED eyes.

Conclusions: Rather than a diagnostic tool, handheld smartphone-based IRT images can be considered as a rapid, noninvasive, and hygienic screening tool in discriminating DED and non-DED and potentially alleviating inconvenience experienced during conventional tests.