June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Layer by layer measurement of tear film and its association with clinical signs and symptoms in patients with dry eye and meibomian gland dysfunction
Author Affiliations & Notes
  • Reiko Arita
    Ophthalmology, Ito Clinic, Saitama, Saitama, Japan
  • Takahiro Imanaka
    Ophthalmology Innovation Center, Santen Pharmaceutical Co. Ltd., Japan
  • Gaku Takeuchi
    Research & Development Division, Topcon Corporation, Japan
  • Takashi Yuasa
    Ophthalmology Innovation Center, Santen Pharmaceutical Co. Ltd., Japan
  • Kiyofumi Sasai
    Product Development, Santen Pharmaceutical Co. Ltd., Japan
  • Masatsugu Nakamura
    Product Development, Santen Pharmaceutical Co. Ltd., Japan
  • Masahiro Akiba
    Research & Development Division, Topcon Corporation, Japan
  • Footnotes
    Commercial Relationships   Reiko Arita TOPCON, Code P (Patent), KOWA, Code P (Patent); Takahiro Imanaka Santen, Code E (Employment); Gaku Takeuchi TOPCON, Code E (Employment); Takashi Yuasa Santen, Code E (Employment); Kiyofumi Sasai Santen, Code E (Employment); Masatsugu Nakamura Santen, Code E (Employment); Masahiro Akiba TOPCON, Code E (Employment)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 1524 – A0249. doi:
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    • Get Citation

      Reiko Arita, Takahiro Imanaka, Gaku Takeuchi, Takashi Yuasa, Kiyofumi Sasai, Masatsugu Nakamura, Masahiro Akiba; Layer by layer measurement of tear film and its association with clinical signs and symptoms in patients with dry eye and meibomian gland dysfunction. Invest. Ophthalmol. Vis. Sci. 2022;63(7):1524 – A0249.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The purpose of this study was to assess the quantified parameters by Tear Film Imager (TFI), a new technology that enables quantification of the lipid and muco-aqueous layer thicknesses of the tear film on the cornea with a nanometer resolution developed by AdOM (Israel) and compare the clinical parameters from conventional ophthalmic examinations and other commercially available interferometry devices.

Methods : Patients with dry eye (DE), meibomian gland dysfunction (MGD), and non-DE/MGD were enrolled at Itoh Clinic (Saitama, Japan) from February 2020 to January 2021. Quantified outputs from TIF were as follows: Lipid Layer Thickness (LLT), Muco-Aqueous Layer Thickness (MALT), MALT Rate of change (MALTR), and Lipid Break Up Time (LBUT). Two other interferometry devices, LipiView2 (Johnson & Johnson Vision, CA, USA) and DR-1α (Kowa, Nagoya, Japan), were used for comparison. Correlation analysis was conducted with these TFI values and the following clinical signs: lid margin abnormalities, fluorescein staining score, meiboscore, fluorescein tear breakup time (BUT), Schirmer's test, the Standard Patient Evaluation of Eye Dryness (SPEED) questionnaire score, Dry Eye related Quality of life Score (DEQS), LLT measured by LipiView2, and interferometric patterns and noninvasive BUT measured by DR-1α. Each patient had one or several study visits. Baseline and changes from baseline values were analyzed.

Results : Twenty-eight patients (8 DE, 13 MGD, and 7 non-DE/MGD) participated in this study. The baseline values of TFI, LipiView2, and DR-1α were correlated with different clinical parameters. The LLT of TFI and LipiView2 showed correlation with lid margin abnormalities: Plugging and Vascularity scores (R=-0.42, -0.43). LBUT and MALTR correlated with Schirmer (R=0.47, -0.46). In correlation with changes, many TFI values showed higher correlation than those of LipiView2 and DR-1α, especially with the questionnaire scores. The correlation coefficients of MALTR and LBUT with SPEED score were 0.59 and -0.50.

Conclusions : TFI can measure the time variation of the thickness of the lipid and aqueous layers separately, and shows good correlation with key DE and MGD parameters. These results suggest that TFI might be useful for objective quantification of the signs and symptoms of DE or MGD, and for treatment monitoring.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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