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. 2019 May 9;14(5):e0215130.
doi: 10.1371/journal.pone.0215130. eCollection 2019.

"Smart Eye Camera": An innovative technique to evaluate tear film breakup time in a murine dry eye disease model

Eisuke Shimizu  1   2 , Yoko Ogawa  1 , Hiroyuki Yazu  1   2   3 , Naohiko Aketa  1   2 , Fan Yang  1   4 , Mio Yamane  1 , Yasunori Sato  5 , Yutaka Kawakami  6 , Kazuo Tsubota  1
Affiliations

"Smart Eye Camera": An innovative technique to evaluate tear film breakup time in a murine dry eye disease model

Eisuke Shimizu et al. PLoS One. .

Abstract

Tear film breakup time (TFBUT) is an essential parameter used to diagnose dry eye disease (DED). However, a robust method for examining TFBUT in murine models has yet to be established. We invented an innovative device, namely, the "Smart Eye Camera", which addresses several problems associated with existing methods and is capable of evaluating TFBUT in a murine DED model. We compared images taken by existing devices and the Smart Eye Camera in a graft-versus-host disease-related DED murine model. We observed that the quality of the images obtained by the Smart Eye Camera were sufficient for practical use. Moreover, this new technique could be used to obtain measurements for several consecutive ocular phenotypes in a variety of environments. Here, we demonstrate the effectiveness of our new invention in the examination of ocular phenotypes, including TFBUT in a murine model. We highlight the potential for future translational studies adopting the Smart Eye Camera in clinical settings.

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Conflict of interest statement

Patent applied by OUI Inc. (Smart Eye Camera, PCT/JP2019/002824. Inventors ES, HY, and AN. Tokyo, Japan). There are no other relevant declarations relating this patent. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The other authors declare no competing interest associated with this manuscript.

Figures

Fig 1
Fig 1. The appearance of Smart Eye Camera and representative photo.
(A) This invention is a portable attachment for smartphones. The current model was designed for the iPhone 7, which contains a convex macro lens and blue filter. (B) The upper row shows representative photos of the eye to which white light has been applied. The lower row shows fluorescein stained images. The left column images were taken by the existing techniques. The right column images were taken by the Smart Eye Camera.
Fig 2
Fig 2. Changes in the tear secretion ratio compared to the baseline.
(A) Consecutive changes in tear secretion (TS) according to group (green: normal group, blue: non-GVHD group, and red: GVHD group). (B) The table shows the TS ratio compared to the baseline (8 weeks of age). Significant differences in TS were observed between the normal and the non-GVHD group and between the normal and the GVHD group from 9 to 12 weeks of age. Furthermore, at 12 weeks of age, TS was significantly decreased in the GVHD group compared to that in the non-GVHD group. N = 5 per group. P < 0.05, Tukey's multiple comparison test.
Fig 3
Fig 3. Changes in the tear film breakup time ratio compared to the baseline recorded by the Smart Eye Camera.
(A) consecutive tear film breakup time (TFBUT) according to group (green: normal group, blue: non-GVHD group, and red: GVHD group). (B) The table shows the TFBUT ratio compared to that at the baseline (8 weeks of age). Significant differences in TFBUT were observed between the normal and GVHD groups from 9 to 12 weeks of age and between the non-GVHD and GVHD groups from 10 to 12 weeks of age. TFBUT was evaluated in the right eye (n = 5 per group. P < 0.05, Tukey's multiple comparison test).
Fig 4
Fig 4. Changes in the corneal fluorescein score ratio compared to the baseline recorded by the Smart Eye Camera.
(A) consecutive values for the corneal fluorescein score (CFS) according to group (green: normal group, blue: non-GVHD group, and red: GVHD group). (B) The table shows the CFS ratio compared to that at the baseline (8 weeks of age). Significant differences in CFS were observed between the normal and GVHD groups from 10 to 12 weeks of age and between the non-GVHD and GVHD groups at 11 and 12 weeks of age. CFS was evaluated in the right eye (n = 5 per group. P < 0.05, Tukey's multiple comparison test).
Fig 5
Fig 5. Comparison between the new and existing techniques.
(A) The left graph shows TFBUT and (B) the right graph shows CFS results (green: normal group, blue: non-GVHD group, and red: GVHD group). In each graph, the two bars side by side demonstrate that there were no significant differences between the use of existing technologies and the Smart Eye Camera in the normal, non-GVHD, and GVHD groups (TFBUT and CFS. all P > 0.05). (C) The table shows the numerical values (n = 5; paired t-test).
Fig 6
Fig 6. Correlation between the results of the Smart Eye Camera and existing device.
(A) The left graph shows TFBUT and (B) the right graph shows CFS results. In each graph, the Y axis shows the numbers evaluated by the Smart Eye Camera and X axis shows evaluations by the existing device. Strong correlations were observed in TFBUT (R = 0.868, 95% CI; 0.656–0.953) and CFS (R = 0.934, 95% CI; 0.823–0.976); n = 15; Lin’s Concordance Correlation Coefficient.
Fig 7
Fig 7. Tear film breakup pattern using the Smart Eye Camera.
The figure shows a set of continuous photos taken by the Smart Eye Camera. The upper row shows images from a GVHD-related dry eye disease model mouse. The tear film was breaking up in 3 s after blinking (Tear Film Breakup Time; TFBUT = 3 s). The lower row shows the normal mouse. The tear film was stabilized in 3 s and breaking up in 6 s after blinking (TFBUT = 6 s). Photos were of the right eye in 12 weeks of age.
See this image and copyright information in PMC

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