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Young-Sik Yoo, Yong Soo Byon, Choun-Ki Joo, Geunyoung Yoon; Evaluation for Dropout Lesions on Infrared Meibography Using Optical Coherence Tomography Meibography. Invest. Ophthalmol. Vis. Sci. 2016;57(12):No Pagination Specified.
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© ARVO (1962-2015); The Authors (2016-present)
The aim of this study was to evaluate the actual structure of the dropout lesion on two dimensional infrared (IR) meibography in dry eye associated with meibomian gland dysfunction (MGD) using three dimensional optical coherence tomography (OCT) meibography.
This study included patients who had dry eye with MGD without any previously ocular disease. The dropout lesions on the IR images were finally enrolled to this study. Three dimensional OCT meibography was performed with the dropout lesion on the IR image as the center. The OCT images were classified according to the state of acina and ducts at the meibomian glands.
115 eyes of 64 subjects had 274 dropout lesions on their meibomian glands. At the IR images, 52 (45.22 %), 25 (21.74 %), 23 (20 %), 15 (13.04%) were located at cetral, nasal, lateral and overall lesions of eyelids, respectively. 35 (30.43 %), 10 (8.70 %), 39 (33.91 %), 15 (13.04%) were located at near lid margin, middle of eyelid, near conjunctival fornix, respectively. On the analysis of OCT images, the dropout lesions were divided into three gropus (Group A; Normal, B; Constricted or Atropic acina, C; No acina). 68.18 % (15/22), 43.48 % (30/69), 29.17 % (7/24) of group A, B, and C was found in the cetral lesion of eyelid, respectively. 0 % (0/15), 73.33 % (11/15), 26.67 % (4/15) was found in cases of dropouts located at overall eyelid. Some cases (5/87, 5.75 %) showed normal structure on IR images showed small size of anica or dilated duct on OCT images and BUT was 4.21 ± 2.12 seconds and Schirmer test was 7.35 ± 3.25 mm.
OCT images provided the detailed information for ania and duct on dropout lesions at the meibomian glands than IR images. OCT meibography may be a useful tool for diagnosis and management of dry eye with MGD.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
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