Classification of Tear Film Lipid Layer En Face Maps Obtained Using Optical Coherence Tomography and Their Correlation With Clinical Parameters. Issue 4 (21st April 2023)

• Record Type: Journal Article
• Authors: Stegmann, Hannes; Aranha Dos Santos, Valentin; Schmidl, Doreen; Garhöfer, Gerhard; Fard, Ali; Bagherinia, Homayoun; Schmetterer, Leopold; Werkmeister, René M.
• Is Part Of: Cornea. Volume 42:Issue 4(2023)
• Page Start: 490
• Page End: 497
• Publication Date: 2023-04-21
• Subjects: tear film -- tear film lipid layer -- lipid layer pattern -- lipid layer thickness -- optical coherence tomography -- reflectance; Cornea -- Periodicals; Cornea -- Periodicals; Cornée -- Périodiques; 617.719
• DOI: 10.1097/ICO.0000000000003172
• Languages: English
• ISSNs: 0277-3740

Abstract

Abstract : Supplemental Digital Content is Available in the Text. Abstract : Purpose: The purpose of this study was to investigate the correlation between the pattern of optical coherence tomography (OCT) en face maps of the tear film lipid layer (TFLL) and lipid layer thickness (LLT), fluorescein breakup time (FBUT), and Schirmer I test values in healthy subjects. Methods: Measurements from four clinical data sets were retrospectively analyzed, and TFLL patterns were classified into 3 categories: homogeneous (HOM), wavy (WAV), or dotted (DOT) appearance. Linear mixed model analyses were performed. Intraclass correlation coefficients and index of qualitative variation were computed to investigate interrater and intrasubject variabilities. Results: For the LLT, a significant difference between HOM and DOT ( P < 0.001, βHOMvsDOT = −6.42 nm) and WAV and DOT ( P = 0.002, βWAVvsDOT = −4.04 nm) was found. Furthermore, the difference between WAV and DOT regarding FBUT ( P < 0.001, βWAVvsDOT = −3.065 seconds) was significant, while no significant differences between any of the classes with respect to the Schirmer I test values were found. An intraclass correlation coefficient of 89.0% reveals a good interrater reliability, and an index of qualitative variation of 60.0% shows, on average, a considerable variability in TFLL pattern class for repeated measurements over 1 hour. Conclusions: A new classification method for OCT en face maps of the TFLL is presented. Significant differences between patterns were found with respect to LLT and FBUT. A dotted pattern on dark background appears to be the most stable type of TFLL. The analysis of OCT en face maps of the TFLL provides complimentary information to conventional imaging methods and might give new insights into the characteristics of the TFLL.