Standardized Three-Dimensional Lateral Distraction Test: Its Reliability to Assess Medial Canthal Tendon Laxity


引用 13|浏览4
Background Assessment of MCT laxity is critical to the surgery options. Our study aimed to analyze the reliability of measuring medial canthal tendon (MCT) laxity by using a novel standardized three-dimensional lateral distraction test (3D-LDT). Methods Forty-eight Caucasian volunteers (25 males and 23 females, 96 eyes) between 22 and 84 years of age (55.6 ± 18.6 years old) were included in our study. From a neutral position, the lower eyelid was gently pulled laterally along a horizontal line to define the most distracted position of the lower punctum. Both in the neutral and distracted position, standardized 3D images were acquired for each subject by two observers, and each image were measured twice by two raters. Four landmarks and six corresponding linear measurements were evaluated for intra-rater, inter-rater, and inter-method reliability. Results Intra-rater, inter-rater and inter-method reliability analyses of 3D-LDT revealed an intraclass correlation of more than 95%, a mean absolute difference of less than 1 mm, and a technical error of measurement of less than 1 mm. Measurements of relative error (2.59–12.04%) and relative technical error (1.83–16.05%) for the inter-landmarks distance from pupil center to the lower punctum were higher than those from limbus nasal center to the lower punctum (6.13–30.39 and 4.34–26.85%, respectively). Conclusions This study provided high reliability of the three-dimensional lateral distraction test (3D-LDT) for assessing medial canthal tendon (MCT) laxity, which were never evaluated by digital imaging system. Level of Evidence IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors .
Medial canthal tendon laxity, Lateral distraction test, Three dimensional stereophotogrammetry, Reliability, Eyelid
AI 理解论文