Glass, Lora R. Dagi

Purpose: To morphologically describe and mathematically quantify a novel clinical feature of thyroid eye disease (TED). Methods: A retrospective study was conducted of TED patients and age-sex-matched normal controls. The arched Rainbow Brow appearance in TED patients was determined by unanimous agreement of 3 oculoplastic surgeons. Eyebrow curvature was assessed by plotting 15 points along the eyebrow in ImageJ. The fourth-degree polynomial (y = ax4 + bx3 + cx2 + dx + e) was fitted to each eyebrow. Results: Two hundred seventy-one eyes were analyzed (200 TED and 71 age-sex-matched normal controls). A Rainbow Brow was identified in 42% of TED patients. A unilateral Rainbow Brow was seen in 15% of patients. The fourth-degree polynomial coefficients yielded significant differences between Rainbow Brow patients and age-sex-matched normal controls for the coefficients a, b, c, and d. Similar analysis of TED patients with and without a Rainbow Brow showed differences in coefficients a and b. Age >50 years (p = 0.009) and the presence of brow fat expansion (p < 0.001) were associated with the presence of a Rainbow Brow. Proptosis >24 mm showed a trend toward association with the presence of a Rainbow Brow (p = 0.057). When considering the contribution of these features in a multivariable analysis, only brow fat expansion was a significant contributing factor (p = 0.009). Conclusions: The Rainbow Brow is a distinct entity in TED and is likely consequent to brow fat pad expansion. Patients with a Rainbow Brow have different eyebrow curvature as compared to both normal age-sex-matched controls and TED patients without a Rainbow Brow.

AbstractThe aim of the study is to describe a mathematical model for analyzing eyebrow curvature that can be applied broadly to curvilinear facial features. A total of 100 digital images (50 men, 50 women) were obtained from standardized headshots of medical professionals. Images were analyzed in ImageJ by plotting either 8 or 15 points along the inferior-most row of contiguous brow cilia. A best-fit curve was automatically fit to these points in Microsoft Excel. The second derivative of the second-degree polynomial and a fourth-degree polynomial were used to evaluate brow curvature. Both techniques were subsequently compared with each other. A second-degree polynomial and fourth-degree polynomial were fit to all eyebrows. Plotting 15 points yielded greater goodness-of-fit than plotting 8 points along the inferior brow and allowed for more sensitive measurement of curvature across all images. A fourth-degree polynomial function provided a closer fit to the eyebrow than a second-degree polynomial function. This method provides a simple and reliable tool for quantitative analysis of eyebrow curvature from images. Fifteen-point plots and a fourth-degree polynomial curve provide a greater goodness-of-fit. The authors believe the described technique can be applied to other curvilinear facial features and will facilitate the analysis of standardized images.