Assessment of Iris Surface Features and Their Relationship with Iris Thickness in Asian Eyes

Abstract

To assess iris surface features in Asian eyes and examine their associations with iris thickness measured by anterior segment optical coherence tomography (AS OCT). Cross-sectional study. We recruited 250 subjects from the Singapore Malay Eye Study. We obtained standardized slit-lamp photographs and developed a grading system assessing iris crypts (by number and size), furrows (by number and circumferential extent), and color (higher grade denoting darker iris). Vertical and horizontal cross-sections of the anterior chamber were imaged using AS OCT. Intragrader and intergrader agreements in the grading of iris surface were assessed by weighted κ (κ(w)) statistic. Associations of the average iris thickness with the grade of iris features were assessed using linear regression analysis. Frequency and size of iris crypts, furrows, and color; iris thickness at 750 μm (IT750) and 2000 μm (IT2000) from the scleral spur; and maximum iris thickness (ITM) averaged from the 4 quarters. Three hundred sixty-four eyes had complete and gradable data for crypts and color; 330 eyes were graded for furrows. The grading scheme showed good intragrader (crypt κ(w) = 0.919, furrow κ(w) =0.901, color κ(w) = 0.925) and intergrader (crypt κ(w) = 0.775, furrow κ(w) = 0.836, color κ(w) = 0.718) agreements. Higher crypt grade was associated independently with thinner IT750 (β [change in iris thickness per grade higher] = -0.007; P = 0.029), IT2000 (β = -0.018; P < 0.001), and ITM (β = -0.012; P < 0.001). More extensive furrows were associated with thicker IT750 (β = 0.022; P < 0.001). Darker iris was also associated with thicker IT750 (β = 0.014; P = 0.001). Iris surface features, assessed and measured from slit-lamp photographs, correlate well with iris thickness. Irises with more crypts are thinner; irises with more extensive furrows and darker color are thicker peripherally. These findings may provide another means to assess angle closure risk based on iris features.