title: Quantification of Astigmatism Induced by Pterygium Using Automated Image Analysis.
abstract: OBJECTIVE
  To determine the factors influencing pterygium-induced astigmatism (PIA) and to develop a prediction model of PIA using these factors.
  
  
  METHODS
  This cross-sectional study included 97 eyes of 97 patients who underwent a pterygium excision and a limbal conjunctival autograft. Anterior segment photographs were taken preoperatively, and corneal topography was done preoperatively and at 3 months postoperatively. PIA was defined as the vector difference between the topographic astigmatism preoperatively and at 3 months postoperatively. Image analysis was performed using anterior segment photographs to measure the relative length (RL) (horizontal length of pterygium invading the cornea/horizontal corneal diameter), relative width (width of pterygium invading the cornea/vertical corneal diameter), relative area (area of pterygium invading the cornea/total corneal area), and vascularity index (VI) (degree of vascularity). Association between these factors and PIA was evaluated with univariate and multivariate analyses. We also attempted to generate a model for prediction of PIA using these factors.
  
  
  RESULTS
  Univariate analysis showed that the RL, relative width, relative area, and VI were significantly associated with PIA (P < 0.001 for all variables, Pearson coefficient (r) = 0.708, 0.555, 0.606, and 0.642, respectively). In multivariate analysis, only the RL (P < 0.001) and VI (P < 0.001) had significant correlation with PIA. A multiple regression model for PIA was generated as follows: PIA = 0.080 × RL (%) + 0.039 × VI - 0.823 (r = 0.502, F = 95.71, P < 0.001).
  
  
  CONCLUSIONS
  Larger lengths and increased vascularity were associated with larger PIA. PIA can be predicted by evaluating the length and vascularity of pterygium involving the cornea.
authors.affiliation: *Department of Ophthalmology, Kangwon National University Hospital, Chuncheon, Korea; †Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea; ‡Biomedical Engineering Branch, Division of Convergence Technology, National Cancer Center, Goyang, Korea; and §Department of Ophthalmology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Sang Beom
authors.initials: SB
authors.lastname: Han
authors.forename: Hyun Sun
authors.initials: HS
authors.lastname: Jeon
authors.forename: Moosang
authors.initials: M
authors.lastname: Kim
authors.forename: Seung-Jun
authors.initials: SJ
authors.lastname: Lee
authors.forename: Hee Kyung
authors.initials: HK
authors.lastname: Yang
authors.forename: Jeong-Min
authors.initials: JM
authors.lastname: Hwang
authors.forename: Kwang Gi
authors.initials: KG
authors.lastname: Kim
authors.forename: Joon Young
authors.initials: JY
authors.lastname: Hyon
authors.forename: Won Ryang
authors.initials: WR
authors.lastname: Wee
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001251:Astigmatism / Q000209:etiology*; D003228:Conjunctiva / Q000601:surgery; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D016850:Limbus Corneae / Q000601:surgery; D008297:Male; D008875:Middle Aged; D011625:Pterygium / Q000150:complications* / Q000473:pathology / Q000601:surgery; D012044:Regression Analysis; D012307:Risk Factors