OBJECTIVE: To prospectively determine if tortuosity assessment by a computer program (ROPtool) that traces retinal blood vessels and measures their tortuosity was more accurate than that of individual pediatric ophthalmologists. METHODS: One hundred eighty-five high-quality RetCam images from premature infants were circulated to 3 retinopathy of prematurity (ROP) experts and 3 other pediatric ophthalmologists ("examiners") who graded the tortuosity in each quadrant as normal, pre-plus, or plus. These same images were analyzed using ROPtool. RESULTS: Using expert consensus as the standard, ROPtool's overall accuracy of 95% (175 of 185) for identifying tortuosity sufficient for plus disease was similar to that of examiner 1 (93%; 172 of 185; P = .50), examiner 2 (93%; 172 of 185; P = .50), and examiner 3 (91%; 168 of 185; P = .10). ROPtool's sensitivity of 97% (36 of 37) compared favorably with that of examiner 1 (65%; 24 of 37; P < .001), examiner 2 (70%; 26 of 37; P < .001), and examiner 3 (81%; 30 of 37; P = .06). CONCLUSION: Computer-assisted analysis of retinal images can potentially reduce subjectivity in the diagnosis of plus disease and optimize timing of follow-up and treatment for ROP.
OBJECTIVE: To prospectively determine if tortuosity assessment by a computer program (ROPtool) that traces retinal blood vessels and measures their tortuosity was more accurate than that of individual pediatric ophthalmologists. METHODS: One hundred eighty-five high-quality RetCam images from premature infants were circulated to 3 retinopathy of prematurity (ROP) experts and 3 other pediatric ophthalmologists ("examiners") who graded the tortuosity in each quadrant as normal, pre-plus, or plus. These same images were analyzed using ROPtool. RESULTS: Using expert consensus as the standard, ROPtool's overall accuracy of 95% (175 of 185) for identifying tortuosity sufficient for plus disease was similar to that of examiner 1 (93%; 172 of 185; P = .50), examiner 2 (93%; 172 of 185; P = .50), and examiner 3 (91%; 168 of 185; P = .10). ROPtool's sensitivity of 97% (36 of 37) compared favorably with that of examiner 1 (65%; 24 of 37; P < .001), examiner 2 (70%; 26 of 37; P < .001), and examiner 3 (81%; 30 of 37; P = .06). CONCLUSION: Computer-assisted analysis of retinal images can potentially reduce subjectivity in the diagnosis of plus disease and optimize timing of follow-up and treatment for ROP.
Authors: Emanuele Trucco; Alfredo Ruggeri; Thomas Karnowski; Luca Giancardo; Edward Chaum; Jean Pierre Hubschman; Bashir Al-Diri; Carol Y Cheung; Damon Wong; Michael Abràmoff; Gilbert Lim; Dinesh Kumar; Philippe Burlina; Neil M Bressler; Herbert F Jelinek; Fabrice Meriaudeau; Gwénolé Quellec; Tom Macgillivray; Bal Dhillon Journal: Invest Ophthalmol Vis Sci Date: 2013-05-01 Impact factor: 4.799
Authors: Jane S Myung; Rony Gelman; Grant D Aaker; Nathan M Radcliffe; R V Paul Chan; Michael F Chiang Journal: Am J Ophthalmol Date: 2011-10-22 Impact factor: 5.258
Authors: Rohini Rao; Nina J Jonsson; Camila Ventura; Rony Gelman; Martin A Lindquist; Daniel S Casper; Michael F Chiang Journal: Retina Date: 2012-06 Impact factor: 4.256
Authors: Sai H Chavala; Sina Farsiu; Ramiro Maldonado; David K Wallace; Sharon F Freedman; Cynthia A Toth Journal: Ophthalmology Date: 2009-09-18 Impact factor: 12.079