PURPOSE: "ROPtool" is a computer program that measures retinal blood vessel tortuosity. Our aim was to determine the feasibility and accuracy of analyzing images with ROPtool, which were obtained using video indirect ophthalmoscopy. METHODS: Forty-five posterior pole still images captured from indirect ophthalmoscopy video clips were selected; 20 were selected for high quality and 25 were randomly selected. One of the authors (S.A.) used ROPtool to measure tortuosity for each quadrant of each image. Two of the authors (D.K.W. and S.F.F.) independently judged tortuosity on a 10-point scale, and their averaged grades were used as the reference standard. RESULTS: Among randomly selected images, ROPtool was able to trace at least two major vessels in 43 of 100 quadrants (43%). Lighter fundus pigment color was associated with ROPtool's ability to analyze images (P = 0.004). When considering analyzable images only, ROPtool's sensitivity in detecting tortuosity sufficient for plus disease was 83% (5/6) and specificity was 90% (18/20). ROPtool's sensitivity for pre-plus tortuosity was 100% (9/9) and specificity was 71% (12/17). CONCLUSION: ROPtool is useful for analyzing video indirect ophthalmoscopy images only when applied to those with high quality. When analyzing these images, ROPtool has very good accuracy compared to consensus of experienced examiners.
PURPOSE: "ROPtool" is a computer program that measures retinal blood vessel tortuosity. Our aim was to determine the feasibility and accuracy of analyzing images with ROPtool, which were obtained using video indirect ophthalmoscopy. METHODS: Forty-five posterior pole still images captured from indirect ophthalmoscopy video clips were selected; 20 were selected for high quality and 25 were randomly selected. One of the authors (S.A.) used ROPtool to measure tortuosity for each quadrant of each image. Two of the authors (D.K.W. and S.F.F.) independently judged tortuosity on a 10-point scale, and their averaged grades were used as the reference standard. RESULTS: Among randomly selected images, ROPtool was able to trace at least two major vessels in 43 of 100 quadrants (43%). Lighter fundus pigment color was associated with ROPtool's ability to analyze images (P = 0.004). When considering analyzable images only, ROPtool's sensitivity in detecting tortuosity sufficient for plus disease was 83% (5/6) and specificity was 90% (18/20). ROPtool's sensitivity for pre-plus tortuosity was 100% (9/9) and specificity was 71% (12/17). CONCLUSION: ROPtool is useful for analyzing video indirect ophthalmoscopy images only when applied to those with high quality. When analyzing these images, ROPtool has very good accuracy compared to consensus of experienced examiners.
Authors: Rolando Estrada; Carlo Tomasi; Michelle T Cabrera; David K Wallace; Sharon F Freedman; Sina Farsiu Journal: Biomed Opt Express Date: 2012-01-18 Impact factor: 3.732
Authors: Michelle T Cabrera; Sharon F Freedman; Mary Elizabeth Hartnett; Sandra S Stinnett; Bei Bei Chen; David K Wallace Journal: Ophthalmic Surg Lasers Imaging Retina Date: 2014 Nov-Dec Impact factor: 1.300
Authors: Rolando Estrada; Carlo Tomasi; Michelle T Cabrera; David K Wallace; Sharon F Freedman; Sina Farsiu Journal: Biomed Opt Express Date: 2011-09-29 Impact factor: 3.732
Authors: Marguerite C Weinert; David K Wallace; Sharon F Freedman; J Wayne Riggins; Keith J Gallaher; S Grace Prakalapakorn Journal: J AAPOS Date: 2020-03-27 Impact factor: 1.220
Authors: Gloria J Hong; Jagger C Koerner; Marguerite C Weinert; Sandra S Stinnett; Sharon F Freedman; David K Wallace; J Wayne Riggins; Keith J Gallaher; S Grace Prakalapakorn Journal: J AAPOS Date: 2021-02-20 Impact factor: 1.220
Authors: Sasapin G Prakalapakorn; Laura A Vickers; Rolando Estrada; Sharon F Freedman; Carlo Tomasi; Sina Farsiu; David K Wallace Journal: Open Ophthalmol J Date: 2017-06-29