Abstract
Purpose
To evaluate aggressive posterior retinopathy of prematurity (AP-ROP) with regard to inter-expert diagnostic agreement and quantitative vascular features.
Methods
Eight ROP experts interpreted 15 retinal images for AP-ROP and plus disease. Inter-expert agreement was calculated by absolute agreement for AP-ROP and plus, and kappa statistic for each expert was compared with others. Retinal vessels were analyzed by a computer-based system to calculate diameter and integrated curvature (IC). Consensus reference standards for images were developed, and quantitative parameters for arterioles and venules were compared among images with AP-ROP vs. not AP-ROP, plus vs. not plus, and AP-ROP vs. plus.
Results
Mean kappa for each expert in AP-ROP diagnosis ranged from −0.15 (no agreement) to 0.42 (moderate agreement). Nine (30 %) of 30 total AP-ROP diagnoses were also classified as not plus disease. Analysis of images with AP-ROP vs. plus showed that images with AP-ROP had higher venular IC (p = 0.04). Arteriolar IC was statistically significant between images with AP-ROP vs. not AP-ROP (p = 0.01) and plus vs. not plus (p = 0.00003). There were no statistically significant differences in diameter between image groups.
Conclusions
Inter-expert agreement with regard to AP-ROP diagnosis is imperfect. Venular curvature may be a distinguishing characteristic between AP-ROP and plus. Future studies involving quantitative features of AP-ROP will have benefits for clinical diagnosis and management.
Similar content being viewed by others
References
Early Treatment For Retinopathy Of Prematurity Cooperative Group (2005) Revised indications for the treatment of retinopathy of prematurity: results of the early treatment for retinopathy of prematurity randomized trial. Arch Ophthalmol 121:1684–1694
Palmer EA, Hardy RJ, Dobson V et al (2005) 15-year outcomes following threshold retinopathy of prematurity: final results from the multicenter trial of cryotherapy for retinopathy of prematurity. Arch Ophthalmol 123:311–318
Silverman WA (1980) Retrolental Fibroplasia: A Modern Parable. Grune and Stratton, Inc., New York, NY
Vinekar A, Avadhani K, Braganza S et al (2011) Outcomes of a protocol-based management for zone 1 retinopathy of prematurity: the Indian Twin Cities ROP Screening Program report number 2. Am J Ophthalmol 152:712
International Committee for the Classification of Retinopathy of Prematurity (2005) The International Classification of Retinopathy of Prematurity revisited. Arch Ophthalmol 123:991–999
Cryotherapy for Retinopathy of Prematurity Cooperative Group (1988) Multicenter trial of cryotherapy for retinopathy of prematurity: preliminary results. Arch Ophthalmol 106:471–479
Wallace DK, Quinn GE, Freedman SF et al (2008) Agreement among pediatric ophthalmologists in diagnosing plus and pre-plus disease in retinopathy of prematurity. J AAPOS 12:352–356
Slidsborg C, Forman JL, Fielder AR et al (2012) Experts do not agree when to treat retinopathy of prematurity based on plus disease. Br J Ophthalmol 96:549–553
Chiang MF, Gelman R, Williams SL et al (2008) Plus disease in retinopathy of prematurity: development of composite images by quantification of expert opinion. Invest Ophthalmol Vis Sci 49:4064–4070
Gelman R, Jiang L, Du YE et al (2007) Plus disease in retinopathy of prematurity: pilot study of computer-based and expert diagnosis. J AAPOS 11:532–540
Gelman R, Martinez-Perez ME, Vanderveen DK et al (2005) Diagnosis of plus disease in retinopathy of prematurity using Retinal Image multiScale Analysis. Invest Ophthalmol Vis Sci 46:4734–4738
Koreen S, Gelman R, Martinez-Perez ME et al (2007) Evaluation of a computer-based system for plus disease diagnosis in retinopathy of prematurity. Ophthalmology 114:e59–e67
Swanson C, Cocker KD, Parker KH et al (2003) Semiautomated computer analysis of vessel growth in preterm infants without and with ROP. Br J Ophthalmol 87:1474–1477
Harris PA, Taylor R, Thielke R et al (2009) Research electronic data capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42:377–381
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174
Martinez-Perez ME, Hughes AD, Stanton AV et al (2002) Retinal vascular tree morphology: a semi-automatic quantification. IEEE Trans Biomed Eng 49:912–917
Martinez-Perez ME, Hughes AD, Thom SA et al (2007) Segmentation of blood vessels from red-free and fluorescein retinal images. Med Image Anal 11:47–61
Chiang MF, Jiang L, Gelman R et al (2007) Interexpert agreement of plus disease diagnosis in retinopathy of prematurity. Arch Ophthalmol 125:875–880
Paul Chan RV, Williams SL, Yonekawa Y et al (2010) Accuracy of retinopathy of prematurity diagnosis by retinal fellows. Retina 30:958–965
Johnston SC, Wallace DK, Freedman SF et al (2009) Tortuosity of arterioles and venules in quantifying plus disease. J AAPOS 13:181–185
Thyparampil PJ, Park Y, Martinez-Perez ME et al (2010) Plus disease in retinopathy of prematurity: quantitative analysis of vascular change. Am J Ophthalmol 150:468–75.e2
Ghodasra DH, Thuangtong A, Karp K et al (2012) The rate of change in retinal vessel width and tortuosity in eyes at risk for retinopathy of prematurity. J AAPOS 16:431–436
Blencowe H, Lawn JE, Vazquez T, Fielder A, Gilbert C (2013) Preterm-associated visual impairment and estimates of retinopathy of prematurity at regional and global levels for 2010. Pediatr Res 74(Suppl 1):35–49
Shah PK, Narendran V, Kalpana N, Gilbert C (2009) Severe retinopathy of prematurity in big babies in India: history repeating itself? Indian J Pediatr 76:801–804
Shah DN, Wilson CM, Ying GS et al (2009) Semiautomated digital image analysis of posterior pole vessels in retinopathy of prematurity. J AAPOS 13:504–506
Wallace DK, Zhao Z, Freedman SF (2007) A pilot study using "ROPtool" to quantify plus disease in retinopathy of prematurity. J AAPOS 11:381–387
Wilson CM, Cocker KD, Moseley MJ et al (2008) Computerized analysis of retinal vessel width and tortuosity in premature infants. Invest Ophthalmol Vis Sci 49:3577–3585
Wittenberg LA, Jonsson NJ, Chan RV, Chiang MF (2012) Computer-based image analysis for plus disease diagnosis in retinopathy of prematurity. J Pediatr Ophthalmol Strabismus 49:11–19
Ataer-Cansizoglu E, You S, Kalpathy-Cramer J et al (2012) Observer and feature analysis on diagnosis of retinopathy of prematurity. IEEE Int Workshop Mach Learn Signal Process 12:1–6
Acknowledgments
Supported by grant EY19474 from the National Institutes of Health (Bethesda, MD) (MFC), the Friends of Doernbecher foundation (Portland, OR) (MFC), unrestricted departmental funding from Research to Prevent Blindness (New York, NY) (RVPC, MFC), the St. Giles Foundation (New York, NY) (RVPC), and the Yale One Year Medical Fellowship (New Haven, CT) (RW).
Conflicts of interest
All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.
MFC is an unpaid member of the Scientific Advisory Board for Clarity Medical Systems (Pleasanton, CA, USA).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Woo, R., Chan, R.V.P., Vinekar, A. et al. Aggressive posterior retinopathy of prematurity: a pilot study of quantitative analysis of vascular features. Graefes Arch Clin Exp Ophthalmol 253, 181–187 (2015). https://doi.org/10.1007/s00417-014-2857-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00417-014-2857-2