Poster 24

Feb 18, 2017 by AAPOS editor in  Poster Session 1

Evaluation of Computer-Based Image Analysis for Retinopathy of Prematurity Screening

Sapna Tibrewal, MD; Peng Tian, BS; Dharanish Kedarisetti, MS; Jayashree Kalpathy-Cramer, PhD; Deniz Erdogmus, PhD; John P. Campbell, MD; Robison V. Chan, MD; Michael F. Chiang, MD

Casey Eye Institute, Oregon Health & Science University

Portland, OR

Introduction:  This project was designed to explore whether the i-ROP computer-based image analysis (CBIA) system could identify infants with clinically-significant retinopathy of prematurity (ROP).

Methods:  We developed a CBIA system (the “i-ROP” system) to calculate a ROP severity score using methods previously published.1 We measured the receiver operating characteristic curve, calculated the area under the curve (AUC), and the sensitivity and specificity of the i-ROP system for detecting pre-plus or worse disease in a database of 195 images. We also compared the i-ROP regression score to zone, stage, and overall ETROP category to determine the sensitivity of detecting clinically-significant disease.

Results:  The AUC for the i-ROP system was 0.94. The system could detect presence of pre-plus or plus disease with a sensitivity of 95% and a specificity of 72%, and could detect 93% of ETROP type 2 disease or worse (n= 47). The sensitivity for detection of ETROP type 1 disease (n = 27) was 100%.

Discussion:  ROP diagnosis may be highly subjective and qualitative, even by experts.2 This study shows that CBIA tools have potential to assist ophthalmologists in making more accurate and consistent diagnoses. These systems could also have a significant impact in ROP telemedicine programs worldwide by optimizing the screening capacity of limited human resources and improving access to care.

Conclusion:  Computer-based image analysis is able to reliably detect clinically-significant ROP with high accuracy.

References:  1. Ataer-Cansizoglu E, Bolon-Canedo V, Campbell JP, Bozkurt A, Erdogmus D, Kalpathy-Cramer J, Patel S, Jonas K, Chan RV, Ostmo S, Chiang MF; i-ROP Research Consortium. Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the “i-ROP” System and Image Features Associated With Expert Diagnosis. Transl Vis Sci Technol. 2015;4:5. eCollection 2015 Nov.

2. Chiang MF, Jiang L, Gelman R, Du YE, Flynn JT. Interexpert agreement of plus disease diagnosis in retinopathy of prematurity. Arch Ophthalmol. 2007;125:875-80.

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