Influence of Computer-Generated Mosaic Photographs on Retinopathy of Prematurity Diagnosis and Management.
OBJECTIVE
Telemedicine is becoming an increasingly important component of clinical care for retinopathy of prematurity (ROP), but little information exists regarding the role of mosaic photography for ROP telemedicine diagnosis.


OBJECTIVE
To examine the potential effect of computer-generated mosaic photographs on the diagnosis and management of ROP.


METHODS
In this prospective cohort study performed from July 12, 2011, through September 21, 2015, images were acquired from ROP screening at 8 academic institutions, and ROP experts interpreted 40 sets (20 sets with individual fundus photographs with ≥3 fields and 20 computer-generated mosaic photographs) of wide-angle retinal images from infants with ROP. All experts independently reviewed the 40 sets and provided a diagnosis and management plan for each set presented.


METHODS
The primary outcome measure was the sensitivity and specificity of the ROP diagnosis by experts that was calculated using a consensus reference standard diagnosis, determined from the diagnosis of fundus photographs by 3 experienced readers in combination with the clinical diagnosis based on ophthalmoscopic examination. Mean unweighted κ statistics were used to analyze the mean intergrader agreement among experts for diagnosis of zone, stage, plus disease, and category.


RESULTS
Nine ROP experts (4 women and 5 men) who have been practicing ophthalmology for a mean of 10.8 years (range, 3-24 years) consented to participate. Diagnosis by the mosaic photographs compared with diagnosis by multiple individual photographs resulted in improvements in sensitivity for diagnosis of stage 2 disease or worse (95.9% vs 88.9%; difference, 7.0; 95% CI, 3.5 to 10.5; P = .02), plus disease (85.7% vs 63.5%; difference, 22.2; 95% CI, 7.6 to 36.9; P = .02), and treatment-requiring ROP (84.4% vs 68.5%; difference, 15.9; 95% CI, 0.8 to 31.7; P = .047). With use of the κ statistic, mosaic photographs, compared with multiple individual photographs, resulted in improvements in intergrader agreement for diagnosis of plus disease or not (0.54 vs 0.40; mean κ difference, 0.14; 95% CI, 0.07 to 0.21; P = .004), stage 3 disease or worse or not (0.60 vs 0.52; mean κ difference, 0.06; 95% CI, -0.06 to 0.18; P = .04), and type 2 ROP or not (0.58 vs 0.51; mean κ difference, 0.07; 95% CI, 0.03 to 0.11; P = .04). After viewing the mosaic photographs, experts altered their choice of management in 42 of 180 responses (23.3%; 95% CI, 17.1%-29.5%).


CONCLUSIONS
Compared with multiple individual photographs, computer-generated mosaic photographs were associated with improved accuracy of image-based diagnosis for certain categories (eg, plus disease, stage 2 disease or worse, and treatment-requiring ROP) of ROP by experts. It is unclear, however, whether these findings are generalizable, and the results of this study may not be relevant to mosaic grading of other retinal vascular conditions.
Department of Ophthalmology, Weill Cornell Medical College, New York, New York.
Samir N
SN
Patel
Stein Eye Institute, University of California, Los Angeles.
Michael A
MA
Klufas
University at Buffalo, State University of New York, Buffalo.
Christina E
CE
Douglas
Department of Ophthalmology, Weill Cornell Medical College, New York, New York4Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago.
Karyn E
KE
Jonas
Casey Eye Institute, Oregon Health & Science University, Portland.
Susan
S
Ostmo
Bascom Palmer Eye Institute, University of Miami, Miami, Florida.
Audina
A
Berrocal
Associated Retinal Consultants, Oakland University, Royal Oak, Michigan.
Antonio
A
Capone
Asociación para Evitar la Ceguera en México, Mexico City, Mexico.
Maria A
MA
Martinez-Castellanos
Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago.
Felix
F
Chau
Associated Retinal Consultants, Oakland University, Royal Oak, Michigan.
Kimberly
K
Drenser
Long Island Vitreoretinal Consultants, Long Island, New York.
Philip
P
Ferrone
Department of Ophthalmology, Weill Cornell Medical College, New York, New York.
Anton
A
Orlin
Stein Eye Institute, University of California, Los Angeles.
Irena
I
Tsui
Department of Ophthalmology, Chang Gung Memorial Hospital, Taoyuan, Taiwan11Department of Ophthalmology, Chang Gung University, College of Medicine, Taoyuan, Taiwan.
Wei-Chi
WC
Wu
Department of Ophthalmology, Weill Cornell Medical College, New York, New York.
Mrinali P
MP
Gupta
Casey Eye Institute, Oregon Health & Science University, Portland.
Michael F
MF
Chiang
Department of Ophthalmology, Weill Cornell Medical College, New York, New York4Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago12Center for Global Health, University of Illinois at Chicago, Chicago.
R V Paul
RV
Chan
D005260:Female; D005865:Gestational Age; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature; D008297:Male; D009887:Ophthalmoscopy / Q000379:methods*; D010781:Photography / Q000379:methods*; D011446:Prospective Studies; D012372:ROC Curve; D015203:Reproducibility of Results; D012160:Retina / Q000000981:diagnostic imaging*; D012178:Retinopathy of Prematurity / Q000175:diagnosis*; D017216:Telemedicine / Q000379:methods*
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