Osode Coki

Telemedical Diagnosis of Retinopathy of Prematurity: Intraphysician Agreement between Ophthalmoscopic Examination and Image-Based Interpretation

OBJECTIVE To evaluate the intraphysician agreement between ophthalmoscopic examination and image-based telemedical interpretation for retinopathy of prematurity (ROP) diagnosis, when performed by the same expert physician grader. DESIGN Prospective, nonrandomized, comparative study. PARTICIPANTS Sixty-seven consecutive premature infants who underwent ROP examination at a major university medical center whose parents consented for participation. METHODS Infants underwent standard dilated ophthalmoscopy by one of two pediatric ophthalmologists, followed by retinal imaging with a commercially available wide-angle fundus camera by a trained neonatal nurse. Study examinations were performed at 31 to 33 weeks postmenstrual age (PMA) and/or 35 to 37 weeks PMA. Images were uploaded to a Web-based telemedicine system developed by the authors. After a 4- to 12-month period, telemedical interpretations were performed in which each physician graded images from infants upon whom he had initially performed ophthalmoscopic examinations. Diagnoses were classified using an ordinal scale: no ROP, mild ROP, type 2 prethreshold ROP, and treatment-requiring ROP. MAIN OUTCOME MEASURES Absolute intraphysician agreement and kappa statistic between ophthalmoscopic examination and telemedical interpretation were calculated by eye. All intraphysician discrepancies were reviewed, and underlying causes were classified by eye as no ROP identified by ophthalmoscopic examination, no ROP identified by telemedical interpretation, discrepancy about presence of zone 1 ROP, discrepancy about presence of plus disease, or other discrepancy in classification of ROP stage. RESULTS Absolute intraphysician agreement between ophthalmoscopic examination and telemedical interpretation was 86.3%. The kappa statistic for intraphysician agreement between examinations ranged from 0.657 (substantial agreement) for diagnosis of treatment-requiring ROP to 0.854 (near-perfect agreement) for diagnosis of mild or worse ROP. Among 206 eye examinations (103 infant examinations), there were 28 (13.6%) intraphysician discrepancies in diagnosis, 8 of which resulted from uncertainty about presence of zone 1 disease and 4 from uncertainty about presence of plus disease. CONCLUSIONS Intraphysician agreement between ophthalmoscopic examination and telemedical interpretation for ROP was very high. Neither examination modality appeared to have a systematic tendency to overdiagnose or underdiagnose ROP. Diagnosis of zone 1 disease and plus disease were major sources of clinically significant discrepancies.

Retinopathy of Prematurity Management using Single-Image vs. Multiple-Image Telemedicine Examinations

PURPOSE To compare performance of single-image vs multiple-image telemedicine examinations for retinopathy of prematurity (ROP) diagnosis. DESIGN Prospective comparative study. METHODS A total of 248 eyes from 67 consecutive infants underwent wide-angle retinal imaging by a trained neonatal nurse at 31 to 33 weeks and/or 35 to 37 weeks postmenstrual age (PMA) at a single academic institution. Data were uploaded to a web-based telemedicine system and interpreted by three masked retinal specialists. Diagnoses were provided based on single images, and subsequently on multiple images, from both eyes of each infant. Findings were compared to a reference standard of indirect ophthalmoscopy by a pediatric ophthalmologist. Primary outcome measures were recommended follow-up interval, presence of plus disease, presence of type-2 or worse ROP, and presence of visible peripheral ROP. RESULTS Among the three graders, mean sensitivity/specificity for detection of infants requiring follow-up in less than one week were 0.85/0.93 by single-image examination and 0.91/0.88 by multiple-image examination at 35 to 37 weeks PMA. Mean sensitivity/specificity for detection of infants with type-2 or worse ROP were 0.82/0.95 by single-image examination and 1.00/0.91 by multiple-image examination at 35 to 37 weeks PMA. Mean sensitivity/specificity for detection of plus disease were 1.00/0.86 by single-image examination and 1.00/0.87 by multiple-image examination at 35 to 37 weeks PMA. There were no statistically-significant intragrader differences between accuracy of single-image and multiple-image telemedicine examinations for detection of plus disease. CONCLUSIONS Single-image and multiple-image telemedicine examinations perform comparably for determination of recommended follow-up interval and detection of plus disease. This may have implications for development of screening protocols, particularly in areas with limited access to ophthalmic care.

Parental perceptions toward digital imaging and telemedicine for retinopathy of prematurity management

BackgroundTelemedicine is an emerging technology with potential to improve care for retinopathy of prematurity (ROP). This study evaluates parental perceptions about digital imaging and telemedicine for ROP care.MethodsDuring a 1-year period, one parent of each infant who underwent wide-field retinal imaging for ROP was given a questionnaire designed to evaluate parental perceptions using a 5-point Likert-type scale. Five items assessed perceptions toward digital retinal imaging, and ten items assessed attitudes toward telemedicine. Construct validity of the questionnaire was examined using factor analysis. Responses were summarized using descriptive and correlational statistics.ResultsForty-two parents participated. Factor analysis extracted two factors explaining 79% of the total variance in digital retinal imaging items (Cronbach’s alpha = 0.843), and three factors explaining 63% of the total variance in telemedicine items (Cronbach’s alpha = 0.631). Among digital imaging items, the highest mean (±SD) score was for “digital pictures of my child’s retinopathy should be included in the permanent medical record” (4.4 ± 0.6), and the lowest was for “digital cameras and computers are reliable” (3.8 ± 0.8). Among telemedicine items, the highest mean (±SD) score was for “technology will improve the quality of medical care for my child” (4.3 ± 0.6), and the lowest was for “technology will make it harder for a patient and doctor to establish a good relationship” (2.6 ± 1.1).ConclusionsParents reported positive perceptions about telemedical ROP diagnosis, but expressed some preference for face-to-face care. Telemedicine has potential to alter the nature of the patient–physician relationship.

Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis.

PURPOSE To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. DESIGN We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. PARTICIPANTS Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. METHODS Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. MAIN OUTCOME MEASURES Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. RESULTS There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). CONCLUSIONS Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future.