Plus Disease Diagnosis in Retinopathy of Prematurity

Keck, Katie; Kalpathy–Cramer, Jayashree; Ataer-Cansızoğlu, Esra; You, Sheng; Erdoğmuş, Deni̇z; Chiang, Michael F.

doi:10.1097/iae.0b013e3182845c39

Cited by 24 publications

(18 citation statements)

References 35 publications

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“…1 That said, numerous studies have shown that a variety of features beyond this standard definition may be considered by physicians while diagnosing plus disease. 12,33,38,43 To address this potential confounder for 12 of the 34 images, 3 experts were asked to re-classify all 34 of the original 2007 cropped images. The average score was not significantly different from their original 2016 gradings (2.60 vs. 2.67); however it was significantly more severe than the original 2007 scores (2.1).…”

Section: Discussionmentioning

confidence: 99%

Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007

Moleta

Campbell

Kalpathy–Cramer

et al. 2017

American Journal of Ophthalmology

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Purpose To identify any temporal trends in the diagnosis of plus disease in retinopathy of prematurity (ROP) by experts. Design Reliability analysis Methods ROP experts were recruited in 2007 and 2016 to classify 34 wide-field fundus images of ROP as plus, pre-plus, or normal, coded as “3,” “2,” and “1” respectively in the database. The main outcome was the average calculated score for each image in each cohort. Secondary outcomes included correlation on the relative ordering of the images in 2016 versus 2007, inter-expert agreement, and intra-expert agreement Results The average score for each image was higher for 30/34 (88%) images in 2016 compared to 2007, influenced by fewer images classified as normal (P<0.01), a similar number of pre-plus (P=0.52), and more classified as plus (P<0.01). The mean weighted kappa values in 2006 were 0.36 (range 0.21 – 0.60) compared to 0.22 (range 0 – 0.40) in 2016. There was good correlation between rankings of disease severity between the two cohorts (Spearman’s rank correlation ρ=0.94) indicating near-perfect agreement on relative disease severity. Conclusions Despite good agreement between cohorts on relative disease severity ranking, the higher average score and classifications for each image demonstrate that experts are diagnosing pre-plus and plus disease at earlier stages of disease severity in 2016, compared with 2007. This has implications for patient care, research, and teaching, and additional studies are needed to better understand this temporal trend in image-based plus disease diagnosis.

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Section: Discussionmentioning

confidence: 99%

Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007

Moleta

Campbell

Kalpathy–Cramer

et al. 2017

American Journal of Ophthalmology

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“…It is well established that inter-expert agreement in ROP classification is imperfect. However, most previous work has focused on plus disease 8,9,11,12,16 and zone classification. 7,19,20 In this study, the majority of discrepancies in stage classification were at the very mild ends of the disease spectrum (stage 0 vs. 1).…”

Section: Discussionmentioning

confidence: 99%

Diagnostic Discrepancies in Retinopathy of Prematurity Classification

et al. 2016

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Objective To identify the most common areas for discrepancy in retinopathy of prematurity (ROP) classification between experts. Design Prospective cohort study. Subjects, Participants, and/or Controls 281 infants were identified as part of a multi-center, prospective, ROP cohort study from 7 participating centers. Each site had participating ophthalmologists who provided the clinical classification after routine examination using binocular indirect ophthalmoscopy (BIO), and obtained wide-angle retinal images, which were independently classified by two study experts. Methods Wide-angle retinal images (RetCam; Clarity Medical Systems, Pleasanton, CA) were obtained from study subjects, and two experts evaluated each image using a secure web-based module. Image-based classifications for zone, stage, plus disease, overall disease category (no ROP, mild ROP, Type II or pre-plus, and Type I) were compared between the two experts, and to the clinical classification obtained by BIO. Main Outcome Measures Inter-expert image-based agreement and image-based vs. ophthalmoscopic diagnostic agreement using absolute agreement and weighted kappa statistic. Results 1553 study eye examinations from 281 infants were included in the study. Experts disagreed on the stage classification in 620/1553 (40%) of comparisons, plus disease classification (including pre-plus) in 287/1553 (18%), zone in 117/1553 (8%), and overall ROP category in 618/1553 (40%). However, agreement for presence vs. absence of type 1 disease was >95%. There were no differences between image-based and clinical classification except for zone III disease. Conclusions The most common area of discrepancy in ROP classification is stage, although inter-expert agreement for clinically-significant disease such as presence vs. absence of type 1 and type 2 disease is high. There were no differences between image-based grading and the clinical exam in the ability to detect clinically-significant disease. This study provides additional evidence that image-based classification of ROP reliably detects clinically significant levels of ROP with high accuracy compared to the clinical exam.

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“…3 Also, the image possesses a narrow field of view (FOV), and does not reveal possible tortuous vessels in the periphery of the retina, which have recently been shown to be more correlated to the presence of plus disease. [10][11][12] The narrow FOV of the standard photograph is believed to represent the FOV of a funduscope when centered on the optic nerve head (ONH). However, to the best of the authors' knowledge, such a limit to the area of analysis has never been justified.…”

Section: Plus Diseasementioning

confidence: 99%

“…Furthermore, all mentioned studies limited the area of analysis to the posterior of the retina; however, peripheral-vessel tortuosity has been shown to be more correlated to the presence of plus disease as compared to posterior-vessel tortuosity. [10][11][12] The main focus of the present work is on the development of image processing methods for detection and quantitative analysis of abnormally tortuous vessels in retinal fundus images as well as an approach to use measures of tortuosity for diagnosis of plus disease. In addition to the results of quantification of tortuosity as a single diagnostic feature, the results of our previous related studies on the thickness 27 and the openness of the MTA 14 are used to perform feature selection and pattern classification.…”

Section: Plus Diseasementioning

confidence: 99%

Computer-aided diagnosis of retinopathy in retinal fundus images of preterm infants via quantification of vascular tortuosity

2016

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Retinopathy of prematurity (ROP), a disorder of the retina occurring in preterm infants, is the leading cause of preventable childhood blindness. An active phase of ROP that requires treatment is associated with the presence of plus disease, which is diagnosed clinically in a qualitative manner by visual assessment of the existence of a certain level of increase in the thickness and tortuosity of retinal vessels. The present study performs computer-aided diagnosis (CAD) of plus disease via quantitative measurement of tortuosity in retinal fundus images of preterm infants. Digital image processing techniques were developed for the detection of retinal vessels and measurement of their tortuosity. The total lengths of abnormally tortuous vessels in each quadrant and the entire image were then computed. A minimum-length diagnostic-decision-making criterion was developed to assess the diagnostic sensitivity and specificity of the values obtained. The area ([Formula: see text]) under the receiver operating characteristic curve was used to assess the overall diagnostic accuracy of the methods. Using a set of 19 retinal fundus images of preterm infants with plus disease and 91 without plus disease, the proposed methods provided an overall diagnostic accuracy of [Formula: see text]. Using the total length of all abnormally tortuous vessel segments in an image, our techniques are capable of CAD of plus disease with high accuracy without the need for manual selection of vessels to analyze. The proposed methods may be used in a clinical or teleophthalmological setting.

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Plus Disease Diagnosis in Retinopathy of Prematurity

Cited by 24 publications

References 35 publications

Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007

Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007

Diagnostic Discrepancies in Retinopathy of Prematurity Classification

Computer-aided diagnosis of retinopathy in retinal fundus images of preterm infants via quantification of vascular tortuosity

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