Please use this identifier to cite or link to this item: https://doi.org/10.1212/WNL.0000000000012226
Title: Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs
Authors: Vasseneix, Caroline
Najjar, Raymond P 
Xu, Xinxing 
Tang, Zhiqun
Loo, Jing Liang
Singhal, Shweta
Tow, Sharon
Milea, Leonard
Ting, Daniel Shu Wei 
Liu, Yong
Wong, Tien Y 
Newman, Nancy J
Biousse, Valerie
Milea, Dan 
Keywords: Science & Technology
Life Sciences & Biomedicine
Clinical Neurology
Neurosciences & Neurology
IDIOPATHIC INTRACRANIAL HYPERTENSION
OPTICAL COHERENCE TOMOGRAPHY
VISUAL-LOSS
CEREBRI
FEASIBILITY
CAMERA
RISK
Issue Date: 27-Jul-2021
Publisher: LIPPINCOTT WILLIAMS & WILKINS
Citation: Vasseneix, Caroline, Najjar, Raymond P, Xu, Xinxing, Tang, Zhiqun, Loo, Jing Liang, Singhal, Shweta, Tow, Sharon, Milea, Leonard, Ting, Daniel Shu Wei, Liu, Yong, Wong, Tien Y, Newman, Nancy J, Biousse, Valerie, Milea, Dan (2021-07-27). Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs. NEUROLOGY 97 (4) : E369-E377. ScholarBank@NUS Repository. https://doi.org/10.1212/WNL.0000000000012226
Abstract: OBJECTIVE: To evaluate the performance of a deep learning system (DLS) in classifying the severity of papilledema associated with increased intracranial pressure on standard retinal fundus photographs. METHODS: A DLS was trained to automatically classify papilledema severity in 965 patients (2,103 mydriatic fundus photographs), representing a multiethnic cohort of patients with confirmed elevated intracranial pressure. Training was performed on 1,052 photographs with mild/moderate papilledema (MP) and 1,051 photographs with severe papilledema (SP) classified by a panel of experts. The performance of the DLS and that of 3 independent neuro-ophthalmologists were tested in 111 patients (214 photographs, 92 with MP and 122 with SP) by calculating the area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, and specificity. Kappa agreement scores between the DLS and each of the 3 graders and among the 3 graders were calculated. RESULTS: The DLS successfully discriminated between photographs of MP and SP, with an AUC of 0.93 (95% confidence interval [CI] 0.89-0.96) and an accuracy, sensitivity, and specificity of 87.9%, 91.8%, and 86.2%, respectively. This performance was comparable with that of the 3 neuro-ophthalmologists (84.1%, 91.8%, and 73.9%, p = 0.19, p = 1, p = 0.09, respectively). Misclassification by the DLS was mainly observed for moderate papilledema (Frisén grade 3). Agreement scores between the DLS and the neuro-ophthalmologists' evaluation was 0.62 (95% CI 0.57-0.68), whereas the intergrader agreement among the 3 neuro-ophthalmologists was 0.54 (95% CI 0.47-0.62). CONCLUSIONS: Our DLS accurately classified the severity of papilledema on an independent set of mydriatic fundus photographs, achieving a comparable performance with that of independent neuro-ophthalmologists. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that a DLS using mydriatic retinal fundus photographs accurately classified the severity of papilledema associated in patients with a diagnosis of increased intracranial pressure.
Source Title: NEUROLOGY
URI: https://scholarbank.nus.edu.sg/handle/10635/210599
ISSN: 00283878
1526632X
DOI: 10.1212/WNL.0000000000012226
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