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1.
Am J Ophthalmol ; 226: 100-107, 2021 06.
Artículo en Inglés | MEDLINE | ID: mdl-33577791

RESUMEN

PURPOSE: To compare the performance of a novel convolutional neural network (CNN) classifier and human graders in detecting angle closure in EyeCam (Clarity Medical Systems, Pleasanton, California, USA) goniophotographs. DESIGN: Retrospective cross-sectional study. METHODS: Subjects from the Chinese American Eye Study underwent EyeCam goniophotography in 4 angle quadrants. A CNN classifier based on the ResNet-50 architecture was trained to detect angle closure, defined as inability to visualize the pigmented trabecular meshwork, using reference labels by a single experienced glaucoma specialist. The performance of the CNN classifier was assessed using an independent test dataset and reference labels by the single glaucoma specialist or a panel of 3 glaucoma specialists. This performance was compared to that of 9 human graders with a range of clinical experience. Outcome measures included area under the receiver operating characteristic curve (AUC) metrics and Cohen kappa coefficients in the binary classification of open or closed angle. RESULTS: The CNN classifier was developed using 29,706 open and 2,929 closed angle images. The independent test dataset was composed of 600 open and 400 closed angle images. The CNN classifier achieved excellent performance based on single-grader (AUC = 0.969) and consensus (AUC = 0.952) labels. The agreement between the CNN classifier and consensus labels (κ = 0.746) surpassed that of all non-reference human graders (κ = 0.578-0.702). Human grader agreement with consensus labels improved with clinical experience (P = 0.03). CONCLUSION: A CNN classifier can effectively detect angle closure in goniophotographs with performance comparable to that of an experienced glaucoma specialist. This provides an automated method to support remote detection of patients at risk for primary angle closure glaucoma.


Asunto(s)
Diagnóstico por Computador/clasificación , Glaucoma de Ángulo Cerrado/diagnóstico , Procesamiento de Imagen Asistido por Computador/clasificación , Redes Neurales de la Computación , Fotograbar/clasificación , Anciano , Anciano de 80 o más Años , Segmento Anterior del Ojo/patología , Área Bajo la Curva , Asiático , China/etnología , Estudios Transversales , Sistemas Especialistas , Femenino , Glaucoma de Ángulo Cerrado/clasificación , Gonioscopía , Humanos , Masculino , Persona de Mediana Edad , Oftalmólogos , Reproducibilidad de los Resultados , Estudios Retrospectivos , Especialización
2.
Case Rep Ophthalmol ; 10(2): 227-234, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-31692625

RESUMEN

Mucoceles of the paranasal sinus commonly involve the frontal sinuses, the ethmoid sinuses, and rarely the maxillary or sphenoid sinuses. They often present with sinus pain or pressure, but rarely can present with more severe symptoms such as changes in mental status or vision due to expansion and invasion through the skull base or orbit. A 62-year-old male presented with optic neuropathy, a relative afferent pupillary defect with proptosis and lateral gaze palsy of the left eye. The patient was found to have a large mucocele extending from the left posterior ethmoid sinus into the left orbital apex. Urgent endoscopic sinus surgery was performed jointly between Oculoplastics and Otolaryngology. Post-operatively, the patient had improvement in diplopia, extraocular motion, and proptosis with stable vision. This case demonstrates the importance of early identification and intervention in a rare presentation of a sinus mucocele to prevent serious complications such as vision loss.

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