Application of Novel Software Algorithms to Spectral-Domain Optical Coherence Tomography for Automated Detection of Diabetic Retinopathy

作者：Adhi Mehreen; Semy Salim K; Stein David W; Potter Daniel M; Kuklinski Walter S; Sleeper Harry A; Duker Jay S; Waheed Nadia K^*

来源：Ophthalmic Surgery Lasers & Imaging Retina, 2016, 47(5): 410-417.

DOI：10.3928/23258160-20160419-03

BACKGROUND AND OBJECTIVE: To present novel software algorithms applied to spectral-domain optical coherence tomography (SD-OCT) for automated detection of diabetic retinopathy (DR).
PATIENTS AND METHODS: Thirty-one diabetic patients (44 eyes) and 18 healthy, nondiabetic controls (20 eyes) who underwent volumetric SD-OCT imaging and fundus photography were retrospectively identified. A retina specialist independently graded DR stage. Trained automated software generated a retinal thickness score signifying macular edema and a cluster score signifying microaneurysms and/or hard exudates for each volumetric SD-OCT.
RESULTS: Of 44 diabetic eyes, 38 had DR and six eyes did not have DR. Leave-one-out cross-validation using a linear discriminant at missed detection/false alarm ratio of 3.00 computed software sensitivity and specificity of 92% and 69%, respectively, for DR detection when compared to clinical assessment.
CONCLUSION: Novel software algorithms applied to commercially available SD-OCT can successfully detect DR and may have potential as a viable screening tool for DR in future.

• 出版日期2016-6