September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Classification of choroidal nevi using swep-source optical coherence tomography and infrared reflectance imaging at different wavelengths
Author Affiliations & Notes
  • Clara Vazquez-Alfageme
    NIHR Biomedical Research Facility at Moorfields Eye Hospital NHS Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Vasilios Papastefanou
    Moorfields Eye Hospital, London, United Kingdom
  • Simona Degli Esposti
    NIHR Biomedical Research Facility at Moorfields Eye Hospital NHS Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Monica Clemo
    NIHR Biomedical Research Facility at Moorfields Eye Hospital NHS Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Praveen J Patel
    NIHR Biomedical Research Facility at Moorfields Eye Hospital NHS Trust and UCL Institute of Ophthalmology, London, United Kingdom
  • Mandeep S Sagoo
    Moorfields Eye Hospital, London, United Kingdom
  • Footnotes
    Commercial Relationships   Clara Vazquez-Alfageme, None; Vasilios Papastefanou, None; Simona Degli Esposti, None; Monica Clemo, None; Praveen Patel, Bayer (C), Heidelberg Inc (F), Novartis (C), SalutarisMD (R), Thrombogenics NV (C), Thrombogenics NV (F), Topcon Inc (F); Mandeep Sagoo, None
  • Footnotes
    Support  Personal grant from the Spanish Retina and Vitreous Society
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5879. doi:
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      Clara Vazquez-Alfageme, Vasilios Papastefanou, Simona Degli Esposti, Monica Clemo, Praveen J Patel, Mandeep S Sagoo; Classification of choroidal nevi using swep-source optical coherence tomography and infrared reflectance imaging at different wavelengths. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5879.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The diagnosis of choroidal nevi has traditionally relied on clinical observations. Continuous advances in retinal and choroidal imaging have provided a platform for a better understanding of these common lesions. We performed a retrospective observational study to attempt a classification of choroidal nevi according to the different reflectivity patterns on swept source optical coherence tomography (SS-OCT) and to learn about the differences on infrared imaging at different wavelengths (830 and 1050nm) between the categories.

Methods : OCT and infrared images were obtained on 110 clinically diagnosed choroidal nevi from 108 different patients with two different devices: Spectralis SD-OCT (Heidelberg) at 830 nm and Atlantis DRI SS-OCT (Topcon) at 1050 nm. Based on the reflectivity pattern displayed on SS-OCT, the lesions were classified by a single grader into: Type A (high reflectivity with optical shadowing), type B (medium reflectivity with partial visualization of scleral boundary) and type C (homogeneous hyporefectivity with visualization of scleral boundary). Infrared images of the lesions at 830nm (NIR) and 1050 nm (IR-SS) were classified into hyper, iso or hyporeflective.

Results : 110 choroidal nevi were classified according to the OCT pattern as follows: 51 (46.36%) as type A, 19 (17.27%) as type B and 30 (27.27%) as type C. 10 lesions (9,09%) did not fall into either category. In type A, 48 lesions (94.12%) displayed low reflectance on IR-SS, but hypereflectivity on NIR. In type B 13 (68.42%) were hypereflective on NIR and iso or hyporeflective on IR-SS. In type C 28 lesions (93.3%) were iso or highly reflective on IR-SS and also iso or highly reflective on NIR.

Conclusions : The deeper penetrance of SS-OCT provides a better visualization of the choroidal anatomy and allows the characterization of choroidal nevi into three distinct patterns according to the reflectivity displayed. The reflectance pattern on infrared image was drastically different between the two different wavelengths across the OCT patterns. Type A and B showed opposite reflectance patterns between the two devices, while type C displayed similar hypereflectivity.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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