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White Paper on Ophthalmic Imaging for Choroidal Nevus Identification and Transformation into Melanoma.

Publication ,  Journal Article
Shields, CL; Lally, SE; Dalvin, LA; Sagoo, MS; Pellegrini, M; Kaliki, S; Gündüz, AK; Furuta, M; Mruthyunjaya, P; Fung, AT; Duker, JS; Yaghy, A ...
Published in: Transl Vis Sci Technol
February 5, 2021

PURPOSE: To discuss the evolution of noninvasive diagnostic methods in the identification of choroidal nevus and determination of risk factors for malignant transformation as well as introduce the novel role that artificial intelligence (AI) can play in the diagnostic process. METHODS: White paper. RESULTS: Longstanding diagnostic methods to stratify benign choroidal nevus from choroidal melanoma and to further determine the risk for nevus transformation into melanoma have been dependent on recognition of key clinical features by ophthalmic examination. These risk factors have been derived from multiple large cohort research studies over the past several decades and have garnered widespread use throughout the world. More recent publications have applied ocular diagnostic testing (fundus photography, ultrasound examination, autofluorescence, and optical coherence tomography) to identify risk factors for the malignant transformation of choroidal nevus based on multimodal imaging features. The widespread usage of ophthalmic imaging systems to identify and follow choroidal nevus, in conjunction with the characterization of malignant transformation risk factors via diagnostic imaging, presents a novel path to apply AI. CONCLUSIONS: AI applied to existing ophthalmic imaging systems could be used for both identification of choroidal nevus and as a tool to aid in earlier detection of transformation to malignant melanoma. TRANSLATIONAL RELEVANCE: Advances in AI models applied to ophthalmic imaging systems have the potential to improve patient care, because earlier detection and treatment of melanoma has been proven to improve long-term clinical outcomes.

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Published In

Transl Vis Sci Technol

DOI

EISSN

2164-2591

Publication Date

February 5, 2021

Volume

10

Issue

2

Start / End Page

24

Location

United States

Related Subject Headings

  • Tomography, Optical Coherence
  • Skin Neoplasms
  • Nevus
  • Melanoma
  • Humans
  • Artificial Intelligence
  • 3212 Ophthalmology and optometry
  • 1113 Opthalmology and Optometry
  • 0903 Biomedical Engineering
 

Citation

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Shields, C. L., Lally, S. E., Dalvin, L. A., Sagoo, M. S., Pellegrini, M., Kaliki, S., … Blumenkranz, M. S. (2021). White Paper on Ophthalmic Imaging for Choroidal Nevus Identification and Transformation into Melanoma. Transl Vis Sci Technol, 10(2), 24. https://doi.org/10.1167/tvst.10.2.24
Shields, Carol L., Sara E. Lally, Lauren A. Dalvin, Mandeep S. Sagoo, Marco Pellegrini, Swathi Kaliki, Ahmet Kaan Gündüz, et al. “White Paper on Ophthalmic Imaging for Choroidal Nevus Identification and Transformation into Melanoma.Transl Vis Sci Technol 10, no. 2 (February 5, 2021): 24. https://doi.org/10.1167/tvst.10.2.24.
Shields CL, Lally SE, Dalvin LA, Sagoo MS, Pellegrini M, Kaliki S, et al. White Paper on Ophthalmic Imaging for Choroidal Nevus Identification and Transformation into Melanoma. Transl Vis Sci Technol. 2021 Feb 5;10(2):24.
Shields, Carol L., et al. “White Paper on Ophthalmic Imaging for Choroidal Nevus Identification and Transformation into Melanoma.Transl Vis Sci Technol, vol. 10, no. 2, Feb. 2021, p. 24. Pubmed, doi:10.1167/tvst.10.2.24.
Shields CL, Lally SE, Dalvin LA, Sagoo MS, Pellegrini M, Kaliki S, Gündüz AK, Furuta M, Mruthyunjaya P, Fung AT, Duker JS, Selig SM, Yaghy A, Ferenczy SR, Eydelman MB, Blumenkranz MS. White Paper on Ophthalmic Imaging for Choroidal Nevus Identification and Transformation into Melanoma. Transl Vis Sci Technol. 2021 Feb 5;10(2):24.

Published In

Transl Vis Sci Technol

DOI

EISSN

2164-2591

Publication Date

February 5, 2021

Volume

10

Issue

2

Start / End Page

24

Location

United States

Related Subject Headings

  • Tomography, Optical Coherence
  • Skin Neoplasms
  • Nevus
  • Melanoma
  • Humans
  • Artificial Intelligence
  • 3212 Ophthalmology and optometry
  • 1113 Opthalmology and Optometry
  • 0903 Biomedical Engineering