scholarly journals Atrophy Expansion Rates in Stargardt Disease Using Ultra-Widefield Fundus Autofluorescence

2021 ◽  
Vol 1 (1) ◽  
pp. 100005
Author(s):  
Rachael C. Heath Jeffery ◽  
Jennifer A. Thompson ◽  
Johnny Lo ◽  
Tina M. Lamey ◽  
Terri L. McLaren ◽  
...  
2017 ◽  
Vol 135 (11) ◽  
pp. 1232 ◽  
Author(s):  
Rupert W. Strauss ◽  
Beatriz Muñoz ◽  
Alexander Ho ◽  
Anamika Jha ◽  
Michel Michaelides ◽  
...  

2012 ◽  
Vol 130 (10) ◽  
pp. 1354 ◽  
Author(s):  
Catherine A. Cukras ◽  
Wai T. Wong ◽  
Rafael Caruso ◽  
Denise Cunningham ◽  
Wadih Zein ◽  
...  

2020 ◽  
Vol 34 (3) ◽  
pp. 3693-3714 ◽  
Author(s):  
Yuan Fang ◽  
Alexander Tschulakow ◽  
Tatjana Taubitz ◽  
Barbara Illing ◽  
Antje Biesemeier ◽  
...  

2020 ◽  
Vol 61 (4) ◽  
pp. 36 ◽  
Author(s):  
Janet S. Sunness ◽  
Abraham Ifrah ◽  
Robert Wolf ◽  
Carol A. Applegate ◽  
Janet R. Sparrow

2010 ◽  
Vol 41 (1) ◽  
pp. 48-53 ◽  
Author(s):  
Andrea Sodi ◽  
Alessandro Bini ◽  
Ilaria Passerini ◽  
Simona Forconi ◽  
Ugo Menchini ◽  
...  

2013 ◽  
Vol 54 (10) ◽  
pp. 6820 ◽  
Author(s):  
Tobias Duncker ◽  
Winston Lee ◽  
Stephen H. Tsang ◽  
Jonathan P. Greenberg ◽  
Jana Zernant ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jason Charng ◽  
Di Xiao ◽  
Maryam Mehdizadeh ◽  
Mary S. Attia ◽  
Sukanya Arunachalam ◽  
...  

Abstract Stargardt disease is one of the most common forms of inherited retinal disease and leads to permanent vision loss. A diagnostic feature of the disease is retinal flecks, which appear hyperautofluorescent in fundus autofluorescence (FAF) imaging. The size and number of these flecks increase with disease progression. Manual segmentation of flecks allows monitoring of disease, but is time-consuming. Herein, we have developed and validated a deep learning approach for segmenting these Stargardt flecks (1750 training and 100 validation FAF patches from 37 eyes with Stargardt disease). Testing was done in 10 separate Stargardt FAF images and we observed a good overall agreement between manual and deep learning in both fleck count and fleck area. Longitudinal data were available in both eyes from 6 patients (average total follow-up time 4.2 years), with both manual and deep learning segmentation performed on all (n = 82) images. Both methods detected a similar upward trend in fleck number and area over time. In conclusion, we demonstrated the feasibility of utilizing deep learning to segment and quantify FAF lesions, laying the foundation for future studies using fleck parameters as a trial endpoint.


2009 ◽  
Vol 50 (8) ◽  
pp. 3953 ◽  
Author(s):  
Nuno L. Gomes ◽  
Vivienne C. Greenstein ◽  
Joshua N. Carlson ◽  
Stephen H. Tsang ◽  
R. Theodore Smith ◽  
...  

Retina ◽  
2016 ◽  
Vol 36 (6) ◽  
pp. 1216-1221 ◽  
Author(s):  
Laura Kuehlewein ◽  
Amir H. Hariri ◽  
Alexander Ho ◽  
Laurie Dustin ◽  
Yulia Wolfson ◽  
...  

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 812
Author(s):  
Virginie M.M. Buhler ◽  
Lieselotte Berger ◽  
André Schaller ◽  
Martin S. Zinkernagel ◽  
Sebastian Wolf ◽  
...  

We genetically characterized 22 Swiss patients who had been diagnosed with Stargardt disease after clinical examination. We identified in 11 patients (50%) pathogenic bi-allelic ABCA4 variants, c.1760+2T>C and c.4496T>C being novel. The dominantly inherited pathogenic ELOVL4 c.810C>G p.(Tyr270*) and PRPH2-c.422A>G p.(Tyr141Cys) variants were identified in eight (36%) and three patients (14%), respectively. All patients harboring the ELOVL4 c.810C>G p.(Tyr270*) variant originated from the same small Swiss area, identifying a founder mutation. In the ABCA4 and ELOVL4 cohorts, the clinical phenotypes of “flecks”, “atrophy”, and “bull”s eye like” were observed by fundus examination. In the small number of patients harboring the pathogenic PRPH2 variant, we could observe both “flecks” and “atrophy” clinical phenotypes. The onset of disease, progression of visual acuity and clinical symptoms, inheritance patterns, fundus autofluorescence, and optical coherence tomography did not allow discrimination between the genetically heterogeneous Stargardt patients. The genetic heterogeneity observed in the relatively small Swiss population should prompt systematic genetic testing of clinically diagnosed Stargardt patients. The resulting molecular diagnostic is required to prevent potentially harmful vitamin A supplementation, to provide genetic counseling with respect to inheritance, and to schedule appropriate follow-up visits in the presence of increased risk of choroidal neovascularization.


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