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Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series

Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive muscular dystrophy with a wide range of manifestations including retinal vasculopathy. This study aimed to analyse retinal vascular involvement in FSHD patients using fundus photographs and optical coherence tomography-angiography...

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Autores principales: Maceroni, Martina, Monforte, Mauro, Cariola, Rossella, Falsini, Benedetto, Rizzo, Stanislao, Savastano, Maria Cristina, Martelli, Francesco, Ricci, Enzo, Bortolani, Sara, Tasca, Giorgio, Minnella, Angelo Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001401/
https://www.ncbi.nlm.nih.gov/pubmed/36900126
http://dx.doi.org/10.3390/diagnostics13050982
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author Maceroni, Martina
Monforte, Mauro
Cariola, Rossella
Falsini, Benedetto
Rizzo, Stanislao
Savastano, Maria Cristina
Martelli, Francesco
Ricci, Enzo
Bortolani, Sara
Tasca, Giorgio
Minnella, Angelo Maria
author_facet Maceroni, Martina
Monforte, Mauro
Cariola, Rossella
Falsini, Benedetto
Rizzo, Stanislao
Savastano, Maria Cristina
Martelli, Francesco
Ricci, Enzo
Bortolani, Sara
Tasca, Giorgio
Minnella, Angelo Maria
author_sort Maceroni, Martina
collection PubMed
description Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive muscular dystrophy with a wide range of manifestations including retinal vasculopathy. This study aimed to analyse retinal vascular involvement in FSHD patients using fundus photographs and optical coherence tomography-angiography (OCT-A) scans, evaluated through artificial intelligence (AI). Thirty-three patients with a diagnosis of FSHD (mean age 50.4 ± 17.4 years) were retrospectively evaluated and neurological and ophthalmological data were collected. Increased tortuosity of the retinal arteries was qualitatively observed in 77% of the included eyes. The tortuosity index (TI), vessel density (VD), and foveal avascular zone (FAZ) area were calculated by processing OCT-A images through AI. The TI of the superficial capillary plexus (SCP) was increased (p < 0.001), while the TI of the deep capillary plexus (DCP) was decreased in FSHD patients in comparison to controls (p = 0.05). VD scores for both the SCP and the DCP results increased in FSHD patients (p = 0.0001 and p = 0.0004, respectively). With increasing age, VD and the total number of vascular branches showed a decrease (p = 0.008 and p < 0.001, respectively) in the SCP. A moderate correlation between VD and EcoRI fragment length was identified as well (r = 0.35, p = 0.048). For the DCP, a decreased FAZ area was found in FSHD patients in comparison to controls (t (53) = −6.89, p = 0.01). A better understanding of retinal vasculopathy through OCT-A can support some hypotheses on the disease pathogenesis and provide quantitative parameters potentially useful as disease biomarkers. In addition, our study validated the application of a complex toolchain of AI using both ImageJ and Matlab to OCT-A angiograms.
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spelling pubmed-100014012023-03-11 Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series Maceroni, Martina Monforte, Mauro Cariola, Rossella Falsini, Benedetto Rizzo, Stanislao Savastano, Maria Cristina Martelli, Francesco Ricci, Enzo Bortolani, Sara Tasca, Giorgio Minnella, Angelo Maria Diagnostics (Basel) Article Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive muscular dystrophy with a wide range of manifestations including retinal vasculopathy. This study aimed to analyse retinal vascular involvement in FSHD patients using fundus photographs and optical coherence tomography-angiography (OCT-A) scans, evaluated through artificial intelligence (AI). Thirty-three patients with a diagnosis of FSHD (mean age 50.4 ± 17.4 years) were retrospectively evaluated and neurological and ophthalmological data were collected. Increased tortuosity of the retinal arteries was qualitatively observed in 77% of the included eyes. The tortuosity index (TI), vessel density (VD), and foveal avascular zone (FAZ) area were calculated by processing OCT-A images through AI. The TI of the superficial capillary plexus (SCP) was increased (p < 0.001), while the TI of the deep capillary plexus (DCP) was decreased in FSHD patients in comparison to controls (p = 0.05). VD scores for both the SCP and the DCP results increased in FSHD patients (p = 0.0001 and p = 0.0004, respectively). With increasing age, VD and the total number of vascular branches showed a decrease (p = 0.008 and p < 0.001, respectively) in the SCP. A moderate correlation between VD and EcoRI fragment length was identified as well (r = 0.35, p = 0.048). For the DCP, a decreased FAZ area was found in FSHD patients in comparison to controls (t (53) = −6.89, p = 0.01). A better understanding of retinal vasculopathy through OCT-A can support some hypotheses on the disease pathogenesis and provide quantitative parameters potentially useful as disease biomarkers. In addition, our study validated the application of a complex toolchain of AI using both ImageJ and Matlab to OCT-A angiograms. MDPI 2023-03-04 /pmc/articles/PMC10001401/ /pubmed/36900126 http://dx.doi.org/10.3390/diagnostics13050982 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Maceroni, Martina
Monforte, Mauro
Cariola, Rossella
Falsini, Benedetto
Rizzo, Stanislao
Savastano, Maria Cristina
Martelli, Francesco
Ricci, Enzo
Bortolani, Sara
Tasca, Giorgio
Minnella, Angelo Maria
Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
title Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
title_full Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
title_fullStr Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
title_full_unstemmed Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
title_short Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
title_sort artificial intelligence for evaluation of retinal vasculopathy in facioscapulohumeral dystrophy using oct angiography: a case series
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001401/
https://www.ncbi.nlm.nih.gov/pubmed/36900126
http://dx.doi.org/10.3390/diagnostics13050982
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