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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10001401 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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