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Interlenghi M, Sborgia G, Venturi A, Sardone R, Pastore V, Boscia G, Landini L, Scotti G, Niro A, Moscara F, Bandi L, Salvatore C, Castiglioni I. A Radiomic-Based Machine Learning System to Diagnose Age-Related Macular Degeneration from Ultra-Widefield Fundus Retinography. Diagnostics (Basel) 2023; 13:2965. [PMID: 37761333 PMCID: PMC10528426 DOI: 10.3390/diagnostics13182965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 09/04/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023] Open
Abstract
The present study was conducted to investigate the potential of radiomics to develop an explainable AI-based system to be applied to ultra-widefield fundus retinographies (UWF-FRTs) with the objective of predicting the presence of the early signs of Age-related Macular Degeneration (AMD) and stratifying subjects with low- versus high-risk of AMD. The ultimate aim was to provide clinicians with an automatic classifier and a signature of objective quantitative image biomarkers of AMD. The use of Machine Learning (ML) and radiomics was based on intensity and texture analysis in the macular region, detected by a Deep Learning (DL)-based macular detector. Two-hundred and twenty six UWF-FRTs were retrospectively collected from two centres and manually annotated to train and test the algorithms. Notably, the combination of the ML-based radiomics model and the DL-based macular detector reported 93% sensitivity and 74% specificity when applied to the data of the centre used for external testing, capturing explainable features associated with drusen or pigmentary abnormalities. In comparison to the human operator's annotations, the system yielded a 0.79 Cohen κ, demonstrating substantial concordance. To our knowledge, these results are the first provided by a radiomic approach for AMD supporting the suitability of an explainable feature extraction method combined with ML for UWF-FRT.
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Affiliation(s)
- Matteo Interlenghi
- DeepTrace Technologies S.R.L., 20122 Milan, Italy; (M.I.); (A.V.); (L.B.)
| | - Giancarlo Sborgia
- Department of Medical Science, Neuroscience and Sense Organs, Eye Clinic, University of Bari Aldo Moro, 70121 Bari, Italy; (G.S.); (V.P.); (G.B.); (L.L.); (G.S.); (F.M.)
| | - Alessandro Venturi
- DeepTrace Technologies S.R.L., 20122 Milan, Italy; (M.I.); (A.V.); (L.B.)
| | - Rodolfo Sardone
- National Institute of Gastroenterology—IRCCS “Saverio de Bellis”, 70013 Castellana Grotte, Italy;
- Unit of Statistics and Epidemiology, Local Healthcare Authority of Taranto, 74121 Taranto, Italy
| | - Valentina Pastore
- Department of Medical Science, Neuroscience and Sense Organs, Eye Clinic, University of Bari Aldo Moro, 70121 Bari, Italy; (G.S.); (V.P.); (G.B.); (L.L.); (G.S.); (F.M.)
| | - Giacomo Boscia
- Department of Medical Science, Neuroscience and Sense Organs, Eye Clinic, University of Bari Aldo Moro, 70121 Bari, Italy; (G.S.); (V.P.); (G.B.); (L.L.); (G.S.); (F.M.)
| | - Luca Landini
- Department of Medical Science, Neuroscience and Sense Organs, Eye Clinic, University of Bari Aldo Moro, 70121 Bari, Italy; (G.S.); (V.P.); (G.B.); (L.L.); (G.S.); (F.M.)
| | - Giacomo Scotti
- Department of Medical Science, Neuroscience and Sense Organs, Eye Clinic, University of Bari Aldo Moro, 70121 Bari, Italy; (G.S.); (V.P.); (G.B.); (L.L.); (G.S.); (F.M.)
| | - Alfredo Niro
- Eye Clinic, Hospital “SS. Annunziata”, ASL Taranto, 74121 Taranto, Italy;
| | - Federico Moscara
- Department of Medical Science, Neuroscience and Sense Organs, Eye Clinic, University of Bari Aldo Moro, 70121 Bari, Italy; (G.S.); (V.P.); (G.B.); (L.L.); (G.S.); (F.M.)
| | - Luca Bandi
- DeepTrace Technologies S.R.L., 20122 Milan, Italy; (M.I.); (A.V.); (L.B.)
| | - Christian Salvatore
- DeepTrace Technologies S.R.L., 20122 Milan, Italy; (M.I.); (A.V.); (L.B.)
- Department of Science, Technology and Society, University School for Advanced Studies IUSS Pavia, 27100 Pavia, Italy
| | - Isabella Castiglioni
- Department of Physics “Giuseppe Occhialini”, University of Milan-Bicocca, 20126 Milan, Italy;
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