Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies
Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer’s...
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2024-12-01
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| author | Rahul Kumar Ethan Waisberg Joshua Ong Phani Paladugu Dylan Amiri Jeremy Saintyl Jahnavi Yelamanchi Robert Nahouraii Ram Jagadeesan Alireza Tavakkoli |
| author_facet | Rahul Kumar Ethan Waisberg Joshua Ong Phani Paladugu Dylan Amiri Jeremy Saintyl Jahnavi Yelamanchi Robert Nahouraii Ram Jagadeesan Alireza Tavakkoli |
| author_sort | Rahul Kumar |
| collection | DOAJ |
| description | Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques—Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging—in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. Despite challenges such as technical variability, data privacy concerns, and regulatory barriers, the potential of AI-enhanced neuroimaging to revolutionize early diagnosis and personalized treatment in neurodegenerative and neuro-ophthalmic disorders is immense. This review underscores the importance of ongoing efforts to validate, standardize, and implement these technologies to maximize their clinical impact. |
| format | Article |
| id | doaj-art-f82c8a4967f644f1817b6feb64921ff1 |
| institution | Kabale University |
| issn | 2076-3425 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Brain Sciences |
| spelling | doaj-art-f82c8a4967f644f1817b6feb64921ff12024-12-27T14:14:57ZengMDPI AGBrain Sciences2076-34252024-12-011412126610.3390/brainsci14121266Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative PathologiesRahul Kumar0Ethan Waisberg1Joshua Ong2Phani Paladugu3Dylan Amiri4Jeremy Saintyl5Jahnavi Yelamanchi6Robert Nahouraii7Ram Jagadeesan8Alireza Tavakkoli9Department of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, 1600 NW 10th Ave, Miami, FL 33136, USADepartment of Clinical Neurosciences, University of Cambridge, Downing Street, Cambridge CB2 3EH, UKDepartment of Ophthalmology and Visual Sciences, University of Michigan Kellogg Eye Center, 1000 Wall St, Ann Arbor, MI 48105, USASidney Kimmel Medical College, Thomas Jefferson University, 1025 Walnut St, Philadelphia, PA 19107, USADepartment of Biology, University of Miami, 1301 Memorial Dr, Coral Gables, FL 33146, USADepartment of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, 1600 NW 10th Ave, Miami, FL 33136, USATandon School of Engineering, New York University, 6 MetroTech Center, Brooklyn, NY 11201, USAMecklenburg Neurology Group, 3541 Randolph Rd #301, Charlotte, NC 28211, USAWhiting School of Engineering, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USAHuman-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada, Reno, 1664 N Virginia St, Reno, NV 89557, USAAdvancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques—Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging—in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. Despite challenges such as technical variability, data privacy concerns, and regulatory barriers, the potential of AI-enhanced neuroimaging to revolutionize early diagnosis and personalized treatment in neurodegenerative and neuro-ophthalmic disorders is immense. This review underscores the importance of ongoing efforts to validate, standardize, and implement these technologies to maximize their clinical impact.https://www.mdpi.com/2076-3425/14/12/1266AI-driven ophthalmologyAI-driven therapyneurodegenerative diseasesmachine learningneural modulation |
| spellingShingle | Rahul Kumar Ethan Waisberg Joshua Ong Phani Paladugu Dylan Amiri Jeremy Saintyl Jahnavi Yelamanchi Robert Nahouraii Ram Jagadeesan Alireza Tavakkoli Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies Brain Sciences AI-driven ophthalmology AI-driven therapy neurodegenerative diseases machine learning neural modulation |
| title | Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies |
| title_full | Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies |
| title_fullStr | Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies |
| title_full_unstemmed | Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies |
| title_short | Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies |
| title_sort | artificial intelligence based methodologies for early diagnostic precision and personalized therapeutic strategies in neuro ophthalmic and neurodegenerative pathologies |
| topic | AI-driven ophthalmology AI-driven therapy neurodegenerative diseases machine learning neural modulation |
| url | https://www.mdpi.com/2076-3425/14/12/1266 |
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