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Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review.
Borchert, Robin J; Azevedo, Tiago; Badhwar, AmanPreet; Bernal, Jose; Betts, Matthew; Bruffaerts, Rose; Burkhart, Michael C; Dewachter, Ilse; Gellersen, Helena M; Low, Audrey; Lourida, Ilianna; Machado, Luiza; Madan, Christopher R; Malpetti, Maura; Mejia, Jhony; Michopoulou, Sofia; Muñoz-Neira, Carlos; Pepys, Jack; Peres, Marion; Phillips, Veronica; Ramanan, Siddharth; Tamburin, Stefano; Tantiangco, Hanz M; Thakur, Lokendra; Tomassini, Alessandro; Vipin, Ashwati; Tang, Eugene; Newby, Danielle; Ranson, Janice M; Llewellyn, David J; Veldsman, Michele; Rittman, Timothy.
Afiliación
  • Borchert RJ; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
  • Azevedo T; Department of Radiology, University of Cambridge, Cambridge, UK.
  • Badhwar A; Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
  • Bernal J; Department of Pharmacology and Physiology, University of Montreal, Montreal, Canada.
  • Betts M; Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada.
  • Bruffaerts R; Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.
  • Burkhart MC; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
  • Dewachter I; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
  • Gellersen HM; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
  • Low A; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
  • Lourida I; Center for Behavioral Brain Sciences, University of Magdeburg, Magdeburg, Germany.
  • Machado L; Computational Neurology, Experimental Neurobiology Unit, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
  • Madan CR; Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium.
  • Malpetti M; Department of Psychology, University of Cambridge, Cambridge, UK.
  • Mejia J; Biomedical Research Institute, Hasselt University, Diepenbeek, Belgium.
  • Michopoulou S; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
  • Muñoz-Neira C; Department of Psychology, University of Cambridge, Cambridge, UK.
  • Pepys J; Department of Psychiatry, University of Cambridge, Cambridge, UK.
  • Peres M; University of Exeter Medical School, Exeter, UK.
  • Phillips V; Department of Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
  • Ramanan S; School of Psychology, University of Nottingham, Nottingham, UK.
  • Tamburin S; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
  • Tantiangco HM; Department of Biomedical Engineering, Universidad de Los Andes, Bogotá, Colombia.
  • Thakur L; Imaging Physics, University Hospital Southampton NHS Foundation Trust, Southampton, UK.
  • Tomassini A; Research into Memory, Brain sciences and dementia Group (ReMemBr Group), Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Vipin A; Artificial Intelligence & Computational Neuroscience Group (AICN Group), Sheffield Institute for Translational Neuroscience (SITraN), Department of Neuroscience, University of Sheffield, Sheffield, UK.
  • Tang E; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
  • Newby D; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
  • Ranson JM; University of Cambridge Medical Library, Cambridge, UK.
  • Llewellyn DJ; Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
  • Veldsman M; Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
  • Rittman T; Information School, University of Sheffield, Sheffield, UK.
Alzheimers Dement ; 19(12): 5885-5904, 2023 Dec.
Article en En | MEDLINE | ID: mdl-37563912
INTRODUCTION: Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia. METHODS: We systematically reviewed studies reporting AI for neuroimaging in diagnosis and/or prognosis of cognitive neurodegenerative diseases. RESULTS: A total of 255 studies were identified. Most studies relied on the Alzheimer's Disease Neuroimaging Initiative dataset. Algorithmic classifiers were the most commonly used AI method (48%) and discriminative models performed best for differentiating Alzheimer's disease from controls. The accuracy of algorithms varied with the patient cohort, imaging modalities, and stratifiers used. Few studies performed validation in an independent cohort. DISCUSSION: The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. We make recommendations to improve model validation including addressing key clinical questions, providing sufficient description of AI methods and validating findings in independent datasets. Collaborative approaches between experts in AI and medicine will help achieve the promising potential of AI tools in practice. HIGHLIGHTS: There has been a rapid expansion in the use of machine learning for diagnosis and prognosis in neurodegenerative disease Most studies (71%) relied on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with no other individual dataset used more than five times There has been a recent rise in the use of more complex discriminative models (e.g., neural networks) that performed better than other classifiers for classification of AD vs healthy controls We make recommendations to address methodological considerations, addressing key clinical questions, and validation We also make recommendations for the field more broadly to standardize outcome measures, address gaps in the literature, and monitor sources of bias.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Neurodegenerativas / Enfermedad de Alzheimer Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Alzheimers Dement Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Neurodegenerativas / Enfermedad de Alzheimer Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Alzheimers Dement Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos