{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:19:36Z","timestamp":1787026776497,"version":"build-2736575974"},"reference-count":192,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T00:00:00Z","timestamp":1681776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:p>\n                    Alzheimer\u2019s disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of\n                    <jats:italic>in vivo<\/jats:italic>\n                    gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.\n                  <\/jats:p>","DOI":"10.3389\/fnagi.2023.1094233","type":"journal-article","created":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T01:37:37Z","timestamp":1681781857000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":47,"title":["Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer\u2019s disease?"],"prefix":"10.3389","volume":"15","author":[{"given":"Sophia","family":"Mirkin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benedict C.","family":"Albensi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,4,18]]},"reference":[{"key":"ref1","year":"2021"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"2247","DOI":"10.1001\/jama.2020.23698","article-title":"Neurodegenerative dementias are differentiated on PET scans","volume":"324","author":"Abbasi","year":"2020","journal-title":"JAMA"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1038\/s41569-022-00717-6","article-title":"Repurposing drugs to treat cardiovascular disease in the era of precision medicine","volume":"19","author":"Abdelsayed","year":"2022","journal-title":"Nat. Rev. Cardiol."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1773","DOI":"10.1038\/s41591-022-01981-2","article-title":"Multimodal biomedical AI","volume":"28","author":"Acosta","year":"2022","journal-title":"Nat. Med."},{"key":"ref5","author":"Adamo","year":"2020"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"e7702","DOI":"10.7717\/peerj.7702","article-title":"The impact of artificial intelligence in medicine on the future role of the physician","volume":"7","author":"Ahuja","year":"2019","journal-title":"PeerJ"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1016\/j.jalz.2011.03.008","article-title":"The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease","volume":"7","author":"Albert","year":"2011","journal-title":"Alzheimers Dement."},{"key":"ref8","first-page":"91","article-title":"For the Alzheimer\u2019s Disease Neuroimaging Initiative, Subasi a. automatic detection of Alzheimer disease based on histogram and random forest","volume-title":"IFMBE proceedings","author":"Alickovic","year":"2020"},{"key":"ref9","year":"2022"},{"key":"ref10","volume-title":"The use of MRI and PET for clinical diagnosis of dementia and investigation of cognitive impairment: a consensus Report","author":"Neuroimaging Work","year":"2003"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1007\/s13311-016-0474-y","article-title":"Amyloid imaging: poised for integration into medical practice","volume":"14","author":"Anand","year":"2017","journal-title":"Neurotherapeutics"},{"key":"ref12","volume-title":"Dementia: assessment, management and support for people living with dementia and their carers","year":"2018"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"700","DOI":"10.1002\/alz.12638","article-title":"Alzheimer\u2019s disease facts and figures","volume":"18","year":"2022","journal-title":"Alzheimers Dement."},{"key":"ref14","doi-asserted-by":"publisher","first-page":"22252","DOI":"10.1038\/s41598-020-79243-9","article-title":"Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging","volume":"10","author":"Bae","year":"2020","journal-title":"Sci. Rep."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"3837","DOI":"10.1007\/s00330-020-07480-7","article-title":"Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation","volume":"31","author":"Baltruschat","year":"2021","journal-title":"Eur. Radiol."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"624330","DOI":"10.3389\/fnagi.2021.624330","article-title":"PET neuroimaging of Alzheimer's disease: radiotracers and their utility in clinical research","volume":"13","author":"Bao","year":"2021","journal-title":"Front. Aging Neurosci."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/1471-2377-12-33","article-title":"Is MRI better than CT for detecting a vascular component to dementia? A systematic review and meta-analysis","volume":"12","author":"Beynon","year":"2012","journal-title":"BMC Neurol."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1186\/s40824-022-00320-3","article-title":"Functional insights from targeted imaging BACE1: the first near-infrared fluorescent probe for Alzheimer\u2019s disease diagnosis","volume":"26","author":"Bi","year":"2022","journal-title":"Biomater. Res."},{"key":"ref19","first-page":"11","article-title":"Hippocampal volume in normal aging and traumatic brain injury","volume":"18","author":"Bigler","year":"1997","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"ref20","doi-asserted-by":"publisher","first-page":"20200037","DOI":"10.1259\/bjro.20200037","article-title":"Artificial intelligence in radiology: does it impact medical students preference for radiology as their future career?","volume":"2","author":"Bin Dahmash","year":"2020","journal-title":"BJR Open"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"827","DOI":"10.1097\/rct.0000000000000435","article-title":"Accelerated brain atrophy on serial computed tomography: potential marker of the progression of Alzheimer disease","volume":"40","author":"Bin Zahid","year":"2016","journal-title":"J. Comput. Assist. Tomogr."},{"key":"ref22","doi-asserted-by":"publisher","first-page":"e12102","DOI":"10.1002\/trc2.12102","article-title":"Evaluating the Alzheimer's disease data landscape","volume":"6","author":"Birkenbihl","year":"2020","journal-title":"Alzheimers Dement (N Y)"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"231","DOI":"10.3390\/diagnostics10040231","article-title":"Artificial intelligence in radiology\u2014ethical considerations","volume":"10","author":"Brady","year":"2020","journal-title":"Diagnostics (Basel)"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"e12098","DOI":"10.1002\/trc2.12098","article-title":"CCCDTD5: clinical role of neuroimaging and liquid biomarkers in patients with cognitive impairment","volume":"6","author":"Brisson","year":"2020","journal-title":"Alzheimers Dement (N Y)"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"5888","DOI":"10.1038\/s41380-021-01263-2","article-title":"For the Alzheimer\u2019s disease Neuroimaging I. 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Disord."},{"key":"ref29","year":"2022"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.jalz.2012.10.006","article-title":"Research and standardization in Alzheimer\u2019s trials: reaching international consensus","volume":"9","author":"Carrillo","year":"2013","journal-title":"Alzheimers Dement."},{"key":"ref31","doi-asserted-by":"publisher","first-page":"25","DOI":"10.3389\/fninf.2020.00025","article-title":"A machine learning approach for the differential diagnosis of Alzheimer and vascular dementia fed by MRI selected features","volume":"14","author":"Castellazzi","year":"2020","journal-title":"Front. Neuroinform."},{"key":"ref32","doi-asserted-by":"publisher","first-page":"1293","DOI":"10.1007\/s00415-018-9016-3","article-title":"Magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment","volume":"266","author":"Chandra","year":"2019","journal-title":"J. Neurol."},{"key":"ref33","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1002\/alz.12675","article-title":"Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease","volume":"19","author":"Chang","year":"2023","journal-title":"Alzheimers Dement."},{"key":"ref34","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1148\/radiol.2018180940","article-title":"Ultra-low-dose (18)F-Florbetaben amyloid PET imaging using deep learning with multi-contrast MRI inputs","volume":"290","author":"Chen","year":"2019","journal-title":"Radiology"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"100","DOI":"10.2967\/jnumed.118.209130","article-title":"Impact of reference and target region selection on amyloid PET SUV ratios in the phase 1b PRIME study of Aducanumab","volume":"60","author":"Chiao","year":"2019","journal-title":"J. Nucl. 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Ther."},{"key":"ref43","doi-asserted-by":"publisher","first-page":"15593258221078392","DOI":"10.1177\/15593258221078392","article-title":"Treatment of early-stage Alzheimer's disease with CT scans of the brain: a case report","volume":"20","author":"Cuttler","year":"2022","journal-title":"Dose Response"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"789","DOI":"10.3233\/jad-180982","article-title":"White matter hyperintensities in Alzheimer's disease: a lesion probability mapping study","volume":"68","author":"Damulina","year":"2019","journal-title":"J. Alzheimers Dis."},{"key":"ref45","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1053\/j.sult.2020.08.010","article-title":"FDG-PET imaging of dementia and neurodegenerative disease","volume":"41","author":"Dave","year":"2020","journal-title":"Semin. 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Gen."},{"key":"ref49","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1148\/radiol.2018180958","article-title":"A deep learning model to predict a diagnosis of Alzheimer disease by using (18)F-FDG PET of the brain","volume":"290","author":"Ding","year":"2019","journal-title":"Radiology"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"1487","DOI":"10.1007\/s00259-018-4032-1","article-title":"Diagnostic utility of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) in asymptomatic subjects at increased risk for Alzheimer\u2019s disease","volume":"45","author":"Drzezga","year":"2018","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"ref51","doi-asserted-by":"publisher","first-page":"21","DOI":"10.3389\/fneur.2020.00021","article-title":"Identifying morphological patterns of hippocampal atrophy in patients with mesial temporal lobe epilepsy and Alzheimer disease","volume":"11","author":"Duan","year":"2020","journal-title":"Front. Neurol."},{"key":"ref52","doi-asserted-by":"publisher","first-page":"e46","DOI":"10.1212\/WNL.0000000000009724","article-title":"ATN classification and clinical progression in subjective cognitive decline: the SCIENCe project","volume":"95","author":"Ebenau","year":"2020","journal-title":"Neurology"},{"key":"ref53","doi-asserted-by":"publisher","first-page":"e210097","DOI":"10.1148\/ryai.2021210097","article-title":"Toward generalizability in the deployment of artificial intelligence in radiology: role of computation stress testing to overcome underspecification","volume":"3","author":"Eche","year":"2021","journal-title":"Radiol Artif Intell"},{"key":"ref54","doi-asserted-by":"publisher","first-page":"e12031","DOI":"10.1002\/dad2.12031","article-title":"Evaluation of the ATN model in a longitudinal memory clinic sample with different underlying disorders","volume":"13","author":"Eckerstr\u00f6m","year":"2021","journal-title":"Alzheimers Dement (Amst)"},{"key":"ref55","author":"Emmady","year":"2022"},{"key":"ref56","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1007\/s00330-009-1581-5","article-title":"Volume changes in Alzheimer's disease and mild cognitive impairment: cognitive associations","volume":"20","author":"Evans","year":"2010","journal-title":"Eur. Radiol."},{"key":"ref57","doi-asserted-by":"publisher","first-page":"100583","DOI":"10.1016\/j.eclinm.2020.100583","article-title":"Linguistic markers predict onset of Alzheimer's disease","volume":"28","author":"Eyigoz","year":"2020","journal-title":"EClinicalMedicine"},{"key":"ref58","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.3390\/diagnostics11081473","article-title":"Artificial intelligence for Alzheimer's disease: promise or challenge?","volume":"11","author":"Fabrizio","year":"2021","journal-title":"Diagnostics"},{"key":"ref59","author":"Farr","year":"2019"},{"key":"ref60","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/s43681-022-00161-9","article-title":"Deep learning in radiology: ethics of data and on the value of algorithm transparency, interpretability and explainability","volume":"3","author":"Fernandez-Quilez","year":"2023","journal-title":"AI Ethics"},{"key":"ref61","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1590\/s1807-59322011001300003","article-title":"Neuroimaging in Alzheimer's disease: current role in clinical practice and potential future applications","volume":"66","author":"Ferreira","year":"2011","journal-title":"Clinics (Sao Paulo)"},{"key":"ref62","doi-asserted-by":"publisher","first-page":"46263","DOI":"10.1038\/srep46263","article-title":"Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications","volume":"7","author":"Ferreira","year":"2017","journal-title":"Sci. Rep."},{"key":"ref63","doi-asserted-by":"publisher","first-page":"2082","DOI":"10.1093\/brain\/awz136","article-title":"Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy","volume":"142","author":"Firth","year":"2019","journal-title":"Brain"},{"key":"ref64","first-page":"313","article-title":"Heuristic scoring method utilizing FDG-PET statistical parametric mapping in the evaluation of suspected Alzheimer disease and frontotemporal lobar degeneration","volume":"11","author":"Ford","year":"2021","journal-title":"Am. J. Nucl. Med. Mol. Imaging"},{"key":"ref65","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1016\/j.jalz.2015.05.010","article-title":"Brain collection, standardized neuropathologic assessment, and comorbidity in Alzheimer's disease Neuroimaging initiative 2 participants","volume":"11","author":"Franklin","year":"2015","journal-title":"Alzheimers Dement."},{"key":"ref66","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1002\/alz.12032","article-title":"Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning","volume":"16","author":"Franzmeier","year":"2020","journal-title":"Alzheimers Dement."},{"key":"ref67","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1136\/jnnp.70.6.711","article-title":"Structural imaging in the clinical diagnosis of Alzheimer's disease: problems and tools","volume":"70","author":"Frisoni","year":"2001","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref68","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1038\/nrneurol.2009.215","article-title":"The clinical use of structural MRI in Alzheimer disease","volume":"6","author":"Frisoni","year":"2010","journal-title":"Nat. Rev. Neurol."},{"key":"ref69","doi-asserted-by":"publisher","first-page":"110231","DOI":"10.1016\/j.ejrad.2022.110231","article-title":"Artificial intelligence and multidisciplinary team meetings; a communication challenge for radiologists' sense of agency and position as spider in a web?","volume":"155","author":"Galsgaard","year":"2022","journal-title":"Eur. J. Radiol."},{"key":"ref70","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ijcce.2021.12.002","article-title":"A review of the application of deep learning in the detection of Alzheimer's disease","volume":"3","author":"Gao","year":"2022","journal-title":"Int. J. Cogn. Comput. Eng."},{"key":"ref71","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1002\/alz.12410","article-title":"White matter hyperintensity topography in Alzheimer's disease and links to cognition","volume":"18","author":"Garnier-Crussard","year":"2022","journal-title":"Alzheimers Dement."},{"key":"ref72","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1377\/hlthaff.2017.1624","article-title":"Precision medicine: from science to value","volume":"37","author":"Ginsburg","year":"2018","journal-title":"Health Aff (Millwood)"},{"key":"ref73","doi-asserted-by":"publisher","first-page":"2172","DOI":"10.1177\/0271678X18783628","article-title":"Quantification of [(18)F]florbetapir: a test-retest tracer kinetic modelling study","volume":"39","author":"Golla","year":"2019","journal-title":"J. Cereb. Blood Flow Metab."},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23094962","article-title":"Biomarkers for Alzheimer's disease in the current state: a narrative review","volume":"23","author":"Gunes","year":"2022","journal-title":"Int. J. Mol. Sci."},{"key":"ref75","doi-asserted-by":"publisher","first-page":"e2113641119","DOI":"10.1073\/pnas.2113641119","article-title":"Amyloid-\u03b2 and tau pathologies relate to distinctive brain dysconnectomics in preclinical autosomal-dominant Alzheimer\u2019s disease","volume":"119","author":"Guzm\u00e1n-V\u00e9lez","year":"2022","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"ref76","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1001\/jamaneurol.2019.1424","article-title":"Association of Amyloid and tau with Cognition in preclinical Alzheimer disease: a longitudinal study","volume":"76","author":"Hanseeuw","year":"2019","journal-title":"JAMA Neurol."},{"key":"ref77","doi-asserted-by":"publisher","first-page":"2669","DOI":"10.1002\/alz.12756","article-title":"The Alzheimer's Association appropriate use recommendations for blood biomarkers in Alzheimer's disease","volume":"18","author":"Hansson","year":"2022","journal-title":"Alzheimers Dement."},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph18042086","article-title":"Efficacy of artificial-intelligence-driven differential-diagnosis list on the diagnostic accuracy of physicians: an open-label randomized controlled study","volume":"18","author":"Harada","year":"2021","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref79","doi-asserted-by":"publisher","first-page":"20190840","DOI":"10.1259\/bjr.20190840","article-title":"Artificial intelligence in diagnostic imaging: impact on the radiography profession","volume":"93","author":"Hardy","year":"2020","journal-title":"Br. J. Radiol."},{"key":"ref80","first-page":"237","article-title":"Medical ethics in radiography","volume":"90","author":"Haskell","year":"2019","journal-title":"Radiol. Technol."},{"key":"ref81","doi-asserted-by":"publisher","first-page":"100085","DOI":"10.1016\/j.ynirp.2022.100085","article-title":"The association between head motion during functional magnetic resonance imaging and executive functioning in older adults","volume":"2","author":"Hausman","year":"2022","journal-title":"Neuroimage Rep."},{"key":"ref82","first-page":"1","article-title":"The appropriate use of neuroimaging in the diagnostic work-up of dementia: an evidence-based analysis","volume":"14","year":"2014","journal-title":"Ont Health Technol Assess Ser"},{"key":"ref83","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1006\/nimg.2002.1208","article-title":"Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET","volume":"17","author":"Herholz","year":"2002","journal-title":"NeuroImage"},{"key":"ref84","volume-title":"Learning radiology: Recognizing the basics E-book","author":"Herring","year":"2011"},{"key":"ref85","year":"2016"},{"key":"ref86","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1038\/s43856-022-00133-4","article-title":"A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease","volume":"2","author":"Inglese","year":"2022","journal-title":"Commun Med (Lond)"},{"key":"ref87","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1093\/brain\/awv326","article-title":"Is amyloid-\u03b2 harmful to the brain?","volume":"139","author":"Jagust","year":"2016","journal-title":"Brain Commun"},{"key":"ref88","doi-asserted-by":"publisher","first-page":"e2136553","DOI":"10.1001\/jamanetworkopen.2021.36553","article-title":"Performance of machine learning algorithms for predicting progression to dementia in memory clinic patients","volume":"4","author":"James","year":"2021","journal-title":"JAMA Netw. Open"},{"key":"ref89","doi-asserted-by":"publisher","first-page":"e23461","DOI":"10.7759\/cureus.23461","article-title":"The potential therapeutic effects of low-dose ionizing radiation in Alzheimer's disease","volume":"14","author":"Jebelli","year":"2022","journal-title":"Cureus"},{"key":"ref90","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1001\/archneur.63.5.674","article-title":"Neuropathologic outcome of mild cognitive impairment following progression to clinical dementia","volume":"63","author":"Jicha","year":"2006","journal-title":"Arch. 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