MRI Characterizes the Progressive Course of AD and Predicts Conversion to Alzheimer's Dementia 24 Months Before Probable Diagnosis

Topic: Amyloid, tau and blood-test diagnosis

There is no disease-modifying treatment currently available for AD, one of the more impacting neurodegenerative diseases affecting more than 47.5 million people worldwide. The definition of new approaches for the design of proper clinical trials is highly demanded in order to achieve non-confounding results and assess more effective treatment. In this study, a cohort of 200 subjects was obtained from the Alzheimer's Disease Neuroimaging Initiative. Subjects were followed-up for 24 months, and classified as AD (50), progressive-MCI to AD (50), stable-MCI (50), and cognitively normal (50). Structural T1-weighted MRI brain studies and neuropsychological measures of these subjects were used to train and optimize an artificial-intelligence classifier to distinguish mild-AD patients who need treatment (AD + pMCI) from subjects who do not need treatment (sMCI + CN). The classifier was able to distinguish between the two groups 24 months before AD definite diagnosis using a combination of MRI brain studies and specific neuropsychological measures, with 85% accuracy, 83% sensitivity, and 87% specificity. The combined-approach model outperformed the classification using MRI data alone (72% classification accuracy, 69% sensitivity, and 75% specificity). The patterns of morphological abnormalities localized in the temporal pole and medial-temporal cortex might be considered as biomarkers of clinical progression and evolution. These regions can be already observed 24 months before AD definite diagnosis. The best neuropsychological predictors mainly included measures of functional abilities, memory and learning, working memory, language, visuoconstructional reasoning, and complex attention, with a particular focus on some of the sub-scores of the FAQ and AVLT tests.

@article{salvatore2018-29881340,
  author  = {Salvatore, C. and Cerasa, A. and Castiglioni, I.},
  title   = {{MRI Characterizes the Progressive Course of AD and Predicts Conversion to Alzheimer's Dementia 24 Months Before Probable Diagnosis}},
  journal = {Frontiers in aging neuroscience},
  year    = {2018},
  doi     = {10.3389/fnagi.2018.00135},
  pmid    = {29881340},
  url     = {https://doi.org/10.3389/fnagi.2018.00135}
}

Key findings

• The definition of new approaches for the design of proper clinical trials is highly demanded in order to achieve non-confounding results and assess more effective treatment.

Why it matters

This study trained an artificial intelligence classifier on MRI and neuropsychological measures to distinguish mild Alzheimer's disease patients who need treatment from those who do not, 24 months before definite diagnosis. The combined approach reached 85% accuracy and outperformed classification using MRI data alone.

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Study details

• Participants200
• Evidence strengthModerate

Read the original

• DOI: 10.3389/fnagi.2018.00135
• PubMed: 29881340
• Original source →
• Free full text: Frontiers in Aging Neuroscience →

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Studies this one cites

Referenced by this study and also in the alzhub library, so you can read them here. Showing 12 of 15.

• The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods Journal of Magnetic Resonance Imaging · 2008-02-26 · usefulness score 72/100 · Brain scans and imaging
• Rate of progression of mild cognitive impairment to dementia--meta-analysis of 41 robust inception cohort studies Acta psychiatrica Scandinavica · 2008-02-18 · usefulness score 71/100 · How common it is
• Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials Alzheimer's & dementia : the journal of the Alzheimer's Association · 2017-03-22 · usefulness score 65/100 · Mild cognitive impairment
• Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria The Lancet. Neurology · 2007-08-01 · usefulness score 63/100 · Getting a diagnosis
• The Clinical Dementia Rating (CDR) Neurology · 1993-11-01 · usefulness score 59/100 · Cognitive tests and assessment
• Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease Neurology · 1984-07-01 · usefulness score 58/100 · Getting a diagnosis
• Neuropathological stageing of Alzheimer-related changes Acta Neuropathologica · 1991-09-01 · usefulness score 58/100 · Brain tissue and pathology
• “Mini-mental state” Journal of Psychiatric Research · 1975-11-01 · usefulness score 55/100 · Cognitive tests and assessment
• Special Care Units and Traditional Care in Dementia: Relationship with Behavior, Cognition, Functional Status and Quality of Life - A Review Dementia and Geriatric Cognitive Disorders Extra · 2013-10-05 · usefulness score 51/100 · Caregiving
• Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly Gerontology · 2014-08-13 · usefulness score 50/100 · Digital health tools
• Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach Frontiers in neuroscience · 2015-09-01 · usefulness score 50/100 · Mild cognitive impairment
• Sparse learning and stability selection for predicting MCI to AD conversion using baseline ADNI data BMC neurology · 2012-06-25 · usefulness score 44/100 · Long-term cohort studies

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• Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment The Cochrane database of systematic reviews · 2020-03-02 · usefulness score 71/100 · Mild cognitive impairment
• Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data BMC medical informatics and decision making · 2019-11-21 · usefulness score 45/100 · Digital health tools

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