1. A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease
- Author
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Inglese, Marianna, Patel, Neva, Linton-Reid, Kristofer, Loreto, Flavia, Win, Zarni, Perry, Richard J, Carswell, Christopher, Grech-Sollars, Matthew, Crum, William R, Lu, Haonan, Malhotra, Paresh A, and Aboagye, Eric O
- Subjects
Health Services and Systems ,Health Sciences ,Clinical Research ,Aging ,Behavioral and Social Science ,Biomedical Imaging ,Acquired Cognitive Impairment ,Alzheimer's Disease ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Dementia ,Neurosciences ,Brain Disorders ,Neurodegenerative ,4.2 Evaluation of markers and technologies ,Detection ,screening and diagnosis ,Neurological ,Alzheimer’s Disease Neuroimaging Initiative ,Alzheimer's disease ,Brain ,Cognitive neuroscience ,Diagnostic markers ,Magnetic resonance imaging - Abstract
BackgroundAlzheimer's disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care.MethodsWe developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO).ResultsThe ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype.ConclusionsThis new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.
- Published
- 2022