A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease
Document Type
Article
Publication Date
12-1-2022
Abstract
Background: Alzheimer’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. Methods: We 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). Results: The 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. Conclusions: This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.
Recommended Citation
Inglese, M., Patel, N., Linton-Reid, K., Loreto, F., Win, Z., Perry, R., Carswell, C., Grech-Sollars, M., Crum, W., Lu, H., Malhotra, P., Silbert, L., Lind, B., Crissey, R., Kaye, J., Carter, R., Dolen, S., Quinn, J., Schneider, L., Pawluczyk, S., Becerra, M., Teodoro, L., Dagerman, K., Spann, B., Brewer, J., Vanderswag, H., Fleisher, A., Ziolkowski, J., Heidebrink, J., Zbizek-Nulph., Lord, J., Zbizek-Nulph, L., Petersen, R., & Mason, S. (2022). A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease. Retrieved from https://repository.lsu.edu/clinical_research_pubs/47