AD Course Map charts Alzheimer’s disease progression
By Igor Koval, Alexandre Bône, Maxime Louis, Thomas Lartigue, Simona Bottani, Arnaud Marcoux, Jorge Samper-González, Ninon Burgos, Benjamin Charlier, Anne Bertrand, Stéphane Epelbaum, Olivier Colliot, Stéphanie Allassonnière & Stanley Durrleman
Keywords: Alzheimer's disease Disease Progression Modelling Forecast of cognitive decline multimodality
In this paper, we have been able to simultaneously characterize the progression of cognitive assessments, the cortical thickness, meshes of the hippocampus and glucose consumption measured with PET-FDG over a period of 30 years during the course of Alzheimer’s disease.
Such a description allows to precisely quantify the influence of different cofactors on the disease progression. But more importantly, this description of unprecedented precision allows to position any individual on the disease timeline in order to forecast the values of his or her modalities up to 4 years ahead.
Some results are presented on www.digital-brain.org
Normative models of Alzheimer’s disease progression shown at 4 Alzheimer Age with estimated time until/from diagnosis. Bottom to top rows show alteration of brain glucose metabolism, hippocampus atrophy, cortical thinning and onset of cognitive decline. Black arrows and ellipses indicate some areas of great changes
Full title AD Course Map charts Alzheimer's disease progression
Article abstract:
Alzheimer’s disease (AD) is characterized by the progressive alterations seen in brain images which give rise to the onset of various sets of symptoms. The variability in the dynamics of changes in both brain images and cognitive impairments remains poorly understood. This paper introduces AD Course Map a spatiotemporal atlas of Alzheimer’s disease progression. It summarizes the variability in the progression of a series of neuropsychological assessments, the propagation of hypometabolism and cortical thinning across brain regions and the deformation of the shape of the hippocampus. The analysis of these variations highlights strong genetic determinants for the progression, like possible compensatory mechanisms at play during disease progression. AD Course Map also predicts the patient’s cognitive decline with a better accuracy than the 56 methods benchmarked in the open challenge TADPOLE. Finally, AD Course Map is used to simulate cohorts of virtual patients developing Alzheimer’s disease. AD Course Map offers therefore new tools for exploring the progression of AD and personalizing patients care.