TY  - JOUR
Y1  - 2019/04/15/
UR  - https://doi.org/10.1016/j.neuroimage.2017.08.059
N2  - Disease progression modeling (DPM) of Alzheimer's disease (AD) aims at revealing long term pathological trajectories from short term clinical data. Along with the ability of providing a data-driven description of the natural evolution of the pathology, DPM has the potential of representing a valuable clinical instrument for automatic diagnosis, by explicitly describing the biomarker transition from normal to pathological stages along the disease time axis. In this work we reformulated DPM within a probabilistic setting to quantify the diagnostic uncertainty of individual disease severity in an hypothetical clinical scenario, with respect to missing measurements, biomarkers, and follow-up information. We show that the staging provided by the model on 582 amyloid positive testing individuals has high face validity with respect to the clinical diagnosis. Using follow-up measurements largely reduces the prediction uncertainties, while the transition from normal to pathological stages is mostly associated with the increase of brain hypo-metabolism, temporal atrophy, and worsening of clinical scores. The proposed formulation of DPM provides a statistical reference for the accurate probabilistic assessment of the pathological stage of de-novo individuals, and represents a valuable instrument for quantifying the variability and the diagnostic value of biomarkers across disease stages.
TI  - Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
JF  - NeuroImage
VL  - 190
ID  - discovery10045201
AV  - public
SP  - 56
A1  - Lorenzi, M
A1  - Filippone, M
A1  - Frisoni, GB
A1  - Alexander, DC
A1  - Ourselin, S
A1  - Alzheimer's Disease Neuroimaging Initiative, .
KW  - Alzheimer's disease
KW  -  Clinical trials
KW  -  Diagnosis
KW  -  Disease progression modeling
KW  -  Gaussian process
EP  - 68
SN  - 1053-8119
ER  -