Citations

AbstractMotivationDiseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long‐term growth curves. The resulting estimates of long‐term progression are fine‐tuned using cognitive trajectories derived from the long‐term “Personnes Agées Quid” study.ResultsWe demonstrate with simulations that the method can recover long‐term disease trends from short‐term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject‐specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer's disease cascade. Other data sets with common outcome measures can be combined using the proposed algorithm.AvailabilitySoftware to fit the model and reproduce results with the statistical software R is available as the grace package. ADNI data can be downloaded from the Laboratory of NeuroImaging.

Background and purposeA subset of patients with Alzheimer's disease (AD) present with early and prominent language deficits. It is unclear whether the burden of underlying β‐amyloid pathology is associated with language or general cognitive impairment in these subjects.MethodsThe relationship between cortical β‐amyloid burden on [11C]Pittsburgh compound B (PiB) positron emission tomography (PET) and performance on the Montreal Cognitive Assessment (MoCA), the Wechsler Memory Scale − Third Edition (WMS‐III), the Boston Naming Test (BNT) and the Western Aphasia Battery (WAB) was assessed using regression and correlation analyses in subjects presenting with aphasia who showed β‐amyloid deposition on PiB PET.ResultsThe global PiB ratio was inversely correlated with MoCA (P = 0.02) and the WMS‐III Visual Reproduction (VR) subtest (VR I, P = 0.02; VR II, P = 0.04). However, the correlations between PiB ratio, BNT (P = 0.13), WAB aphasia quotient (P = 0.11) and WAB repetition scores (P = 0.34) were not significant.ConclusionThis study demonstrates that an increased cortical β‐amyloid burden is associated with cognitive impairment, but not language deficits, in AD subjects presenting with aphasia. The results suggest that β‐amyloid deposition could be partly contributing to impaired cognition in such patients whilst language dysfunction may be more influenced by other pathological mechanisms, perhaps downstream pathways of β‐amyloid deposition.

ABSTRACTBACKGROUND AND PURPOSEAn effort to define and validate a Harmonized Protocol for standard hippocampal segmentation is being carried out. We wished to estimate the effect of magnetic resonance image (MRI) spatial orientation on manual hippocampal segmentations to define optimal standard orientation of MRIs for hippocampal volumetry.METHODSThree expert tracers segmented twice the hippocampi of 10 ADNI subjects on MRI slices oriented perpendicular to the anterior‐posterior commissure (AC‐PC) line and the long hippocampal axes plane, following internationally harmonized landmarks. We computed intra and interrater reliability figures for total volumes and similarity coefficients.RESULTSTotal volume reliability was similar for both orientations. Similarity coefficients were significantly higher for the AC‐PC orientation (exact P = 0.002).DISCUSSIONThese data show that AC‐PC orientation is slightly more reliable for manual segmentations, possibly due to better visualization of the cerebrospinal fluid spaces separating hippocampal head and amygdala. A Delphi panel of experts has used these data to decide on the optimal orientation for a Harmonized Protocol for hippocampal segmentation.