scholarly journals Enhanced detection of cortical atrophy in Alzheimer's disease using structural MRI with anatomically constrained longitudinal registration

2021 ◽  
Author(s):  
Emily Iannopollo ◽  
Kara Garcia ◽  
Brain ◽  
2018 ◽  
Vol 141 (12) ◽  
pp. 3443-3456 ◽  
Author(s):  
Mara ten Kate ◽  
Ellen Dicks ◽  
Pieter Jelle Visser ◽  
Wiesje M van der Flier ◽  
Charlotte E Teunissen ◽  
...  

Abstract Alzheimer’s disease is a heterogeneous disorder. Understanding the biological basis for this heterogeneity is key for developing personalized medicine. We identified atrophy subtypes in Alzheimer’s disease dementia and tested whether these subtypes are already present in prodromal Alzheimer’s disease and could explain interindividual differences in cognitive decline. First we retrospectively identified atrophy subtypes from structural MRI with a data-driven cluster analysis in three datasets of patients with Alzheimer’s disease dementia: discovery data (dataset 1: n = 299, age = 67 ± 8, 50% female), and two independent external validation datasets (dataset 2: n = 181, age = 66 ± 7, 52% female; dataset 3: n = 227, age = 74 ± 8, 44% female). Subtypes were compared on clinical, cognitive and biological characteristics. Next, we classified prodromal Alzheimer’s disease participants (n = 603, age = 72 ± 8, 43% female) according to the best matching subtype to their atrophy pattern, and we tested whether subtypes showed cognitive decline in specific domains. In all Alzheimer’s disease dementia datasets we consistently identified four atrophy subtypes: (i) medial-temporal predominant atrophy with worst memory and language function, older age, lowest CSF tau levels and highest amount of vascular lesions; (ii) parieto-occipital atrophy with poor executive/attention and visuospatial functioning and high CSF tau; (iii) mild atrophy with best cognitive performance, young age, but highest CSF tau levels; and (iv) diffuse cortical atrophy with intermediate clinical, cognitive and biological features. Prodromal Alzheimer’s disease participants classified into one of these subtypes showed similar subtype characteristics at baseline as Alzheimer’s disease dementia subtypes. Compared across subtypes in prodromal Alzheimer’s disease, the medial-temporal subtype showed fastest decline in memory and language over time; the parieto-occipital subtype declined fastest on executive/attention domain; the diffuse subtype in visuospatial functioning; and the mild subtype showed intermediate decline in all domains. Robust atrophy subtypes exist in Alzheimer’s disease with distinct clinical and biological disease expression. Here we observe that these subtypes can already be detected in prodromal Alzheimer’s disease, and that these may inform on expected trajectories of cognitive decline.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 801-801
Author(s):  
Dawn Mechanic-Hamilton ◽  
Sean Lydon ◽  
Alexander Miller ◽  
Kimberly Halberstadter ◽  
Jacqueline Lane ◽  
...  

Abstract This study investigates the psychometric properties of the mobile cognitive app performance platform (mCAPP), designed to detect memory changes associated with preclinical Alzheimer’s Disease (AD). The mCAPP memory task includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features, and spatial memory. Participants included 30 older adults with normal cognition. They completed the mCAPP, paper and pencil neuropsychological tests and a subset completed a high-resolution structural MRI. The majority of participants found the difficulty level of the mCAPP game to be “just right”. Accuracy on the mCAPP correlated with performance on memory and executive measures, while speed of performance on the mCAPP correlated with performance on attention and executive function measures. Longer trial duration correlated with measures of the parahippocampal cortex. The relationship of mCAPP variables with molecular biomarkers, at-home and burst testing, and development of additional cognitive measures will also be discussed.


NeuroImage ◽  
2020 ◽  
Vol 215 ◽  
pp. 116795 ◽  
Author(s):  
F.R. Farina ◽  
D.D. Emek-Savaş ◽  
L. Rueda-Delgado ◽  
R. Boyle ◽  
H. Kiiski ◽  
...  

2016 ◽  
Vol 113 (42) ◽  
pp. E6535-E6544 ◽  
Author(s):  
Xiuming Zhang ◽  
Elizabeth C. Mormino ◽  
Nanbo Sun ◽  
Reisa A. Sperling ◽  
Mert R. Sabuncu ◽  
...  

We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer’s disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid–positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.


PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0129250 ◽  
Author(s):  
Hyuk Jin Yun ◽  
Kichang Kwak ◽  
Jong-Min Lee ◽  

NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S113
Author(s):  
SF Carter ◽  
GJM Parker ◽  
MA Lambon Ralph ◽  
K Herholz

2021 ◽  
Vol 141 (5) ◽  
pp. 697-708
Author(s):  
Yang Shi ◽  
Alexey G. Murzin ◽  
Benjamin Falcon ◽  
Alexander Epstein ◽  
Jonathan Machin ◽  
...  

AbstractTau and Aβ assemblies of Alzheimer’s disease (AD) can be visualized in living subjects using positron emission tomography (PET). Tau assemblies comprise paired helical and straight filaments (PHFs and SFs). APN-1607 (PM-PBB3) is a recently described PET ligand for AD and other tau proteinopathies. Since it is not known where in the tau folds PET ligands bind, we used electron cryo-microscopy (cryo-EM) to determine the binding sites of APN-1607 in the Alzheimer fold. We identified two major sites in the β-helix of PHFs and SFs and a third major site in the C-shaped cavity of SFs. In addition, we report that tau filaments from posterior cortical atrophy (PCA) and primary age-related tauopathy (PART) are identical to those from AD. In support, fluorescence labelling showed binding of APN-1607 to intraneuronal inclusions in AD, PART and PCA. Knowledge of the binding modes of APN-1607 to tau filaments may lead to the development of new ligands with increased specificity and binding activity. We show that cryo-EM can be used to identify the binding sites of small molecules in amyloid filaments.


Sign in / Sign up

Export Citation Format

Share Document