Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy.

By Jason P. Lerch, Jens C. Pruessner, Alex P. Zijdenbos, Harald Hampel, Stefan J. Teipel, Alan C. Evans. Cerebral Cortex, 2004

450 citations recorded by the source corpus.

Alzheimer's disease (AD) is characterized by a heterogeneous distribution of pathological changes throughout the brain. Magnetic resonance imaging can be used to investigate the regional distribution of cortical atrophy in AD in vivo. One marker for the disease-specific atrophy is the thickness of the cortical mantle across the brain, obtained with automated 3-D image processing. Here, we present data from 36 subjects (17 controls and, 19 patients diagnosed as probable AD) investigated for cortical thickness across the entire brain. We show significant cortical thickness decline in AD in temporal, orbitofrontal and parietal regions, with the most pronounced changes occurring in the allocortical region of the medial temporal lobes, outlining the parahippocampal gyrus, and representing a loss of >1.25 millimeters of cortical thickness. Moreover, focal cortical areas decline with progression of the disease as measured by time from baseline scan as well as the Mini-Mental State Exam. The results demonstrate the ability of this method to detect changes in cortical thickness in AD, across the entire brain, without need of prior anatomical definitions. The regional distribution of changes reported here is consistent with independent findings on the distribution of neuropathological alterations in AD. Using cortical thickness, moreover, we provide a direct quantitative index of atrophy in the disease.

Subfields: Cognitive Neuroscience, Physiology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/aed8dfc7dd76d6ca5a8c1660190a758d632224dc

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Citations in the corpus

Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging (2009, unknown): “…atrophy is also present in a distributed pattern of brain regions, including the temporal neocortex, the cingulate gyrus, the precuneus, the temporo-parietal association and the perisylvian association (Baron et al., 2001; Chételat et al., 2002, 2005; Karas et al., 2003, 2004; Lerch et al., 2005).”
The Cortical Signature of Alzheimer's Disease: Regionally Specific Cortical Thinning Relates to Symptom Severity in Very Mild to Mild AD Dementia and is Detectable in Asymptomatic Amyloid-Positive Individuals (2008, methodology): “…1999; Killiany et al. 2000; Dickerson et al. 2001) and more recently using semiautomated exploratory mapping techniques (Baron et al. 2001; Thompson et al. 2001; Good et al. 2002; Scahill et al. 2002; Karas et al. 2003; Buckner et al. 2005; Lerch et al. 2005; Du et al. 2007; Whitwell et al. 2008).”
Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease (2008, methodology): “, 2006) and applied to recent AD studies (Lerch et al., 2005; Singh et al., 2006).”
Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. (2007, methodology): “2006), and recently applied to Alzheimer’s disease (Lerch et al. 2005) and cortical development studies (Shaw et al.”
Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests (2015, unknown): “AD's effect on the cortical thickness has been documented in numerous studies (Baron et al., 2001; Lerch et al., 2005; Lerch et al., 2008).”
Highly Accurate Inverse Consistent Registration: A Robust Approach (2010, background): “, 2003, 2004), Alzheimer’s disease (Dickerson et al., 2001; Thompson et al., 2003; Lerch et al., 2005), Huntington’s disease (Rosas et al.”
Brain imaging in Alzheimer disease. (2012, background): “Rates of hippocampal and whole brain atrophy on MRI have to date been the most widely included imaging measures in trials; however, other MRI measures show promise, including cortical thickness or composites of change (Lerch et al. 2005; Hua et al. 2008; Jack et al. 2008a; Vemuri et al. 2009).”
New diagnostic EEG markers of the Alzheimer’s disease using visibility graph (2010, background): “Complexity in EEG and MEG records is an effective criterion to reveal changes in the dynamics of AD brain caused by loss of neuronal synapses and cortical changes (Geula and Mesulam 1996; Lerch et al. 2005; Fjell et al. 2009; Kuczynski et al. 2010; Stephen et al. 2010).”
Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI (2006, methodology): “We used FDR since it provides the greatest ability to threshold data stemming from multiple different statistical tests simultaneously, as described in (Lerch et al., 2005).”
Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database (2011, background): “…temporal, inferior parietal, and posterior cingulated cortices and with a lesser extent parietal, frontal, and lateral occipital cortices, which is consistent with the previous group studies based on cortical thickness (Thompson et al., 2004; Lerch et al., 2005, 2008; McDonald et al., 2009).”
Statistical Analysis of Longitudinal Neuroimage Data with Linear Mixed Effects Models (2012, methodology): “(Davatzikos and Resnick, 2002; Driscoll et al., 2012; Lau et al., 2008; Lerch et al., 2005; Shaw et al., 2008; Thambisetty et al., 2010; Tosun et al., 2010; Whitwell et al., 2011), there are two alternative methods that have been widely used to analyze LNI data in a large number of prior studies.”
An unbiased iterative group registration template for cortical surface analysis (2007, methodology): “In recent years, morphometric analysis of cortical MRI data using explicit cortical representations has become a widely employed procedure (e.g., Lerch et al., 2005; Luders et al., 2004; Van Essen et al., 2006; Salat et al., 2004).”
Gender difference analysis of cortical thickness in healthy young adults with surface-based methods (2006, methodology): “, 2003) with 20 mm FWHM was performed to improve statistical power (Chung et al., 2002; Lerch et al., 2005).”
The NIH MRI study of normal brain development (2006, unknown): “Recently, a Laplacian-based enhancement has improved the surface detection for pediatric brain MRI (Kim et al., 2005; Lerch et al., 2005).”