Cortical change in Alzheimer's disease detected with a disease-specific population-based brain atlas.

By Paul M. Thompson, M. Mega, R. Woods, C. Zoumalan, C. Lindshield, R. Blanton, J. Moussai, C. Holmes, Jeffrey L. Cummings, Arthur W. Toga. 2001

474 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Physiology, Psychiatry and Mental health

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Citations in the corpus

Visual Feature Attribution Using Wasserstein GANs (2017, background): “Statistical analysis of medical images for identifying disease effects has been an instrumental tool for various diseases and disorders [56, 46, 9] as well as other nondisease related factors [17, 38, 28, 59, 42, 55].”
Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study (2008, methodology): “Unlike VBM-type methods, which are mass univariate and don't consider statistical associations among different brain regions, high-dimensional pattern classification methods are multivariate, thereby leading to better group separation, which is critical for individual diagnosis.”
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): “…observations using voxel-based morphometry (Baron et al. 2001; Karas et al. 2003; Bozzali et al. 2006; Whitwell et al. 2008) and similar techniques (Thompson et al. 2001; Scahill et al. 2002; Buckner et al. 2005; Apostolova et al. 2007) as well as 2 previous investigations using cortical thickness…”
Mapping Continued Brain Growth and Gray Matter Density Reduction in Dorsal Frontal Cortex: Inverse Relationships during Postadolescent Brain Maturation (2001, methodology): “Given that the deformation maps (acquired during cortical surface matching) associate the same cortical anatomy in each subject, a local measurement of gray matter density (at each point over the surface of the brain) could be made for each subject in addition to the DFC measures and averaged across”
Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. (2004, methodology): “…whole brain analysis approaches has been restricted to voxel-based morphometry (VBM) (Ashburner and Friston, 2000), implemented volumetrically (Baron et al. , 2001) across the cortex (Thompson, 1989; Thompson et al. , 2001), or as deformation analysis in longitudinal datasets (Good et al. , 2002).”
Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases (2016, background): “Such disease-eﬀect maps have been studied for various neurodegenerative conditions in the literature [4,5,6].”
Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths (2008, methodology): “Furthermore, the measure typically analyzed by voxel-based techniques – ‘grey matter density’ (Thompson et al., 2001) – is difficult to interpret quantitatively with respect to a particular morphometric property of cerebral tissue (i.”
Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children (2004, unknown): “…associated with the same cortical anatomy in each subject, the local measurement of gray matter thickness (at each point over the surface of the brain) for each subject could be averaged across corresponding regions of cortex for all subjects studied (Sowell et al., 2001b; Thompson et al., 2001b).”
Non-rigid image registration: theory and practice. (2004, methodology): “Disease-specific atlases carefully constructed using elastic registration of cortical surfaces and major sulci had also previously been used to analyse structural changes in early Alzheimer’s disease [13].”
Morphological classification of brains via high-dimensional shape transformations and machine learning methods (2004, unknown): “Brain diseases, including Alzheimer’s disease (AD), introduce tissue loss that is believed to be regionally specific (Bobinski et al., 1999; Braak et al., 1998; Csernansky et al., 2000; DeLeon et al., 1991; deToledo-Morrell et al., 1997; Freeborough and Fox, 1998; Golomb et al., 1993; Gomez-Isla et ”
Genetic influences on brain structure (2001, background): “Composite maps of these features, generated for large populations, can reveal patterns not observable in an individua”
Mapping brain asymmetry (2003, background): “In Alzheimer's disease, a spreading wave of grey matter loss emerges initially in entorhinal and temporal–parietal cortices, sweeping into frontal and ultimately sensorimotor territory as the disease progresse”