A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging.

By Rachael I. Scahill, C. Frost, Rhian Jenkins, Jennifer L. Whitwell, Martin Rossor, Nick C Fox. Archives of Neurology, 2003

934 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Psychiatry and Mental health, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/6ac8bf928fab053d6b4cb14e04b6eadf949dfa22

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Citations in the corpus

Tensor-Based Morphometry as a Neuroimaging Biomarker for Alzheimer’s Disease: An MRI Study of 676 AD, MCI, and Normal Subjects (2008, positive): “…measures can optimally predict future clinical decline, often defined as conversion to AD over a specific follow-up interval (Jack et al., 1998; Scahill et al., 2003; Apostolova et al., 2006; Fleisher et al., 2008), and which measures link best with standard cognitive assessments (Fox et al.,…”
Trajectories of brain aging in middle-aged and older adults: Regional and individual differences (2010, positive): “, 2004) and longitudinal reports support that hypothesis at least regarding the hippocampus (Scahill et al., 2003; Raz et al., 2005; Fjell et al., 2009b)”
Longitudinal Changes in Cortical Thickness Associated with Normal Aging (2010, background): “Structural neuroimaging studies of the aging brain have largely focused on volumetric measures of the cerebral cortex (Coffey et al., 1992; Good et al., 2001; Liu et al., 2003; Resnick et al., 2000; Scahill et al., 2003; Tang et al., 2001).”
What is normal in normal aging? Effects of Aging, Amyloid and Alzheimer’s Disease on the Cerebral Cortex and the Hippocampus (2014, background): “Annual atrophy rates of 0.79–2.0% for the hippocampus (Jack et al., 1998; Scahill et al., 2003; Ezekiel et al., 2004; Raz et al., 2005; Du et al., 2006; Fjell et al., 2009a) and of 0.3–2.4% for the entorhinal cortex (Du et al., 2003, 2006; Ezekiel et al., 2004; Raz et al., 2005; Fjell et al.,…”
Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. (2004, methodology): “The longitudinal aspect of our analysis should be explored in greater detail and compared to non-linear registration methods that have recently been used in the analysis of AD populations and normal aging (Fox et al. , 2000; Scahill et al. , 2002, 2003).”
Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. (2005, background): “Three exceptions are longitudinal studies revealing significant shrinkage of prefrontal regions with smaller but significant declines of other regions (Pfefferbaum et al., 1998; Resnick et al., 2003; Scahill et al., 2003).”
Head size, age and gender adjustment in MRI studies: a necessary nuisance? (2010, methodology): “, 2007) which disappears with head size correction (Scahill et al., 2003).”
One year brain atrophy evident in healthy aging (2009, background): “…with age in cross-sectional (Good et al., 2001; Raz et al., 2004; Walhovd et al., 2005) and longitudinal (Jack et al., 1998; Resnick et al., 2003; Scahill et al., 2003; Ezekiel et al., 2004; Raz et al., 2005; Du et al., 2006; Driscoll et al., 2009) studies, but usually not more strongly than the…”
Machine learning framework for early MRI-based Alzheimer’s conversion prediction in MCI subjects (2014, positive): “We estimated theage-related effects on theGM densitiesof NCsubjects by using a linear regression model that is similar to a method applied in earlier studies (Dukart et al., 2011; Scahill et al., 2003).”
Differential aging of the brain: patterns, cognitive correlates and modifiers. (2006, positive): “In addition, at least one study (Scahill et al., 2003) reported a significant age-related acceleration of ventricular expansion with age without providing the percent values.”
When does age-related cognitive decline begin? (2009, background): “…regional brain volume, which is a variable presumably related to cognitive functioning but not susceptible to practice effects, have reported longitudinal age declines that are at least as large as the cross-sectional differences (Fotenos et al., 2005; Raz et al., 2005; Scahill et al., 2003).”
Preclinical detection of Alzheimer's disease: hippocampal shape and volume predict dementia onset in the elderly (2005, background): “Also, correlations have been previously reported between age and various brain structure volumes and age, and correlations between age and hippocampal volume in particular, while somewhat inconsistent, suggest that decreases in hippocampal volume can occur with healthy aging (Good et al., 2001; Liu ”
Assessing the effects of age on long white matter tracts using diffusion tensor tractography (2009, background): “Post-mortem and in vivo studies of the structural composition of the human brain converge on the idea that aging is associated with significant changes in white matter architecture (Meier-Ruge et al., 1992; for review, see Raz, 2005; Resnick et al., 2003; Scahill et al., 2003; Tang and Nyengaard, 19”
Efficiency and Cost of Economical Brain Functional Networks (2007, background): “For example, this functional observation might be related to structural neuroimaging evidence for grey and white matter deficits of frontal and temporal regions due to normal aging [37,38].”