Automatic Differentiation of Anatomical Patterns in the Human Brain: Validation with Studies of Degenerative Dementias

By Catriona D. Good, Rachael I. Scahill, Nick C Fox, John Ashburner, Karl J. Friston, D. Chan, William R. Crum, Martin Rossor, Richard S. J. Frackowiak. NeuroImage, 2002

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We compared voxel-based morphometry (VBM) with independent accurate region-of-interest (ROI) measurements of temporal lobe structures in order to validate the usefulness of this fully automated and unbiased technique in Alzheimer's disease (AD) and semantic dementia (SD). In AD, ROI analyses appear more sensitive to volume loss in the amygdalae, whereas VBM analyses appear more sensitive to right middle temporal gyrus and regional hippocampal volume loss. In SD, ROI analyses appear more sensitive to left middle and inferior temporal gyrus volume loss, whereas VBM appears more sensitive to regional hippocampal volume loss. In addition the significance of volume reductions was generally less in VBM owing to more stringent corrections for multiple comparisons. In conclusion, the automated technique detects a general trend of atrophy similar to that of expertly labeled ROI measurements in AD and SD, although there are discrepancies in the ranking of severity and in the significance of volume reductions that are more marked in AD.

Subfields: Neurology, Physiology, Psychiatry and Mental health

View Paper: https://www.semanticscholar.org/paper/63aab2e74af64cd3d663cf14763fecfbc40aa70c

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Citations in the corpus

MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection (2015, neutral): “delineation of regions of interest (ROIs), onMR images is an extremely important task for quantitative analysis of structural and functional brain changes, particularly in studies with large datasets (Good et al., 2002; Poldrack, 2007).”
Cognition and anatomy in three variants of primary progressive aphasia (2004, methodology): “VBM recently has been shown to be sensitive in detecting changes in gray matter volumes in neurodegenerative disorders.(53) The spatial resolution of the technique is 12mm, and the risk of false-negatives when considering single subjects limits its routine clinical use.”
Cerebral atrophy in Parkinson's disease with and without dementia: a comparison with Alzheimer's disease, dementia with Lewy bodies and controls. (2004, methodology): “Optimized VBM Following the creation of study speci®c grey matter templates, the optimized protocol was subsequently applied to the original data (Good et al., 2001, 2002).”
Why voxel-based morphometric analysis should be used with great caution when characterizing group differences (2004, background): “…and Friston, 2000; Chung et al., 2001; Davatzikos et al., 1996, 2001; Thompson et al., 1997) has gained attention in the neuroimaging literature (Good et al., 2002; Hulshoff Pol et al., 2001; Job et al., 2002; Kubicki et al., 2002; Mehta et al., 2003), mostly because it does not require an a…”
Whole-brain voxel-based statistical analysis of gray matter and white matter in temporal lobe epilepsy (2004, methodology): “Comparison of VBM and ROI-based segmentation in TLE The accuracy and sensitivity of VBM analysis depend upon the quality of the underlying preprocessing steps, including tissue segmentation (Ashburner and Friston, 2000; Good et al., 2002).”
Structural brain variation and general intelligence (2004, neutral): “, 2001), dementia (Good et al., 2002), and Down syndrome (White et al.”
Morphological classification of brains via high-dimensional shape transformations and machine learning methods (2004, neutral): “A new class of methods for morphological analysis of brain images has emerged during the past decade which is based on voxel-wise measurements, with no a priori hypothesis (Ashburner et al., in press; Csernansky et al., 2000; Davatzikos et al., 1996, 2001; Freeborough and Fox, 1998; Good et al., 200”
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).”
COMPARE: Classification of Morphological Patterns Using Adaptive Regional Elements (2007, methodology): “ROI method that are often based on prior knowledge of what specific regions might be affected by disease, and the limitations of voxel-based morphometric analysis methods [3], [6] that use”
Head size, age and gender adjustment in MRI studies: a necessary nuisance? (2010, methodology): “, 2003) and statistical adjustment with the nuisance variable as a covariate (Good et al., 2002).”
The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence (2007, background): “…Friston 2001; Bookstein 2001; Davatzikos 2004), although several recent studies have compared VBM to traditional region-of-interest (ROI) tracing techniques in the same subjects and determined generally good correspondence between methods (Giuliani et al. 2005; Good et al. 2002; Testa et al. 2004).”
Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study (2008, methodology): “It bears similarities with the “optimized VBM” approach (Good et al., 2002), except that it uses a highly conforming high-dimensional image warping algorithm that captures finer structural details.”
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).”
Ventromedial prefrontal volume predicts understanding of others and social network size (2011, methodology): “The original T1 scans were then normalized and segmented using the optimized VBM approach developed by Good et al. (2001, 2002).”
Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline (2008, methodology): “It bears similarities with the " optimized VBM " approach (Good et al., 2002), except it uses a highly conforming high-dimensional image warping algorithm that captures finer structural details.”