Comparison of different methodological implementations of voxel-based morphometry in neurodegenerative disease

Senjem, Matthew L.; Gunter, Jeffrey L.; Shiung, Maria M.; Petersen, Ronald C.; Jack, Clifford R.

doi:10.1016/j.neuroimage.2005.02.005

Cited by 178 publications

(177 citation statements)

References 25 publications

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“…may impact the sensitivity SPM2 results. Senjem et al (2005) recently compared a number of different methodological implementations of SPM2 in the analysis of morphological changes in Alzheimer's disease. One of the methods he presented did include removal of non-brain tissue from the image inputs (brain extraction).…”

Section: Discussionmentioning

confidence: 99%

Statistical parametric mapping of brain morphology: Sensitivity is dramatically increased by using brain-extracted images as inputs

et al. 2006

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A major attraction of voxel-based morphometry (VBM) is that it allows researchers to explore large datasets with minimal human intervention. However, the validity and sensitivity of the Statistical Parametric Mapping (SPM2) approach to VBM is the subject of considerable debate. We visually inspected the SPM2 gray matter segmentations for 101 research participants and found a gross inclusion of non-brain tissue surrounding the entire brain as gray matter in five subjects, and focal areas bordering the brain in which non-brain tissue was classified as gray matter in many other subjects. We also found many areas in which the cortical grey matter was incorrectly excluded from the segmentation of the brain. The major source of these errors was the misregistration of individual brain images with the reference T1-weighted brain template. These errors could be eliminated if SPM2 operated on images from which non-brain tissues (scalp, skull, and meninges) are removed (brain-extracted images). We developed a modified SPM2 processing pipeline that used brainextracted images as inputs to test this hypothesis. We describe the modifications to the SPM2 pipeline that allow analysis of brain-extracted inputs. Using brain-extracted inputs eliminated the non-brain matter inclusions and the cortical gray matter exclusions noted above, reducing the residual mean square errors (RMSEs, the error term of the SPM2 statistical analyses) by over thirty percent. We show how this reduction in the RMSEs profoundly affects power analyses. SPM2 analyses of brainextracted images may require sample sizes only half as great as analyses of non-brain extracted images.

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Section: Discussionmentioning

confidence: 99%

Statistical parametric mapping of brain morphology: Sensitivity is dramatically increased by using brain-extracted images as inputs

et al. 2006

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“…This custom template also enables statistically fair comparisons between the two groups while guaranteeing the ability to capture the finest shape differences. It has been previously shown that normalization to a custom template improves localization accuracy, reduces bias in statistical testing, and ultimately yields more biologically plausible results (Kochunov et al, 2005;Kochunov et al, 2001;Leow et al, 2006;Senjem, Gunter, Shiung, Petersen, & Jack, 2005;Woods, 2003). Lastly, the present study also attempted to control for the effects of the macroscopic focal lesions on the group differences by conducting a subgroup analysis after excluding subjects with such lesions.…”

Section: Introductionmentioning

confidence: 94%

Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

et al. 2008

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Traumatic brain injury (TBI) is one of the most common causes of long-term disability. Despite the importance of identifying neuropathology in individuals with chronic TBI, methodological challenges posed at the stage of inter-subject image registration have hampered previous voxel-based MRI studies from providing a clear pattern of structural atrophy after TBI. We used a novel symmetric diffeomorphic image normalization method to conduct a tensor-based morphometry (TBM) study of TBI. The key advantage of this method is that it simultaneously estimates an optimal template brain and topology preserving deformations between this template and individual subject brains. Detailed patterns of atrophies are then revealed by statistically contrasting control and subject deformations to the template space. Participants were 29 survivors of TBI and 20 control subjects who were matched in terms of age, gender, education, and ethnicity. Localized volume losses were found most prominently in white matter regions and the subcortical nuclei including the thalamus, the midbrain, the corpus callosum, the mid-and posterior cingulate cortices, and the caudate. Significant voxel-wise volume loss clusters were also detected in the cerebellum and the frontal/ temporal neocortices. Volume enlargements were identified largely in ventricular regions. A similar pattern of results was observed in a subgroup analysis where we restricted our analysis to the 17 TBI participants who had no macroscopic focal lesions (total lesion volume> 1.5 cm 3 ). The current study confirms, extends, and partly challenges previous structural MRI studies in chronic TBI. By demonstrating that a large deformation image registration technique can be successfully combined with TBM to identify TBI-induced diffuse structural changes with greater precision, our approach is expected to increase the sensitivity of future studies examining brain-behavior relationships in the TBI population.

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“…An optimized method of VBM was applied [2,47], implemented using SPM2 (http://www.fil.ion.ucl.ac.uk/spm). In order to reduce any potential normalization bias across the disease groups' customized templates and prior probability maps were created from all subjects in the study.…”

Section: Volumetric Mrimentioning

confidence: 99%

Imaging correlates of posterior cortical atrophy

Whitwell

Jack

Kantarci

et al. 2007

Neurobiology of Aging

183

143

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The aim of this study was to compare patterns of cerebral atrophy on MRI, and neurochemistry on magnetic resonance spectroscopy (MRS), in subjects with posterior cortical atrophy (PCA) and typical Alzheimer's disease (AD). Voxel-based morphometry was used to assess grey matter atrophy in 38 subjects with PCA, 38 subjects with typical AD, and 38 controls. Clinical data was assessed in all PCA subjects. Single-voxel 1 H MRS located in the posterior cingulate was analyzed in a subset of subjects with PCA, typical AD, and control subjects. PCA showed a pattern of atrophy affecting occipital, parietal and posterior temporal lobes, compared to controls. The pattern was bilateral, but more severe on the right. Subjects with PCA showed greater atrophy in the right visual association cortex than subjects with typical AD, whereas those with AD showed greater atrophy in the left hippocampus than those with PCA. 1 H MRS suggested loss of neuronal integrity and glial activation in subjects with PCA and AD. The differing patterns of atrophy on MRI suggest that PCA should be considered a distinct entity from typical AD.

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Comparison of different methodological implementations of voxel-based morphometry in neurodegenerative disease

Cited by 178 publications

References 25 publications

Statistical parametric mapping of brain morphology: Sensitivity is dramatically increased by using brain-extracted images as inputs

Statistical parametric mapping of brain morphology: Sensitivity is dramatically increased by using brain-extracted images as inputs

Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

Imaging correlates of posterior cortical atrophy

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