Advances in functional and structural MR image analysis and implementation as FSL

Smith, Stephen M.; Jenkinson, Mark; Woolrich, Mark W.; Beckmann, Christian F.; Behrens, Timothy E.J.; Johansen‐Berg, Heidi; Bannister, P.; Luca, Maria De; Drobnjak, Ivana; Flitney, David; Niazy, Rami K.; Saunders, Jenny; Vickers, John; Zhang, Y; Stefano, Nicola De; Brady, J. Michael; Matthews, Paul M.

doi:10.1016/j.neuroimage.2004.07.051

Cited by 11,927 publications

(9,807 citation statements)

References 41 publications

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“…Acquisition parameters were TE = 88 ms, TR = 13 s and voxel size 2 × 2 × 2 mm (Siemens); TE = 56ms and TR = 11s and voxel size 1.96 × 1.96 × 2.75 mm (Philips). The diffusion data were preprocessed using standard FSL pipelines (Smith et al, 2004). …”

Section: Methodsmentioning

confidence: 99%

Natural biological variation of white matter microstructure is accentuated in Huntington's disease

Gregory

Crawford

Seunarine

et al. 2018

Human Brain Mapping

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Huntington's disease (HD) is a monogenic neurodegenerative disorder caused by a CAG‐repeat expansion in the Huntingtin gene. Presence of this expansion signifies certainty of disease onset, but only partly explains age at which onset occurs. Genome‐wide association studies have shown that naturally occurring genetic variability influences HD pathogenesis and disease onset. Investigating the influence of biological traits in the normal population, such as variability in white matter properties, on HD pathogenesis could provide a complementary approach to understanding disease modification. We have previously shown that while white matter diffusivity patterns in the left sensorimotor network were similar in controls and HD gene‐carriers, they were more extreme in the HD group. We hypothesized that the influence of natural variation in diffusivity on effects of HD pathogenesis on white matter is not limited to the sensorimotor network but extends to cognitive, limbic, and visual networks. Using tractography, we investigated 32 bilateral pathways within HD‐related networks, including motor, cognitive, and limbic, and examined diffusivity metrics using principal components analysis. We identified three independent patterns of diffusivity common to controls and HD gene‐carriers that predicted HD status. The first pattern involved almost all tracts, the second was limited to sensorimotor tracts, and the third encompassed cognitive network tracts. Each diffusivity pattern was associated with network specific performance. The consistency in diffusivity patterns across both groups coupled with their association with disease status and task performance indicates that naturally‐occurring patterns of diffusivity can become accentuated in the presence of the HD gene mutation to influence clinical brain function.

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Section: Methodsmentioning

confidence: 99%

Natural biological variation of white matter microstructure is accentuated in Huntington's disease

Gregory

Crawford

Seunarine

et al. 2018

Human Brain Mapping

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“…Structural data were analyzed with FSL‐VBM, an optimized voxel‐based morphometry style analysis 32 carried out with FSL tools 33, which allows to detect potential differences in the local gray matter volume between different groups of subjects. In a first step, structural images were brain‐extracted using BET 34.…”

Section: Methodsmentioning

confidence: 99%

Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder

Amann

Canales‐Rodríguez

Madre

et al. 2015

Acta Psychiatr Scand

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ObjectiveBrain structural changes in schizoaffective disorder, and how far they resemble those seen in schizophrenia and bipolar disorder, have only been studied to a limited extent.MethodForty‐five patients meeting DSM‐IV and RDC criteria for schizoaffective disorder, groups of patients with 45 matched schizophrenia and bipolar disorder, and 45 matched healthy controls were examined using voxel‐based morphometry (VBM).ResultsAnalyses comparing each patient group with the healthy control subjects found that the patients with schizoaffective disorder and the patients with schizophrenia showed widespread and overlapping areas of significant volume reduction, but the patients with bipolar disorder did not. A subsequent analysis compared the combined group of patients with the controls followed by extraction of clusters. In regions where the patients differed significantly from the controls, no significant differences in mean volume between patients with schizoaffective disorder and patients with schizophrenia in any of five regions of volume reduction were found, but mean volumes in the patients with bipolar disorder were significantly smaller in three of five.ConclusionThe findings provide evidence that, in terms of structural gray matter brain abnormality, schizoaffective disorder resembles schizophrenia more than bipolar disorder.

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“…Regarding intensity normalization and tissue segmentation, both SPM and SIENAX use an integrated approach to this process (Ashburner & Friston, 2005; Smith et al., 2004; Zhang, Brady, & Smith, 2001). One advantage to using whole‐brain atrophy as a metric is its relative insensitivity to GM and WM tissue misclassification, as these two measures are summated to yield whole‐brain volumes.…”

Section: Discussionmentioning

confidence: 99%

“…In the BPV pipeline, raw MDEFT images were resliced to the axial plane, followed by removal of all slices inferior to the cervico‐medullary junction using JIM v7 (http://www.xinapse.com). Images then underwent automated segmentation and template normalization using SIENAX, (Smith et al., 2002) part of FSL (v5.0) (Smith et al., 2004) using a previously optimized brain extraction tool (BET) threshold of 0.2 (Chu et al., 2016). T2‐hyperintense lesion volumes were obtained by expert semiautomated segmentation with an edge‐finding tool based on local image intensity thresholds using JIM (v5) as previously published (Dell'Oglio et al., 2015); manual corrections were applied as needed (Ceccarelli et al., 2012).…”

Section: Methodsmentioning

confidence: 99%

Whole‐brain atrophy assessed by proportional‐ versus registration‐based pipelines from 3TMRIin multiple sclerosis

et al. 2018

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Background and PurposeWhole‐brain atrophy is a standard outcome measure in multiple sclerosis (MS) clinical trials as assessed by various software tools. The effect of processing method on the validity of such data obtained from high‐resolution 3T MRI is not known. We compared two commonly used methods of quantifying whole‐brain atrophy.MethodsThree‐dimensional T1‐weighted and FLAIR images were obtained at 3T in MS (n = 61) and normal control (NC, n = 30) groups. Whole‐brain atrophy was assessed by two automated pipelines: (a) SPM8 to derive brain parenchymal fraction (BPF, proportional‐based method); (b) SIENAX to derive normalized brain parenchymal volume (BPV, registration method). We assessed agreement between BPF and BPV, as well their relationship to Expanded Disability Status Scale (EDSS) score, timed 25‐foot walk (T25FW), cognition, and cerebral T2 (FLAIR) lesion volume (T2LV).ResultsBrain parenchymal fraction and BPV showed only partial agreement (r = 0.73) in the MS group, and r = 0.28 in NC. Both methods showed atrophy in MS versus NC (BPF p < 0.01, BPV p < 0.05). Within MS group comparisons, BPF (p < 0.05) but not BPV (p > 0.05) correlated with EDSS score. BPV (p = 0.03) but not BPF (p = 0.08) correlated with T25FW. Both metrics correlated with T2LV (p < 0.05) and cognitive subscales. BPF (p < 0.05) but not BPV (p > 0.05) showed lower brain volume in cognitively impaired (n = 23) versus cognitively preserved (n = 38) patients. However, direct comparisons of BPF and BPV sensitivities to atrophy and clinical correlations were not statistically significant.ConclusionWhole‐brain atrophy metrics may not be interchangeable between proportional‐ and registration‐based automated pipelines from 3T MRI in patients with MS.

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Advances in functional and structural MR image analysis and implementation as FSL

Cited by 11,927 publications

References 41 publications

Natural biological variation of white matter microstructure is accentuated in Huntington's disease

Natural biological variation of white matter microstructure is accentuated in Huntington's disease

Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder

Whole‐brain atrophy assessed by proportional‐ versus registration‐based pipelines from 3TMRIin multiple sclerosis

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