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The benefits of skull stripping in the normalization of clinical fMRI data.

Fischmeister FP, Höllinger I, Klinger N, Geissler A, Wurnig MC, Matt E, Rath J, Robinson SD, Trattnig S, Beisteiner R - Neuroimage Clin (2013)

Bottom Line: The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed.Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches.Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space - particularly when used in combination with the New Segment normalization technique.

View Article: PubMed Central - PubMed

Affiliation: Study Group Clinical fMRI, Department of Neurology, Medical University of Vienna, Austria ; High Field MR Center, Medical University of Vienna, Austria.

ABSTRACT
Establishing a reliable correspondence between lesioned brains and a template is challenging using current normalization techniques. The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed. Here we provide a first investigation into whether clinical fMRI benefits from skull stripping, based on data from a presurgical language localization task. Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches. Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space - particularly when used in combination with the New Segment normalization technique.

No MeSH data available.


Histogram of lesion size across the three lesioned brain groups. The numbers on the abscissa correspond to the patient numbers listed in Table 1.
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f0005: Histogram of lesion size across the three lesioned brain groups. The numbers on the abscissa correspond to the patient numbers listed in Table 1.

Mentions: 36 patients (22 male, 14 female, mean age 42.5 years) fulfilling the above criteria were included in this study (see Table 1). These patients and four healthy subjects (2 male, 2 female, mean age 33.75 years) were subdivided into four equally sized groups according to the extent of the lesion (calculated from the lesion mask). These groups were no-lesion (comprising healthy subjects and epileptic patients), small-lesion, medium-lesion and large-lesion (see Fig. 1). These subgroups were formed to assess the effects of lesion size on normalization differences related to skull-stripping.


The benefits of skull stripping in the normalization of clinical fMRI data.

Fischmeister FP, Höllinger I, Klinger N, Geissler A, Wurnig MC, Matt E, Rath J, Robinson SD, Trattnig S, Beisteiner R - Neuroimage Clin (2013)

Histogram of lesion size across the three lesioned brain groups. The numbers on the abscissa correspond to the patient numbers listed in Table 1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814956&req=5

f0005: Histogram of lesion size across the three lesioned brain groups. The numbers on the abscissa correspond to the patient numbers listed in Table 1.
Mentions: 36 patients (22 male, 14 female, mean age 42.5 years) fulfilling the above criteria were included in this study (see Table 1). These patients and four healthy subjects (2 male, 2 female, mean age 33.75 years) were subdivided into four equally sized groups according to the extent of the lesion (calculated from the lesion mask). These groups were no-lesion (comprising healthy subjects and epileptic patients), small-lesion, medium-lesion and large-lesion (see Fig. 1). These subgroups were formed to assess the effects of lesion size on normalization differences related to skull-stripping.

Bottom Line: The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed.Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches.Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space - particularly when used in combination with the New Segment normalization technique.

View Article: PubMed Central - PubMed

Affiliation: Study Group Clinical fMRI, Department of Neurology, Medical University of Vienna, Austria ; High Field MR Center, Medical University of Vienna, Austria.

ABSTRACT
Establishing a reliable correspondence between lesioned brains and a template is challenging using current normalization techniques. The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed. Here we provide a first investigation into whether clinical fMRI benefits from skull stripping, based on data from a presurgical language localization task. Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches. Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space - particularly when used in combination with the New Segment normalization technique.

No MeSH data available.