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Functional MRI Preprocessing in Lesioned Brains: Manual Versus Automated Region of Interest Analysis.

Garrison KA, Rogalsky C, Sheng T, Liu B, Damasio H, Winstein CJ, Aziz-Zadeh LS - Front Neurol (2015)

Bottom Line: Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis.Task interactions, however, were consistent across ROI analysis approaches.These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry, Yale School of Medicine , New Haven, CT , USA ; Division of Biokinesiology and Physical Therapy, University of Southern California , Los Angeles, CA , USA ; Brain and Creativity Institute, University of Southern California , Los Angeles, CA , USA.

ABSTRACT
Functional magnetic resonance imaging (fMRI) has significant potential in the study and treatment of neurological disorders and stroke. Region of interest (ROI) analysis in such studies allows for testing of strong a priori clinical hypotheses with improved statistical power. A commonly used automated approach to ROI analysis is to spatially normalize each participant's structural brain image to a template brain image and define ROIs using an atlas. However, in studies of individuals with structural brain lesions, such as stroke, the gold standard approach may be to manually hand-draw ROIs on each participant's non-normalized structural brain image. Automated approaches to ROI analysis are faster and more standardized, yet are susceptible to preprocessing error (e.g., normalization error) that can be greater in lesioned brains. The manual approach to ROI analysis has high demand for time and expertise, but may provide a more accurate estimate of brain response. In this study, commonly used automated and manual approaches to ROI analysis were directly compared by reanalyzing data from a previously published hypothesis-driven cognitive fMRI study, involving individuals with stroke. The ROI evaluated is the pars opercularis of the inferior frontal gyrus. Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis. Task interactions, however, were consistent across ROI analysis approaches. These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design.

No MeSH data available.


Related in: MedlinePlus

Left inferior frontal gyrus pars opercularis (BA 44) regions of interest (gray) defined for a participant with stroke according to the (A) automated approach and (B) manual approach, and for a control participant according to the (C) automated approach and (D) manual approach. Automated BA 44 was defined from SPM Anatomy toolbox and is overlaid onto the individual participant’s spatially normalized brain image. Manual BA 44 was defined by-hand based on neuroanatomy and is overlaid onto the individual participant’s non-normalized brain image.
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Figure 1: Left inferior frontal gyrus pars opercularis (BA 44) regions of interest (gray) defined for a participant with stroke according to the (A) automated approach and (B) manual approach, and for a control participant according to the (C) automated approach and (D) manual approach. Automated BA 44 was defined from SPM Anatomy toolbox and is overlaid onto the individual participant’s spatially normalized brain image. Manual BA 44 was defined by-hand based on neuroanatomy and is overlaid onto the individual participant’s non-normalized brain image.

Mentions: Region of interest (ROIs) included the left and right pars opercularis of the inferior frontal gyrus (BA 44). The methods to define ROIs using the manual approach and the automated approach are described below. Examples of ROIs defined using each of the approaches are displayed in Figure 1.


Functional MRI Preprocessing in Lesioned Brains: Manual Versus Automated Region of Interest Analysis.

Garrison KA, Rogalsky C, Sheng T, Liu B, Damasio H, Winstein CJ, Aziz-Zadeh LS - Front Neurol (2015)

Left inferior frontal gyrus pars opercularis (BA 44) regions of interest (gray) defined for a participant with stroke according to the (A) automated approach and (B) manual approach, and for a control participant according to the (C) automated approach and (D) manual approach. Automated BA 44 was defined from SPM Anatomy toolbox and is overlaid onto the individual participant’s spatially normalized brain image. Manual BA 44 was defined by-hand based on neuroanatomy and is overlaid onto the individual participant’s non-normalized brain image.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585177&req=5

Figure 1: Left inferior frontal gyrus pars opercularis (BA 44) regions of interest (gray) defined for a participant with stroke according to the (A) automated approach and (B) manual approach, and for a control participant according to the (C) automated approach and (D) manual approach. Automated BA 44 was defined from SPM Anatomy toolbox and is overlaid onto the individual participant’s spatially normalized brain image. Manual BA 44 was defined by-hand based on neuroanatomy and is overlaid onto the individual participant’s non-normalized brain image.
Mentions: Region of interest (ROIs) included the left and right pars opercularis of the inferior frontal gyrus (BA 44). The methods to define ROIs using the manual approach and the automated approach are described below. Examples of ROIs defined using each of the approaches are displayed in Figure 1.

Bottom Line: Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis.Task interactions, however, were consistent across ROI analysis approaches.These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychiatry, Yale School of Medicine , New Haven, CT , USA ; Division of Biokinesiology and Physical Therapy, University of Southern California , Los Angeles, CA , USA ; Brain and Creativity Institute, University of Southern California , Los Angeles, CA , USA.

ABSTRACT
Functional magnetic resonance imaging (fMRI) has significant potential in the study and treatment of neurological disorders and stroke. Region of interest (ROI) analysis in such studies allows for testing of strong a priori clinical hypotheses with improved statistical power. A commonly used automated approach to ROI analysis is to spatially normalize each participant's structural brain image to a template brain image and define ROIs using an atlas. However, in studies of individuals with structural brain lesions, such as stroke, the gold standard approach may be to manually hand-draw ROIs on each participant's non-normalized structural brain image. Automated approaches to ROI analysis are faster and more standardized, yet are susceptible to preprocessing error (e.g., normalization error) that can be greater in lesioned brains. The manual approach to ROI analysis has high demand for time and expertise, but may provide a more accurate estimate of brain response. In this study, commonly used automated and manual approaches to ROI analysis were directly compared by reanalyzing data from a previously published hypothesis-driven cognitive fMRI study, involving individuals with stroke. The ROI evaluated is the pars opercularis of the inferior frontal gyrus. Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis. Task interactions, however, were consistent across ROI analysis approaches. These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design.

No MeSH data available.


Related in: MedlinePlus