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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

Brain activation associated with right hand action observation in the left hemisphere of a control participant as evaluated by: (A) a commonly used automated approach to ROI analysis, normalized and overlaid onto the MNI brain image; and (B) a manual approach to ROI analysis, overlaid onto the participant’s non-normalized brain image. ROI masks for the left BA 44 are displayed in gray. In this example, the larger automated ROI in (A) captured a larger number of activated voxels than the smaller manually defined ROI in (B). For display, activation maps are shown at T = 1.67–10 corresponding to p < 0.05 uncorrected.
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Figure 4: Brain activation associated with right hand action observation in the left hemisphere of a control participant as evaluated by: (A) a commonly used automated approach to ROI analysis, normalized and overlaid onto the MNI brain image; and (B) a manual approach to ROI analysis, overlaid onto the participant’s non-normalized brain image. ROI masks for the left BA 44 are displayed in gray. In this example, the larger automated ROI in (A) captured a larger number of activated voxels than the smaller manually defined ROI in (B). For display, activation maps are shown at T = 1.67–10 corresponding to p < 0.05 uncorrected.

Mentions: A four-way repeated measures ANOVA determined that effect size differed significantly between approaches [F(1,22) = 23.075, p = 0.000085; Table 1]. A post hoc pairwise comparison using the Bonferroni correction revealed a significantly larger effect size for automated as compared to manual ROI analysis (automated = 0.329 ± 0.09, manual = 0.090 ± 0.109; p = 0.000085; Figure 3). Pairwise comparisons for each method, group, hemisphere, and condition are displayed in Figure 3. Additional within-subjects test results are provided in Table 1. Other main effects and interactions related to the methods comparison were not significant, including interactions between method and group (p = 0.416), method and hemisphere (p = 0.231), and method, group, and hemisphere (p = 0.418). However, as expected based on prior analysis of this dataset (5), a significant three-way interaction was found between cognitive task condition, group, and hemisphere [F(1,22) = 8.438, p = 0.008; Table 1] that was consistent when tested as a three-way repeated measures ANOVA separately for either the automated [F(1,22) = 7.350, p = 0.013] or manual approach [F(1,22) = 6.824, p = 0.016]. Note that for participants with stroke, the left hemisphere is the lesioned hemisphere. Representative activation maps from individual participants are displayed in Figures 4–6 to illustrate the differences between automated and manual approaches to ROI definition, and are discussed in more detail below.


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)

Brain activation associated with right hand action observation in the left hemisphere of a control participant as evaluated by: (A) a commonly used automated approach to ROI analysis, normalized and overlaid onto the MNI brain image; and (B) a manual approach to ROI analysis, overlaid onto the participant’s non-normalized brain image. ROI masks for the left BA 44 are displayed in gray. In this example, the larger automated ROI in (A) captured a larger number of activated voxels than the smaller manually defined ROI in (B). For display, activation maps are shown at T = 1.67–10 corresponding to p < 0.05 uncorrected.
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Related In: Results  -  Collection

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

Figure 4: Brain activation associated with right hand action observation in the left hemisphere of a control participant as evaluated by: (A) a commonly used automated approach to ROI analysis, normalized and overlaid onto the MNI brain image; and (B) a manual approach to ROI analysis, overlaid onto the participant’s non-normalized brain image. ROI masks for the left BA 44 are displayed in gray. In this example, the larger automated ROI in (A) captured a larger number of activated voxels than the smaller manually defined ROI in (B). For display, activation maps are shown at T = 1.67–10 corresponding to p < 0.05 uncorrected.
Mentions: A four-way repeated measures ANOVA determined that effect size differed significantly between approaches [F(1,22) = 23.075, p = 0.000085; Table 1]. A post hoc pairwise comparison using the Bonferroni correction revealed a significantly larger effect size for automated as compared to manual ROI analysis (automated = 0.329 ± 0.09, manual = 0.090 ± 0.109; p = 0.000085; Figure 3). Pairwise comparisons for each method, group, hemisphere, and condition are displayed in Figure 3. Additional within-subjects test results are provided in Table 1. Other main effects and interactions related to the methods comparison were not significant, including interactions between method and group (p = 0.416), method and hemisphere (p = 0.231), and method, group, and hemisphere (p = 0.418). However, as expected based on prior analysis of this dataset (5), a significant three-way interaction was found between cognitive task condition, group, and hemisphere [F(1,22) = 8.438, p = 0.008; Table 1] that was consistent when tested as a three-way repeated measures ANOVA separately for either the automated [F(1,22) = 7.350, p = 0.013] or manual approach [F(1,22) = 6.824, p = 0.016]. Note that for participants with stroke, the left hemisphere is the lesioned hemisphere. Representative activation maps from individual participants are displayed in Figures 4–6 to illustrate the differences between automated and manual approaches to ROI definition, and are discussed in more detail below.

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