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Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke.

Zavaglia M, Forkert ND, Cheng B, Gerloff C, Thomalla G, Hilgetag CC - Neuroimage Clin (2015)

Bottom Line: The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures.There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS.Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany ; School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, Bremen 28759, Germany.

ABSTRACT
Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a 'map of stroke'.

No MeSH data available.


Related in: MedlinePlus

Lesion Overlap in MNI152 standard atlas space. From top to bottom, representation of MNI atlas (we selected three representative slices from the MNI atlas that covered all structural regions), Lesion Overlap and Median VOI Lesion Overlap, in neurological convention. While the lesion overlap focuses at the scale of voxels, median VOI lesion overlap shows the relative (median percentage) infarction within the confines of the predefined 2 × 8 VOIs.
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f0010: Lesion Overlap in MNI152 standard atlas space. From top to bottom, representation of MNI atlas (we selected three representative slices from the MNI atlas that covered all structural regions), Lesion Overlap and Median VOI Lesion Overlap, in neurological convention. While the lesion overlap focuses at the scale of voxels, median VOI lesion overlap shows the relative (median percentage) infarction within the confines of the predefined 2 × 8 VOIs.

Mentions: Initially, we visualized the distribution of stroke lesions using two different approaches. The first one was Lesion Overlap, which is a widely used, straightforward assessment of lesion patterns, e.g. Karnath et al. (2001), based here on the MNI atlas. Specifically, it shows the overlap (in %) between the voxels defined in the MNI ICBM152 structural atlas space and the patient-specific acute ischemic stroke lesion. The second approach, Median VOI Lesion Overlap, is identical to Lesion Overlap, but is based on VOIs, rather than voxels. It shows the normalized overlap of lesions within the parcellation of the 2 × 8 VOIs in MNI ICBM152 standard atlas space. The two overlay measures allow a straightforward assessment of relative lesion size and frequency (Fig. 2). However, it needs to be pointed out that lesion overlays are insufficient for drawing reliable inferences from lesion data (Rorden and Karnath, 2004). Therefore, we only used them for an initial visualization of the lesion patterns and performed detailed comparisons of the MSA outcomes using more principled approaches.


Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke.

Zavaglia M, Forkert ND, Cheng B, Gerloff C, Thomalla G, Hilgetag CC - Neuroimage Clin (2015)

Lesion Overlap in MNI152 standard atlas space. From top to bottom, representation of MNI atlas (we selected three representative slices from the MNI atlas that covered all structural regions), Lesion Overlap and Median VOI Lesion Overlap, in neurological convention. While the lesion overlap focuses at the scale of voxels, median VOI lesion overlap shows the relative (median percentage) infarction within the confines of the predefined 2 × 8 VOIs.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4544394&req=5

f0010: Lesion Overlap in MNI152 standard atlas space. From top to bottom, representation of MNI atlas (we selected three representative slices from the MNI atlas that covered all structural regions), Lesion Overlap and Median VOI Lesion Overlap, in neurological convention. While the lesion overlap focuses at the scale of voxels, median VOI lesion overlap shows the relative (median percentage) infarction within the confines of the predefined 2 × 8 VOIs.
Mentions: Initially, we visualized the distribution of stroke lesions using two different approaches. The first one was Lesion Overlap, which is a widely used, straightforward assessment of lesion patterns, e.g. Karnath et al. (2001), based here on the MNI atlas. Specifically, it shows the overlap (in %) between the voxels defined in the MNI ICBM152 structural atlas space and the patient-specific acute ischemic stroke lesion. The second approach, Median VOI Lesion Overlap, is identical to Lesion Overlap, but is based on VOIs, rather than voxels. It shows the normalized overlap of lesions within the parcellation of the 2 × 8 VOIs in MNI ICBM152 standard atlas space. The two overlay measures allow a straightforward assessment of relative lesion size and frequency (Fig. 2). However, it needs to be pointed out that lesion overlays are insufficient for drawing reliable inferences from lesion data (Rorden and Karnath, 2004). Therefore, we only used them for an initial visualization of the lesion patterns and performed detailed comparisons of the MSA outcomes using more principled approaches.

Bottom Line: The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures.There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS.Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany ; School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, Bremen 28759, Germany.

ABSTRACT
Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a 'map of stroke'.

No MeSH data available.


Related in: MedlinePlus