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The brain atlas concordance problem: quantitative comparison of anatomical parcellations.

Bohland JW, Bokil H, Allen CB, Mitra PP - PLoS ONE (2009)

Bottom Line: These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain.At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs.At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available.

View Article: PubMed Central - PubMed

Affiliation: Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America. jbohland@bu.edu

ABSTRACT
Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info.

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Related in: MedlinePlus

Comparison of Adjusted Rand Index and S index.The values of both computed indices of global concordance plotted against each other for each atlas pair.
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pone-0007200-g009: Comparison of Adjusted Rand Index and S index.The values of both computed indices of global concordance plotted against each other for each atlas pair.

Mentions: Figure 8(A) shows the global atlas concordance results as calculated using the Adjusted Rand Index. The computed ARI for each pair of atlases is shown in the above diagonal entries, with those values appearing in green exceeding the 95th percentile index in the corresponding chance similarity distribution. Shown in the corresponding sub-diagonal entries are the 1000 sorted chance similarity values obtained by simulation (black curve), as well as a red horizontal line indicating the ARI for the true atlas pair. Global atlas concordance as assessed by the ARI was surprisingly poor, with many parcellation pairs judged to be concordant at or below chance levels. Because the ARI penalizes anatomical region refinement (subset or hierarchical relationships), however, we designed and utilized a second similarity index (SI; see Equation 7) intended to better capture the notion of global concordance for atlases that may contain brain parcels subdivided with different levels of granularity. The global concordance results computed using SI are shown in Figure 8(B). Here, most of the concordance values for pairs of parcellations rise above chance levels, as would be expected for parcellations of the same brain that are, in most cases, based on sulcal/gyral landmarks. As hypothesized, the two parcellations that used the test brain directly as a reference (AAL and ICBM) had the highest overall concordance, and the two probabilistic atlases of similar scope (H-O and LPBA40) had the next highest similarity. Still it is worth noting that no concordance values observed approached the maximum theoretical value of 1, and several pairs, particularly those involving the Talairach-based parcellations, remain at or below the concordance values expected by chance according to simulations. Figure 9 illustrates the relationship between the ARI and the new S-index. The indices show considerable correlation (r = 0.87) but are not so tightly coupled as to be completely redundant.


The brain atlas concordance problem: quantitative comparison of anatomical parcellations.

Bohland JW, Bokil H, Allen CB, Mitra PP - PLoS ONE (2009)

Comparison of Adjusted Rand Index and S index.The values of both computed indices of global concordance plotted against each other for each atlas pair.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2748707&req=5

pone-0007200-g009: Comparison of Adjusted Rand Index and S index.The values of both computed indices of global concordance plotted against each other for each atlas pair.
Mentions: Figure 8(A) shows the global atlas concordance results as calculated using the Adjusted Rand Index. The computed ARI for each pair of atlases is shown in the above diagonal entries, with those values appearing in green exceeding the 95th percentile index in the corresponding chance similarity distribution. Shown in the corresponding sub-diagonal entries are the 1000 sorted chance similarity values obtained by simulation (black curve), as well as a red horizontal line indicating the ARI for the true atlas pair. Global atlas concordance as assessed by the ARI was surprisingly poor, with many parcellation pairs judged to be concordant at or below chance levels. Because the ARI penalizes anatomical region refinement (subset or hierarchical relationships), however, we designed and utilized a second similarity index (SI; see Equation 7) intended to better capture the notion of global concordance for atlases that may contain brain parcels subdivided with different levels of granularity. The global concordance results computed using SI are shown in Figure 8(B). Here, most of the concordance values for pairs of parcellations rise above chance levels, as would be expected for parcellations of the same brain that are, in most cases, based on sulcal/gyral landmarks. As hypothesized, the two parcellations that used the test brain directly as a reference (AAL and ICBM) had the highest overall concordance, and the two probabilistic atlases of similar scope (H-O and LPBA40) had the next highest similarity. Still it is worth noting that no concordance values observed approached the maximum theoretical value of 1, and several pairs, particularly those involving the Talairach-based parcellations, remain at or below the concordance values expected by chance according to simulations. Figure 9 illustrates the relationship between the ARI and the new S-index. The indices show considerable correlation (r = 0.87) but are not so tightly coupled as to be completely redundant.

Bottom Line: These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain.At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs.At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available.

View Article: PubMed Central - PubMed

Affiliation: Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America. jbohland@bu.edu

ABSTRACT
Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info.

Show MeSH
Related in: MedlinePlus