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<meta name="category" content="abstract" />
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<meta name="DC.Title" content="A brain image database for structure/function analysis." />
<meta name="DC.Date" content="1998-11-01" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE Lesion-deficit-based structure-function analysis has traditionally been empirical and nonquantitative. Our purpose was to establish a new brain image database (BRAID) that allows the statistical correlation of brain functional measures with anatomic lesions revealed by clinical brain images.

METHODS Data on 303 participants in the MR Feasibility Study of the Cardiovascular Health Study were tested for lesion/deficit correlations. Functional data were derived from a limited neurologic examination performed at the time of the MR examination. Image data included 3D lesion descriptions derived from the MR examinations by hand segmentation. MR images were normalized in-plane using local, linear Talairach normalization. A database was implemented to support spatial data structures and associated geometric and statistical operations. The database stored the segmented lesions, patient functional scores, and several anatomic atlases. Lesion-deficit association was sought by contingency testing (chi2-test) for every possible combination of each neurologic variable and each labeled atlas structure. Significant associations that confirmed accepted lesion-deficit relationships were sought.

RESULTS Two-hundred thirty-five infarctlike lesions in 117 subjects were viewed collectively after mapping into Talairach cartesian coordinates. Anatomic structures most strongly correlated with neurologic deficits tended to be situated in anatomically appropriate areas. For example, infarctlike lesions associated with visual field defects were correlated with structures in contralateral occipital structures, including the optic radiations and occipital gyri.

CONCLUSION Known lesion-deficit correlations can be established by a database using a standard coordinate system for representing spatial data and incorporating functional and structural data together with appropriate query mechanisms. Improvements and further applications of this methodology may provide a powerful technique for uncovering new structure-function relationships." />
<meta name="DC.Contributor" content="S I Letovsky" />
<meta name="DC.Contributor" content="S H Whitehead" />
<meta name="DC.Contributor" content="C H Paik" />
<meta name="DC.Contributor" content="G A Miller" />
<meta name="DC.Contributor" content="J Gerber" />
<meta name="DC.Contributor" content="E H Herskovits" />
<meta name="DC.Contributor" content="T K Fulton" />
<meta name="DC.Contributor" content="R N Bryan" />
<meta name="article:published_time" content="1998-11-01" />
<meta name="citation_title" content="A brain image database for structure/function analysis." />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE&lt;/h3&gt;
&lt;p&gt;Lesion-deficit-based structure-function analysis has traditionally been empirical and nonquantitative. Our purpose was to establish a new brain image database (BRAID) that allows the statistical correlation of brain functional measures with anatomic lesions revealed by clinical brain images.&lt;/p&gt;&lt;h3&gt;METHODS&lt;/h3&gt;
&lt;p&gt;Data on 303 participants in the MR Feasibility Study of the Cardiovascular Health Study were tested for lesion/deficit correlations. Functional data were derived from a limited neurologic examination performed at the time of the MR examination. Image data included 3D lesion descriptions derived from the MR examinations by hand segmentation. MR images were normalized in-plane using local, linear Talairach normalization. A database was implemented to support spatial data structures and associated geometric and statistical operations. The database stored the segmented lesions, patient functional scores, and several anatomic atlases. Lesion-deficit association was sought by contingency testing (chi2-test) for every possible combination of each neurologic variable and each labeled atlas structure. Significant associations that confirmed accepted lesion-deficit relationships were sought.&lt;/p&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;
&lt;p&gt;Two-hundred thirty-five infarctlike lesions in 117 subjects were viewed collectively after mapping into Talairach cartesian coordinates. Anatomic structures most strongly correlated with neurologic deficits tended to be situated in anatomically appropriate areas. For example, infarctlike lesions associated with visual field defects were correlated with structures in contralateral occipital structures, including the optic radiations and occipital gyri.&lt;/p&gt;&lt;h3&gt;CONCLUSION&lt;/h3&gt;
&lt;p&gt;Known lesion-deficit correlations can be established by a database using a standard coordinate system for representing spatial data and incorporating functional and structural data together with appropriate query mechanisms. Improvements and further applications of this methodology may provide a powerful technique for uncovering new structure-function relationships.&lt;/p&gt;" />
<meta name="citation_journal_title" content="American Journal of Neuroradiology" />
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<meta name="citation_publication_date" content="1998/11/01" />
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<meta name="citation_author" content="S I Letovsky" />
<meta name="citation_author" content="S H Whitehead" />
<meta name="citation_author" content="C H Paik" />
<meta name="citation_author" content="G A Miller" />
<meta name="citation_author" content="J Gerber" />
<meta name="citation_author" content="E H Herskovits" />
<meta name="citation_author" content="T K Fulton" />
<meta name="citation_author" content="R N Bryan" />
<meta name="twitter:title" content="A brain image database for structure/function analysis." />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE Lesion-deficit-based structure-function analysis has traditionally been empirical and nonquantitative. Our purpose was to establish a new brain image database (BRAID) that allows the statistical correlation of brain functional measures with anatomic lesions revealed by clinical brain images.

METHODS Data on 303 participants in the MR Feasibility Study of the Cardiovascular Health Study were tested for lesion/deficit correlations. Functional data were derived from a limited neurologic examination performed at the time of the MR examination. Image data included 3D lesion descriptions derived from the MR examinations by hand segmentation. MR images were normalized in-plane using local, linear Talairach normalization. A database was implemented to support spatial data structures and associated geometric and statistical operations. The database stored the segmented lesions, patient functional scores, and several anatomic atlases. Lesion-deficit association was sought by contingency testing (chi2-test) for every possible combination of each neurologic variable and each labeled atlas structure. Significant associations that confirmed accepted lesion-deficit relationships were sought.

RESULTS Two-hundred thirty-five infarctlike lesions in 117 subjects were viewed collectively after mapping into Talairach cartesian coordinates. Anatomic structures most strongly correlated with neurologic deficits tended to be situated in anatomically appropriate areas. For example, infarctlike lesions associated with visual field defects were correlated with structures in contralateral occipital structures, including the optic radiations and occipital gyri.

CONCLUSION Known lesion-deficit correlations can be established by a database using a standard coordinate system for representing spatial data and incorporating functional and structural data together with appropriate query mechanisms. Improvements and further applications of this methodology may provide a powerful technique for uncovering new structure-function relationships." />
<meta name="og-title" property="og:title" content="A brain image database for structure/function analysis." />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/19/10/1869" />
<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE Lesion-deficit-based structure-function analysis has traditionally been empirical and nonquantitative. Our purpose was to establish a new brain image database (BRAID) that allows the statistical correlation of brain functional measures with anatomic lesions revealed by clinical brain images.

METHODS Data on 303 participants in the MR Feasibility Study of the Cardiovascular Health Study were tested for lesion/deficit correlations. Functional data were derived from a limited neurologic examination performed at the time of the MR examination. Image data included 3D lesion descriptions derived from the MR examinations by hand segmentation. MR images were normalized in-plane using local, linear Talairach normalization. A database was implemented to support spatial data structures and associated geometric and statistical operations. The database stored the segmented lesions, patient functional scores, and several anatomic atlases. Lesion-deficit association was sought by contingency testing (chi2-test) for every possible combination of each neurologic variable and each labeled atlas structure. Significant associations that confirmed accepted lesion-deficit relationships were sought.

RESULTS Two-hundred thirty-five infarctlike lesions in 117 subjects were viewed collectively after mapping into Talairach cartesian coordinates. Anatomic structures most strongly correlated with neurologic deficits tended to be situated in anatomically appropriate areas. For example, infarctlike lesions associated with visual field defects were correlated with structures in contralateral occipital structures, including the optic radiations and occipital gyri.

CONCLUSION Known lesion-deficit correlations can be established by a database using a standard coordinate system for representing spatial data and incorporating functional and structural data together with appropriate query mechanisms. Improvements and further applications of this methodology may provide a powerful technique for uncovering new structure-function relationships." />
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      <h1 class="highwire-cite-title" id="page-title">A brain image database for structure/function analysis.</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">S I Letovsky</span>, <span class="highwire-citation-author" data-delta="1">S H Whitehead</span>, <span class="highwire-citation-author" data-delta="2">C H Paik</span>, <span class="highwire-citation-author" data-delta="3">G A Miller</span>, <span class="highwire-citation-author" data-delta="4">J Gerber</span>, <span class="highwire-citation-author" data-delta="5">E H Herskovits</span>, <span class="highwire-citation-author" data-delta="6">T K Fulton</span> and <span class="highwire-citation-author" data-delta="7">R N Bryan</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">November 1998,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">19 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1869-1877; </span></div>
  
  
  
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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 19</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 10 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Nov 1998 </div></div>
      
      
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