Seed-based d mapping

<h2 id="the-seed-based-d-mapping-approach">The seed-based d mapping approach</h2>
<h3>Overview of the method</h3>
<p>SDM adopted and combined various positive features from previous methods, such as ALE or MKDA, and introduced a series of improvements and novel features.<a class="footnote-ref" id="fnref:1" href="#fn:1"><sup>1</sup></a> One of the new features, introduced to avoid positive and negative findings in the same <a href="/facts/Voxel/xo077lPE">voxel</a> as seen in previous methods, was the representation of both positive differences and negative differences in the same map, thus obtaining a signed differential map (SDM). Another relevant feature, introduced in version 2.11, was the use of <a href="/facts/Effect_size/mIpNrPte">effect sizes</a> (leading to effect-size SDM or 'ES-SDM'), which allows combination of reported peak coordinates with statistical parametric maps, thus allowing more exhaustive and accurate meta-analyses.<a class="footnote-ref" id="fnref:2" href="#fn:2"><sup>2</sup></a>
</p><p>The method has three steps. First, coordinates of cluster peaks (e.g. the <a href="/facts/Voxel/xo077lPE">voxels</a> where the differences between patients and healthy controls were highest), and statistical maps if available, are selected according to SDM inclusion criteria. Second, coordinates are used to recreate statistical maps, and effect-sizes maps and their variances are derived from <a href="/facts/T-statistic/eTlyuoqG">t-statistics</a> (or equivalently from <a href="/facts/P-value/InnYd1bz">p-values</a> or <a href="/facts/Standard_score/lF8v0Mcy">z-scores</a>). Finally, individual study maps are <a href="/facts/Meta-analysis/IcfChd8z">meta-analyzed</a> using different tests to complement the main outcome with sensitivity and <a href="/facts/Study_heterogeneity/AnKsu2K3">heterogeneity</a> analyses.
</p>
<h3>Inclusion criteria</h3>
<p>It is not uncommon in <a href="/facts/Neuroimaging/dA5Cteaf">neuroimaging</a> studies that some regions (e.g. a priori <a href="/facts/Region_of_interest/C8k58oC5">regions of interest</a>) are more liberally <a href="/facts/Statistical_hypothesis_testing/yv9RPF6U">thresholded</a> than the rest of the <a href="/facts/Brain/EKla9NkJ">brain</a>. However, a <a href="/facts/Meta-analysis/IcfChd8z">meta-analysis</a> of studies with such intra-study regional differences in <a href="/facts/Statistical_hypothesis_testing/yv9RPF6U">thresholds</a> would be <a href="/facts/Bias_of_an_estimator/oxIvEgmd">biased</a> towards these regions, as they are more likely to be reported just because authors apply more liberal <a href="/facts/Statistical_hypothesis_testing/yv9RPF6U">thresholds</a> in them. In order to overcome this issue SDM introduced a criterion in the selection of the coordinates: while different studies may employ different thresholds, you should ensure that the same threshold throughout the whole brain was used within each included study.<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a>
</p>
<h3>Pre-processing of studies</h3>
<p>After conversion of statistical parametric maps and peak coordinates to <a href="/facts/Talairach_coordinates/sY7VK05C">Talairach space</a>, an SDM map is created for each study within a specific gray or white matter template.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> Pre-processing of statistical parametric maps is straightforward, while pre-processing of reported peak coordinates requires recreating the clusters of difference by means of an un-normalized <a href="/facts/Gaussian_function/5bG8Kpp9">Gaussian Kernel</a>, so that <a href="/facts/Voxels/xo077lPE">voxels</a> closer to the peak coordinate have higher values. A rather large <a href="/facts/Full_width_at_half_maximum/oXSLXf7S">full-width at half-maximum</a> (FWHM) of 20mm is used to account for different sources of spatial error, e.g. <a href="/facts/Coregistration/y2KUwdRL">coregistration</a> mismatch in the studies, the size of the cluster or the location of the peak within the cluster. Within a study, values obtained by close <a href="/facts/Gaussian_function/5bG8Kpp9">Gaussian kernels</a> are summed, though values are combined by square-distance-weighted averaging.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a>
</p>
<h3>Statistical comparisons</h3>
<p>SDM provides several different statistical analyses in order to complement the main outcome with sensitivity and <a href="/facts/Study_heterogeneity/AnKsu2K3">heterogeneity</a> analyses.
</p>
<ul><li>The main statistical analysis is the <a href="/facts/Mean/swcEd4Pg">mean</a> analysis, which consists in calculating the <a href="/facts/Mean/swcEd4Pg">mean</a> of the <a href="/facts/Voxel/xo077lPE">voxel</a> values in the different studies. This <a href="/facts/Mean/swcEd4Pg">mean</a> is <a href="/facts/Weight_function/YNJL7o99">weighted</a> by the inverse of the variance and accounts for <a href="/facts/Study_heterogeneity/AnKsu2K3">inter-study heterogeneity</a> (QH maps).<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a></li>
<li><a href="/facts/Subgroup_analysis/9wfKYw3C">Subgroup analyses</a> are mean analyses applied to groups of studies to allow the study of <a href="/facts/Study_heterogeneity/AnKsu2K3">heterogeneity</a>.</li>
<li><a href="/facts/Linear_model/x1we3e1d">Linear model</a> analyses (e.g. meta-regression) are a generalization of the mean analysis to allow comparisons between groups and the study of possible <a href="/facts/Confounding/G4TVx1dt">confounds</a>.<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a> A low variability of the regressor is critical in meta-regressions, so they are recommended to be understood as exploratory and to be more conservatively thresholded.<a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a></li>
<li><a href="/facts/Resampling_(statistics)/yq6LXqnX">Jack-knife analysis</a> consists in repeating a test as many times as studies have been included, discarding one different study each time, i.e. removing one study and repeating the analyses, then putting that study back and removing another study and repeating the analysis, and so on. The idea is that if a significant brain region remains significant in all or most of the combinations of studies it can be concluded that this finding is highly replicable.<a class="footnote-ref" id="fnref:9" href="#fn:9"><sup>9</sup></a></li></ul>
<p>The <a href="/facts/Statistical_significance/PMxjdlAu">statistical significance</a> of the analyses is checked by standard <a href="/facts/Monte_Carlo_method/AkHjY7jc">randomization tests</a>. It is recommended to use uncorrected p-values = 0.005, as this significance has been found in this method to be approximately equivalent to a corrected p-value = 0.05.<a class="footnote-ref" id="fnref:10" href="#fn:10"><sup>10</sup></a> A <a href="/facts/False_discovery_rate/NqyJxV8s">false discovery rate</a> (FDR) = 0.05 has been found in this method to be too conservative. Values in a Talairach label or coordinate can also be extracted for further processing or graphical presentation.
</p>
<h2 id="sdm-software">SDM software</h2>
<p>SDM is software written by the SDM project to aid the meta-analysis of <a href="/facts/Voxel/xo077lPE">voxel-based</a> neuroimaging data. It is distributed as <a href="/facts/Freeware/c8oGA9ju">freeware</a> including a graphical interface and a menu/command-line console. It can also be integrated as an <a href="/facts/Statistical_parametric_mapping/NDJ7qx6M">SPM</a> extension.
</p>

<h2 id="external-links">External links</h2>
<ul><li><a href="http://www.sdmproject.com/">SDM</a> software and documentation from the SDM Project.</li></ul>

<h2 id="references">References</h2>

<ol>
<li id="fn:1"><p>Radua, Joaquim; Mataix-Cols, David (1 November 2009). "Voxel-wise meta-analysis of grey matter changes in obsessive–compulsive disorder". The British Journal of Psychiatry. 195 (5): 393–402. doi:10.1192/bjp.bp.108.055046. PMID 19880927. <a href="https://doi.org/10.1192%2Fbjp.bp.108.055046" target="_blank">https://doi.org/10.1192%2Fbjp.bp.108.055046</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li>
<li id="fn:2"><p>Radua, Joaquim; Mataix-Cols, David; Phillips, Mary L.; El-Hage, Wissam; Kronhaus, Dina M.; Cardoner, Narcís; Surguladze, Simon (2012). "A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps". European Psychiatry. 27 (8): 605–611. doi:10.1016/j.eurpsy.2011.04.001. PMID 21658917. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li>
<li id="fn:3"><p>Radua, Joaquim; Mataix-Cols, David (1 November 2009). "Voxel-wise meta-analysis of grey matter changes in obsessive–compulsive disorder". The British Journal of Psychiatry. 195 (5): 393–402. doi:10.1192/bjp.bp.108.055046. PMID 19880927. <a href="https://doi.org/10.1192%2Fbjp.bp.108.055046" target="_blank">https://doi.org/10.1192%2Fbjp.bp.108.055046</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li>
<li id="fn:4"><p>Radua, Joaquim; Via, Esther; Catani, Marco; Mataix-Cols, David (2010). "Voxel-based meta-analysis of regional white-matter volume differences in autism spectrum disorder versus healthy controls". Psychological Medicine. 41 (7): 1–12. doi:10.1017/S0033291710002187. PMID 21078227. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li>
<li id="fn:5"><p>Radua, Joaquim; Mataix-Cols, David; Phillips, Mary L.; El-Hage, Wissam; Kronhaus, Dina M.; Cardoner, Narcís; Surguladze, Simon (2012). "A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps". European Psychiatry. 27 (8): 605–611. doi:10.1016/j.eurpsy.2011.04.001. PMID 21658917. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li>
<li id="fn:6"><p>Radua, Joaquim; Mataix-Cols, David; Phillips, Mary L.; El-Hage, Wissam; Kronhaus, Dina M.; Cardoner, Narcís; Surguladze, Simon (2012). "A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps". European Psychiatry. 27 (8): 605–611. doi:10.1016/j.eurpsy.2011.04.001. PMID 21658917. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li>
<li id="fn:7"><p>Radua, Joaquim; van den Heuvel, Odile A.; Surguladze, Simon; Mataix-Cols, David (5 July 2010). "Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs other anxiety disorders". Archives of General Psychiatry. 67 (7): 701–711. doi:10.1001/archgenpsychiatry.2010.70. PMID 20603451. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li>
<li id="fn:8"><p>Radua, Joaquim; Mataix-Cols, David (1 November 2009). "Voxel-wise meta-analysis of grey matter changes in obsessive–compulsive disorder". The British Journal of Psychiatry. 195 (5): 393–402. doi:10.1192/bjp.bp.108.055046. PMID 19880927. <a href="https://doi.org/10.1192%2Fbjp.bp.108.055046" target="_blank">https://doi.org/10.1192%2Fbjp.bp.108.055046</a> <a href="#fnref:8" class="footnote-back-ref">↩</a></p></li>
<li id="fn:9"><p>Radua, Joaquim; Mataix-Cols, David (1 November 2009). "Voxel-wise meta-analysis of grey matter changes in obsessive–compulsive disorder". The British Journal of Psychiatry. 195 (5): 393–402. doi:10.1192/bjp.bp.108.055046. PMID 19880927. <a href="https://doi.org/10.1192%2Fbjp.bp.108.055046" target="_blank">https://doi.org/10.1192%2Fbjp.bp.108.055046</a> <a href="#fnref:9" class="footnote-back-ref">↩</a></p></li>
<li id="fn:10"><p>Radua, Joaquim; Mataix-Cols, David; Phillips, Mary L.; El-Hage, Wissam; Kronhaus, Dina M.; Cardoner, Narcís; Surguladze, Simon (2012). "A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps". European Psychiatry. 27 (8): 605–611. doi:10.1016/j.eurpsy.2011.04.001. PMID 21658917. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:10" class="footnote-back-ref">↩</a></p></li>
</ol>

Seed-based d mapping open-in-new

Seed-based d mapping