Seed-based d mapping is a method for putting the meta-analyzing neuroimaging studies that may seem contradictory. For example, the results from studies of gray matter abnormalities in OCD. Previous meta-analytic methods have commonly assessed whether studies support more statistical peaks in one reason or in another, while SDM-PSI assesses whether there is an effect in a particular reason.
Researchers have mostly used SDM to investigate the neural substrates of psychological functions and neuropsychiatric disorders, which may include fMRI, VBM, DTI, PET or SBM studies. The use of SDM-PSI so far is quite straightforward. However, the most important steps for conducting a correct meta-analysis are designing an accurate meta-analysis plan and carefully collecting the data.
To perform an exhaustive search, open the database of interest and enter various keywords that will allow searching for any study that might meet the inclusion criteria. Then, record the number of studies retrieved and the number of studies excluded for each reason. Consider creating a PRISMA flow diagram with these numbers.
After reading the manuscripts of interest to find the specific data to extract, to convert Z-values and P-values into T-values, click Convert peaks in the SDM-PSI software. Then use positive T-values for peaks of increase and negative T-values for peaks of decrease, using the table for guidance for how to decide the sign of the T-values. In two sample studies, you use positive T-values when MRI signal is higher in patients than in controls.
And use negative T-values when MRI signal is lower in patients than in controls. To introduce the data into SDM-PSI, open SDM-PSI graphic user interface and close the About splash window. Click Change meta-analysis to select a new empty directory for the meta-analysis.
Click SDM table editor to input general information from the studies and open a text editor to create a text file for each study to type the coordinates and T-values of the peaks. And name the file, the software program used and the stereotactic space. For preprocessing of the data, click the preprocessing button, select the modality of the studies at the list box labeled Modality and press OK.Then wait several minutes while the permutation of subject images program calculated the maps of the lower and upper bounds of the potential effect sizes.
To perform the main analysis, click the Mean button and press OK.After the SDM-PSI has conducted the multiple imputation and meta-analysis, click Threshold, select the uncorrected P-values of the main analysis and click OK.SDM-PSI will automatically open both MRIcron to visualize the results and a web page with a detailed report of the results. Click family-wise error correction to select the main analysis in the list box and click OK.The SDM-PSI program will conduct the permutation test over several hours or days. At the end of the rest, click Threshold, select the TFCE correction of the main analysis and click OK.The program will automatically open both MRIcron to visualize the results and a web page with a detailed report of the analysis.
For heterogeneity, publication bias and grading, click extract, select a peak from the main analysis and press OK.The program will automatically open a web page with statistics of this P.Record the heterogeneity I-squared statistic. Next click the Bias Test button, select a peak from the main analysis and click OK.The program will automatically open a web page with a funnel plot and the results of a test for small-study effect and a test for excess significance. Then click the Evidence Grading button from the top tool box.
Select the main analysis from the list box and click OK to view the results. As observed in these representative maps, patients with OCD have a statistically significantly smaller gray matter volume in the dorsal anterior cingulate medial frontal cortex. The cluster is moderately small and mainly located at Brodmann area 32 with the peak of the cluster at MNI two, 32, 32 with a Z-value of 4.97 and a family-wise error rate corrected P-value of 0.01.
In this data analysis, the low I-squared statistic indicates very small heterogeneity and the funnel plot does not show asymmetries. Key aspects of a successful meta-analysis are the creation of clear inclusion and exclusion criteria, the careful collection of data and not limiting the results to P-values. SDM-PSI incorporates the general linear model for which users might conduct meta-regressions or meta-compressions of groups of studies and or at compare it to the analysis.
Many SDM meta-analysis have had a considerable influence on their specific fields. For example, several meta-analysis have revealed interesting effects of stimulants on the brain abnormalities observed in ADHD.
