Gray matter volume differences of the right middle cingulate cortex/posterior cingulate cortex/precuneus.

<p>Gray matter volume enlargement was found in the right middle cingulate cortex/posterior cingulate cortex/precuneus of patients with borderline personality disorder compared with healthy controls (MNI coordinates, x = 11, y = –40, z = 34; P_{FDR-corrected} = 0.011; extent threshold, 1239 voxels).</p

Characteristics of EOS and control groups in fMRI analysis.

<p>Characteristics of EOS and control groups in fMRI analysis.</p

Classification of Different Therapeutic Responses of Major Depressive Disorder with Multivariate Pattern Analysis Method Based on Structural MR Scans

<div><h3>Background</h3><p>Previous studies have found numerous brain changes in patients with major depressive disorder (MDD), but no neurological biomarker has been developed to diagnose depression or to predict responses to antidepressants. In the present study, we used multivariate pattern analysis (MVPA) to classify MDD patients with different therapeutic responses and healthy controls and to explore the diagnostic and prognostic value of structural neuroimaging data of MDD.</p> <h3>Methodology/Principal Findings</h3><p>Eighteen patients with treatment-resistant depression (TRD), 17 patients with treatment-sensitive depression (TSD) and 17 matched healthy controls were scanned using structural MRI. Voxel-based morphometry, together with a modified MVPA technique which combined searchlight algorithm and principal component analysis (PCA), was used to classify the subjects with TRD, those with TSD and healthy controls. The results revealed that both gray matter (GM) and white matter (WM) of frontal, temporal, parietal and occipital brain regions as well as cerebellum structures had a high classification power in patients with MDD. The accuracy of the GM and WM that correctly discriminated TRD patients from TSD patients was both 82.9%. Meanwhile, the accuracy of the GM that correctly discriminated TRD or TSD patients from healthy controls were 85.7% and 82.4%, respectively; and the WM that correctly discriminated TRD or TSD patients from healthy controls were 85.7% and 91.2%, respectively.</p> <h3>Conclusions/Significance</h3><p>These results suggest that structural MRI with MVPA might be a useful and reliable method to study the neuroanatomical changes to differentiate patients with MDD from healthy controls and patients with TRD from those with TSD. This method might also be useful to study potential brain regions associated with treatment response in patients with MDD.</p> </div

Most important gray matter regions discriminating between TRD patients and TSD patients.

<p>The <i>P</i> values were obtained by permutation test. BA, Broadmann’s area.</p

Comparison of discriminative performance of different MVPA methods on TRD versus TSD and TRD or TSD versus controls.

<p>PCA, Principal component analysis; RFE, recursive feature elimination; LLE, locally linear embedding; TRD, treatment-resistant depression; TSD, treatment-sensitive depression; HC, healthy control.</p

Flow chart of the proposed MVPA method.

<p>Flow chart of the proposed MVPA method.</p

Resulting spatial maps of accuracy for discriminating between TRD patients and TSD patients using gray matter.

<p>These clusters were identified by setting the threshold of accuracy higher than 70% and cluster size more than 50 voxels.</p

Resulting spatial maps of accuracy for discriminating between TRD patients and TSD patients using white matter.

<p>These clusters were identified by setting the threshold of accuracy higher than 70% and cluster size more than 50 voxels.</p

Most important white matter regions discriminating between TRD patients and TSD patients.

<p>The <i>P</i> values were obtained by permutation test. BA, Broadmann’s area.</p