Current image processing methods for dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) do not capture complex dynamic information of time-signal intensity curves. We investigated whether an autoencoder-based pattern analysis of DSC MRI captured representative temporal features that improves tissue characterization and tumor diagnosis in a multicenter setting. The autoencoder was applied to the time-signal intensity curves to obtain representative temporal patterns, which were subsequently learned by a convolutional neural network. This network was trained with 216 preoperative DSC MRI acquisitions and validated using external data (n = 43) collected with different DSC acquisition protocols. The autoencoder applied to time-signal intensity curves and clustering obtained nine representative clusters of temporal patterns, which accurately identified tumor and non-tumoral tissues. The dominant clusters of temporal patterns distinguished primary central nervous system lymphoma (PCNSL) from glioblastoma (AUC 0.89) and metastasis from glioblastoma (AUC 0.95). The autoencoder captured DSC time-signal intensity patterns that improved identification of tumoral tissues and differentiation of tumor type and was generalizable across centers.

Background: Major depressive disorder (MDD) is a mood disorder associated with disruptions in emotional control. Previous studies have investigated abnormal regional activity and connectivity within the fronto-limbic circuit. However, condition-specific connectivity changes and their association with the pathophysiology of MDD remain unexplored. This study investigated effective connectivity in the fronto-limbic circuit induced by negative emotional processing from patients with MDD. Methods: Thirty-four unmedicated female patients with MDD and 28 healthy participants underwent event-related functional magnetic resonance imaging at 7T while viewing emotionally negative and neutral images. Brain regions whose dynamics are driven by experimental conditions were identified by using statistical parametric mapping. Effective connectivity among regions of interest was then estimated by using dynamic causal modeling. Results: Patients with MDD had lower activation of the orbitofrontal cortex (OFC) and higher activation of the parahippocampal gyrus (PHG) than healthy controls (HC). In association with these regional changes, we found that patients with MDD did not have significant modulatory connections from the primary visual cortex (V1) to OFC, whereas those connections of HC were significantly positively modulated during negative emotional processing. Regarding the PHG activity, patients with MDD had greater modulatory connection from the V1, but reduced negative modulatory connection from the OFC, compared with healthy participants. Conclusions: These results imply that disrupted effective connectivity among regions of the OFC, PHG, and V1 may be closely associated with the impaired regulation of negative emotional processing in the female patients with MDD.

We aimed to assess whether brain volumes may affect the results of deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). Eighty-one consecutive patients with PD (male:female 40:41), treated with DBS between June 2012 and December 2017, were enrolled. Total and regional brain volumes were measured using automated brain volumetry (NeuroQuant). The Unified Parkinson Disease Rating Scale motor score quotient was used to assess changes in clinical outcome and compare the preoperative regional brain volume in patients categorized into the higher motor improvement and lower motor improvement groups based on changes in the postoperative scores. The study groups showed significant volume differences in multiple brain areas. In the higher motor improvement group, the anterior cingulate and right thalamus showed high volumes after false discovery rate (FDR) correction. In the lower motor improvement group, the left caudate, paracentral, right primary sensory and left primary motor cortex showed high volume, but no area showed high volumes after FDR correction. Our data suggest that the effectiveness of DBS in patients with PD may be affected by decreased brain volume in different areas, including the cingulate gyrus and thalamus. Preoperative volumetry could help predict outcomes in patients with PD undergoing DBS.