Cerebellar gray matter volume difference in first-episode bipolar and unipolar depression

Early differential diagnosis of bipolar disorder (BD) and unipolar depression (UD) remains a major clinical challenge, especially during the initial depressive episode. This study aimed to investigate whether cerebellar gray matter volume could serve as a potential neuroimaging biomarker to distinguish BD from UD at an early stage.

Structural MRI data were obtained from 42 patients with BD, 48 patients with UD, and 83 matched healthy controls. The cerebellum was parcellated into 28 lobules and 7 functional networks using the SUIT anatomical and Buckner-Yeo functional atlases. Voxel-based and region-of-interest (ROI) analyses were conducted, and a machine learning model was applied.

Whole-cerebellum analyses revealed that the total cerebellar gray matter volume in UD patients was significantly larger than in BD patients. Voxel-based studies indicated that the regions of Vermis IX, Vermis VI, and Left VI were significantly smaller in the BD group compared to the UD group. ROI-based comparisons showed a significant higher in the volume of gray matter in the limbic network in UD patients compared to BD. Furthermore, the gray matter volume of the limbic network in the dorsal attention network and the default mode network was significantly reduction in BD patients compared to healthy controls. The machine learning model constructed using cerebellar lobules with significant inter-group differences achieved an accuracy of 76.3% and a sensitivity of 83.0%.

Cerebellar gray matter volume may serve as a clinical marker to differentiate the depressive phase of bipolar disorder (after the first manic or hypomanic episode) from unipolar depression.