Differential Cerebral White Matter Tract Alterations in Generalized Anxiety Disorder Revealed by Ultra-High Field 7T Diffusion-Weighted Imaging

BackgroundGeneralized anxiety disorder (GAD) is characterized by chronic worry and emotional dysregulation, yet its underlying white matter (WM) architecture remains inconsistent in previous neuroimaging studies. This study aimed to delineate microstructural WM alterations in GAD using ultra-high field (7T) diffusion tensor imaging (DTI) and advanced correlational tractography, evaluating their associations with symptom severity and diagnostic-aided value. MethodsEighty-eight participants (27 GAD, 61 healthy controls, HCs) underwent 7T DTI scanning with 1.5-mm isotropic resolution. Whole-brain correlational tractography was applied to identify tracts exhibiting significant group-related differences in diffusion indices while controlling for demographic covariates. Associations with Hamilton Anxiety Rating Scale (HAM-A) and Penn State Worry Questionnaire (PSWQ) scores were examined, and machine learning-based models were used to assess the diagnostic-aided utility of identified WM features. ResultsTwo tract bundles showed significant fractional anisotropy (FA) alterations in GAD: decreased FA in the right prefrontal pathway (PFDR = 0.039) and increased FA in the right cingulum (PFDR < 0.001). The anterior portions of both tracts exhibited stronger effects of GAD. FA in the right cingulum positively correlated with HAM-A and PSWQ scores, indicating that greater microstructural coherence was associated with higher anxiety and worry severity (both PFDRs < 0.001). Inclusion of WM features could improve classification performance beyond neuropsychological measures alone. ConclusionsUltra-high field 7T tractometry revealed a differential pattern of WM abnormalities in GAD, suggesting weakened prefrontal control and hyper-integrated cingulate connectivity as structural correlates of emotional dysregulation. These findings indicate the potential of 7T DTI markers for advancing mechanistic and diagnostic understanding of GAD.