Depressive disorder is one of the leading causes of disability worldwide, with a high prevalence and chronic course. Depressive disorder carries an increased risk of suicide. Alterations in brain structure and networks may play an important role in suicidality among depressed patients. Diffusion magnetic resonance imaging (MRI) is a noninvasive method to map white-matter fiber orientations and provide quantitative parameters. This study investigated the neurological structural differences and network alterations in depressed patients with suicide attempts by using generalized q-sampling imaging (GQI). Our study recruited 155 participants and assigned them into three groups: 44 depressed patients with a history of suicide attempts (SA), 56 depressed patients without a history of suicide attempts (D) and 55 healthy controls (HC). We used the GQI to analyze the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values in voxel-based statistical analysis, topological parameters in graph theoretical analysis and subnetwork connectivity in network-based statistical analysis. GFA indicates the measurement of neural anisotropy and represents white-matter integrity; NQA indicates the amount of anisotropic spins that diffuse along fiber orientations and represents white-matter compactness. In the voxel-based statistical analysis, we found lower GFA and NQA values in the SA group than in the D and HC groups and lower GFA and NQA values in the D group than in the HC group. In the graph theoretical analysis, the SA group demonstrated higher local segregation and lower global integration among the three groups. In the network-based statistical analysis, the SA group showed stronger subnetwork connections in the frontal and parietal lobes, and the D group showed stronger subnetwork connections in the parietal lobe than the HC group. Alternations were found in the structural differences and network measurements in healthy controls and depressed patients with and without a history of suicide attempt.

Suicide is one of the leading causes of mortality worldwide. Various factors could lead to suicidal ideation (SI), while depression is the predominant cause among all mental disorders. Studies have shown that alterations in brain structures and networks may be highly associated with suicidality. This study investigated both neurological structural variations and network alterations in depressed patients with suicidal ideation by using generalized q-sampling imaging (GQI) and Graph Theoretical Analysis (GTA). This study recruited 155 participants and divided them into three groups: 44 depressed patients with suicidal ideation (SI+; 20 males and 24 females with mean age = 42, SD = 12), 56 depressed patients without suicidal ideation (Depressed; 24 males and 32 females with mean age = 45, SD = 11) and 55 healthy controls (HC; nine males and 46 females with mean age = 39, SD = 11). Both the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values were evaluated in a voxel-based statistical analysis by GQI. We analyzed different topological parameters in the graph theoretical analysis and the subnetwork interconnections in the Network-based Statistical (NBS) analysis. In the voxel-based statistical analysis, both the GFA and NQA values in the SI+ group were generally lower than those in the Depressed and HC groups in the corpus callosum and cingulate gyrus. Furthermore, we found that the SI+ group demonstrated higher global integration and lower local segregation among the three groups of participants. In the network-based statistical analysis, we discovered that the SI+ group had stronger connections of subnetworks in the frontal lobe than the HC group. We found significant structural differences in depressed patients with suicidal ideation compared to depressed patients without suicidal ideation and healthy controls and we also found several network alterations among these groups of participants, which indicated that white matter integrity and network alterations are associated with patients with depression as well as suicidal ideation.