Tractography in Type 2 Diabetes Mellitus With Subjective Memory Complaints: A Diffusion Tensor Imaging Study - Wang, Jun; Ma, Laiyang; Liu, Guangyao; Bai, Wenjuan; Ai, Kai; Zhang, Pengfei; Hu, Wanjun; Zhang, Jing (Frontiers in Neuroscience, 2022)
The brain white matter (WM) structural injury caused by type 2 diabetes mellitus (T2DM) has been linked to cognitive impairment. However, the focus was mainly on the mild cognitive impairment (MCI) stage in most previous studies, with little attention made to subjective memory complaints (SMC). The main purpose of current study was to investigate the characteristics of white matter injury in T2DM patients and its correlation with SMC symptoms. In a group of 66 participants (33 HCs and 33 T2DM-S), pointwise differences along WM tracts were identified using the automatic fiber quantitative (AFQ) approach. Then, we investigated the utility of DTI properties along major WM tracts as features to distinguish patients with T2DM-S from HCs via the support vector machine (SVM). Based on AFQ analysis, 10 primary fiber tracts that represent the subtle alterations of WM in T2DM-S were identified. Lower fractional anisotropy (FA) in the right SLF tract (r = -0.538, p = 0.0013), higher radial diffusivity (RD) in the thalamic radiation tract (r = 0.433, p = 0.012) and higher mean diffusivity (MD) in the right inferior fronto-occipital fasciculus (IFOF) tract (r = 0.385, p = 0.0029), were significantly associated with long period of disease. Decreased axial diffusivity (AD) in left arcuate was associated with HbA1c (r = -0.368, p = 0.049). In addition, we found a significant negative correlation between delayed recall and abnormal MD in the left corticospinal tract (r = -0.546, p = 0.001). The FA of the right SLF tracts and bilateral arcuate can be used to differentiate the T2DM-S and the HC at a high accuracy up to 88.45% and 87.8%, respectively. In conclusion, WM microstructure injury in T2DM may be associated with SMC, and these abnormalities identified by DTI can be used as an effective biomarker.