In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy.
Yu-Chao JiangWei LiYingjie QinLe ZhangXin TongFenglai XiaoSisi JiangYunfang LiQi-Yong GongDong ZhouDongmei AnDezhong YaoCheng LuoPublished in: Human brain mapping (2023)
Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1-weighted and T2-weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel-wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1-weighted and T2-weighted MRI to investigate in vivo the myelin-related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.
Keyphrases
- magnetic resonance imaging
- contrast enhanced
- temporal lobe epilepsy
- magnetic resonance
- end stage renal disease
- ejection fraction
- newly diagnosed
- white matter
- computed tomography
- network analysis
- machine learning
- oxidative stress
- patient reported outcomes
- multiple sclerosis
- cognitive impairment
- brain injury
- patient reported