Study of structural network connectivity using DTI tractography in insomnia disorder
Masoumeh Rostampour1, Zeinab Gharaylou2, Ali Rostampour3
1Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Psychiatry Research. Neuroimaging
|November 9, 2023
Summary
This study improved brain imaging analysis for insomnia disorder (ID) using COMMIT2 tractography. The findings reveal altered structural connectivity in ID patients, highlighting the need for accurate brain network analysis.
Area of Science:
- Neuroimaging
- Brain Connectivity
- Sleep Medicine
Background:
- Tractography studies in insomnia disorder (ID) often report decreased structural connectivity.
- Standard diffusion tensor imaging (DTI) tractography can produce false-positive connections.
Purpose of the Study:
- To enhance the accuracy of whole-brain connectome reconstruction in ID using COMMIT2.
- To identify altered structural connectivity networks in ID patients compared to healthy controls.
Main Methods:
- Employed convex optimization modeling for microstructure informed tractography-2 (COMMIT2) for improved tractography.
- Utilized NBS-predict on the COMMIT2-weighted connectome for network analysis.
- Compared results with standard connectivity analysis.
Main Results:
- Insomnia patients showed decreased structural connectivity in several brain networks, including somatomotor, attention, and default mode networks.
- Sleep efficiency negatively correlated with structural connectivity in multiple networks.
- COMMIT2 filtering reduced false-positive connections, clarifying abnormal connectivity in ID.
Conclusions:
- Accurate tractography is crucial for understanding structural connectivity in insomnia disorder.
- COMMIT2 provides a more reliable method for assessing brain networks in ID.
- Findings underscore the network-level impact of insomnia on brain structure.
