| Autor: |
Moshchin M; University of Wisconsin-Madison, Madison, WI USA., Cheng KP; University of Wisconsin-Madison, Madison, WI USA., Osting S; University of Wisconsin-Madison, Madison, WI USA., Laluzerne M; University of Wisconsin-Madison, Madison, WI USA., Hurley SA; University of Wisconsin-Madison, Madison, WI USA., Singh AP; University of Wisconsin-Madison, Madison, WI USA., Trevathan JK; University of Wisconsin-Madison, Madison, WI USA., Brzeczkowski A; University of Wisconsin-Madison, Madison, WI USA., Yu JJ; University of Wisconsin-Madison, Madison, WI USA., Lake WB; University of Wisconsin-Madison, Madison, WI USA., Ludwig KA; University of Wisconsin-Madison, Madison, WI USA., Suminski AJ; University of Wisconsin-Madison, Madison, WI USA. |
| Abstrakt: |
In recent years, tractography based on diffusion magnetic resonance imaging (dMRI) has become a popular tool for studying microstructural changes resulting from brain diseases like Parkinson's Disease (PD). Quantitative anisotropy (QA) is a parameter that is used in deterministic fiber tracking as a measure of connection between brain regions. It remains unclear, however, if microstructural changes caused by lesioning the median forebrain bundle (MFB) to create a Parkinsonian rat model can be resolved using tractography based on ex-vivo diffusion MRI. This study aims to fill this gap and enable future mechanistic research on structural changes of the whole brain network rodent models of PD. Specifically, it evaluated the ability of correlational tractography to detect structural changes in the MFB of 6-hydroxydopamine (6-OHDA) lesioned rats. The findings reveal that correlational tractography can detect structural changes in lesioned MFB and differentiate between the 6-OHDA and control groups. Imaging results are supported by behavioral and histological evidence demonstrating that 6-OHDA lesioned rats were indeed Parkinsonian. The results suggest that QA and correlational tractography is appropriate to examine local structural changes in rodent models of neurodegenerative disease. More broadly, we expect that similar techniques may provide insight on how disease alters structure throughout the brain, and as a tool to optimize therapeutic interventions. |
