Ex vivo mesoscopic diffusion MRI correlates with seizure frequency in patients with uncontrolled mesial temporal lobe...

Area of Science:

• Neuroimaging
• Epilepsy Research
• Diffusion Tensor Imaging

Background:

• The role of hippocampal connectivity in mesial temporal lobe epilepsy (mTLE) is not well understood.
• Ex vivo hippocampal samples from mTLE patients can be studied using mesoscale diffusion MRI.
• This technique allows for the identification of individual cell layers impacted by seizure activity.

Purpose of the Study:

• To investigate intra-hippocampal connectivity in mTLE using mesoscale diffusion MRI.
• To evaluate how epilepsy affects diffusion metrics (MD, AD, RD, FA) and streamline density.
• To correlate diffusion changes with clinical measures of disease severity.

Main Methods:

• Diffusion Tensor Imaging (DTI) was performed on ex vivo control (n=3) and mTLE (n=7) hippocampi using an 11.7 T MRI scanner.
• Regional measurements assessed volume loss in specific hippocampal subfields (e.g., PCL in CA1).
• Diffusion metrics and streamline density were compared between control and mTLE groups.

Main Results:

• Volume loss in the pyramidal cell layer (PCL) of the CA1 subfield was observed in mTLE patients.
• Diffusion measurements and streamline density were generally higher in mTLE hippocampi, potentially due to tissue fixation.
• Variability in mTLE measurements strongly correlated with disease severity, notably FA in the stratum radiatum with seizure frequency (r=0.87).
• Mean diffusivity (MD) and radial diffusivity (RD) in the PCL of CA3 and CA4 also correlated with disease severity.

Conclusions:

• Mesoscale diffusion MRI is a valuable tool for examining layer-specific diffusion changes and connectivity in the hippocampus.
• Observed diffusion changes and variability in mTLE correlate with clinical measures of disease severity, particularly seizure frequency.
• These findings advance the understanding of intra-hippocampal connectivity alterations in epilepsy and can inform novel hypotheses about seizure networks.