7T MRI Automated Software Segmentation of the Hippocampus for Epilepsy: Prospective Performance Evaluation

Area of Science:

• Neuroimaging
• Medical Physics

Background:

• 7T MRI offers advanced visualization for epilepsy imaging.
• Hippocampus volume quantification is a key biomarker for epilepsy.
• Automated tools are needed to leverage 7T MRI's potential.

Purpose of the Study:

• Evaluate automated hippocampal volume measurement software at 7T MRI.
• Compare performance against 3T MRI and manual segmentation.
• Assess software accuracy and reproducibility in epilepsy patients and controls.

Main Methods:

• Prospective 7T MRI acquisition in 50 participants.
• Automated hippocampal segmentation using FreeSurfer and NeuroQuant at 3T and 7T.
• Comparison with manual segmentation and intraclass correlation coefficient (ICC) analysis.

Main Results:

• Higher segmentation error rates at 7T vs. 3T for both software packages.
• Poor correlation between 7T automated and manual segmentation (ICC < 0.4).
• Fair to good correlation between 7T and 3T volumes; excellent reproducibility at 7T for automated software.

Conclusions:

• Automated 7T MRI hippocampus volumetry has high reproducibility but significant segmentation errors.
• Current automated tools show suboptimal correlation with 3T MRI and manual measurements.
• Further development of 7T-specific segmentation methods is crucial for epilepsy imaging.