Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T.
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4 février 2019
- doi: 10.1038/s41598-018-37825-8
- issn: 2045-2322
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info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-018-37825-8
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info:eu-repo/semantics/altIdentifier/pmid/30718634
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info:eu-repo/semantics/altIdentifier/eissn/2045-2322
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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_B1F0F0F9F61B6
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
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Nerves--Surgery NeurosurgeryCiter ce document
E. Najdenovska et al., « Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T. », Serveur académique Lausannois, ID : 10.1038/s41598-018-37825-8
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Résumé
The ventro-intermediate nucleus (Vim), as part of the motor thalamic nuclei, is a commonly used target in functional stereotactic neurosurgery for treatment of drug-resistant tremor. As it cannot be directly visualized on routinely used magnetic resonance imaging (MRI), its clinical targeting is performed using indirect methods. Recent literature suggests that the Vim can be directly visualized on susceptibility-weighted imaging (SWI) acquired at 7 T. Our work aims to assess the distinguishable Vim on 7 T SWI in both healthy-population and patients and, using it as a reference, to compare it with: (1) The clinical targeting, (2) The automated parcellation of thalamic subparts based on 3 T diffusion MRI (dMRI), and (3) The multi-atlas segmentation techniques. In 95.2% of the data, the manual outline was adjacent to the inferior lateral border of the dMRI-based motor-nuclei group, while in 77.8% of the involved cases, its ventral part enclosed the Guiot points. Moreover, the late MRI signature in the patients was always observed in the anterior part of the manual delineation and it overlapped with the multi-atlas outline. Overall, our study provides new insight on Vim discrimination through MRI and imply novel strategies for its automated segmentation, thereby opening new perspectives for standardizing the clinical targeting.