Surgical neurology international · 2025
Dentato-rubro-thalamic tract tractography: Constrained spherical deconvolution versus diffusion tensor imaging for essential tremor deep brain stimulation targeting.
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Menezes Ryan Fernando, Prudente Rafael Lisboa, Freitas Erom Lucas Alves, Fernandes de Oliveira Santos Bruno
Аннотация
BACKGROUND: This study aimed to compare diffusion tensor imaging (DTI) and constrained spherical deconvolution (CSD) techniques in the segmentation of the dentate-rubro-thalamic tract (DRTT), evaluating their anatomical accuracy and applicability for surgical planning in deep brain stimulation (DBS) for essential tremor surgery in two patients.
METHODS: The images were acquired using two 1.5 Tesla magnetic resonance imaging protocols optimized for both DTI and CSD. Preprocessing included noise removal, artifact correction, and distortion adjustments. Segmentation was performed using region-of-interest definitions from specific atlases. CSD was applied with response function estimation, followed by fiber orientation reconstruction and tracking using the probabilistic improved fiber orientation distribution 2(iFOD2) algorithm. The DTI technique was conducted with tensor calculation and fractional anisotropy (FA) analysis. Volume and FA metrics were compared between techniques to evaluate segmentation accuracy for the DRTT.
RESULTS: CSD-based segmentation showed significantly larger volumes in the left hemisphere compared to DTI, along with higher FA values. In the right hemisphere, the difference was not statistically significant. Dice similarity index analysis revealed very low correspondence between the techniques in both hemispheres, suggesting greater precision of CSD in DRTT segmentation.
CONCLUSION: CSD proved to be more effective in DRTT segmentation, with better angular resolution and greater detailing of axonal trajectories, especially in regions with fiber crossing.
METHODS: The images were acquired using two 1.5 Tesla magnetic resonance imaging protocols optimized for both DTI and CSD. Preprocessing included noise removal, artifact correction, and distortion adjustments. Segmentation was performed using region-of-interest definitions from specific atlases. CSD was applied with response function estimation, followed by fiber orientation reconstruction and tracking using the probabilistic improved fiber orientation distribution 2(iFOD2) algorithm. The DTI technique was conducted with tensor calculation and fractional anisotropy (FA) analysis. Volume and FA metrics were compared between techniques to evaluate segmentation accuracy for the DRTT.
RESULTS: CSD-based segmentation showed significantly larger volumes in the left hemisphere compared to DTI, along with higher FA values. In the right hemisphere, the difference was not statistically significant. Dice similarity index analysis revealed very low correspondence between the techniques in both hemispheres, suggesting greater precision of CSD in DRTT segmentation.
CONCLUSION: CSD proved to be more effective in DRTT segmentation, with better angular resolution and greater detailing of axonal trajectories, especially in regions with fiber crossing.