Abstract
Diffusion Tensor Imaging (DTI) and fiber tractography are established methods to reconstruct major white matter tracts in the human brain in-vivo. Particularly in the context of neurosurgical procedures, reliable information about the course of fiber bundles is important to minimize postoperative deficits while maximizing the tumor resection volume. Since routinely used deterministic streamline tractography approaches often underestimate the spatial extent of white matter tracts, a novel approach to improve fiber segmentation is presented here, considering clinical time constraints. Therefore, fiber tracking visualization is enhanced with statistical information from multiple tracking applications to determine uncertainty in reconstruction based on clinical DTI data. After initial deterministic fiber tracking and centerline calculation, new seed regions are generated along the result’s midline. Tracking is applied to all new seed regions afterwards, varying in number and applied offset. The number of fibers passing each voxel is computed to model different levels of fiber bundle membership. Experimental results using an artificial data set of an anatomical software phantom are presented, using the Dice Similarity Coefficient (DSC) as a measure of segmentation quality. Different parameter combinations were classified to be superior to others providing significantly improved results with DSCs of 81.02%±4.12%, 81.32%±4.22% and 80.99%±3.81% for different levels of added noise in comparison to the deterministic fiber tracking procedure using the two-ROI approach with average DSCs of 65.08%±5.31%, 64.73%±6.02% and 65.91%±6.42%. Whole brain tractography based on the seed volume generated by the calculated seeds delivers average DSCs of 67.12%±0.86%, 75.10%±0.28% and 72.91%±0.15%, original whole brain tractography delivers DSCs of 67.16%, 75.03% and 75.54%, using initial ROIs as combined include regions, which is clearly improved by the repeated fiber tractography method.
Highlights
Multimodal navigation guidance is a routine tool in neurosurgical operating theaters to achieve best possible resection of the lesion with minimum postoperative morbidity, displaying outlines of the segmented objects in the microscope heads-up display
We focus on the reconstruction and visualization of subcortical fiber bundles, delivered by Diffusion Tensor Imaging (DTI) and fiber tractography
The adapted version of whole brain tractography led to an underestimation of the tract volume with a Dice Similarity Coefficient (DSC) of 67.12% 60.86% for noise level 0, a DSC of 75.10% 60.28% for noise level 1 and a DSC of 72.91% 60.15% for noise level 2
Summary
Multimodal navigation guidance is a routine tool in neurosurgical operating theaters to achieve best possible resection of the lesion with minimum postoperative morbidity, displaying outlines of the segmented objects in the microscope heads-up display. Whereas the correlation of their extent of resection (EOR) and patient outcome has been a long-term point of discussion, recent literature favors radical EOR in surgery of low-grade and high-grade gliomas [1,2,3,4,5]. Another major addition to multimodal navigation is intraoperative MRI (iMRI) followed by an update of the navigation to compensate for the effects of brain shift (brain deformations due to e.g. loss of cerebrospinal fluid, tumor resection, edema) [6,7,8,9]. It was demonstrated that iMRI combined with navigation guidance and an intraoperative update of image data leads to higher rates of EOR and gross total resection rates in glioma surgery with low postoperative morbidity [10,11,12,13]
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