Virtual reality system for planning minimally invasive neurosurgery. Technical note

OBJECT: The authors report on their experience with a 3D virtual reality system for planning minimally invasive neurosurgical procedures. METHODS: Between October 2002 and April 2006, the authors used the Dextroscope (Volume Interactions, Ltd.) to plan neurosurgical procedures in 106 patients, including 100 with intracranial and 6 with spinal lesions. The planning was performed 1 to 3 days preoperatively, and in 12 cases, 3D prints of the planning procedure were taken into the operating room. A questionnaire was completed by the neurosurgeon after the planning procedure. RESULTS: After a short period of acclimatization, the system proved easy to operate and is currently used routinely for preoperative planning of difficult cases at the authors' institution. It was felt that working with a virtual reality multimodal model of the patient significantly improved surgical planning. The pathoanatomy in individual patients could easily be understood in great detail, enabling the authors to determine the surgical trajectory precisely and in the most minimally invasive way. CONCLUSIONS: The authors found the preoperative 3D model to be in high concordance with intraoperative conditions; the resulting intraoperative "déjà-vu" feeling enhanced surgical confidence. In all procedures planned with the Dextroscope, the chosen surgical strategy proved to be the correct choice. Three-dimensional virtual reality models of a patient allow quick and easy understanding of complex intracranial lesions

White Matter Fiber Tracking Computation Based on Diffusion Tensor Imaging for Clinical Applications

Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine is still in its infancy. In this study, we present a new software for fiber tracking, developed on top of a general-purpose DICOM (digital imaging and communications in medicine) framework, which can be easily integrated into existing picture archiving and communication system (PACS) of radiological institutions. Images combining anatomical information and the localization of different fiber tract trajectories can be encoded and exported in DICOM and Analyze formats, which are valuable resources in the clinical applications of this method. Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors. We successfully performed fiber tracking on MR-DTI data sets from 26 patients with different types of brain lesions affecting the corticospinal tracts. In all cases, the trajectories of the central spinal tract (pyramidal tract) were reconstructed and could be applied at the planning phase of the surgery as well as in intraoperative neuronavigation

Nonlinear distortion correction of diffusion MR images improves quantitative DTI measurements in glioblastoma

The purpose of this study was to use a retrospective nonlinear distortion correction technique and evaluate the changes in DTI metrics in areas of interest in and around GBM tumors. A total of 24 histologically confirmed GBM patients with pre-operative 20-direction DTI scans were examined. Variability in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in normal tissue before and after distortion correction were examined. Changes in mean, median and variance of ADC and FA in contrast enhancing and T2/FLAIR ROIs were also examined with and without distortion correction. Results suggest the intra-subject standard deviations of ADC and FA decreased in normal tissue after the application of distortion correction (P<0.0001). FA mean and median values decreased after distortion correction in both T1+C and T2 ROIs (P<0.017), while ADC mean and median values did not significantly change except for the median ADC in T1+C ROIs (P=0.0054). The intra-subject standard deviation of ADC and FA values in tumor ROIs changed significantly with distortion correction, and Bland-Altman analysis indicated that the bias and the standard deviation of the bias of these intra-subject standard deviations were larger than those of the mean and median terms. Additionally, the means of the two curves of a double Gaussian fit to the histogram of ADC values from T1+C ROIs, ADC(L) (mean of lower Gaussian) as well as ADC(H) (mean of the higher Gaussian) were found to change significantly with distortion correction (P=0.0045 for ADC(L) and P=0.0370 for ADC(H)). Nonlinear distortion correction better aligns neuro-anatomical structures between DTI and anatomical scans, and significantly alters the measurement of values within tumor ROIs for GBM patients