PURPOSE: In many minimally invasive neurosurgical procedures, the surgical workspace is a small tortuous cavity that is accessed using straight, rigid instruments with limited dexterity. Specifically considering neuroendoscopy, it is often challenging for surgeons, using standard instruments, to reach multiple surgical targets from a single incision. To address this problem, continuum tools are under development to create highly dexterous minimally invasive instruments. However, this design process is not trivial, and therefore, a user-friendly design platform capable of easily incorporating surgeon input is needed.
METHODS: We propose a method that uses simulation and visual verification to design continuum tools that are patient and procedure specific. Our software module utilizes pre-operative scans and virtual threedimensional (3D) patient models to intuitively aid instrument design. The user specifies basic tool parameters and the parameterized tools and trocar are modeled within the virtual patient. By selecting and dragging the instrument models, the tools are instantly reshaped and repositioned. The tool geometry and surgical entry points are then returned as outputs to undergo optimization. We have completed an initial validation of the software by comparing a simulation of a physical instrument’s reachability to the corresponding virtual design.
RESULTS AND CONCLUSION: The software was assessed qualitatively by two neurosurgeons, who design tools for an intraventricular endoscopic procedure. Further, validation experiments comparing the design of a virtual instrument to a physical tool demonstrate that the software module functions correctly. Thus, our platform permits user-friendly, application specific design of continuum instruments. These instruments will give surgeons much more flexibility in developing future minimally invasive procedures.
Intraventricular hemorrhage (IVH) affects nearly 15% of preterm infants. It can lead to ventricular dilation and cognitive impairment. To ablate IVH clots, MR-guided focused ultrasound surgery (MRgFUS) is investigated. This procedure requires accurate, fast and consistent quantification of ventricle and clot volumes. We developed a semi-autonomous segmentation (SAS) algorithm for measuring changes in the ventricle and clot volumes. Images are normalized, and then ventricle and clot masks are registered to the images. Voxels of the registered masks and voxels obtained by thresholding the normalized images are used as seed points for competitive region growing, which provides the final segmentation. The user selects the areas of interest for correspondence after thresholding and these selections are the final seeds for region growing. SAS was evaluated on an IVH porcine model. SAS was compared to ground truth manual segmentation (MS) for accuracy, efficiency, and consistency. Accuracy was determined by comparing clot and ventricle volumes produced by SAS and MS, and comparing contours by calculating 95% Hausdorff distances between the two labels. In Two-One-Sided Test, SAS and MS were found to be significantly equivalent (p < 0.01). SAS on average was found to be 15 times faster than MS (p < 0.01). Consistency was determined by repeated segmentation of the same image by both SAS and manual methods, SAS being significantly more consistent than MS (p < 0.05). SAS is a viable method to quantify the IVH clot and the lateral brain ventricles and it is serving in a large-scale porcine study of MRgFUS treatment of IVH clot lysis.