Naoyuki Shono

Microsurgery Simulator of Cerebral Aneurysm Clipping with Interactive Cerebral Deformation Featuring a Virtual Arachnoid

BACKGROUND A virtual reality simulator for aneurysmal clipping surgery is an attractive research target for neurosurgeons. Brain deformation is one of the most important functionalities necessary for an accurate clipping simulator and is vastly affected by the status of the supporting tissue, such as the arachnoid membrane. However, no virtual reality simulator implementing the supporting tissue of the brain has yet been developed. OBJECTIVE To develop a virtual reality clipping simulator possessing interactive brain deforming capability closely dependent on arachnoid dissection and apply it to clinical cases. METHODS Three-dimensional computer graphics models of cerebral tissue and surrounding structures were extracted from medical images. We developed a new method for modifiable cerebral tissue complex deformation by incorporating a nonmedical image-derived virtual arachnoid/trabecula in a process called multitissue integrated interactive deformation (MTIID). MTIID made it possible for cerebral tissue complexes to selectively deform at the site of dissection. Simulations for 8 cases of actual clipping surgery were performed before surgery and evaluated for their usefulness in surgical approach planning. RESULTS Preoperatively, each operative field was precisely reproduced and visualized with the virtual brain retraction defined by users. The clear visualization of the optimal approach to treating the aneurysm via an appropriate arachnoid incision was possible with MTIID. CONCLUSION A virtual clipping simulator mainly focusing on supporting tissues and less on physical properties seemed to be useful in the surgical simulation of cerebral aneurysm clipping. To our knowledge, this article is the first to report brain deformation based on supporting tissues.

Usefulness of high-resolution 3D multifusion medical imaging for preoperative planning in patients with posterior fossa hemangioblastoma: technical note

Successful resection of hemangioblastoma depends on preoperative assessment of the precise locations of feeding arteries and draining veins. Simultaneous 3D visualization of feeding arteries, draining veins, and surrounding structures is needed. The present study evaluated the usefulness of high-resolution 3D multifusion medical imaging (hr-3DMMI) for preoperative planning of hemangioblastoma. The hr-3DMMI combined MRI, MR angiography, thin-slice CT, and 3D rotated angiography. Surface rendering was mainly used for the creation of hr-3DMMI using multiple thresholds to create 3D models, and processing took approximately 3-5 hours. This hr-3DMMI technique was used in 5 patients for preoperative planning and the imaging findings were compared with the operative findings. Hr-3DMMI could simulate the whole 3D tumor as a unique sphere and show the precise penetration points of both feeding arteries and draining veins with the same spatial relationships as the original tumor. All feeding arteries and draining veins were found intraoperatively at the same position as estimated preoperatively, and were occluded as planned preoperatively. This hr-3DMMI technique could demonstrate the precise locations of feeding arteries and draining veins preoperatively and estimate the appropriate route for resection of the tumor. Hr-3DMMI is expected to be a very useful support tool for surgery of hemangioblastoma.

Neurosurgical Virtual Reality Simulation for Brain Tumor Using High-definition Computer Graphics: A Review of the Literature

Simulation and planning of surgery using a virtual reality model is becoming common with advances in computer technology. In this study, we conducted a literature search to find trends in virtual simulation of surgery for brain tumors. A MEDLINE search for “neurosurgery AND (simulation OR virtual reality)” retrieved a total of 1,298 articles published in the past 10 years. After eliminating studies designed solely for education and training purposes, 28 articles about the clinical application remained. The finding that the vast majority of the articles were about education and training rather than clinical applications suggests that several issues need be addressed for clinical application of surgical simulation. In addition, 10 of the 28 articles were from Japanese groups. In general, the 28 articles demonstrated clinical benefits of virtual surgical simulation. Simulation was particularly useful in better understanding complicated spatial relations of anatomical landmarks and in examining surgical approaches. In some studies, Virtual reality models were used on either surgical navigation system or augmented reality technology, which projects virtual reality images onto the operating field. Reported problems were difficulties in standardized, objective evaluation of surgical simulation systems; inability to respond to tissue deformation caused by surgical maneuvers; absence of the system functionality to reflect features of tissue (e.g., hardness and adhesion); and many problems with image processing. The amount of description about image processing tended to be insufficient, indicating that the level of evidence, risk of bias, precision, and reproducibility need to be addressed for further advances and ultimately for full clinical application.

Feedback methods for collision avoidance using virtual fixtures for robotic neurosurgery in deep and narrow spaces

Robotic assistance enables a surgeon to perform dexterous and precise manipulations. However, conducting robot assisted neurosurgery within the deep and narrow spaces of the brain presents the risk of unexpected collisions between the shafts of robotic instruments and their surroundings out of the microscopic view. Thus, we propose the provision of feedback using a truncated cone shaped virtual fixture generated by marking the edges of the top and bottom plane of a workspace in the deep and narrow spaces within the brain with the slave manipulator. The experimental results show that the virtual fixture generation method could precisely model the workspace. We also implemented force feedback, visual feedback, and motion scaling feedback in the microsurgical robotic system in order to inform the surgeon of the risk of collision. Performance of each feedback method and their combinations was evaluated in two experiments. The experimental results showed that the combination of the force and the visual feedback methods were the most beneficial for avoiding collisions.

Intelligent control of neurosurgical robot MM-3 using dynamic motion scaling

OBJECTIVE Advanced and intelligent robotic control is necessary for neurosurgical robots, which require great accuracy and precision. In this article, the authors propose methods for dynamically and automatically controlling the motion-scaling ratio of a master-slave neurosurgical robotic system to reduce the task completion time. METHODS Three dynamic motion-scaling modes were proposed and compared with the conventional fixed motion-scaling mode. These 3 modes were defined as follows: 1) the distance between a target point and the tip of the slave manipulator, 2) the distance between the tips of the slave manipulators, and 3) the velocity of the master manipulator. Five test subjects, 2 of whom were neurosurgeons, sutured 0.3-mm artificial blood vessels using the MM-3 neurosurgical robot in each mode. RESULTS The task time, total path length, and helpfulness score were evaluated. Although no statistically significant differences were observed, the mode using the distance between the tips of the slave manipulators improves the suturing performance. CONCLUSIONS Dynamic motion scaling has great potential for the intelligent and accurate control of neurosurgical robots.

Interactive Volume Segmentation with Threshold Field Painting

An interactive method for segmentation and isosurface extraction of medical volume data is proposed. In conventional methods, users decompose a volume into multiple regions iteratively, segment each region using a threshold, and then manually clean the segmentation result by removing clutter in each region. However, this is tedious and requires many mouse operations from different camera views. We propose an alternative approach whereby the user simply applies painting operations to the volume using tools commonly seen in painting systems, such as flood fill and brushes. This significantly reduces the number of mouse and camera control operations. Our technical contribution is in the introduction of the threshold field, which assigns spatially-varying threshold values to individual voxels. This generalizes discrete decomposition of a volume into regions and segmentation using a constant threshold in each region, thereby offering a much more flexible and efficient workflow. This paper describes the details of the user interaction and its implementation. Furthermore, the results of a user study are discussed. The results indicate that the proposed method can be a few times faster than a conventional method.