BACKGROUND:Chronic subdural hematoma evacuation can be achieved in select patients through bedside placement of the Subdural Evacuation Port System (SEPS; Medtronic, Inc., Dublin, Ireland). This procedure involves drilling a burr hole at the thickest part of the hematoma. Identifying this location is often difficult, given the variable tilt of available imaging and distant anatomic landmarks. This paper evaluates the feasibility and accuracy of a bedside navigation system that relies on visible light-based 3-dimensional (3D) scanning and image registration to a pre-procedure computed tomography scan. The information provided by this system may increase accuracy of the burr hole location.METHODS:In Part 1, the accuracy of this system was evaluated using a rigid 3D printed phantom head with implanted fiducials. In Part 2, the navigation system was tested on 3 patients who underwent SEPS placement.RESULTS:The error in registration of this system was less than 2.5 mm when tested on a rigid 3D printed phantom head. Fiducials located in the posterior aspect of the head were difficult to reliably capture. For the 3 patients who underwent 5 SEPS placements, the distance between anticipated SEPS burr hole location based on registration and actual burr hole location was less than 1cm.CONCLUSIONS:A bedside cranial navigation system based on 3D scanning and image registration has been introduced. Such a system may increase the success rate of bedside procedures, such as SEPS placement. However, technical challenges such as the ability to scan hair and practical challenges such as minimization of patient movement during scans must be overcome.

Conventional optical tracking systems use cameras sensitive to near-infrared (NIR) light and NIR illuminated/active-illuminating markers to localize instrumentation and the patient in the operating room (OR) physical space. This technology is widely used within the neurosurgical theater and is a staple in the standard of care for craniotomy planning. To accomplish, planning is largely conducted at the time of the procedure in the OR with the patient in a fixed head orientation. We propose a framework to achieve this in the OR without conventional tracking technology, i.e., a "trackerless" approach. Briefly, we investigate an extension of the 3D Slicer which combines surgical planning and craniotomy designation. While taking advantage of the well-developed 3D Slicer platform, we implement advanced features to aid the neurosurgeon in planning the location of the anticipated craniotomy relative to the preoperatively imaged tumor in a physical-to-virtual setup, and then subsequently aid the true physical procedure by correlating that physical-to-virtual plan with an intraoperative magnetic resonance imaging-to-physical registered field-of-view display. These steps are done such that the craniotomy can be designated without the use of a conventional optical tracking technology. To test this approach, four experienced neurosurgeons performed experiments on five different surgical cases using our 3D Slicer module as well as the conventional procedure for comparison. The results suggest that our planning system provides a simple, cost-efficient, and reliable solution for surgical planning and delivery without the use of conventional tracking technologies. We hypothesize that the combination of this craniotomy planning approach and our past developments in cortical surface registration and deformation tracking using stereo-pair data from the surgical microscope may provide a fundamental realization of an integrated trackerless surgical guidance platform.

Brain shift invalidates the assumption of most neuronavigation systems that rigid registration is sufficient for mapping pre-operative image data to patient coordinates during surgery. Brain shift has been measured to be as large as 25 mm at the cortical surface and greater than 3 mm at deep tumour margins, where precision is required to achieve good outcomes. Thus, it is critical that brain shift be accounted for in neuronavigation. Unfortunately, brain shift is complex, patient- and tumour-specific, varies throughout the brain and as surgery progresses, and depends on many variables that are hard to predict and model preoperatively. For these reasons, the need to measure and compensate for brain shift intraoperatively is critical. This chapter reviews previous work to measure brain shift and summarises both quantitative results and qualitative observations reported in this work. It discusses intra-operative methods for measuring brain shift that are currently being used clinically and for research purposes in the operating room. These methods include intra-operative MRI and CT, cortical surface measurements, and intra-operative 3D ultrasound.

Conventional optical tracking systems use cameras sensitive to near-infra-red (NIR) light detecting cameras and passively/actively NIR-illuminated markers to localize instrumentation and the patient in the operating room (OR) physical space. This technology is widely-used within the neurosurgical theatre and is a staple in the standard of care in craniotomy planning. To accomplish, planning is largely conducted at the time of the procedure with the patient in a fixed OR head presentation orientation. In the work presented herein, we propose a framework to achieve this in the OR that is free of conventional tracking technology, i.e. a trackerless approach. Briefly, we are investigating a collaborative extension of 3D slicer that combines surgical planning and craniotomy designation in a novel manner. While taking advantage of the well-developed 3D slicer platform, we implement advanced features to aid the neurosurgeon in planning the location of the anticipated craniotomy relative to the preoperatively imaged tumor in a physical-to-virtual setup, and then subsequently aid the true physical procedure by correlating that physical-to-virtual plan with a novel intraoperative MR-to-physical registered field-of-view display. These steps are done such that the craniotomy can be designated without use of a conventional optical tracking technology. To test this novel approach, an experienced neurosurgeon performed experiments on four different mock surgical cases using our module as well as the conventional procedure for comparison. The results suggest that our planning system provides a simple, cost-efficient, and reliable solution for surgical planning and delivery without the use of conventional tracking technologies. We hypothesize that the combination of this early-stage craniotomy planning and delivery approach, and our past developments in cortical surface registration and deformation tracking using stereo-pair data from the surgical microscope may provide a fundamental new realization of an integrated trackerless surgical guidance platform.

Intra-operative soft tissue deformation, referred to as brain shift, compromises the application of current imageguided surgery (IGS) navigation systems in neurosurgery. A computational model driven by sparse data has been used as a cost effective method to compensate for cortical surface and volumetric displacements. Stereoscopic microscopes and laser range scanners (LRS) are the two most investigated sparse intra-operative imaging modalities for driving these systems. However, integrating these devices in the clinical workflow to facilitate development and evaluation requires developing systems that easily permit data acquisition and processing. In this work we present a mock environment developed to acquire stereo images from a tracked operating microscope and to reconstruct 3D point clouds from these images. A reconstruction error of 1 mm is estimated by using a phantom with a known geometry and independently measured deformation extent. The microscope is tracked via an attached tracking rigid body that facilitates the recording of the position of the microscope via a commercial optical tracking system as it moves during the procedure. Point clouds, reconstructed under different microscope positions, are registered into the same space in order to compute the feature displacements. Using our mock craniotomy device, realistic cortical deformations are generated. Our experimental results report approximately 2mm average displacement error compared with the optical tracking system. These results demonstrate the practicality of using tracked stereoscopic microscope as an alternative to LRS to collect sufficient intraoperative information for brain shift correction.

Brain shift compensation using computer modeling strategies is an important research area in the field of image-guided neurosurgery (IGNS). One important source of available sparse data during surgery to drive these frameworks is deformation tracking of the visible cortical surface. Possible methods to measure intra-operative cortical displacement include laser range scanners (LRS), which typically complicate the clinical workflow, and reconstruction of cortical surfaces from stereo pairs acquired with the operating microscopes. In this work, we propose and demonstrate a craniotomy simulation device that permits simulating realistic cortical displacements designed to measure and validate the proposed intra-operative cortical shift measurement systems. The device permits 3D deformations of a mock cortical surface which consists of a membrane made of a Dragon Skin® high performance silicone rubber on which vascular patterns are drawn. We then use this device to validate our stereo pair-based surface reconstruction system by comparing landmark positions and displacements measured with our systems to those positions and displacements as measured by a stylus tracked by a commercial optical system. Our results show a 1mm average difference in localization error and a 1.2mm average difference in displacement measurement. These results suggest that our stereo-pair technique is accurate enough for estimating intra-operative displacements in near real-time without affecting the surgical workflow.

In this paper, we present a simple way “Walking in place” to navigate a virtual environment using Microsoft Kinect. Our system can be reimplemented in relatively low-cost. In order to evaluate this navigation method, we also use Xbox game controller as another navigation method. A fun finding red balls experiment is proposed to evaluate these two methods. Ten subjects participated this experiment with different background and pre-experience. The result contradicts our original hypothesis that Kinect perform better than Xbox game controller after statistical analysis. The possible reasons are discussed in the paper. Keywords—Virtual environment; Kinect; head-mounted display; subjects; evaluate

Introduction Deformation Based Morphometry (DBM) aims to detect morphological differences between groups based on statistical analysis of deformation fields generated by nonrigid registrations, which warp individual volumes to a standard coordinate system [1]. Since DBM relies on the deformation fields obtained from non-rigid registrations, it is very important to assess and compare the effect of various registration techniques on the performance of DBM analysis. Several studies have compared non-rigid registration algorithms [2-3]. Most notably, Klein et al [3] conducted a comprehensive evaluation of 14 nonlinear deformation algorithms by comparing atlas-based segmentation with manual tracing. However, few studies have compared the effect of registration algorithms on population differences that may be uncovered through DBM, presumably due to a lack of “ground truth” for deformation fields. In this study, we simulated two groups of normal brain images and deformation fields via the Statistical Simulation of Deformations (SSD) model [4], introduced known growths in one group, and evaluated the effect of five different nonrigid registration methods on DBM analysis of the groups without and with growths.