Ultra-High Field Magnetic Resonance Imaging for Stereotactic Neurosurgery

Stereotactic neurosurgery is a subspecialty within neurosurgery concerned with accurate targeting of brain structures. Deep brain stimulation (DBS) is a specific type of stereotaxy in which electrodes are implanted in deep brain structures. It has proven therapeutic efficacy in Parkinson’s disease and Essential Tremor, but with an expanding number of indications under evaluation including Alzheimer’s disease, depression, epilepsy, and obesity, many more Canadians with chronic health conditions may benefit. Accurate surgical targeting is crucial with millimeter deviations resulting in unwanted side effects including muscle contractions, or worse, vessel injury. Lack of adequate visualization of surgical targets with conventional lower field strengths (1.5/3 Tesla) has meant that standard-of-care surgical treatment has relied on indirect targeting using standardized landmarks to find a correspondence with a histological ``template\u27\u27 of the brain. For this reason, these procedures routinely require awake testing and microelectrode recording, which increases operating room time, patient discomfort, and risk of complications. Advances in ultra-high field (\u3e= 7 Tesla or 7T) imaging have important potential implications for targeting structures enabling better visualization as a result of its increased (sub-millimeter) spatial resolution, tissue contrast, and signal-to-noise ratio. The work in this thesis explores ways in which ultra-high field magnetic resonance imaging can be integrated into the practice of stereotactic neurosurgery. In Chapter 2, an ultra-high field MRI template is integrated into the surgical workflow to assist with planning for deep brain stimulation surgery cases. Chapter 3 describes a novel anatomical fiducial placement protocol that is developed, validated, and used prospectively to quantify the limits of template-assisted surgical planning. In Chapter 4, geometric distortions at 7T that may impede the ability to perform accurate surgical targeting are characterized in participant data, and generally noted to be away from areas of interest for stereotactic targeting. Finally, Chapter 5 discusses a number of important stereotactic targets that are directly visualized and described for the first time in vivo, paving the way for patient-specific surgical planning using ultra-high field MRI

Towards development of automatic path planning system in image-guided neurosurgery

With the advent of advanced computer technology, many computer-aided systems have evolved to assist in medical related work including treatment, diagnosis, and even surgery. In modern neurosurgery, Magnetic Resonance Image guided stereotactic surgery exactly complies with this trend. It is a minimally invasive operation being much safer than the traditional open-skull surgery, and offers higher precision and more effective operating procedures compared to conventional craniotomy. However, such operations still face significant challenges of planning the optimal neurosurgical path in order to reach the ideal position without damage to important internal structures. This research aims to address this major challenge. The work begins with an investigation of the problem of distortion induced by MR images. It then goes on to build a template of the Circle of Wills brain vessels, realized from a collection of Magnetic Resonance Angiography images, which is needed to maintain operating standards when, as in many cases, Magnetic Resonance Angiography images are not available for patients. Demographic data of brain tumours are also studied to obtain further understanding of diseased human brains through the development of an effect classifier. The developed system allows the internal brain structure to be ‘seen’ clearly before the surgery, giving surgeons a clear picture and thereby makes a significant contribution to the eventual development of a fully automatic path planning system

Neurosurgical Ultrasound Pose Estimation Using Image-Based Registration and Sensor Fusion - A Feasibility Study

Modern neurosurgical procedures often rely on computer-assisted real-time guidance using multiple medical imaging modalities. State-of-the-art commercial products enable the fusion of pre-operative with intra-operative images (e.g., magnetic resonance [MR] with ultrasound [US] images), as well as the on-screen visualization of procedures in progress. In so doing, US images can be employed as a template to which pre-operative images can be registered, to correct for anatomical changes, to provide live-image feedback, and consequently to improve confidence when making resection margin decisions near eloquent regions during tumour surgery. In spite of the potential for tracked ultrasound to improve many neurosurgical procedures, it is not widely used. State-of-the-art systems are handicapped by optical tracking’s need for consistent line-of-sight, keeping tracked rigid bodies clean and rigidly fixed, and requiring a calibration workflow. The goal of this work is to improve the value offered by co-registered ultrasound images without the workflow drawbacks of conventional systems. The novel work in this thesis includes: the exploration and development of a GPU-enabled 2D-3D multi-modal registration algorithm based on the existing LC2 metric; and the use of this registration algorithm in the context of a sensor and image-fusion algorithm. The work presented here is a motivating step in a vision towards a heterogeneous tracking framework for image-guided interventions where the knowledge from intraoperative imaging, pre-operative imaging, and (potentially disjoint) wireless sensors in the surgical field are seamlessly integrated for the benefit of the surgeon. The technology described in this thesis, inspired by advances in robot localization demonstrate how inaccurate pose data from disjoint sources can produce a localization system greater than the sum of its parts

Development of a Fluoroscopic Radiostereometric Analysis System With an Application to Glenohumeral Joint Kinematics

Ideally, joint kinematics should be measured with high accuracy, void of skin motion artefact, in three dimensions, and under dynamic conditions. Radiostereometric analysis (RSA) has the potential to fulfill all of these requirements. The objectives of this thesis were (1) to implement and validate a fluoroscopy-based RSA system, (2) to determine the effect of varying the calibration frame, (3) to correct image distortion, (4) to investigate errors in coordinate system creation for glenohumeral (shoulder) joint kinematics, (5) to introduce a new coordinate system definition for the scapula with limited radiation exposure, and (6) to use RSA to examine glenohumeral joint motions in- vivo. An RSA system consisting of two portable C-arm fluoroscopy units and two personal computers was assembled. Calibration was performed using a custom-made calibration frame. Images were digitized and RSA reconstruction was performed using custom-written software. Images taken using fluoroscopy under ideal conditions can produce reconstructions that are as accurate as those taken with digital radiography, with standard errors of measurement of 43pm and 0.23° and 36pm and 0.12°, respectively. RSA is more accurate than optical tracking for rigid body motion. The fluoroscopes may be positioned at angles less than 135° without affecting the accuracy of reconstruction. A global polynomial approach to distortion correction is appropriate for use with RSA; however, the polynomial degree must be determined for each system with an independent accuracy measure. m An alternative scapular coordinate system was introduced to decrease the required radiation exposure for coordinate system creation by approximately half. The kinematic angles obtained using the alternative coordinate system were different from those obtained using the International Society of Biomechanics standard; however, the differences are not clinically significant. As a first clinical application, glenohumeral joint translation was examined. The preliminary data suggests that humeral head position does not differ in active and static joint positioning. Fluoroscopy allows subjects to be examined while in motion and should enable substantial improvements to the study of even subtle in-vivo kinematics. It is likely that the RSA system will lead to an increased understanding of the effects of disease progression, surgical techniques and rehabilitation protocols on joint motion

Simultaneous intracranial EEG and fMRI of interictal epileptic discharges in humans

Simultaneous scalp EEG–fMRI measurements allow the study of epileptic networks and more generally, of the coupling between neuronal activity and haemodynamic changes in the brain. Intracranial EEG (icEEG) has greater sensitivity and spatial specificity than scalp EEG but limited spatial sampling. We performed simultaneous icEEG and functional MRI recordings in epileptic patients to study the haemodynamic correlates of intracranial interictal epileptic discharges (IED). Two patients undergoing icEEG with subdural and depth electrodes as part of the presurgical assessment of their pharmaco-resistant epilepsy participated in the study. They were scanned on a 1.5 T MR scanner following a strict safety protocol. Simultaneous recordings of fMRI and icEEG were obtained at rest. IED were subsequently visually identified on icEEG and their fMRI correlates were mapped using a general linear model (GLM). On scalp EEG–fMRI recordings performed prior to the implantation, no IED were detected. icEEG–fMRI was well tolerated and no adverse health effect was observed. intra-MR icEEG was comparable to that obtained outside the scanner. In both cases, significant haemodynamic changes were revealed in relation to IED, both close to the most active electrode contacts and at distant sites. In one case, results showed an epileptic network including regions that could not be sampled by icEEG, in agreement with findings from magneto-encephalography, offering some explanation for the persistence of seizures after surgery. Hence, icEEG–fMRI allows the study of whole-brain human epileptic networks with unprecedented sensitivity and specificity. This could help improve our understanding of epileptic networks with possible implications for epilepsy surgery

Towards efficient neurosurgery: Image analysis for interventional MRI

Interventional magnetic resonance imaging (iMRI) is being increasingly used for performing imageguided neurosurgical procedures. Intermittent imaging through iMRI can help a neurosurgeon visualise the target and eloquent brain areas during neurosurgery and lead to better patient outcome. MRI plays an important role in planning and performing neurosurgical procedures because it can provide highresolution anatomical images that can be used to discriminate between healthy and diseased tissue, as well as identify location and extent of functional areas. This is of significant clinical utility as it helps the surgeons maximise target resection and avoid damage to functionally important brain areas. There is clinical interest in propagating the pre-operative surgical information to the intra-operative image space as this allows the surgeons to utilise the pre-operatively generated surgical plans during surgery. The current state of the art neuronavigation systems achieve this by performing rigid registration of pre-operative and intra-operative images. As the brain undergoes non-linear deformations after craniotomy (brain shift), the rigidly registered pre-operative images do not accurately align anymore with the intra-operative images acquired during surgery. This limits the accuracy of these neuronavigation systems and hampers the surgeon’s ability to perform more aggressive interventions. In addition, intra-operative images are typically of lower quality with susceptibility artefacts inducing severe geometric and intensity distortions around areas of resection in echo planar MRI images, significantly reducing their utility in the intraoperative setting. This thesis focuses on development of novel methods for an image processing workflow that aims to maximise the utility of iMRI in neurosurgery. I present a fast, non-rigid registration algorithm that can leverage information from both structural and diffusion weighted MRI images to localise target lesions and a critical white matter tract, the optic radiation, during surgical management of temporal lobe epilepsy. A novel method for correcting susceptibility artefacts in echo planar MRI images is also developed, which combines fieldmap and image registration based correction techniques. The work developed in this thesis has been validated and successfully integrated into the surgical workflow at the National Hospital for Neurology and Neurosurgery in London and is being clinically used to inform surgical decisions