Ian J. Gerard

Brain shift in neuronavigation of brain tumors: A review

Purpose: Neuronavigation based on preoperative imaging data is a ubiquitous tool for image guidance in neurosurgery. However, it is rendered unreliable when brain shift invalidates the patient‐to‐image registration. Many investigators have tried to explain, quantify, and compensate for this phenomenon to allow extended use of neuronavigation systems for the duration of surgery. The purpose of this paper is to present an overview of the work that has been done investigating brain shift. Methods: A review of the literature dealing with the explanation, quantification and compensation of brain shift is presented. The review is based on a systematic search using relevant keywords and phrases in PubMed. The review is organized based on a developed taxonomy that classifies brain shift as occurring due to physical, surgical or biological factors. Results: This paper gives an overview of the work investigating, quantifying, and compensating for brain shift in neuronavigation while describing the successes, setbacks, and additional needs in the field. An analysis of the literature demonstrates a high variability in the methods used to quantify brain shift as well as a wide range in the measured magnitude of the brain shift, depending on the specifics of the intervention. The analysis indicates the need for additional research to be done in quantifying independent effects of brain shift in order for some of the state of the art compensation methods to become useful. Conclusion: This review allows for a thorough understanding of the work investigating brain shift and introduces the needs for future avenues of investigation of the phenomenon. HighlightsA comprehensive review of research on the phenomenon of brain shift.A new taxonomy separating brain shift into physical, biological and surgical factors.Contrast between brain shift corrections through intraoperative imaging methods.Recommendations for future focus of brain shift research. Graphical abstract Figure. Image, graphical abstract

Augmented reality in neurovascular surgery: feasibility and first uses in the operating room

PurposeThe aim of this report is to present a prototype augmented reality (AR) intra-operative brain imaging system. We present our experience of using this new neuronavigation system in neurovascular surgery and discuss the feasibility of this technology for aneurysms, arteriovenous malformations (AVMs), and arteriovenous fistulae (AVFs).MethodsWe developed an augmented reality system that uses an external camera to capture the live view of the patient on the operating room table and to merge this view with pre-operative volume-rendered vessels. We have extensively tested the system in the laboratory and have used the system in four surgical cases: one aneurysm, two AVMs and one AVF case.ResultsThe developed AR neuronavigation system allows for precise patient-to-image registration and calibration of the camera, resulting in a well-aligned augmented reality view. Initial results suggest that augmented reality is useful for tailoring craniotomies, localizing vessels of interest, and planning resection corridors.ConclusionAugmented reality is a promising technology for neurovascular surgery. However, for more complex anomalies such as AVMs and AVFs, better visualization techniques that allow one to distinguish between arteries and veins and determine the absolute depth of a vessel of interest are needed.

IBIS: an OR ready open-source platform for image-guided neurosurgery.

PurposeNavigation systems commonly used in neurosurgery suffer from two main drawbacks: (1) their accuracy degrades over the course of the operation and (2) they require the surgeon to mentally map images from the monitor to the patient. In this paper, we introduce the Intraoperative Brain Imaging System (IBIS), an open-source image-guided neurosurgery research platform that implements a novel workflow where navigation accuracy is improved using tracked intraoperative ultrasound (iUS) and the visualization of navigation information is facilitated through the use of augmented reality (AR).MethodsThe IBIS platform allows a surgeon to capture tracked iUS images and use them to automatically update preoperative patient models and plans through fast GPU-based reconstruction and registration methods. Navigation, resection and iUS-based brain shift correction can all be performed using an AR view. IBIS has an intuitive graphical user interface for the calibration of a US probe, a surgical pointer as well as video devices used for AR (e.g., a surgical microscope).ResultsThe components of IBIS have been validated in the laboratory and evaluated in the operating room. Image-to-patient registration accuracy is on the order of

Augmented Reality in Neurovascular Surgery: First Experiences

3.72\pm 1.27\,\hbox {mm}

Towards Augmented Reality Guided Craniotomy Planning in Tumour Resections

3.72±1.27mm and can be improved with iUS to a median target registration error of 2.54 mm. The accuracy of the US probe calibration is between 0.49 and 0.82 mm. The average reprojection error of the AR system is

New Protocol for Skin Landmark Registration in Image-Guided Neurosurgery: Technical Note.

0.37\pm 0.19\,\hbox {mm}