Framework for a low-cost intra-operative image-guided neuronavigator including brain shift compensation

In this paper we present a methodology to address the problem of brain tissue deformation referred to as 'brain-shift'. This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on pre-operative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intra-operative image-guided system, we describe a procedure to generate patient specific finite element meshes of the brain and propose a biomechanical model which can take into account tissue deformations and surgical procedures that modify the brain structure, like tumour or tissue resection

A method for the assessment of time-varying brain shift during navigated epilepsy surgery

Image guidance is widely used in neurosurgery. Tracking systems (neuronavigators) allow registering the preoperative image space to the surgical space. The localization accuracy is influenced by technical and clinical factors, such as brain shift. This paper aims at providing quantitative measure of the time-varying brain shift during open epilepsy surgery, and at measuring the pattern of brain deformation with respect to three potentially meaningful parameters: craniotomy area, craniotomy orientation and gravity vector direction in the images reference frame

Framework and Bio-Mechanical Model for a Per-Operative Image-Guided Neuronavigator Including 'Brain-Shift' Compensation

In this paper we present a methodology to adress the problem of brain tissue deformation referred to as "brainshift". This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on preoperative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intraoperative image-guided system, we propose a biomechanical model of the brain which can take into account interactively such deformations as well as surgical procedures that modify the brain structure, like tumour or tissue resection

Non-contact strain determination of cell traction effects

Irreversible tissue damage leading to organ failure is a common health problem in today's world. Regenerating these damaged tissues with the help of scaffolds is the solution offered by tissue engineering. In cases where the extra-cellular matrix (ECM) is to be replaced by an artificial substrate (scaffold) or matrix, cellular traction forces (CTF) are exerted by the cells on the scaffold surface. An ideal scaffold should exhibit mechanical characteristics similar to those of the ECM it is intended to replace. In other words, the capacity of a scaffold to withstand deformation should be comparable to that of a natural ECM. And with knowledge of those forces and deformations the properties of the scaffolds may be inferred. Digital Image Correlation (DIC), a non-contact image analysis technique enables us to measure point to point deformation of the scaffold by comparing a sequence of images captured during the process of scaffold deformation. This review discusses the methodology involved and implementation of DIC to measure displacements and strain.Irreversible tissue damage leading to organ failure is a common health problem in today's world. Regenerating these damaged tissues with the help of scaffolds is the solution offered by tissue engineering. In cases where the extra-cellular matrix (ECM) is to be replaced by an artificial substrate (scaffold) or matrix, cellular traction forces (CTF) are exerted by the cells on the scaffold surface. An ideal scaffold should exhibit mechanical characteristics similar to those of the ECM it is intended to replace. In other words, the capacity of a scaffold to withstand deformation should be comparable to that of a natural ECM. And with knowledge of those forces and deformations the properties of the scaffolds may be inferred. Digital Image Correlation (DIC), a non-contact image analysis technique enables us to measure point to point deformation of the scaffold by comparing a sequence of images captured during the process of scaffold deformation. This review discusses the methodology involved and implementation of DIC to measure displacements and strain

Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work

Non-rigid registration of serial intra-operative images for automatic brain shift estimation

Measurement of intra-operative brain motion is important to provide boundary conditions to physics-based deformation models that can be used to register pre- and intra-operative information. In this paper we present and test a technique that can be used to measure brain surface motion automatically. This method relies on a tracked laser range scanner (LRS) that can acquire simultaneously a picture and the 3D physical coordinates of objects within its field of view. This reduces the 3D tracking problem to a 2D non-rigid registration problem which we solve with a Mutual Information-based algorithm. Results obtained on images of a phantom and on images acquired intra-operatively that demonstrate the feasibility of the method are presented