Non-rigid Registration of 3D Ultrasound Images of Brain Tumours Acquired during Neurosurgery

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.

Quantitative evaluation of three calibration methods for 3-D freehand ultrasound

In this paper, three different calibration methods for three-dimensional (3-D) freehand ultrasound (US) are evaluated. Calibration is the process of estimating the rigid transformation from US image coordinates to the coordinate system of the tracking sensor mounted onto the probe. Calibration accuracy has an important impact on quantitative studies. Geometrical precision can also be crucial in many interventions and surgery. The proposed evaluation framework relies on a single point phantom and a 3-D US phantom which mimics the US characteristics of human liver. Four quality measures are used: 3-D point localization criterion, distance and volume measurements, and shape based criterion. Results show that during the acquisition procedure, volumetric measurements and shapes of the reconstructed object depend on probe motion used, particularly fan motions for which errors are larger. It is also shown that accurate calibration is essential to obtain reliable quantitative information.

Neuronavigation and surgery of intracerebral tumours

Approximately four decades after the successful clinical introduction of framebased stereotactic neurosurgery by Spiegel and Wycis, frameless stereotaxy emerged to enable more elaborate image guidance in open neurosurgical procedures. Frameless stereotaxy, or neuronavigation, relies on one of several different localizing techniques to determine the position of an operative instrument relative to the surgical field, without the need for a coordinate frame rigidly fixed to the patients' skull. Currently, most systems are based on the optical triangulation of infrared light sources fixed to the surgical instrument. In its essence, a navigation system is a three-dimensional digitiser that correlates its measurements to a reference data set, i.e. a preoperatively acquired CT or MRI image stack. This correlation is achieved through a patient-to-image registration procedure resulting in a mathematical transformation matrix mapping each position in 'world space' onto 'image space'. Thus, throughout the remainder of the surgical procedure, the position of the surgical instrument can be demonstrated on a computer screen, relative to the CT or MRI images. Though neuronavigation has become a routinely used addition to the neurosurgical armamentarium, its impact on surgical results has not yet been examined sufficiently. Therefore, the surgeon is left to decide on a case-by-case basis whether to perform surgery with or without neuronavigation. Future challenges lie in improvement of the interface between the surgeon and the neuronavigator and in reducing the brainshift error, i.e. inaccuracy introduced by changes in tissue positions after image acquisition.