System architecture for intraoperative ultrasound registration in image-based medical navigation.

Medical navigation systems for orthopedic surgery are becoming more and more important with the increasing proportion of older people in the population, and hence the increasing incidence of diseases of the musculoskeletal system. The central problem for such systems is the exact transformation of the preoperatively acquired datasets to the coordinate system of the patient's body, which is crucial for the accuracy of navigation. Our approach, based on the use of intraoperative ultrasound for image registration, is capable of robustly registering bone structures for different applications, e.g., at the spine or the knee. Nevertheless, this new procedure demands additional steps of preparation of preoperative data. To increase the clinical acceptance of this procedure, it is useful to automate most of the data processing steps. In this article, we present the architecture of our system with focus on the automation of the data processing steps. In terms of accuracy, a mean target registration error of 0.68 mm was achieved for automatically segmented and registered phantom data where the reference transformation was obtained by performing point-based registration using artificial structures. As the overall accuracy for subject data cannot be determined non-invasively, automatic segmentation and registration were judged by visual inspection and precision, which showed a promising result of 1.76 mm standard deviation for 100 registration trials based on automatic segmentation of magnetic resonance imaging data of the spine.

Toward registration of 3D ultrasound and CT images of the spine in clinical praxis: design and evaluation of a data acquisition protocol.

Recent work has demonstrated the accuracy and operational viability of an algorithm proposed by the authors that successfully registers 3-D ultrasound data with CT or MRI data. The successful application of this method to intraoperative navigation, however, depends critically on the quality of the acquired ultrasound data. This gives rise to two questions concerning the usability of the algorithm in clinical praxis. First, how can one guarantee high-quality, user-independent ultrasound registration data with this procedure? Second, can this approach work reliably in clinical practice, namely within the operating theater? To address both of these questions, we present an ultrasound data acquisition protocol that leads the user through the data acquisition process and also provides the criteria to adjust the relevant ultrasound parameters. We also evaluated criteria for the visual inspection of the suitability of the ultrasound data for the registration process. Results for this evaluation show that these visual criteria can be used to decide preoperatively if an ultrasound registration will be successful in a patient. The intraoperative evaluation of the protocol showed that high-quality registrations can be achieved under realistic conditions. This protocol and the visual inspection criteria, together with the ultrasound registration algorithm, provide a surgical team with a means of performing precise, cost-effective navigation in patients for whom a navigated intervention was previously impossible. We evaluated the proposed procedure in clinical practice.