AcouStick: An optically tracked A-mode ultrasonography system for registration in image-guided neurosurgery

Referencing for intraoperative navigation: Evaluation of human bias

Navigation-assisted surgery is the gold standard for complex reconstructive procedures of the midface and facial skeleton, and artificial and anatomical landmarks are often used for reference. The correct identification of these landmarks before surgery is crucial for the accuracy of the navigation system. This study aimed to investigate the human errors in reference point placement. This retrospective study investigated 228 reference-point positions in 51 cases where navigation was utilized. The discrepancies between the actual reference point-position and manually planned preoperative reference points were quantified using Brainlab iPlanCMF 3.0.6. The referencing methods used in these cases included dental registration splints, osteosynthesis materials, anatomical landmarks, and combinations of these methods. The average discrepancy in the actual and manually planned reference points was 0.29 ± 0.41 mm. The use of anatomical landmarks demonstrated a significantly lower deviation (p < 0.05), although the differences between the errors in reference-point placement using dental registration splints, osteosynthesis materials, or combinations of these methods were not statistically significant. The frequency of misplacement of reference points was significantly higher than expected. These errors might have been caused by human bias during manual placement of the points or intraoperative difficulties caused by extensive metal artifacts. Thus, we postulate that the surgical personnel involved in planning navigation-assisted surgery should undergo intensive training. The development of new referencing methods that are less susceptible to these causes of error might help overcome human bias.

[New developments in computer-assisted surgery (CAS). From intraoperative imaging to ultrasound-based navigation]

Ever faster processor capacity is having an impact on computer-assisted or computer-aided surgery (CAS). The fusion of different imaging modalities enables functional data such as PET-CT, for example, to be available in image-guided surgery. Referencing of image data is the key to precise navigation. Intraoperative data acquisition is a new approach to improving accuracy. Thus, intraoperative CT conducted under navigational support enables automatic referencing of up-to-date image data. Alternatively, intraoperative magnetic resonance imaging or intraoperative sonography can be performed. Ultrasound systems have already been successfully integrated in existing navigational systems to compensate for intraoperative tissue shifting. Ultrasound systems may play a role in the future as a single modality in image-guided surgery in soft tissue of the neck and skull bone.

Accuracy of ultrasound measurements for skull bone thickness using coded signals

The knowledge of skull bone thickness would be helpful for a great variety of surgical interventions of the head. Ultrasound (US) can offer this information intraoperatively in real time. A-mode US measurements of skull bone thickness were performed with different pulse characteristics: 1) in water and 2) by directly coupling a 2.25-MHz US transducer integrated in a handpiece with a soft delay line using coded excitation (CE) (SonoPointer). Mechanical measurements by calipers served as controls. The specimen were 16 nonselected human cadaveric skull bones preserved with formaldehyde. The average difference between the bone thickness measured by the SonoPointer and the mechanical control measurements was 0.04 +/- 0.62 mm. The 95% limits of agreement between the two methods were -1.18 and 1.25 mm. However, even the gold standard of two repeated caliper measurements had limits of agreement of -0.4 and 0.42 mm. Using a standard US pulse in water, only 62.5% sample points were measurable, whereas the SonoPointer produced the thickness measurement in 97.9% of points. CE proved to be superior to single burst or needle US pulses. A-mode US measurements of skull bone thickness using the SonoPointer are feasible. It may provide valuable information on skull bone thickness, e.g., for osteosynthesis, calvarial split bone harvesting, implantation of hearing devices, osseointegrated titanium fixtures, and skull base surgery.

A-mode ultrasound-based intra-femoral bone cement detection and 3D reconstruction in RTHR

Due to the difficulty of determining the 3D boundary of the cement-bone interface in Revision Total Hip Replacement (RTHR), the removal of the distal intra-femoral bone cement can be a time-consuming and risky operation. Within the framework of computer- and robot-assisted cement removal, the principles and first results of an automatic detection and 3D surface reconstruction of the cement-bone boundary using A-mode ultrasound are described. Sound propagation time and attenuation of cement were determined considering different techniques for the preparation of bone cement, such as the use of a vacuum system (Optivac, Biomet). A laboratory setup using a rotating, standard 5-MHz transducer was developed. The prototype enables scanning of bisected cement-prepared femur samples in a 90 degrees rotation range along their rotation axis. For system evaluation ex vivo, the distal femur of a human cadaver was prepared with bone cement and drilled (Ø 10 mm) to simulate the prosthesis cavity in a first approximation. The sample was cut in half and CT scanned (0.24 mm resolution; 0.5 mm distance; 0.5 mm thickness), and 3D voxel models of the manually segmented bone cement were reconstructed, providing the ground truth. Afterwards, 90 degrees segments of each ex-vivo sample were scanned by the A-mode ultrasound system. To obtain better ultrasound penetration, we used coded signal excitation and pulse compression filtering. A-mode ultrasound signal detection, filtering and segmentation were accomplished fully automatically. Subsequently, 3D voxel models of each sample were calculated. Accuracy evaluation of the measured ultrasound data was performed by ICP matching of each ultrasound dataset ( approximately 8000 points) to the corresponding CT dataset and calculation of the residual median distance error between the corresponding datasets. Prior to each ICP matching, an initial pre-registration was calculated using prominent landmarks in the corresponding datasets. This method yielded a median distance error in the region of 0.25 mm for the cement-bone interface in both femur halves.

A faster method for 3D/2D medical image registration--a simulation study

3D/2D patient-to-computed-tomography (CT) registration is a method to determine a transformation that maps two coordinate systems by comparing a projection image rendered from CT to a real projection image. Iterative variation of the CT's position between rendering steps finally leads to exact registration. Applications include exact patient positioning in radiation therapy, calibration of surgical robots, and pose estimation in computer-aided surgery. One of the problems associated with 3D/2D registration is the fact that finding a registration includes solving a minimization problem in six degrees of freedom (dof) in motion. This results in considerable time requirements since for each iteration step at least one volume rendering has to be computed. We show that by choosing an appropriate world coordinate system and by applying a 2D/2D registration method in each iteration step, the number of iterations can be grossly reduced from n6 to n5. Here, n is the number of discrete variations around a given coordinate. Depending on the configuration of the optimization algorithm, this reduces the total number of iterations necessary to at least 1/3 of it's original value. The method was implemented and extensively tested on simulated x-ray images of a tibia, a pelvis and a skull base. When using one projective image and a discrete full parameter space search for solving the optimization problem, average accuracy was found to be 1.0 +/- 0.6(degrees) and 4.1 +/- 1.9 (mm) for a registration in six parameters, and 1.0 +/- 0.7(degrees) and 4.2 +/- 1.6 (mm) when using the 5 + 1 dof method described in this paper. Time requirements were reduced by a factor 3.1. We conclude that this hardware-independent optimization of 3D/2D registration is a step towards increasing the acceptance of this promising method for a wide number of clinical applications.