A comparison study assessing the feasibility of ultrasound-initialized deformable bone models

The state-of-the-art in ultrasound-guided spine interventions

During the last two decades, intra-operative ultrasound (iUS) imaging has been employed for various surgical procedures of the spine, including spinal fusion and needle injections. Accurate and efficient registration of pre-operative computed tomography or magnetic resonance images with iUS images are key elements in the success of iUS-based spine navigation. While widely investigated in research, iUS-based spine navigation has not yet been established in the clinic. This is due to several factors including the lack of a standard methodology for the assessment of accuracy, robustness, reliability, and usability of the registration method. To address these issues, we present a systematic review of the state-of-the-art techniques for iUS-guided registration in spinal image-guided surgery (IGS). The review follows a new taxonomy based on the four steps involved in the surgical workflow that include pre-processing, registration initialization, estimation of the required patient to image transformation, and a visualization process. We provide a detailed analysis of the measurements in terms of accuracy, robustness, reliability, and usability that need to be met during the evaluation of a spinal IGS framework. Although this review is focused on spinal navigation, we expect similar evaluation criteria to be relevant for other IGS applications.

Accurate 3D reconstruction of bony surfaces using ultrasonic synthetic aperture techniques for robotic knee arthroplasty

Robotically guided knee arthroplasty systems generally require an individualized, preoperative 3D model of the knee joint. This is typically measured using Computed Tomography (CT) which provides the required accuracy for preoperative surgical intervention planning. Ultrasound imaging presents an attractive alternative to CT, allowing for reductions in cost and the elimination of doses of ionizing radiation, whilst maintaining the accuracy of the 3D model reconstruction of the joint. Traditional phased array ultrasound imaging methods, however, are susceptible to poor resolution and signal to noise ratios (SNR). Alleviating these weaknesses by offering superior focusing power, synthetic aperture methods have been investigated extensively within ultrasonic non-destructive testing. Despite this, they have yet to be fully exploited in medical imaging. In this paper, the ability of a robotic deployed ultrasound imaging system based on synthetic aperture methods to accurately reconstruct bony surfaces is investigated. Employing the Total Focussing Method (TFM) and the Synthetic Aperture Focussing Technique (SAFT), two samples were imaged which were representative of the bones of the knee joint: a human-shaped, composite distal femur and a bovine distal femur. Data were captured using a 5MHz, 128 element 1D phased array, which was manipulated around the samples using a robotic positioning system. Three dimensional surface reconstructions were then produced and compared with reference models measured using a precision laser scanner. Mean errors of 0.82mm and 0.88mm were obtained for the composite and bovine samples, respectively, thus demonstrating the feasibility of the approach to deliver the sub-millimetre accuracy required for the application.

Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation

Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.