Analysis of Surgical Forces Required to Gain Access Using a Probe for Minimally Invasive Spine Surgery via Cadaveric-Based Experiments Towards Use in Training Simulators

Face, content, and construct validity of a novel VR/AR surgical simulator of a minimally invasive spine operation

Mixed-reality surgical simulators are seen more objective than conventional training. The simulators' utility in training must be established through validation studies. Establish face-, content-, and construct-validity of a novel mixed-reality surgical simulator developed by McGill University, CAE-Healthcare, and DePuy Synthes. This study, approved by a Research Ethics Board, examined a simulated L4-L5 oblique lateral lumbar interbody fusion (OLLIF) scenario. A 5-point Likert scale questionnaire was used. Chi-square test verified validity consensus. Construct validity investigated 276 surgical performance metrics across three groups, using ANOVA, Welch-ANOVA, or Kruskal-Wallis tests. A post-hoc Dunn's test with a Bonferroni correction was used for further analysis on significant metrics. Musculoskeletal Biomechanics Research Lab, McGill University, Montreal, Canada. DePuy Synthes, Johnson & Johnson Family of Companies, research lab. Thirty-four participants were recruited: spine surgeons, fellows, neurosurgical, and orthopedic residents. Only seven surgeons out of the 34 were recruited in a side-by-side cadaver trial, where participants completed an OLLIF surgery first on a cadaver and then immediately on the simulator. Participants were separated a priori into three groups: post-, senior-, and junior-residents. Post-residents rated validity, median > 3, for 13/20 face-validity and 9/25 content-validity statements. Seven face-validity and 12 content-validity statements were rated neutral. Chi-square test indicated agreeability between group responses. Construct validity found eight metrics with significant differences (p < 0.05) between the three groups. Validity was established. Most face-validity statements were positively rated, with few neutrally rated pertaining to the simulation's graphics. Although fewer content-validity statements were validated, most were rated neutral (only four were negatively rated). The findings underscored the importance of using realistic physics-based forces in surgical simulations. Construct validity demonstrated the simulator's capacity to differentiate surgical expertise.

System identification and simulation of soft tissue force feedback in a spine surgical simulator

Surgical simulators are being introduced as training modalities for surgeons. This paper aims to evaluate dynamic models used to convey force feedback from puncturing the soft tissue during a spine surgical simulation. The force feedback of the tissue is treated as a dynamic system. This is done by performing classical system identification across a bandwidth of frequencies on a tissue analogue and fitting that behaviour to dynamic viscoelastic models. The models that are tested are an inverted linear model, the Maxwell model, the Kelvin-Boltzmann (KB) model, and a higher-order blackbox (HO) model. Several error metrics such as percent variance accounted for (%VAF) are determined to measure solution accuracy. The force feedback models are programmed into a surgical simulator and tested with study participants who rated them based on how well the identified models match the behaviour of the rubber tissue analogue. The highest %VAF is 82.64% when the tissue is modelled as the HO model. Statistically significant differences (p < 0.05) are found between all model ratings from participants except between the HO model and the KB model. However, the HO model has the highest percentage (37.8%) of participants who rank its performance as the closest to the tissue analogue compared to the other force feedback models. The more accurately the dynamic behaviour resembles the tissue analogue, the higher the model was rated by study participants. This study highlights the importance of utilizing dynamic signals to generate dynamic models of soft tissue for spine surgical simulators.

Multimodal Haptic Simulation for Ventriculostomy Training. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083370 DOI: 10.1109/embc40787.2023.10340701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Freehand ventriculostomy is a frequent surgical procedure and is among the first ones that junior neurosurgery residents learn. Although training simulators exist, none has been adopted in the clinical routine to train junior residents. This paper focuses on a novel multimodal haptic training simulator that will lift the limitations of current simulators. We thus propose an architecture that integrates (1) visual feedback through augmented MRIs, and (2) a physical mock-up of the patient's skull to (3) active haptic feedback.

Vacuum curette lumbar discectomy mechanics for use in spine surgical training simulators

Simulation in surgical training is a growing field and this study aims to understand the force and torque experienced during lumbar spine surgery to design simulator haptic feedback. It was hypothesized that force and torque would differ among lumbar spine levels and the amount of tissue removed by ≥ 7%, which would be detectable to a user. Force and torque profiles were measured during vacuum curette insertion and torsion, respectively, in multiple spinal levels on two cadavers. Multiple tests per level were performed. Linear and torsional resistances of 2.1 ± 1.6 N/mm and 5.6 ± 4.3 N mm/°, respectively, were quantified. Statistically significant differences were found in linear and torsional resistances between all passes through disc tissue (both p = 0.001). Tool depth (p < 0.001) and lumbar level (p < 0.001) impacted torsional resistance while tool speed affected linear resistance (p = 0.022). Average differences in these statistically significant comparisons were ≥ 7% and therefore detectable to a surgeon. The aforementioned factors should be considered when developing haptic force and torque feedback, as they will add to the simulated lumbar discectomy realism. These data can additionally be used inform next generation tool design. Advances in training and tools may help improve future surgeon training.

Feasibility of extracting tissue material properties via cohesive elements: a finite element approach to probe insertion procedures in non-invasive spine surgeries

Modeling the mechanical behavior of soft tissue probe insertion remains a challenging endeavor due to involved interdependent phenomena comprising tissue nonlinear deformation, contact between the probe and the tissue, crack propagation, and viscoelastic effects. To that matter, cohesive elements allow simulating crack formation and propagation, which provides a promising path to modeling the mechanical behavior of probe insertion in soft tissues. As such, the aim of the present study was to investigate the feasibility of devising and integrating an algorithm in a finite element (FE) case study in efforts of reverse engineering the material properties of non-homogeneous soft tissues. A layered nonlinear tissue model with a cohesive zone was created in the commercial software ABAQUS. Material properties were iteratively modified via a hybrid gradient descent optimization algorithm: minimizing the resultant error to first find optimum Ogden's hyperelastic parameters, followed by obtaining the damage parameters. Perceived material properties were then compared to those obtained via experimental human cadaver testing. Under the investigated four-layered muscle model, numerical results overlapped, to a great extent, with six different force-insertion experimental profiles with an average error of [Formula: see text] 15%. The best profile fit was realized when the highest sudden force drop was less than 60% of the peak force. Lastly, the FE analysis revealed an increase in stiffness as the probe advanced inside the tissue. The optimization algorithm demonstrated its capability to reverse engineer the material parameters required for the FE analysis of real, non-homogeneous, soft tissues. The significance of this procedure lies within its ability to extract tissue material parameters, in real time, with little to no intervention or invasive experimental tests. This could potentially further serve as a database for different muscle layers and force-insertion profiles, used for surgeon and physician clinical training purposes.