Usability of Graphical Visualizations on a Tool-Mounted Interface for Spine Surgery

Accurate placement of thoracolumbar pedicle screws using a handheld iOS-based navigation device: a prospective intra-patient agreement study

BACKGROUND

Accurate pedicle screw placement is a challenge with reported misplacement rates of 10% and higher. A handheld navigation device (HND) may provide accuracy equal to CT-based navigation (CT-Nav) but without the cost and complexity.

OBJECTIVE

To study the accuracy of a handheld navigation device for pedicle screw placement.

STUDY DESIGN

This prospective cross-sectional study with consistently applied reference standard enrolled 20 patients undergoing 92 pedicle screw placements.

PATIENTS

Patients who underwent pedicle screw placement between May 2022 and September 2022.

OUTCOME MEASURES

Pedicle screw placement accuracy per Gertzbein-Robbins.

METHODS

Once the screw pilot hole was established, the proposed trajectory of the HND was compared with that proposed by CT-Nav. Postoperatively, screw accuracy was graded according to Gertzbein-Robbins by a blinded radiologist based on CT scans. Accuracy was compared between the two systems and published control for fluoroscopy assisted and CT-Nav placement using Bayesian posterior distribution.

RESULTS

The trajectory proposed by the HND and CT-Nav were in agreement in 98.9% (95% Exact CI; 94.09%-99.97%). The HND accuracy was 98.9% with 91 screws rated "A" and 1 rated "C". Noninferiority to fluoroscopic placement was achieved because the one-sided normal-approximation 95% CI Lower Bound (LB) of 95.3% is greater than the Performance Goal (PG) of 83.4%. Posthoc analysis demonstrated that the probability of superiority of the HND relative to the historical accuracy rate of 91.5% for fluoroscopy assisted procedures is >0.999 and that the HND's accuracy rate is within 4.5% of CT-Nav of 95.5% is >0.999. No adverse events or intra-operative complications associated with HND were observed. There was 1 (1.1%) intra-operative repositioning and no reoperations for any reason.

CONCLUSIONS

The accuracy rate of the HND was 98.9%, and the proposed trajectory matched with CT-Nav in 98.9% of the time. This is superior to the historical published accuracy rate for fluoroscopy-assisted procedures and equivalent to the historical published accuracy rate for CT-Nav.

CLINICAL TRIAL REGISTRATION NUMBER

Dutch trial register NL74268.058.20.

Towards Reducing Visual Workload in Surgical Navigation: Proof-of-concept of an Augmented Reality Haptic Guidance System

The integration of navigation capabilities into the operating room has enabled surgeons take on more precise procedures guided by a pre-operative plan. Traditionally, navigation information based on this plan is presented using monitors in the surgical theater. But the monitors force the surgeon to frequently look away from the surgical area. Alternative technologies, such as augmented reality, have enabled surgeons to visualize navigation information in-situ. However, burdening the visual field with additional information can be distracting. In this work, we propose integrating haptic feedback into a surgical tool handle to enable surgical guidance capabilities. This property reduces the amount of visual information, freeing surgeons to maintain visual attention over the patient and the surgical site. To investigate the feasibility of this guidance paradigm we conducted a pilot study with six subjects. Participants traced paths, pinpointed locations and matched alignments with a mock surgical tool featuring a novel haptic handle. We collected quantitative data, tracking user's accuracy and time to completion as well as subjective cognitive load. Our results show that haptic feedback can guide participants using a tool to sub-millimeter and sub-degree accuracy with only little training. Participants were able to match a location with an average error of 0.82  mm , desired pivot alignments with an average error of 0.83 ° and desired rotations to 0.46 °.

Best Papers in Human Factors and Sociotechnical Development

OBJECTIVES

To select the best papers that made original and high impact contributions in human factors and organizational issues in biomedical informatics in 2021.

METHODS

A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2021 that address human factors and organizational issues in biomedical informatics. The screening of papers on titles and abstracts independently by the two section editors led to a total of 3,206 papers. These papers were discussed for a selection of 12 finalist papers, which were then reviewed by the two section editors, two chief editors, and by three external reviewers from internationally renowned research teams.

RESULTS

The query process resulted in 12 papers that reveal interesting and rigorous methods and important studies in human factors that move the field forward, particularly in clinical informatics and emerging technologies such as brain-computer interfaces and mobile health. This year three papers were clearly outstanding and help advance in the field. They provide examples of examining novel and important topics such as the nature of human-machine interaction behavior and norms, use of social-media based design for an electronic health record, and emerging topics such as brain-computer interfaces. thematic development of electronic health records and usability techniques, and condition-focused patient facing tools. Those concerning the Corona Virus Disease 2019 (COVID-19) were included as part of that section.

CONCLUSION

The selected papers make important contributions to human factors and organizational issues, expanding and deepening our knowledge of how to apply theory and applications of new technologies in health.

AR-Supported Supervision of Conditional Autonomous Robots: Considerations for Pedicle Screw Placement in the Future

Robotic assistance is applied in orthopedic interventions for pedicle screw placement (PSP). While current robots do not act autonomously, they are expected to have higher autonomy under surgeon supervision in the mid-term. Augmented reality (AR) is promising to support this supervision and to enable human–robot interaction (HRI). To outline a futuristic scenario for robotic PSP, the current workflow was analyzed through literature review and expert discussion. Based on this, a hypothetical workflow of the intervention was developed, which additionally contains the analysis of the necessary information exchange between human and robot. A video see-through AR prototype was designed and implemented. A robotic arm with an orthopedic drill mock-up simulated the robotic assistance. The AR prototype included a user interface to enable HRI. The interface provides data to facilitate understanding of the robot’s ”intentions”, e.g., patient-specific CT images, the current workflow phase, or the next planned robot motion. Two-dimensional and three-dimensional visualization illustrated patient-specific medical data and the drilling process. The findings of this work contribute a valuable approach in terms of addressing future clinical needs and highlighting the importance of AR support for HRI.