PURPOSE: The open-source Perk Tutor training platform has been shown to improve trainee performance in
interventions that require ultrasound guidance. Our goal was to determine if needle coordination of medical
trainees can be improved by training with Perk Tutor compared to training with ultrasound only.
METHODS: Twenty participants with no previous experience were randomized into two groups; the Perk
Tutor group and the Control group. The Perk Tutor group had access to the 3D visualization while the Control
group used ultrasound only during their training. Performance was analyzed, measured and compared by Perk
Tutor with regards to four needle coordination metrics. None of the groups had access to 3D visualization during
RESULTS: The needle tracking measurements showed, for the Perk Tutor group, lower average distance
between the needle tip and ultrasound (1.2 [0.9 – 2.8] mm vs 2.7 [2.3 – 4.0] mm, respectively; P = 0.023) and
lower maximum distance between the needle tip and ultrasound (2.2 [1.9 – 3.2] mm vs 4.6 [3.9 – 6.2] mm,
respectively; P = 0.013). There was no significant difference in average needle to ultrasound plane angle and
maximum needle to ultrasound plane distance. All participants were successful in the procedure.
CONCLUSION: The Perk Tutor group had significantly reduced distance from the needle tip to the ultrasound
plane. Training with Perk Tutor can improve trainees’ needle and ultrasound coordination.
PURPOSE: The intraoperative measurement of tracking error is crucial to ensure the reliability of electromagnetically
navigated procedures. For intraoperative use, methods need to be quick to set up, easy to interpret, and not interfere with
the ongoing procedure. Our goal was to evaluate the feasibility of using redundant electromagnetic sensors to alert users
to tracking error in a navigated intervention setup.
METHODS: Electromagnetic sensors were fixed to a rigid frame around a region of interest and on surgical tools. A
software module was designed to detect tracking error by comparing real-time measurements of the differences between
inter-sensor distances and angles to baseline measurements. Once these measurements were collected, a linear support
vector machine-based classifier was used to predict tracking errors from redundant sensor readings.
RESULTS: Measuring the deviation in the reported inter-sensor distance and angle between the needle and cautery served
as a valid indicator for electromagnetic tracking error. The highest classification accuracy, 86%, was achieved based on
readings from the cautery when the two sensors on the cautery were close together. The specificity of this classifier was
93% and the sensitivity was 82%.
CONCLUSION: Placing redundant electromagnetic sensors in a workspace seems to be feasible for the intraoperative
detection of electromagnetic tracking error in controlled environments. Further testing should be performed to optimize
the measurement error threshold used for classification in the support vector machine, and improve the sensitivity of our
method before application in real procedures.
PURPOSE: Optical pose tracking of medical instruments is often used in image-guided interventions. Unfortunately, compared to commonly used computing devices, optical trackers tend to be large, heavy, and expensive devices. Compact 3D vision systems, such as Intel RealSense cameras can capture 3D pose information at several magnitudes lower cost, size, and weight. We propose to use Intel SR300 device for applications where it is not practical or feasible to use conventional trackers and limited range and tracking accuracy is acceptable. We also put forward a vertebral level localization application utilizing the SR300 to reduce risk of wrong-level surgery. METHODS: The SR300 was utilized as an object tracker by extending the PLUS toolkit to support data collection from RealSense cameras. Accuracy of the camera was tested by comparing to a high-accuracy optical tracker. CT images of a lumbar spine phantom were obtained and used to create a 3D model in 3D Slicer. The SR300 was used to obtain a surface model of the phantom. Markers were attached to the phantom and a pointer and tracked using Intel RealSense SDK’s built-in object tracking feature. 3D Slicer was used to align CT image with phantom using landmark registration and display the CT image overlaid on the optical image. RESULTS: Accuracy of the camera yielded a median position error of 3.3mm (95th percentile 6.7mm) and orientation error of 1.6° (95th percentile 4.3°) in a 20x16x10cm workspace, constantly maintaining proper marker orientation. The model and surface correctly aligned demonstrating the vertebral level localization application. CONCLUSION: The SR300 may be usable for pose tracking in medical procedures where limited accuracy is acceptable. Initial results suggest the SR300 is suitable for vertebral level localization.
PURPOSE: The measurement of tracking error is crucial to ensure the safety and feasibility of electromagnetically tracked, image-guided procedures. Measurement should occur in a clinical environment because electromagnetic field distortion depends on positioning relative to the field generator and metal objects. However, we could not find an accessible and open-source system for calibration, error measurement, and visualization. We developed such a system and tested it in a navigated breast surgery setup.
METHODS: A pointer tool was designed for concurrent electromagnetic and optical tracking. Software modules were developed for automatic calibration of the measurement system, real-time error visualization, and analysis. The system was taken to an operating room to test for field distortion in a navigated breast surgery setup. Positional and rotational electromagnetic tracking errors were then calculated using optical tracking as a ground truth.
RESULTS: Our system is quick to set up and can be rapidly deployed. The process from calibration to visualization also only takes a few minutes. Field distortion was measured in the presence of various surgical equipment. Positional and rotational error in a clean field was approximately 0.90 mm and 0.31°. The presence of a surgical table, an electrosurgical cautery, and anesthesia machine increased the error by up to a few tenths of a millimeter and tenth of a degree.
CONCLUSION: In a navigated breast surgery setup, measurement and visualization of tracking error defines a safe working area in the presence of surgical equipment. Our system is available as an extension for the open-source 3D Slicer platform.
Electromagnetic tracking allows for increased flexibility in designing image-guided interventions, however it is well understood that electromagnetic tracking is prone to error. Visualization and assessment of the tracking error should take place in the operating room with minimal interference with the clinical procedure. The goal was to achieve this ideal in an open-source software implementation in a plug and play manner, without requiring programming from the user. We use optical tracking as a ground truth. An electromagnetic sensor and optical markers are mounted onto a stylus device, pivot calibrated for both trackers. Electromagnetic tracking error is defined as difference of tool tip position between electromagnetic and optical readings. Multiple measurements are interpolated into the thin-plate B-spline transform visualized in real time using 3D Slicer. All tracked devices are used in a plug and play manner through the open-source SlicerIGT and PLUS extensions of the 3D Slicer platform. Tracking error was measured multiple times to assess reproducibility of the method, both with and without placing ferromagnetic objects in the workspace. Results from exhaustive grid sampling and freehand sampling were similar, indicating that a quick freehand sampling is sufficient to detect unexpected or excessive field distortion in the operating room. The software is available as a plug-in for the 3D Slicer platforms. Results demonstrate potential for visualizing electromagnetic tracking error in real time for intraoperative environments in feasibility clinical trials in image-guided interventions.