Sensor-Based Automated Detection of Electrosurgical Cautery States.

In computer-assisted surgery, it is typically required to detect when the tool comes into contact with the patient. In activated electrosurgery, this is known as the energy event. By continuously tracking the electrosurgical tools' location using a navigation system, energy events can help determine locations of sensor-classified tissues. Our objective was to detect the energy event and determine the settings of electrosurgical cautery-robustly and automatically based on sensor data. This study aims to demonstrate the feasibility of using the cautery state to detect surgical incisions, without disrupting the surgical workflow. We detected current changes in the wires of the cautery device and grounding pad using non-invasive current sensors and an oscilloscope. An open-source software was implemented to apply machine learning on sensor data to detect energy events and cautery settings. Our methods classified each cautery state at an average accuracy of 95.56% across different tissue types and energy level parameters altered by surgeons during an operation. Our results demonstrate the feasibility of automatically identifying energy events during surgical incisions, which could be an important safety feature in robotic and computer-integrated surgery. This study provides a key step towards locating tissue classifications during breast cancer operations and reducing the rate of positive margins.

Optically Tracked Needle for Ultrasound-Guided Percutaneous Nephrolithotomy Puncture: A Preliminary Report.

Background and Aim: Precise needle puncture of the renal collecting system is an essential step for effective percutaneous nephrolithotomy (PCNL). The use of ultrasound for puncture is receiving increased attention. Ultrasound has recognized limitations related to poor observation of the needle tip. We aimed to assess whether an affordable open-source computerized needle navigation training system, using optically tracked ultrasonography, could improve performance of simulated PCNL puncture by urologic trainees, compared with conventional free hand manual sonographic puncture. Materials and Methods: This study describes a PCNL navigation system that can be recreated with any standard ultrasound machine using relatively inexpensive components. The system allows the needle tip to be precisely appreciated in the ultrasound image, its trajectory planned, and the appreciation of needle tip to target calix proximity sound effect. Eight participants (six trainees and two qualified urologists) assessed the PCNL training model. Alternating starting with freehand (control) and tracked needle (experimental) punctures were performed on a phantom kidney. Total procedure and the number of reinsertions required were recorded. Results: The mean time for freehand puncture was 89 seconds (range 13-173), whereas that of the optically tracked needle was 36 seconds (range 12-72). Thus, puncture time was significantly reduced by an average of 53 seconds (p = 0.045) in the experimental arm. The mean number of needle reinsertions was 3.3 with freehand compared with 1.3 in the optically tracked puncture (p = 0.005). The mean square root error of the optical tracking system was 1.8 mm (four calibrations averaged). Conclusion: This study demonstrates that affordable hardware and open-source software can be used to construct an optically tracked ultrasound navigation system for PCNL training. Statistically significant reduced puncture time and number of passes required for effective puncture are demonstrated. We feel that computerized needle tracking during PCNL puncture deserves further evaluation in a training and, potentially, in a clinical setting.

SlicerVR for Medical Intervention Training and Planning in Immersive Virtual Reality.

Virtual reality (VR) provides immersive visualization that has proved to be useful in a variety of medical applications. Currently, however, no free open-source software platform exists that would provide comprehensive support for translational clinical researchers in prototyping experimental VR scenarios in training, planning or guiding medical interventions. By integrating VR functions in 3D Slicer, an established medical image analysis and visualization platform, SlicerVR enables virtual reality experience by a single click. It provides functions to navigate and manipulate the virtual scene, as well as various settings to abate the feeling of motion sickness. SlicerVR allows for shared collaborative VR experience both locally and remotely. We present illustrative scenarios created with SlicerVR in a wide spectrum of applications, including echocardiography, neurosurgery, spine surgery, brachytherapy, intervention training and personalized patient education. SlicerVR is freely available under BSD type license as an extension to 3D Slicer and it has been downloaded over 7,800 times at the time of writing this article.