KEYWORDS: Sensors, Aneurysms, Arteries, Image registration, Equipment, Brain, Prototyping, Electromagnetism, 3D tracking, 3D modeling, Magnetic tracking, Tracking and scene analysis, Shape analysis, Image guided intervention
Purpose. Neuroendovascular procedures, characterized by their minimally invasive nature and effectiveness, are increasingly used in the management of cerebrovascular diseases such as acute stroke and cerebral aneurysms. These procedures, however, rely on x-ray fluoroscopy for catheter guidance, exposing patients, surgeons, and surgical staff to ionizing radiation with associated health risks. To address this problem, this work introduces a new electromagnetic-based (EM) catheter navigation solution. Methods. A custom catheter was designed and constructed to integrate a 5-degree-of-freedom EM coil sensor at its tip. The recorded sensor position was used in: (1) estimating the tip direction to guide it through vessel bifurcations; and (2) dynamically reconstructing the catheter shape as it is advanced or retracted within the vessels. Instrument overlay on angiography CT images is enabled by registering the reconstructed shape to the extracted vessel centerlines. The accuracy of direction estimation, shape sensing, and path-based registration was evaluated in experimental studies on an anthropomorphic phantom. Results. The results demonstrated a mean deviation of 4.1 mm for catheter shape estimation. The catheter tip direction was resolved to within 3.4° error to permit navigation through vessel bifurcations. Registration of reconstructed instrument poses to vessel centerlines achieved 5.1 mm TRE. The results demonstrate sufficient guidance accuracy within the main arteries, such as the femoral artery (⌀8.2-9.8 mm) or the abdominal aorta (⌀30 mm). Conclusions. This work reports a new system for catheter navigation during endovascular interventions. The proposed solution provides a new mode of image guidance that offers accurate treatment for the patient and helps reduce radiation exposure to the surgeon and the surgical staff.
Purpose. Conventional image-guided spine surgery relies on surgical trackers for real-time localization of instruments with respect to pre- or intra-operative CT images. These solutions, however, are susceptible to anatomical deformations that may occur due to patient repositioning or imparted changes during surgery. This work presents an approach that uses intraoperative tracked ultrasound (US) imaging to provide real-time verification and recovery of surgical tracking accuracy following spinal deformations. Methods. The approach combines deep-learning segmentation of the posterior vertebral cortices with a multi-step point-to- surface registration that maps reconstructed US features to the 3D CT image. The method was trained on co-registered CT and US images from 5 cadaveric specimens and validated on 2 separate specimens. The geometric accuracy of the registrations was quantified over target regions covering potential pedicle screw entry points. Results. The study confirmed the optimal level for the confidence threshold of the network output and evaluated the minimum required scan length. Vertebrae with simulated displacements were registered with 1.7 ± 0.3 mm of error. The results were robust for up to 50 mm of initial displacement. Conclusions. The solution offers a fast (real-time), portable (small device footprint), and safe (no ionizing radiation) method of tracking anatomical change during surgery. Work currently underway includes implementation of a prototype system for real-time use and evaluation of the surgical workflow with respect to factors including acquisition time, scan extent (number of vertebrae), and scan planes/trajectories.
Existing methods to improve the accuracy of tibiofibular joint reduction present workflow challenges, high radiation exposure, and a lack of accuracy and precision, leading to poor surgical outcomes. To address these limitations, we propose a method to perform robot-assisted joint reduction using intraoperative imaging to align the dislocated fibula to a target pose relative to the tibia. The approach (1) localizes the robot via 3D-2D registration of a custom plate adapter attached to its end effector, (2) localizes the tibia and fibula using multi-body 3D-2D registration, and (3) drives the robot to reduce the dislocated fibula according to the target plan. The custom robot adapter was designed to interface directly with the fibular plate while presenting radiographic features to aid registration. Registration accuracy was evaluated on a cadaveric ankle specimen, and the feasibility of robotic guidance was assessed by manipulating a dislocated fibula in a cadaver ankle. Using standard AP and mortise radiographic views registration errors were measured to be less than 1 mm and 1° for the robot adapter and the ankle bones. Experiments in a cadaveric specimen revealed up to 4 mm deviations from the intended path, which was reduced to ⪅2 mm using corrective actions guided by intraoperative imaging and 3D-2D registration. Preclinical studies suggest that significant robot flex and tibial motion occur during fibula manipulation, motivating the use of the proposed method to dynamically correct the robot trajectory. Accurate robot registration was achieved via the use of fiducials embedded within the custom design. Future work will evaluate the approach on a custom radiolucent robot design currently under construction and verify the solution on additional cadaveric specimens.
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