Initial experience, feasibility, and technical development with an electromagnetic navigation assistance in percutaneous pelvic bone cementoplasty: retrospective analysis

In Vivo Safety and Feasibility of a CT-Guided Robotic Device for Percutaneous Needle Placement in Bone

PURPOSE

To evaluate the feasibility and accuracy of a robotic device used clinically in soft tissues (abdomen and lung), modified in design and workflow, to perform needle insertions in percutaneous skeletal procedures.

MATERIALS AND METHODS

The primary objective was safety (severe adverse events) of robotic-assisted insertion in this new application. Secondary objectives were feasibility (placement technical success), performance (rate of acceptable insertions), accuracy (lateral deviation), number of intermediate computed tomography (CT) scans, and tolerability (mild/moderate adverse events). Robotic-assisted insertions were performed by 6 interventional radiologists on 3 male pigs under general anesthesia. Needle trajectory was planned on the device software, and then needles were inserted with robotic guidance to reach the cortical bone. Intermediate CT was then performed to verify needle direction; if needed, the trajectory was modified, and robotic-assisted modified insertion into the target was performed. As many intermediate CT scans and trajectory modifications as needed by the operator were allowed.

RESULTS

Twenty-eight needles were inserted (10 in the spine and 18 in the pelvis). No adverse event was reported. Technical success rate was 96.4% (27/28). One insertion was not feasible after several robotic attempts. The placement success rate was 100% (27/27). After the planned intermediate CT scan, 13 (48.1%) of 27 trajectories did not require any modification, and 11 (40.7%) of 27 trajectories required a single modification. One needle was removed and replaced to achieve correct placement. Placement accuracy was similar for spinal and pelvic insertions, with a mean lateral deviation of 2.1 mm (SD ± 1.3).

CONCLUSIONS

Preclinical robotic-assisted needle insertions in bone were safe and feasible, with satisfactory accuracy. A multicenter in-human study is ongoing to evaluate feasibility and safety for percutaneous bone ablation and consolidation procedures.

The Role and Future of Artificial Intelligence in Robotic Image-Guided Interventions

Artificial intelligence and robotics are transforming interventional radiology, driven by advancements in computer vision, robotics and procedural automation. Historically focused on diagnostics, AI now also enhances procedural capabilities in IR, enabling future robotic systems to handle complex tasks such as catheter manipulation or needle placement with increasing precision and reliability. Early robotic systems in IR demonstrated improved accuracy in both vascular and percutaneous interventions, though none were equipped with automatic decision-making. This review tends to show the potential in improving procedural outcomes with AI for robotics, though challenges remain. Techniques like reinforcement learning and haptic vision are under investigation to address several issues, training robots to adapt based on real-time feedback from the environment. As AI-driven robotics evolve, IR could shift towards a model where human expertise oversees the technology rather than performs the intervention itself.

Innovations in Image-Guided Procedures: Unraveling Robot-Assisted Non-Hepatic Percutaneous Ablation

Interventional oncology is routinely tasked with the feat of tumor characterization or destruction, via image-guided biopsy and tumor ablation, which may pose difficulties due to challenging-to-reach structures, target complexity, and proximity to critical structures. Such procedures carry a risk-to-benefit ratio along with measurable radiation exposure. To streamline the complexity and inherent variability of these interventions, various systems, including table-, floor-, gantry-, and patient-mounted (semi-) automatic robotic aiming devices, have been developed to decrease human error and interoperator and intraoperator outcome variability. Their implementation in clinical practice holds promise for enhancing lesion targeting, increasing accuracy and technical success rates, reducing procedure duration and radiation exposure, enhancing standardization of the field, and ultimately improving patient outcomes. This narrative review collates evidence regarding robotic tools and their implementation in interventional oncology, focusing on clinical efficacy and safety for nonhepatic malignancies.

Navigation and Robotics in Interventional Oncology: Current Status and Future Roadmap

Interventional oncology (IO) is the field of Interventional Radiology that provides minimally invasive procedures under imaging guidance for the diagnosis and treatment of malignant tumors. Sophisticated devices can be utilized to increase standardization, accuracy, outcomes, and "repeatability" in performing percutaneous Interventional Oncology techniques. These technologies can reduce variability, reduce human error, and outperform human hand-to-eye coordination and spatial relations, thus potentially normalizing an otherwise broad diversity of IO techniques, impacting simulation, training, navigation, outcomes, and performance, as well as verification of desired minimum ablation margin or other measures of successful procedures. Stereotactic navigation and robotic systems may yield specific advantages, such as the potential to reduce procedure duration and ionizing radiation exposure during the procedure and, at the same time, increase accuracy. Enhanced accuracy, in turn, is linked to improved outcomes in many clinical scenarios. The present review focuses on the current role of percutaneous navigation systems and robotics in diagnostic and therapeutic Interventional Oncology procedures. The currently available alternatives are presented, including their potential impact on clinical practice as reflected in the peer-reviewed medical literature. A review of such data may inform wiser investment of time and resources toward the most impactful IR/IO applications of robotics and navigation to both standardize and address unmet clinical needs.