Assessed the effectiveness of ANT-X, an AI-powered surgical robot, in aiding Percutaneous Nephrolithotomy (PCNL), a technique used for the removal of large kidney stones.
A recent trial conducted by clinical researchers at Nagoya City University in Japan has examined the effectiveness of an AI-driven surgical robot in aiding percutaneous nephrolithotomy (PCNL), a procedure used to remove large kidney stones through minimally invasive means. Typically, this procedure demands the expertise of highly skilled surgeons to access the kidney through the skin.
The robot, known as the Automated Needle Targeting with X-ray (ANT-X), was developed by NDR Medical Technology, a Singapore-based medical startup. ANT-X aims to streamline needle placement and calculate targeting rapidly using a single X-ray image, making the procedure notably smoother. In the trial, the robot significantly eased the PCNL procedure.
Percutaneous nephrolithotomy (PCNL) entails accessing the kidney through the back skin, a technically challenging task. Erroneous renal access can lead to severe complications such as bowel perforation, substantial bleeding, and sepsis, necessitating years of surgical training.
The ANT-X robot is tailored to assist with PCNL, potentially enhancing safety for less experienced surgeons. Integrated with C-arm fluoroscopy, the robot employs AI to analyze X-ray images and automate needle alignment, allowing the surgeon to concentrate on insertion depth.
In a recent study conducted at Nagoya City University Hospital, researchers compared the robot-assisted PCNL with conventional ultrasound-guided PCNL in a patient cohort. A novice surgeon performed robot-assisted renal access procedures, while experienced surgeons conducted conventional renal access procedures.
The study revealed that successful renal access with a single needle puncture occurred 50% of the time in the robot-assisted group, compared to 34% in the conventional group. Additionally, the average number of required needle punctures was lower in the robot-assisted group (1.82 times vs. 2.51 times). Notably, 14.3% of procedures in the conventional group required intervention from a different surgeon due to unsuccessful renal access, which did not occur in the robot-assisted group.
These findings underscore the effectiveness and safety of AI-driven robots in executing intricate surgical tasks. Kazumi Taguchi, a researcher involved in the study, highlighted the potential of ANT-X to simplify complex procedures like PCNL, enabling a broader pool of doctors to perform them and benefit more patients. With its AI-driven technology, ANT-X may pave the way for automating similar interventional surgeries, potentially reducing procedure times, alleviating burdens on senior doctors, and mitigating the occurrence of complications.
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