BACKGROUND: Pelvic fractures pose significant surgical challenges due to complex anatomy and proximity to neurovascular structures. This study evaluated the clinical efficacy of artificial intelligence (AI)-assisted Holosight robotic percutaneous screw fixation compared to conventional fluoroscopy-guided internal fixation for pelvic fractures.
METHODS: A retrospective cohort analysis was conducted on 89 patients with pelvic fractures treated between September 2016 and December 2024. Patients were divided into two groups: those who underwent robot-assisted percutaneous screw fixation (Robot group, n = 68) and those who received conventional fluoroscopy-guided screw fixation (Control group, n = 21). In selected cases within the robot group, AI was utilized for preoperative screw trajectory planning. Clinical outcomes including operative time, intraoperative blood loss, fluoroscopy frequency, guidewire insertion attempts, Majeed functional scores, and fracture healing time were compared between groups.
RESULTS: The robot-assisted group demonstrated significantly shorter operative time (P < 0.01), reduced intraoperative blood loss (P < 0.01), fewer fluoroscopic exposures (P < 0.01), and fewer guidewire insertion attempts (P < 0.01) compared to the control group. No statistically significant differences were observed in Majeed functional scores between the two groups (P > 0.05).
CONCLUSION: Robot-assisted percutaneous screw fixation for pelvic fractures offers superior surgical precision and reduced invasiveness compared to conventional methods. The integration of AI-based preoperative planning enhances screw trajectory accuracy, potentially reducing the risk of neurovascular injury. While the clinical benefits are promising, larger prospective multicenter trials are warranted to validate these findings.
Read the article: PubMed · Publisher (DOI)