Innovative 3D structured light technology for robotic-assisted surgery in selected spontaneous medium-volume basal ganglia hematomas: enhancing precision, surgical nuance, and clinical outcomes
摘要
A structured-light robotic system enables noninvasive surface-based facial registration for patient-to-image alignment; however, it has not been widely adopted for basal ganglia hematoma treatment. This study evaluates its safety, accuracy, and efficiency in patients with basal ganglia hematomas.
MethodsRetrospective consecutive patients with spontaneous basal ganglia hematomas (10–30 mL) admitted from January 2022 to January 2024 were grouped as surgical or non-surgical. Outcomes were analyzed, focusing on registration accuracy and surgical efficiency.
ResultsBaseline preoperative hematoma volume, GCS, NIHSS, and coagulation disorders were comparable between groups (p > 0.05). Mean registration time was 120 ± 56 s and surgery time 102.22 ± 6.33 min; hematoma clearance was 72% initially and 93% at 7 days. Entry-point discrepancy was 2.2 ± 0.7 mm; catheter tip alignment in the upper/middle/lower hematoma segments was 4%/80%/16%, with a maximum 5.7-mm deviation from the midline axis. The surgery group showed faster recovery with higher 24 h-GCS (p < 0.001) and better NIHSS/ADL/mRS than non-surgery (p < 0.001 at all time points; p = 0.003 and p = 0.026 at 30 and 90 days; p = 0.041). At 90 days, facial palsy, sensory loss, and ulcers were similar (p > 0.05), whereas pneumonia (p = 0.034) and UTIs (p = 0.002) were lower in the surgery group. No mortality, bleeding, or reoperations occurred.
ConclusionsSurface registration using the 3D structured light technique is a fast and precise alternative treatment for selected patients with spontaneous medium-volume basal ganglia hematomas, which can improve clinical efficiency while maintaining sufficient accuracy and safety to meet clinical requirements.
Trial registrationretrospectively registered with approval by the Ethics Committee of Shanghai Fourth people’s hospital, Tongji University School of Medicine (No. 2022327-001).