Real-time intraoperative ultrasound registration for accurate surgical navigation in patients with pelvic malignancies.

PURPOSE

Surgical navigation aids surgeons in localizing and adequately resecting pelvic malignancies. Accuracy of the navigation system highly depends on the preceding registration procedure, which is generally performed using intraoperative fluoroscopy or CT. However, these ionizing methods are time-consuming and peroperative updates of the registration are cumbersome. In this present clinical study, several real-time intraoperative ultrasound (iUS) registration methods have been developed and evaluated for accuracy.

METHODS

During laparotomy in prospectively included patients, sterile electromagnetically tracked iUS acquisitions of the pelvic vessels and bones were collected. An initial registration and five other rigid iUS registration methods were developed including real-time deep learning bone and artery segmentation of 2D ultrasound. For each registration method, the accuracy was computed as the target registration error (TRE) using pelvic lymph nodes (LNs) as targets.

RESULTS

Thirty patients were included. The mean ± SD ultrasound acquisition time was 4.2 ± 1.4 min for the pelvic bone and 4.0 ± 1.1 min for the arteries. Deep learning bone and artery ultrasound segmentation resulted in an average (centerline)Dice of 0.85 and a mean surface distance below 2 mm. In 21 patients with visible LNs, initial registration resulted in a median (interquartile range [IQR]) TRE of 7.4 (5.9-10.9) mm. For the other five methods, 2D and 3D bone registration resulted in significantly lower TREs than 2D artery, 3D artery and bifurcation registration (two-sided Wilcoxon rank-sum test p < 0.01). The real-time 2D bone registration method was most accurate with a median (IQR) TRE of 2.6 (1.3-5.7) mm.

CONCLUSION

Real-time 2D iUS bone registration is a fast and accurate method for patient registration prior to surgical navigation and has advantages over current registration techniques. Because of the user dependency of iUS, intuitive software is crucial for optimal clinical implementation. Trial registration number ClinicalTrials.gov (No. NCT05637346).