Ultrasound-guided robotic percutaneous puncture for liver tumors with respiratory gating via attention-enhanced Siamese networks.

BACKGROUND AND

OBJECTIVE

Accurate and safe needle insertion is critical in abdominal percutaneous interventions, particularly for liver-targeted procedures. Respiratory-induced organ motion presents a major challenge to precision, motivating the need for robotic assistance and real-time motion compensation.

METHODS

This study presents a robotic puncture system integrated with ultrasound image-based respiratory gating for improved needle placement. The system incorporates preoperative puncture path planning, intraoperative calibration and image-to-patient registration, robot-assisted needle alignment, and real-time ultrasound monitoring. A channel attention-enhanced fusion Siamese network (SE-FSiamFC) is proposed for robust target tracking within ultrasound image sequences, enabling respiratory phase estimation to guide puncture timing.

RESULTS

Phantom experiments demonstrated that the robotic system achieved a calibration time of under 100 s with a calibration accuracy of <1 mm. The average targeting accuracy in phantom-based needle insertions was 1.72 ± 0.25 mm. On the CLUST 2015 ultrasound dataset, the SE-FSiamFC network achieved the best tracking performance on the challenging MED group, with an accuracy of 2.170 ± 1.289 mm. In vivo puncture experiments on two pig models showed that without respiratory gating, the targeting errors were 3.03 ± 0.82 mm and 2.77 ± 0.69 mm, respectively. With respiratory gating, the errors were 1.93 ± 0.33 mm and 1.76 ± 0.29 mm, respectively.

CONCLUSIONS

The proposed robotic system enables efficient calibration, accurate tracking, and reliable needle guidance under respiratory motion. The integration of ultrasound-based respiratory gating provides favorable temporal windows for needle insertion, enhancing the safety and precision of abdominal percutaneous interventions.