Abstract:Surgical resection of malignant solid tumors is critically dependent on the surgeon's ability to accurately identify pathological tissue and remove the tumor while preserving surrounding healthy structures. However, building an intraoperative 3D tumor model for subsequent removal faces major challenges due to the lack of high-fidelity tumor reconstruction, difficulties in developing generalized tissue models to handle the inherent complexities of tumor diagnosis, and the natural physical limitations of bimanual operation, physiologic tremor, and fatigue creep during surgery. To overcome these challenges, we introduce "TumorMap", a surgical robotic platform to formulate intraoperative 3D tumor boundaries and achieve autonomous tissue resection using a set of multifunctional lasers. TumorMap integrates a three-laser mechanism (optical coherence tomography, laser-induced endogenous fluorescence, and cutting laser scalpel) combined with deep learning models to achieve fully-automated and noncontact tumor resection. We validated TumorMap in murine osteoscarcoma and soft-tissue sarcoma tumor models, and established a novel histopathological workflow to estimate sensor performance. With submillimeter laser resection accuracy, we demonstrated multimodal sensor-guided autonomous tumor surgery without any human intervention.
Abstract:Robot-assisted ultrasound scanning promises to advance autonomous and accessible medical imaging. However, ensuring patient safety and compliant human-robot interaction (HRI) during probe contact poses a significant challenge. Most existing systems either have high mechanical stiffness or are compliant but lack sufficient force and precision. This paper presents a novel single-degree-of-freedom end-effector for safe and accurate robotic ultrasound imaging, using a quasi-direct drive actuator to achieve both passive mechanical compliance and precise active force regulation, even during motion. The end-effector demonstrates an effective force control bandwidth of 100 Hz and can apply forces ranging from 2.5N to 15N. To validate the end-effector's performance, we developed a novel ex vivo actuating platform, enabling compliance testing of the end-effector on simulated abdominal breathing and sudden patient movements. Experiments demonstrate that the end-effector can maintain consistent probe contact during simulated respiratory motion at 2.5N, 5N, 10N, and 15N, with an average force tracking RMS error of 0.83N compared to 4.70N on a UR3e robot arm using conventional force control. This system represents the first compliant ultrasound end-effector tested on a tissue platform simulating dynamic movement. The proposed solution provides a novel approach for designing and evaluating compliant robotic ultrasound systems, advancing the path for more compliant and patient-friendly robotic ultrasound systems in clinical settings.