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Ultrasound-Led Multimodality Imaging-Guided Robotic Needle Insertion With Respiratory Phase Consistency in Phantom
Fan Xiao1, Wen-Zhen Ding1, Chuan Pang1
1Senior Department of Oncology, Chinese PLA General Hospital, Beijing, China.
Ultrasound in Medicine & Biology
|August 11, 2026
Summary
The TONGMAI robotic system demonstrated consistent puncture accuracy for experienced physicians and improved accuracy for inexperienced physicians in phantom and animal studies. This novel ultrasound-guided robotic system shows promise for complex procedures.
Area of Science:
- Medical Robotics
- Surgical Navigation
- Medical Imaging
Background:
- Accurate needle placement is crucial for minimally invasive procedures.
- Robotic systems offer potential for enhanced precision and control in interventions.
- Ultrasound (US)-guided interventions require high accuracy, especially in dynamic environments.
Purpose of the Study:
- To evaluate the puncture accuracy and feasibility of the TONGMAI robotic system.
- The system utilizes electromagnetic tracking and US-guided multimodality imaging with respiratory compensation.
- Assessment was performed in phantom and animal models.
Main Methods:
- Experienced and inexperienced physicians performed needle insertions using TONGMAI, freehand, or needle-guide assistance.
- Experiments included static and respiratory phantoms, rabbit liver, and miniature pig liver models.
- The primary outcome was real-time US-based puncture accuracy (US-Error).
Main Results:
- Experienced physicians showed no significant difference in US-Error across methods.
- TONGMAI significantly reduced US-Error for inexperienced physicians compared to freehand or needle-guide methods in phantom and animal models.
- No procedure-related complications occurred during exploratory non-hepatic punctures.
Conclusions:
- TONGMAI supports consistent puncture performance in experienced physicians.
- The robotic system enhances accuracy for inexperienced physicians in various conditions.
- Results support further development of US-led robotic workflows for deformable targets.

