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Force-Sensing-Integrated Flexible Tool for Precise Lesion Resection in Minimally Invasive Breast Surgery
Peng Wang1, Li Jiang1, Yangjunjian Zhou1
1State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China.
Background:
Minimally invasive breast surgery often suffers from incomplete lesion removal due to poor ultrasound visualisation.
Methods:
Given the difference in hardness between lesions and adipose tissue, this study proposes a method to assess tissue boundaries by measuring cutting force. Based on the Intact Lesion Excision System, a breast biopsy tool capable of tissue grasping and cutting, a cutting force detection algorithm was developed. This algorithm establishes a mechanical relationship among DILES deformation, actuation tension, and actual cutting force, and estimates tissue type by measuring cutting resistance.
Results:
Experimental results show that the tool can detect cutting forces lower than 0.05 N. Force prediction achieved an RMSE of 0.0116 N and an R2 of 0.892. In simulated lesion excision, force-sensing guidance improved the complete resection rate from 40% (visual alone) to 90% (visual plus force feedback).
Conclusions:
This force-sensing approach enhances lesion resection completeness and shows strong potential for clinical application.