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Force-Sensing-Integrated Flexible Tool for Precise Lesion Resection in Minimally Invasive Breast Surgery.

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Τίτλος: Force-Sensing-Integrated Flexible Tool for Precise Lesion Resection in Minimally Invasive Breast Surgery.
Συγγραφείς: Wang P; State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China., Jiang L; State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China., Zhou Y; State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China., Shi K; State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China., Liu H; State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China.
Πηγή: The international journal of medical robotics + computer assisted surgery : MRCAS [Int J Med Robot] 2026 Aug; Vol. 22 (4), pp. e70202.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wiley Country of Publication: England NLM ID: 101250764 Publication Model: Print Cited Medium: Internet ISSN: 1478-596X (Electronic) Linking ISSN: 14785951 NLM ISO Abbreviation: Int J Med Robot Subsets: MEDLINE
Imprint Name(s): Publication: 2006- : West Sussex, England : Wiley
Original Publication: Ilkley, UK : Robotic Publications, c2004-
Ιατρικοί όροι (MeSH): Minimally Invasive Surgical Procedures*/methods , Minimally Invasive Surgical Procedures*/instrumentation , Breast Neoplasms*/surgery , Breast*/surgery , Robotic Surgical Procedures*/methods , Robotic Surgical Procedures*/instrumentation, Surgery, Computer-Assisted/methods ; Humans ; Female ; Algorithms ; Equipment Design
Περίληψη: 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.
(© 2026 John Wiley & Sons Ltd.)
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Grant Information: 91948302 Innovative Research Group Project of the National Natural Science Foundation of China; T2388101 Innovative Research Group Project of the National Natural Science Foundation of China
Contributed Indexing: Keywords: flexible mechanism; force sensor; minimally invasive surgery
Entry Date(s): Date Created: 20260709 Date Completed: 20260709 Latest Revision: 20260709
Update Code: 20260709
DOI: 10.1002/rcs.70202
PMID: 42423141
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1478-596X
DOI:10.1002/rcs.70202