Autonomous System for Tumor Resection (ASTR) - Dual-Arm Robotic Midline Partial Glossectomy

Head and neck cancers are the seventh most common cancers worldwide, with squamous cell carcinoma being the most prevalent histologic subtype. Surgical resection is a primary treatment modality for many patients with head and neck squamous cell carcinoma, and accurately identifying tumor boundaries...

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Vydáno v:IEEE robotics and automation letters Ročník 9; číslo 2; s. 1166 - 1173
Hlavní autoři: Ge, Jiawei, Kam, Michael, Opfermann, Justin D., Saeidi, Hamed, Leonard, Simon, Mady, Leila J., Schnermann, Martin J., Krieger, Axel
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.02.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Biomedical measurement
Cancer
Color
control architectures and programming
Control equipment
Feasibility studies
Fluorescence
Grasping
Inks
Instruments
Medical robotics
Medical robots and systems
Robot control
Robot programming
Software architecture
software architecture for robotic and automation
Surgery
Tongue
Tumors
Vision systems
Workflow
Medical robots and systems
software architecture for robotic and automation
control architectures and programming
ISSN:2377-3766, 2377-3766
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Shrnutí:Head and neck cancers are the seventh most common cancers worldwide, with squamous cell carcinoma being the most prevalent histologic subtype. Surgical resection is a primary treatment modality for many patients with head and neck squamous cell carcinoma, and accurately identifying tumor boundaries and ensuring sufficient resection margins are critical for optimizing oncologic outcomes. This letter presents an innovative autonomous system for tumor resection (ASTR) and conducts a feasibility study by performing supervised autonomous midline partial glossectomy for pseudotumor with millimeter accuracy. The proposed ASTR system consists of a dual-camera vision system, an electrosurgical instrument, a newly developed vacuum grasping instrument, two 6-DOF manipulators, and a novel autonomous control system. The letter introduces an ontology-based research framework for creating and implementing a complex autonomous surgical workflow, using the glossectomy as a case study. Porcine tongue tissues are used in this study, and marked using color inks and near-infrared fluorescent (NIRF) markers to indicate the pseudotumor. ASTR actively monitors the NIRF markers and gathers spatial and color data from the samples, enabling planning and execution of robot trajectories in accordance with the proposed glossectomy workflow. The system successfully performs six consecutive supervised autonomous pseudotumor resections on porcine specimens. The average surface and depth resection errors measure <inline-formula><tex-math notation="LaTeX">0.73\pm 0.60</tex-math></inline-formula> <inline-formula><tex-math notation="LaTeX">\text{mm}</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">1.89\pm 0.54</tex-math></inline-formula> <inline-formula><tex-math notation="LaTeX">\text{mm}</tex-math></inline-formula>, respectively, with no positive tumor margins detected in any of the six resections. The resection accuracy is demonstrated to be on par with manual pseudotumor glossectomy performed by an experienced otolaryngologist.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2023.3341773