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Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations.
Audette, Michel A; Bordas, Stéphane P A; Blatt, Jason E.
Afiliación
  • Audette MA; Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, VA, USA.
  • Bordas SPA; Institute of Computational Engineering, University of Luxembourg, Faculty of Sciences Communication and Technology, Esch-Sur-Alzette, Luxembourg.
  • Blatt JE; Department of Neurosurgery, University of Florida, Gainesville, FL, USA.
Robot Surg ; 7: 1-23, 2020.
Article en En | MEDLINE | ID: mdl-32258180
This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue shift estimation through imaging scans acquired during the procedure, and simulation-based prediction. Neurosurgical scenarios tend to emphasize straight needles so far, and span deep-brain stimulation (DBS), stereoelectroencephalography (SEEG), intracerebral drug delivery (IDD), stereotactic brain biopsy (SBB), stereotactic needle aspiration for hematoma, cysts and abscesses, and brachytherapy as well as thermal ablation of brain tumors and seizure-generating regions. We emphasize therapeutic considerations and complications that have been documented in conjunction with these applications.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Robot Surg Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Robot Surg Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos