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Gervasoni S, Pedrini N, Rifai T, Fischer C, Landers FC, Mattmann M, Dreyfus R, Viviani S, Veciana A, Masina E, Aktas B, Puigmartí-Luis J, Chautems C, Pané S, Boehler Q, Gruber P, Nelson BJ. A Human-Scale Clinically Ready Electromagnetic Navigation System for Magnetically Responsive Biomaterials and Medical Devices. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2310701. [PMID: 38733269 DOI: 10.1002/adma.202310701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 04/15/2024] [Indexed: 05/13/2024]
Abstract
Magnetic navigation systems are used to precisely manipulate magnetically responsive materials enabling the realization of new minimally invasive procedures using magnetic medical devices. Their widespread applicability has been constrained by high infrastructure demands and costs. The study reports on a portable electromagnetic navigation system, the Navion, which is capable of generating a large magnetic field over a large workspace. The system is easy to install in hospital operating rooms and transportable through health care facilities, aiding in the widespread adoption of magnetically responsive medical devices. First, the design and implementation approach for the system are introduced and its performance is characterized. Next, in vitro navigation of different microrobot structures is demonstrated using magnetic field gradients and rotating magnetic fields. Spherical permanent magnets, electroplated cylindrical microrobots, microparticle swarms, and magnetic composite bacteria-inspired helical structures are investigated. The navigation of magnetic catheters is also demonstrated in two challenging endovascular tasks: 1) an angiography procedure and 2) deep navigation within the circle of Willis. Catheter navigation is demonstrated in a porcine model in vivo to perform an angiography under magnetic guidance.
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Affiliation(s)
- Simone Gervasoni
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Norman Pedrini
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Tarik Rifai
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Cedric Fischer
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Fabian C Landers
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Michael Mattmann
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Roland Dreyfus
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Silvia Viviani
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Andrea Veciana
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Enea Masina
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Buse Aktas
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Josep Puigmartí-Luis
- Departament de Ciència dels Materials i Química Física, Institut de Química Teòrica i Computacional, University of Barcelona (UB), 08028, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Pg. Lluís Companys 23, 08010, Barcelona, Spain
| | | | - Salvador Pané
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Quentin Boehler
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
| | - Philipp Gruber
- Kantonsspital Aarau AG, Tellstrasse 25, CH-5001, Aarau, Switzerland
| | - Bradley J Nelson
- Multi-Scale Robotics Lab, ETH Zurich, CH-8092, Zurich, Switzerland
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Khawaja AM, McNulty J, Thakur UV, Chawla S, Devi S, Liew A, Mirshahi S, Du R, Mekary RA, Gormley W. Transcranial Doppler and computed tomography angiography for detecting cerebral vasospasm post-aneurysmal subarachnoid hemorrhage. Neurosurg Rev 2022; 46:3. [PMID: 36471088 DOI: 10.1007/s10143-022-01913-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/29/2022] [Indexed: 12/12/2022]
Abstract
Cerebral vasospasm is a life-threatening complication following aneurysmal subarachnoid hemorrhage (aSAH). While digital subtraction angiography (DSA) is the current gold standard for detection, the diagnostic performance of computed tomography angiography (CTA) and transcranial Doppler (TCD) remains controversial. We aimed to summarize the available evidence and provide recommendations for their use based on GRADE criteria. A literature search was conducted for studies comparing CTA or TCD to DSA for adults ≥ 18 years with aSAH for radiographic vasospasm detection. The DerSimonian-Laird random-effects model was used to pool sensitivity and specificity and their 95% confidence intervals (CI) and derive positive and negative pooled likelihood ratios (LR + /LR -). Out of 2070 studies, seven studies (1646 arterial segments) met inclusion criteria and were meta-analyzed. Compared to the gold standard (DSA), CTA had a pooled sensitivity of 82% (95%CI, 68-91%) and a specificity of 97% (95%CI, 93-98%), while TCD had lower sensitivity 38% (95%CI, 19-62%) and specificity of 91% (95%CI, 87-94%). Only the LR + for CTA (27.3) reached clinical significance to rule in diagnosis. LR - for CTA (0.19) and TCD (0.68) approached clinical significance (< 0.1) to rule out diagnosis. CTA showed higher LR + and lower LR - than TCD for diagnosing radiographic vasospasm, thereby achieving a strong recommendation for its use in ruling in or out vasospasm, based on the high quality of evidence. TCDs had very low LR + and a reasonably low LR - , thereby achieving a weak recommendation against its use in ruling in vasospasm and weak recommendation for its use in ruling out vasospasm.
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Affiliation(s)
- Ayaz M Khawaja
- Department of Neurology, Wayne State University, Detroit, MI, 48201, USA
| | - Jack McNulty
- Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Harvard Medical School, Brigham and Women's Hospital, 179 Longwood Avenue, MA, 02115, Boston, USA
| | | | - Shreya Chawla
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Harvard Medical School, Brigham and Women's Hospital, 179 Longwood Avenue, MA, 02115, Boston, USA
- Faculty of Life Science and Medicine, King's College London, London, UK
| | - Sharmila Devi
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Harvard Medical School, Brigham and Women's Hospital, 179 Longwood Avenue, MA, 02115, Boston, USA
- Faculty of Life Science and Medicine, King's College London, London, UK
| | - Aaron Liew
- Portiuncula University Hospital and National University of Ireland Galway (NUIG), Galway, Ireland
| | - Shervin Mirshahi
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Rose Du
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Rania A Mekary
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Harvard Medical School, Brigham and Women's Hospital, 179 Longwood Avenue, MA, 02115, Boston, USA.
- School of Pharmacy, MCPHS University, Boston, MA, USA.
| | - William Gormley
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Harvard Medical School, Brigham and Women's Hospital, 179 Longwood Avenue, MA, 02115, Boston, USA
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, 02115, USA
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