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Liu X, Wang L, Xiang Y, Liao F, Li N, Li J, Wang J, Wu Q, Zhou C, Yang Y, Kou Y, Yang Y, Tang H, Zhou N, Wan C, Yin Z, Yang GZ, Tao G, Zang J. Magnetic soft microfiberbots for robotic embolization. Sci Robot 2024; 9:eadh2479. [PMID: 38381840 DOI: 10.1126/scirobotics.adh2479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 01/24/2024] [Indexed: 02/23/2024]
Abstract
Cerebral aneurysms and brain tumors are leading life-threatening diseases worldwide. By deliberately occluding the target lesion to reduce the blood supply, embolization has been widely used clinically to treat cerebral aneurysms and brain tumors. Conventional embolization is usually performed by threading a catheter through blood vessels to the target lesion, which is often limited by the poor steerability of the catheter in complex neurovascular networks, especially in submillimeter regions. Here, we propose magnetic soft microfiberbots with high steerability, reliable maneuverability, and multimodal shape reconfigurability to perform robotic embolization in submillimeter regions via a remote, untethered, and magnetically controllable manner. Magnetic soft microfiberbots were fabricated by thermal drawing magnetic soft composite into microfibers, followed by magnetizing and molding procedures to endow a helical magnetic polarity. By controlling magnetic fields, magnetic soft microfiberbots exhibit reversible elongated/aggregated shape morphing and helical propulsion in flow conditions, allowing for controllable navigation through complex vasculature and robotic embolization in submillimeter regions. We performed in vitro embolization of aneurysm and tumor in neurovascular phantoms and in vivo embolization of a rabbit femoral artery model under real-time fluoroscopy. These studies demonstrate the potential clinical value of our work, paving the way for a robotic embolization scheme in robotic settings.
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Affiliation(s)
- Xurui Liu
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Liu Wang
- CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Modern Mechanics, University of Science and Technology of China, Hefei 230026, PR China
- State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Science, 15 Beisihuan West Road, Beijing 100190, China
| | - Yuanzhuo Xiang
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Fan Liao
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Na Li
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jiyu Li
- CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Modern Mechanics, University of Science and Technology of China, Hefei 230026, PR China
| | - Jiaxin Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, PR China
| | - Qingyang Wu
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Cheng Zhou
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Youzhou Yang
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yuanshi Kou
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yueying Yang
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hanchuan Tang
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ning Zhou
- Division of Cardiology, Department of Internal Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430074, China
| | - Chidan Wan
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Zhouping Yin
- Flexible Electronics Research Center, State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Guang-Zhong Yang
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Guangming Tao
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- State Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
- Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Institute of Medical Equipment Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jianfeng Zang
- School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
- State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Li N, Fei P, Tous C, Rezaei Adariani M, Hautot ML, Ouedraogo I, Hadjadj A, Dimov IP, Zhang Q, Lessard S, Nosrati Z, Ng CN, Saatchi K, Häfeli UO, Tremblay C, Kadoury S, Tang A, Martel S, Soulez G. Human-scale navigation of magnetic microrobots in hepatic arteries. Sci Robot 2024; 9:eadh8702. [PMID: 38354257 DOI: 10.1126/scirobotics.adh8702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 01/17/2024] [Indexed: 02/16/2024]
Abstract
Using external actuation sources to navigate untethered drug-eluting microrobots in the bloodstream offers great promise in improving the selectivity of drug delivery, especially in oncology, but the current field forces are difficult to maintain with enough strength inside the human body (>70-centimeter-diameter range) to achieve this operation. Here, we present an algorithm to predict the optimal patient position with respect to gravity during endovascular microrobot navigation. Magnetic resonance navigation, using magnetic field gradients in clinical magnetic resonance imaging (MRI), is combined with the algorithm to improve the targeting efficiency of magnetic microrobots (MMRs). Using a dedicated microparticle injector, a high-precision MRI-compatible balloon inflation system, and a clinical MRI, MMRs were successfully steered into targeted lobes via the hepatic arteries of living pigs. The distribution ratio of the microrobots (roughly 2000 MMRs per pig) in the right liver lobe increased from 47.7 to 86.4% and increased in the left lobe from 52.2 to 84.1%. After passing through multiple vascular bifurcations, the number of MMRs reaching four different target liver lobes had a 1.7- to 2.6-fold increase in the navigation groups compared with the control group. Performing simulations on 19 patients with hepatocellular carcinoma (HCC) demonstrated that the proposed technique can meet the need for hepatic embolization in patients with HCC. Our technology offers selectable direction for actuator-based navigation of microrobots at the human scale.
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Affiliation(s)
- Ning Li
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Phillip Fei
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Cyril Tous
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Mahdi Rezaei Adariani
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
- Inria, Palaiseau 91120, France
| | - Marie-Lou Hautot
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Inès Ouedraogo
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Nantes, Nantes 44035, France
| | - Amina Hadjadj
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Ivan P Dimov
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Quan Zhang
- School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
- School of Artificial Intelligence, Shanghai University, Shanghai 200444, China
| | - Simon Lessard
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
| | - Zeynab Nosrati
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Courtney N Ng
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Katayoun Saatchi
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Urs O Häfeli
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Charles Tremblay
- Department of Computer Engineering and Software Engineering, Polytechnique Montréal, Montréal, Québec H3T 1J4, Canada
| | - Samuel Kadoury
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Department of Computer Engineering and Software Engineering, Polytechnique Montréal, Montréal, Québec H3T 1J4, Canada
| | - An Tang
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
- Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec H2X 0C1, Canada
| | - Sylvain Martel
- Department of Computer Engineering and Software Engineering, Polytechnique Montréal, Montréal, Québec H3T 1J4, Canada
- Department of Bioengineering, McGill University, Montréal, Québec H3A 0E9, Canada
| | - Gilles Soulez
- Clinical Laboratory of Image Processing (LCTI), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec H2X 0A9, Canada
- Université de Montréal, Montréal, Québec H3T 1J4, Canada
- Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec H2X 0C1, Canada
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Li N, Tous C, Dimov IP, Fei P, Zhang Q, Lessard S, Tang A, Martel S, Soulez G. Design of a Low-Cost, Self-Adaptive and MRI-Compatible Cardiac Gating System. IEEE Trans Biomed Eng 2023; 70:3126-3136. [PMID: 37276095 DOI: 10.1109/tbme.2023.3280348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
OBJECTIVE Cardiac gating, synchronizing medical scans with cardiac activity, is widely used to make quantitative measurements of physiological events and to obtain high-quality scans free of pulsatile artefacts. This can provide important information for disease diagnosis, targeted control of medical microrobots, etc. The current work proposes a low-cost, self-adaptive, MRI-compatible cardiac gating system. METHOD The system and its processing algorithm, based on the monitoring and analysis of blood pressure waveforms, are proposed. The system is tested in an in vitro experiment and two living pigs using four-dimensional (4D) flow magnetic resonance imaging (MRI) and two-dimensional phase-contrast (2D-PC) sequences. RESULTS in vitro and in vivo experiments reveal that the proposed system can provide stable cardiac synchronicity, has good MRI compatibility, and can cope with the fringe magnetic field of the MRI scanner, radiofrequency signals during image acquisition, and heart rate changes. High-resolution 4D flow imaging is successfully acquired both in vivo and in vitro. The difference between the 2D and 4D measurements is ≤ 21%. The incidence of false triggers is 0% in all tests, which is unattainable for other known cardiac gating methods. CONCLUSION The system has good MRI compatibility and can provide a stable and accurate trigger signal based on pressure waveform. It opens the door to applications where the previous gating methods were difficult to implement or not applicable.
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Li N, Tous C, Dimov IP, Fei P, Zhang Q, Lessard S, Moran G, Jin N, Kadoury S, Tang A, Martel S, Soulez G. Design of a Patient-Specific Respiratory-Motion-Simulating Platform for In Vitro 4D Flow MRI. Ann Biomed Eng 2022; 51:1028-1039. [PMID: 36580223 DOI: 10.1007/s10439-022-03117-6] [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] [Received: 03/23/2022] [Accepted: 12/04/2022] [Indexed: 12/30/2022]
Abstract
Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a leading-edge imaging technique and has numerous medicinal applications. In vitro 4D flow MRI can offer some advantages over in vivo ones, especially in accurately controlling flow rate (gold standard), removing patient and user-specific variations, and minimizing animal testing. Here, a complete testing method and a respiratory-motion-simulating platform are proposed for in vitro validation of 4D flow MRI. A silicon phantom based on the hepatic arteries of a living pig is made. Under the free-breathing, a human volunteer's liver motion (inferior-superior direction) is tracked using a pencil-beam MRI navigator and is extracted and converted into velocity-distance pairs to program the respiratory-motion-simulating platform. With the magnitude displacement of about 1.3 cm, the difference between the motions obtained from the volunteer and our platform is ≤ 1 mm which is within the positioning error of the MRI navigator. The influence of the platform on the MRI signal-to-noise ratio can be eliminated even if the actuator is placed in the MRI room. The 4D flow measurement errors are respectively 0.4% (stationary phantom), 9.4% (gating window = 3 mm), 27.3% (gating window = 4 mm) and 33.1% (gating window = 7 mm). The vessel resolutions decreased with the increase of the gating window. The low-cost simulation system, assembled from commercially available components, is easy to be duplicated.
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Affiliation(s)
- Ning Li
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Cyril Tous
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Ivan P Dimov
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Phillip Fei
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Quan Zhang
- Shanghai University, 266 Jufengyuan Rd, Shanghai, 200444, China
| | - Simon Lessard
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Gerald Moran
- Siemens Canada, 1577 North Service Rd E, Oakville, ON, L6H 0H6, Canada
| | - Ning Jin
- Siemens Medical Solutions Inc., 40 Liberty Boulevard, Malvern, PA, 19355, USA
| | - Samuel Kadoury
- Polytechnique Montréal, 2500 Chemin de Polytechnique, Montreal, QC, H3T 1J4, Canada
| | - An Tang
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
- Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), 1000 Rue Saint-Denis, Montreal, QC, H2X 0C1, Canada
| | - Sylvain Martel
- Polytechnique Montréal, 2500 Chemin de Polytechnique, Montreal, QC, H3T 1J4, Canada
| | - Gilles Soulez
- Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada.
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada.
- Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), 1000 Rue Saint-Denis, Montreal, QC, H2X 0C1, Canada.
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Li N, Tous C, Dimov IP, Cadoret D, Fei P, Majedi Y, Lessard S, Nosrati Z, Saatchi K, Hafeli UO, Tang A, Kadoury S, Martel S, Soulez G. Quantification and 3D localization of magnetically navigated superparamagnetic particles using MRI in phantom and swine chemoembolization models. IEEE Trans Biomed Eng 2022; 69:2616-2627. [PMID: 35167442 DOI: 10.1109/tbme.2022.3151819] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Superparamagnetic nanoparticles (SPIONs) can be combined with tumor chemoembolization agents to form magnetic drug-eluting beads (MDEBs), which are navigated magnetically in the MRI scanner through the vascular system. We aim to develop a method to accurately quantify and localize these particles and to validate the method in phantoms and swine models. METHODS MDEBs were made of Fe3O4 SPIONs. After injected known numbers of MDEBs, susceptibility artifacts in three-dimensional (3D) volumetric interpolated breath-hold examination (VIBE) sequences were acquired in glass and Polyvinyl alcohol (PVA) phantoms, and two living swine. Image processing of VIBE images provided the volume relationship between MDEBs and their artifact at different VIBE acquisitions and post-processing parameters. Simulated hepatic-artery embolization was performed in vivo with an MRI-conditional magnetic-injection system, using the volume relationship to locate and quantify MDEB distribution. RESULTS Individual MDEBs were spatially identified, and their artifacts quantified, showing no correlation with magnetic-field orientation or sequence bandwidth, but exhibiting a relationship with echo time and providing a linear volume relationship. Two MDEB aggregates were magnetically steered into desired liver regions while the other 19 had no steering, and 25 aggregates were injected into another swine without steering. The MDEBs were spatially identified and the volume relationship showed accuracy in assessing the number of the MDEBs, with small errors (8.8%). CONCLUSION AND SIGNIFICANCE MDEBs were able to be steered into desired body regions and then localized using 3D VIBE sequences. The resulting volume relationship was linear, robust, and allowed for quantitative analysis of the MDEB distribution.
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Tous C, Li N, Dimov IP, Kadoury S, Tang A, Häfeli UO, Nosrati Z, Saatchi K, Moran G, Couch MJ, Martel S, Lessard S, Soulez G. Navigation of Microrobots by MRI: Impact of Gravitational, Friction and Thrust Forces on Steering Success. Ann Biomed Eng 2021; 49:3724-3736. [PMID: 34622313 DOI: 10.1007/s10439-021-02865-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 09/07/2021] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Magnetic resonance navigation (MRN) uses MRI gradients to steer magnetic drug-eluting beads (MDEBs) across vascular bifurcations. We aim to experimentally verify our theoretical forces balance model (gravitational, thrust, friction, buoyant and gradient steering forces) to improve the MRN targeted success rate. METHOD A single-bifurcation phantom (3 mm inner diameter) made of poly-vinyl alcohol was connected to a cardiac pump at 0.8 mL/s, 60 beats/minutes with a glycerol solution to reproduce the viscosity of blood. MDEB aggregates (25 ± 6 particles, 200 [Formula: see text]) were released into the main branch through a 5F catheter. The phantom was tilted horizontally from - 10° to +25° to evaluate the MRN performance. RESULTS The gravitational force was equivalent to 71.85 mT/m in a 3T MRI. The gradient duration and amplitude had a power relationship (amplitude=78.717 [Formula: see text]). It was possible, in 15° elevated vascular branches, to steer 87% of injected aggregates if two MRI gradients are simultaneously activated ([Formula: see text] = +26.5 mT/m, [Formula: see text]= +18 mT/m for 57% duty cycle), the flow velocity was minimized to 8 cm/s and a residual pulsatile flow to minimize the force of friction. CONCLUSION Our experimental model can determine the maximum elevation angle MRN can perform in a single-bifurcation phantom simulating in vivo conditions.
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Affiliation(s)
- Cyril Tous
- Centre de recherche du Centre hospitalier de l, Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada.,Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Ning Li
- Centre de recherche du Centre hospitalier de l, Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada.,Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Ivan P Dimov
- Centre de recherche du Centre hospitalier de l, Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada
| | - Samuel Kadoury
- Polytechnique Montréal, 2500 Chemin de Polytechnique, 28, Montreal, QC, H3T 1J4, Canada
| | - An Tang
- Centre de recherche du Centre hospitalier de l, Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada.,Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada
| | - Urs O Häfeli
- University of British Columbia, 2405 Westbrook Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Zeynab Nosrati
- University of British Columbia, 2405 Westbrook Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Katayoun Saatchi
- University of British Columbia, 2405 Westbrook Mall, Vancouver, BC, V6T 1Z3, Canada
| | | | | | - Sylvain Martel
- Polytechnique Montréal, 2500 Chemin de Polytechnique, 28, Montreal, QC, H3T 1J4, Canada
| | - Simon Lessard
- Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada.,École de Technologie Supérieur, 1100 Rue Notre-Dame O, Montreal, QC, H3C 1K3, Canada
| | - Gilles Soulez
- Centre de recherche du Centre hospitalier de l, Université de Montréal (CRCHUM), 900 Rue Saint-Denis, Montreal, QC, H2X 0A9, Canada. .,Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC, H3T 1J4, Canada.
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Future Advances in Diagnosis and Drug Delivery in Interventional Radiology Using MR Imaging-Steered Theranostic Iron Oxide Nanoparticles. J Vasc Interv Radiol 2021; 32:1292-1295.e1. [PMID: 34462079 DOI: 10.1016/j.jvir.2021.05.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 05/11/2021] [Accepted: 05/26/2021] [Indexed: 11/24/2022] Open
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8
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Li N, Jiang Y, Plantefève R, Michaud F, Nosrati Z, Tremblay C, Saatchi K, Häfeli UO, Kadoury S, Moran G, Joly F, Martel S, Soulez G. Magnetic Resonance Navigation for Targeted Embolization in a Two-Level Bifurcation Phantom. Ann Biomed Eng 2019; 47:2402-2415. [PMID: 31290038 DOI: 10.1007/s10439-019-02317-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 06/28/2019] [Indexed: 12/22/2022]
Abstract
This work combines a particle injection system with our proposed magnetic resonance navigation (MRN) sequence with the intention of validating MRN in a two-bifurcation phantom for endovascular treatment of hepatocellular carcinoma (HCC). A theoretical physical model used to calculate the most appropriate size of the magnetic drug-eluting bead (MDEB, 200 μm) aggregates was proposed. The aggregates were injected into the phantom by a dedicated particle injector while a trigger signal was automatically sent to the MRI to start MRN which consists of interleaved tracking and steering sequences. When the main branch of the phantom was parallel to B0, the aggregate distribution ratio in the (left-left, left-right, right-left and right-right divisions was obtained with results of 8, 68, 24 and 0% respectively at baseline (no MRN) and increased to 84%, 100, 84 and 92% (p < 0.001, p = 0.004, p < 0.001, p < 0.001) after implementing our MRN protocol. When the main branch was perpendicular to B0, the right-left branch, having the smallest baseline distribution rate of 0%, reached 80% (p < 0.001) after applying MRN. Moreover, the success rate of MRN was always more than 92% at the 1st bifurcation in the experiments above.
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Affiliation(s)
- Ning Li
- Polytechnique Montréal, Chemin de Polytechnique, 2500 Chemin de Polytechnique, Montréal, QC, 28 H3T 1J4, Canada.,Laboratory of Clinical Image Processing, Le Centre de recherche du CHUM (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
| | - Yuting Jiang
- Laboratory of Clinical Image Processing, Le Centre de recherche du CHUM (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada.,Department of Radiology, Radiation-Oncology and Nuclear Medicine and Institute of Biomedical Engineering, Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montréal, QC, H3T 1J4, Canada
| | - Rosalie Plantefève
- Laboratory of Clinical Image Processing, Le Centre de recherche du CHUM (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
| | - Francois Michaud
- Laboratory of Clinical Image Processing, Le Centre de recherche du CHUM (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada.,Department of Radiology, Radiation-Oncology and Nuclear Medicine and Institute of Biomedical Engineering, Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montréal, QC, H3T 1J4, Canada
| | - Zeynab Nosrati
- University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Charles Tremblay
- Polytechnique Montréal, Chemin de Polytechnique, 2500 Chemin de Polytechnique, Montréal, QC, 28 H3T 1J4, Canada
| | - Katayoun Saatchi
- University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Urs O Häfeli
- University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Samuel Kadoury
- Polytechnique Montréal, Chemin de Polytechnique, 2500 Chemin de Polytechnique, Montréal, QC, 28 H3T 1J4, Canada.,Laboratory of Clinical Image Processing, Le Centre de recherche du CHUM (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada
| | | | - Florian Joly
- INRIA Paris, 2 rue Simone Iff, 75012, Paris, France
| | - Sylvain Martel
- Polytechnique Montréal, Chemin de Polytechnique, 2500 Chemin de Polytechnique, Montréal, QC, 28 H3T 1J4, Canada
| | - Gilles Soulez
- Laboratory of Clinical Image Processing, Le Centre de recherche du CHUM (CRCHUM), 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada. .,Department of Radiology, Radiation-Oncology and Nuclear Medicine and Institute of Biomedical Engineering, Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montréal, QC, H3T 1J4, Canada.
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