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Rosalia L, Ozturk C, Goswami D, Bonnemain J, Wang SX, Bonner B, Weaver JC, Puri R, Kapadia S, Nguyen CT, Roche ET. Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling. Sci Robot 2023; 8:eade2184. [PMID: 36812335 PMCID: PMC10280738 DOI: 10.1126/scirobotics.ade2184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 01/30/2023] [Indexed: 02/24/2023]
Abstract
Aortic stenosis (AS) affects about 1.5 million people in the United States and is associated with a 5-year survival rate of 20% if untreated. In these patients, aortic valve replacement is performed to restore adequate hemodynamics and alleviate symptoms. The development of next-generation prosthetic aortic valves seeks to provide enhanced hemodynamic performance, durability, and long-term safety, emphasizing the need for high-fidelity testing platforms for these devices. We propose a soft robotic model that recapitulates patient-specific hemodynamics of AS and secondary ventricular remodeling which we validated against clinical data. The model leverages 3D-printed replicas of each patient's cardiac anatomy and patient-specific soft robotic sleeves to recreate the patients' hemodynamics. An aortic sleeve allows mimicry of AS lesions due to degenerative or congenital disease, whereas a left ventricular sleeve recapitulates loss of ventricular compliance and diastolic dysfunction (DD) associated with AS. Through a combination of echocardiographic and catheterization techniques, this system is shown to recreate clinical metrics of AS with greater controllability compared with methods based on image-guided aortic root reconstruction and parameters of cardiac function that rigid systems fail to mimic physiologically. Last, we leverage this model to evaluate the hemodynamic benefit of transcatheter aortic valves in a subset of patients with diverse anatomies, etiologies, and disease states. Through the development of a high-fidelity model of AS and DD, this work demonstrates the use of soft robotics to recreate cardiovascular disease, with potential applications in device development, procedural planning, and outcome prediction in industrial and clinical settings.
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Affiliation(s)
- Luca Rosalia
- Health Sciences and Technology Program, Harvard–Massachusetts Institute of Technology, Cambridge, MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, USA
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Caglar Ozturk
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Debkalpa Goswami
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Health Sciences and Technology, ETH-Zürich, Zürich, Switzerland
- Institute of Robotics and Intelligent Systems, ETH-Zürich, Zürich, Switzerland
| | - Jean Bonnemain
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Adult Intensive Care Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sophie X. Wang
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Benjamin Bonner
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, USA
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - James C. Weaver
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
| | - Rishi Puri
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Samir Kapadia
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Christopher T. Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, USA
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
- Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ellen T. Roche
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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6
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Rosalia L, Ozturk C, Coll-Font J, Fan Y, Nagata Y, Singh M, Goswami D, Mauskapf A, Chen S, Eder RA, Goffer EM, Kim JH, Yurista S, Bonner BP, Foster AN, Levine RA, Edelman ER, Panagia M, Guerrero JL, Roche ET, Nguyen CT. A soft robotic sleeve mimicking the haemodynamics and biomechanics of left ventricular pressure overload and aortic stenosis. Nat Biomed Eng 2022; 6:1134-1147. [PMID: 36163494 PMCID: PMC9588718 DOI: 10.1038/s41551-022-00937-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 08/12/2022] [Indexed: 12/14/2022]
Abstract
Preclinical models of aortic stenosis can induce left ventricular pressure overload and coarsely control the severity of aortic constriction. However, they do not recapitulate the haemodynamics and flow patterns associated with the disease. Here we report the development of a customizable soft robotic aortic sleeve that can mimic the haemodynamics and biomechanics of aortic stenosis. By allowing for the adjustment of actuation patterns and blood-flow dynamics, the robotic sleeve recapitulates clinically relevant haemodynamics in a porcine model of aortic stenosis, as we show via in vivo echocardiography and catheterization studies, and a combination of in vitro and computational analyses. Using in vivo and in vitro magnetic resonance imaging, we also quantified the four-dimensional blood-flow velocity profiles associated with the disease and with bicommissural and unicommissural defects re-created by the robotic sleeve. The design of the sleeve, which can be adjusted on the basis of computed tomography data, allows for the design of patient-specific devices that may guide clinical decisions and improve the management and treatment of patients with aortic stenosis.
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Affiliation(s)
- Luca Rosalia
- Health Sciences and Technology Program, Harvard - Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA,Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA,Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Caglar Ozturk
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA
| | - Jaume Coll-Font
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Yiling Fan
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA,Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA,Department of Mechanical Engineering, Massachusetts Institute of Technology, 33 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Yasufumi Nagata
- Cardiac Ultrasound Laboratory, Massachusetts General Hospital, 55 Fruit Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Manisha Singh
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA
| | - Debkalpa Goswami
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA
| | - Adam Mauskapf
- Corrigan Minehan Heart Center, Massachusetts General Hospital, Boston, 55 Fruit Boston, MA 02114, USA
| | - Shi Chen
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Robert A. Eder
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Efrat M. Goffer
- Health Sciences and Technology Program, Harvard - Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA,Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA
| | - Jo H. Kim
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Salva Yurista
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Benjamin P. Bonner
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Anna N. Foster
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA
| | - Robert A. Levine
- Cardiac Ultrasound Laboratory, Massachusetts General Hospital, 55 Fruit Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Elazer R. Edelman
- Health Sciences and Technology Program, Harvard - Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA,Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA,Brigham and Women’s Hospital, Cardiovascular Division, 75 Francis Street, Boston, MA 02115, USA
| | - Marcello Panagia
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,Cardiovascular Medicine Section, Department of Medicine, Boston University Medical Center, 715 Albany Street, Boston, MA 02118, USA
| | - Jose L. Guerrero
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Ellen T. Roche
- Health Sciences and Technology Program, Harvard - Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA,Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA 02139, USA,Department of Mechanical Engineering, Massachusetts Institute of Technology, 33 Massachusetts Avenue, Cambridge, MA 02139, USA,Correspondence and requests for materials should be addressed to ;
| | - Christopher T. Nguyen
- Health Sciences and Technology Program, Harvard - Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA,Cardiovascular Research Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street Charlestown, MA 02129, USA,Department of Medicine, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA,Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA,Correspondence and requests for materials should be addressed to ;
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