Estimation of Contraction Coefficient of Gorlin Equation for Assessment of Aortic Valve Area in Aortic Stenosis

Migliore, Ricardo A.; Adaniya, María E.; Barranco, Miguel Angel Molinero; Miramont, Guillermo; González, Silvia; Tamagusuku, Horacio

doi:10.4236/wjcd.2017.74012

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…3E), leading to overestimated values of flow velocities predicted by the continuity equation (Fig. 3, D and G) (35,36). Conversely, by mimicking the biomechanics of the native heart in both physiology and disease, we overcame these limitations and recreated both pressure and flow in a more clinically relevant manner (Fig.…”

Section: Discussionmentioning

confidence: 99%

Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling

et al. 2023

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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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Section: Discussionmentioning

confidence: 99%

Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling

et al. 2023

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“…3F), leading to overestimated values of flow velocities predicted by the continuity equation (Fig. 3E) (39,40). Conversely, by mimicking the biomechanics of the native heart, we overcome these limitations and recreate both pressure and flow in a more physiological manner (Fig.…”

Section: Discussionmentioning

confidence: 99%

Tunable, soft robotics-enabled patient-specific hydrodynamic model of aortic stenosis and secondary ventricular remodeling

Rosalia

Ozturk

Goswami

et al. 2022

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Aortic stenosis (AS) affects approximately 1.5 million people in the US 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 of high-fidelity testing platforms for these devices. We propose a soft robotic model of AS capable of recapitulating patient-specific hemodynamics of AS and secondary ventricular remodeling, 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, while a left ventricular sleeve recapitulates loss of ventricular compliance, and impaired filling 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 to methods based on image-guided aortic root reconstruction, and parameters of cardiac function which rigid systems fail to mimic physiologically. Finally, we demonstrate the use of this model for the evaluation 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 secondary remodeling, this work pioneers the use of patient-specific soft robotic platforms of cardiovascular disease, with potential application in device development, procedural planning, and outcome prediction in industrial and clinical settings.One Sentence SummaryA high-fidelity, soft robotics-driven model recreates patient-specific biomechanics and hemodynamics of cardiovascular disease.

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Estimation of Contraction Coefficient of Gorlin Equation for Assessment of Aortic Valve Area in Aortic Stenosis

Cited by 2 publications

References 24 publications

Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling

Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling

Tunable, soft robotics-enabled patient-specific hydrodynamic model of aortic stenosis and secondary ventricular remodeling

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