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Samant S, Bakhos JJ, Wu W, Zhao S, Kassab GS, Khan B, Panagopoulos A, Makadia J, Oguz UM, Banga A, Fayaz M, Glass W, Chiastra C, Burzotta F, LaDisa JF, Iaizzo P, Murasato Y, Dubini G, Migliavacca F, Mickley T, Bicek A, Fontana J, West NEJ, Mortier P, Boyers PJ, Gold JP, Anderson DR, Tcheng JE, Windle JR, Samady H, Jaffer FA, Desai NR, Lansky A, Mena-Hurtado C, Abbott D, Brilakis ES, Lassen JF, Louvard Y, Stankovic G, Serruys PW, Velazquez E, Elias P, Bhatt DL, Dangas G, Chatzizisis YS. Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions. JACC Cardiovasc Interv 2023; 16:2479-2497. [PMID: 37879802 DOI: 10.1016/j.jcin.2023.07.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 07/11/2023] [Accepted: 07/13/2023] [Indexed: 10/27/2023]
Abstract
Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general.
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Affiliation(s)
- Saurabhi Samant
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Jules Joel Bakhos
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Wei Wu
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Shijia Zhao
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Ghassan S Kassab
- California Medical Innovations Institute, San Diego, California, USA
| | - Behram Khan
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Anastasios Panagopoulos
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Janaki Makadia
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Usama M Oguz
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Akshat Banga
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Muhammad Fayaz
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - William Glass
- Interprofessional Experiential Center for Enduring Learning, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Claudio Chiastra
- PoliTo(BIO)Med Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Francesco Burzotta
- Department of Cardiovascular Sciences, Università Cattolica Del Sacro Cuore, Rome, Italy
| | - John F LaDisa
- Departments of Biomedical Engineering and Pediatrics - Division of Cardiology, Herma Heart Institute, Children's Wisconsin and the Medical College of Wisconsin, and the MARquette Visualization Lab, Marquette University, Milwaukee, Wisconsin, USA
| | - Paul Iaizzo
- Visible Heart Laboratories, Department of Surgery, University of Minnesota, Minnesota, USA
| | - Yoshinobu Murasato
- Department of Cardiology, National Hospital Organization Kyushu Medical Center, Fukuoka, Japan
| | - Gabriele Dubini
- Department of Chemistry, Materials and Chemical Engineering 'Giulio Natta', Politecnico di Milano, Milan, Italy
| | - Francesco Migliavacca
- Department of Chemistry, Materials and Chemical Engineering 'Giulio Natta', Politecnico di Milano, Milan, Italy
| | | | - Andrew Bicek
- Boston Scientific Inc, Marlborough, Massachusetts, USA
| | | | | | | | - Pamela J Boyers
- Interprofessional Experiential Center for Enduring Learning, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Jeffrey P Gold
- Interprofessional Experiential Center for Enduring Learning, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Daniel R Anderson
- Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - James E Tcheng
- Cardiovascular Division, Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - John R Windle
- Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Habib Samady
- Georgia Heart Institute, Gainesville, Georgia, USA
| | - Farouc A Jaffer
- Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Nihar R Desai
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Alexandra Lansky
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Carlos Mena-Hurtado
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Dawn Abbott
- Cardiovascular Institute, Warren Alpert Medical School at Brown University, Providence, Rhode Island, USA
| | - Emmanouil S Brilakis
- Center for Advanced Coronary Interventions, Minneapolis Heart Institute, Minneapolis, Minnesota, USA
| | - Jens Flensted Lassen
- Department of Cardiology B, Odense University Hospital, Odense, Syddanmark, Denmark
| | - Yves Louvard
- Institut Cardiovasculaire Paris Sud, Massy, France
| | - Goran Stankovic
- Department of Cardiology, Clinical Center of Serbia, Belgrade, Serbia
| | - Patrick W Serruys
- Department of Cardiology, National University of Ireland, Galway, Galway, Ireland
| | - Eric Velazquez
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Pierre Elias
- Seymour, Paul, and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, NewYork-Presbyterian Hospital, New York, New York, USA
| | - Deepak L Bhatt
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - George Dangas
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yiannis S Chatzizisis
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA.
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Klug G, Reinstadler S, Troger F, Holzknecht M, Reindl M, Tiller C, Lechner I, Fink P, Pamminger M, Kremser C, Ulmer H, Bauer A, Metzler B, Mayr A. Cardiac magnetic resonance imaging versus computed tomography to guide transcatheter aortic valve replacement: study protocol for a randomized trial (TAVR-CMR). Trials 2022; 23:726. [PMID: 36056444 PMCID: PMC9438296 DOI: 10.1186/s13063-022-06638-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 08/05/2022] [Indexed: 11/10/2022] Open
Abstract
Background The standard procedure for the planning of transcatheter aortic valve replacement (TAVR) is the combination of echocardiography, coronary angiography, and cardiovascular computed tomography (TAVR-CT) for the exact determination of the aortic valve dimensions, valve size, and implantation route. However, up to 80% of the patients undergoing TAVR suffer from chronic renal insufficiency. Alternatives to reduce the need for iodinated contrast agents are desirable. Cardiac magnetic resonance (CMR) imaging recently has emerged as such an alternative. Therefore, we aim to investigate, for the first time, the non-inferiority of TAVR-CMR to TAVR-CT regarding efficacy and safety end-points. Methods This is a prospective, randomized, open-label trial. It is planned to include 250 patients with symptomatic severe aortic stenosis scheduled for TAVR based on a local heart-team decision. Patients will be randomized in a 1:1 fashion to receive a predefined TAVR-CMR protocol or to receive a standard TAVR-CT protocol within 2 weeks after inclusion. Follow-up will be performed at hospital discharge after TAVR and after 1 and 2 years. The primary efficacy outcome is device implantation success at discharge. The secondary endpoints are a combined safety endpoint and a combined clinical efficacy endpoint at baseline and at 1 and 2 years, as well as a comparison of imaging procedure related variables. Endpoint definitions are based on the updated 2012 VARC-2 consensus document. Discussion TAVR-CMR might be an alternative to TAVR-CT for planning a TAVR procedure. If proven to be effective and safe, a broader application of TAVR-CMR might reduce the incidence of acute kidney injury after TAVR and thus improve outcomes. Trial registration The trial is registered at ClinicalTrials.gov (NCT03831087). The results will be disseminated at scientific meetings and publication in peer-reviewed journals.
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Affiliation(s)
- Gert Klug
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
| | - Sebastian Reinstadler
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Felix Troger
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.,University Clinic of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Magdalena Holzknecht
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Martin Reindl
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Christina Tiller
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Ivan Lechner
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Priscilla Fink
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Mathias Pamminger
- University Clinic of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Christian Kremser
- University Clinic of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Hanno Ulmer
- Department for Medical Statistics, Informatics and Health Economy, Medical University of Innsbruck, Innsbruck, Austria
| | - Axel Bauer
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Bernhard Metzler
- University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - Agnes Mayr
- University Clinic of Radiology, Medical University of Innsbruck, Innsbruck, Austria
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Danilov VV, Klyshnikov KY, Gerget OM, Skirnevsky IP, Kutikhin AG, Shilov AA, Ganyukov VI, Ovcharenko EA. Aortography Keypoint Tracking for Transcatheter Aortic Valve Implantation Based on Multi-Task Learning. Front Cardiovasc Med 2021; 8:697737. [PMID: 34350220 PMCID: PMC8326378 DOI: 10.3389/fcvm.2021.697737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/10/2021] [Indexed: 11/15/2022] Open
Abstract
Currently, transcatheter aortic valve implantation (TAVI) represents the most efficient treatment option for patients with aortic stenosis, yet its clinical outcomes largely depend on the accuracy of valve positioning that is frequently complicated when routine imaging modalities are applied. Therefore, existing limitations of perioperative imaging underscore the need for the development of novel visual assistance systems enabling accurate procedures. In this paper, we propose an original multi-task learning-based algorithm for tracking the location of anatomical landmarks and labeling critical keypoints on both aortic valve and delivery system during TAVI. In order to optimize the speed and precision of labeling, we designed nine neural networks and then tested them to predict 11 keypoints of interest. These models were based on a variety of neural network architectures, namely MobileNet V2, ResNet V2, Inception V3, Inception ResNet V2 and EfficientNet B5. During training and validation, ResNet V2 and MobileNet V2 architectures showed the best prediction accuracy/time ratio, predicting keypoint labels and coordinates with 97/96% accuracy and 4.7/5.6% mean absolute error, respectively. Our study provides evidence that neural networks with these architectures are capable to perform real-time predictions of aortic valve and delivery system location, thereby contributing to the proper valve positioning during TAVI.
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Affiliation(s)
- Viacheslav V. Danilov
- Research Laboratory for Processing and Analysis of Big Data, Tomsk Polytechnic University, Tomsk, Russia
| | - Kirill Yu. Klyshnikov
- Department of Experimental Medicine, Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Olga M. Gerget
- Research Laboratory for Processing and Analysis of Big Data, Tomsk Polytechnic University, Tomsk, Russia
| | - Igor P. Skirnevsky
- Research Laboratory for Processing and Analysis of Big Data, Tomsk Polytechnic University, Tomsk, Russia
| | - Anton G. Kutikhin
- Department of Experimental Medicine, Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Aleksandr A. Shilov
- Department of Experimental Medicine, Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Vladimir I. Ganyukov
- Department of Experimental Medicine, Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Evgeny A. Ovcharenko
- Department of Experimental Medicine, Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
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