1
|
Toggweiler S, Wyler von Ballmoos MC, Moccetti F, Douverny A, Wolfrum M, Imamoglu Z, Mohler A, Gülan U, Kim WK. A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement. CARDIOVASCULAR REVASCULARIZATION MEDICINE 2024; 65:25-31. [PMID: 38467531 DOI: 10.1016/j.carrev.2024.03.008] [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: 02/16/2024] [Revised: 02/29/2024] [Accepted: 03/05/2024] [Indexed: 03/13/2024]
Abstract
BACKGROUND Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatment of aortic stenosis. Computed tomography (CT) analysis is essential for pre-procedural planning. Currently available software packages for TAVR planning require substantial human interaction. We describe development and validation of an artificial intelligence (AI) powered software to automatically rend anatomical measurements and other information required for TAVR planning and implantation. METHODS Automated measurements from 100 CTs were compared to measurements from three expert clinicians and TAVR operators using commercially available software packages. Correlation coefficients and mean differences were calculated to assess precision and accuracy. RESULTS AI-generated annular measurements had excellent agreements with manual measurements by expert operators yielding correlation coefficients of 0.97 for both perimeter and area. There was no relevant bias with a mean difference of -0.07 mm and - 1.4 mm2 for perimeter and area, respectively. For the ascending aorta measured 5 cm above the annular plane, correlation coefficient was 0.95 and mean difference was 1.4 mm. Instruction for use-based sizing yielded agreement with the effective implant size in 87-88 % of patients for self-expanding valves (perimeter-based sizing) and in 88 % for balloon-expandable valves (area-based sizing). CONCLUSIONS A fully automated software enables accurate and precise anatomical segmentation and measurements required for TAVR planning without human interaction and with high reliability.
Collapse
Affiliation(s)
| | - Moritz C Wyler von Ballmoos
- Department of Cardiovascular & Thoracic Surgery, Texas Health Harris Methodist Hospital, Fort Worth, TX, USA
| | | | | | - Mathias Wolfrum
- Heart Center Lucerne, Luzerner Kantonsspital, Lucerne, Switzerland
| | | | | | | | - Won-Keun Kim
- University of Giessen/Marburg, Department of Cardiology, Giessen, Germany
| |
Collapse
|
2
|
Mao Y, Zhu G, Zhai M, Ma Y, Li L, Jin P, Liu Y, Yang J. Transcatheter Aortic Valve Replacement and Coronary Protection Guided by Deep Learning and 3-Dimensional Printing. Surg Innov 2024; 31:256-262. [PMID: 38565982 DOI: 10.1177/15533506241244571] [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] [Indexed: 04/04/2024]
Abstract
OBJECTIVE In this case report, the auxiliary role of deep learning and 3-dimensional printing technology in the perioperative period was discussed to guide transcatheter aortic valve replacement and coronary stent implantation simultaneously. CASE PRESENTATION A 68-year-old man had shortness of breath and chest tightness, accompanied by paroxysmal nocturnal dyspnea, 2 weeks before presenting at our hospital. Echocardiography results obtained in the outpatient department showed severe aortic stenosis combined with regurgitation and pleural effusion. The patient was first treated with closed thoracic drainage. After 800 mL of pleural effusion was collected, the patient's symptoms were relieved and he was admitted to the hospital. Preoperative transthoracic echocardiography showed severe bicuspid aortic valve stenosis combined with calcification and aortic regurgitation (mean pressure gradient, 42 mmHg). Preoperative computed tomography results showed a type I bicuspid aortic valve with severe eccentric calcification. The leaflet could be seen from the left coronary artery plane, which indicated an extremely high possibility of coronary obstruction. After preoperative imaging assessment, deep learning and 3-dimensional printing technology were used for evaluation and simulation. Guided transcatheter aortic valve replacement and a coronary stent implant were completed successfully. Postoperative digital subtraction angiography showed that the bioprosthesis and the chimney coronary stent were in ideal positions. Transesophageal echocardiography showed normal morphology without paravalvular regurgitation. CONCLUSION The perioperative guidance of deep learning and 3-dimensional printing are of great help for surgical strategy formulation in patients with severe bicuspid aortic valve stenosis with calcification and high-risk coronary obstruction.
Collapse
Affiliation(s)
- Yu Mao
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Guangyu Zhu
- School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Mengen Zhai
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Yanyan Ma
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Lanlan Li
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Ping Jin
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Yang Liu
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Jian Yang
- Department of Cardiovascular Surgery, Xijing Hospital, Air Force Medical University, Xi'an, China
| |
Collapse
|
3
|
Annoni AD, Mancini ME, Carlicchi E, Belmonte M, Formenti A, Mushtaq S, Marchetti F, Cilia F, Baggiano A, Fusini L, Bonomi A, Gennari M, Montorsi P, Pepi M, Pontone G. Pre-TAVI aortic annulus sizing: comparison between manual and semi-automated new generation software measurements in operators with different experience. Br J Radiol 2023; 96:20220733. [PMID: 37449675 PMCID: PMC10461289 DOI: 10.1259/bjr.20220733] [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: 07/27/2022] [Revised: 04/07/2023] [Accepted: 04/28/2023] [Indexed: 07/18/2023] Open
Abstract
OBJECTIVES Aim of the study is to compare manual and semi-automatic measurements for aortic annulus assessment among different operators. METHODS Eighty patients who underwent TAVI were retrospectively enrolled. The measurements manually performed by an experienced reader for aortic annulus (minimum and maximum diameters, perimeter, area), annulus-to-coronary ostia distance and time needed for the whole evaluation, were collected. The same operator (observer 1) and two less experienced readers (observer 2 and 3, with >5 years and 1 year of experience, respectively) assessed the same measurements using a semi-automatic software. Differences between manual and semi-automatic measurements, reading time and suggested valves size derived by CT were compared. RESULTS Very good correlations were found between manual and software-aided measurements for aortic annulus area and perimeter in comparison with standard measurements for the three readers (ICC range 0.81-0.98). Good correlations were found for the distance with coronary ostia(0.75-0.79). The same area-derived prosthesis size for manual and semi-automatic measurements was selected in 96% of cases for observer 1; very good correlations were also found for observer 2 and 3 (ICC = 0.89 and 0.88, respectively). Using semi-automatic measurements, the mean time needed for CT images was significantly lower for observers 1 and 2 (1.50 and 1.72versus 3.14 min), respectively. CONCLUSIONS Pre-TAVI CT using semi-automatic software allows accurate and reproducible measurements, reducing reconstruction time up to 50% and is reliable even for operators with different experience. ADVANCES IN KNOWLEDGE The use of semi-automatic dedicated software for CT in TAVI planning is reliable even for operators without long time experience and allows accurate and reproducible measurements improving pre-TAVI workflow.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Laura Fusini
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - Alice Bonomi
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | | | | | - Mauro Pepi
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | | |
Collapse
|
4
|
Dahle G, Walther T. The 10 Commandments for Transapical TAVI. INNOVATIONS-TECHNOLOGY AND TECHNIQUES IN CARDIOTHORACIC AND VASCULAR SURGERY 2023; 18:223-228. [PMID: 37309902 PMCID: PMC10315863 DOI: 10.1177/15569845231177052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Affiliation(s)
- Gry Dahle
- Department of Cardiothoracic Surgery, Oslo University Hospital, Norway
| | - Thomas Walther
- Klinik für -Herz- und Gefässchirurgie, Universitätsklinikum Frankfurt, Germany
| |
Collapse
|
5
|
Bertsche D, Rottbauer W, Rasche V, Buckert D, Markovic S, Metze P, Gonska B, Luo E, Dahme T, Vernikouskaya I, Schneider LM. Computed tomography angiography/magnetic resonance imaging-based preprocedural planning and guidance in the interventional treatment of structural heart disease. Front Cardiovasc Med 2022; 9:931959. [PMID: 36324746 PMCID: PMC9620519 DOI: 10.3389/fcvm.2022.931959] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 09/28/2022] [Indexed: 11/18/2022] Open
Abstract
Preprocedural planning and periprocedural guidance based on image fusion are widely established techniques supporting the interventional treatment of structural heart disease. However, these two techniques are typically used independently. Previous works have already demonstrated the benefits of integrating planning details into image fusion but are limited to a few applications and the availability of the proprietary tools used. We propose a vendor-independent approach to integrate planning details into periprocedural image fusion facilitating guidance during interventional treatment. In this work, we demonstrate the feasibility of integrating planning details derived from computer tomography and magnetic resonance imaging into periprocedural image fusion with open-source and commercially established tools. The integration of preprocedural planning details into periprocedural image fusion has the potential to support safe and efficient interventional treatment of structural heart disease.
Collapse
|
6
|
Ruyra X, Permanyer E, Huguet M, Maldonado G. Use of virtual reality for procedural planning of transcatheter aortic valve replacement. Interact Cardiovasc Thorac Surg 2022; 35:6751790. [PMID: 36205608 PMCID: PMC9639804 DOI: 10.1093/icvts/ivac248] [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: 10/27/2021] [Revised: 09/22/2022] [Accepted: 10/04/2022] [Indexed: 12/03/2022] Open
Abstract
This study sought to evaluate the impact of virtual reality (VR) tools in procedural planning of transcatheter aortic valve replacement. A prospective study involving 11 patients referred for transcatheter aortic valve replacement was conducted. A multidetector computed tomography was used to acquire and segment the anatomy of the access route and landing zone. From the information obtained with the multidetector computed tomography in DICOM format, we built a virtual platform (VisuaMed, Techer Team, Valencia, Spain) that contains all the clinical information of the patients and a virtualized model of their anatomy. Wearing VR devices, the professional was able to 'walk inside' the anatomy in an interactive and immersive way. Decisions after the evaluation of routine clinical images were compared with those after experience with VR models and intraprocedural findings.
Collapse
Affiliation(s)
- Xavier Ruyra
- Cardiac Surgery Department, Quironsalud Teknon Heart Institute, Barcelona, Spain
| | - Eduard Permanyer
- Corresponding author. Cardiac Surgery Department, Quironsalud Teknon Heart Institute, Carrer Vilana 12, 08022 Barcelona, Spain. Tel: +34-93-2906251; e-mail: (E. Permanyer)
| | - Marina Huguet
- Department of Diagnostic Imaging, Quironsalud Teknon Heart Institute, Barcelona, Spain
| | - Giuliana Maldonado
- Cardiology Department, Quironsalud Teknon Heart Institute, Barcelona, Spain,Cardiology Department, Quironsalud Hospital General de Catalunya, Sant Cugat, Spain
| |
Collapse
|
7
|
Steblovnik K, Bunc M. Technical Aspects and Development of Transcatheter Aortic Valve Implantation. J Cardiovasc Dev Dis 2022; 9:282. [PMID: 36005446 PMCID: PMC9409777 DOI: 10.3390/jcdd9080282] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/12/2022] [Accepted: 08/18/2022] [Indexed: 11/16/2022] Open
Abstract
Aortic stenosis is the most common valve disease requiring surgery or percutaneous treatment. Since the first-in-man implantation in 2002 we have witnessed incredible progress in transcatheter aortic valve implantation (TAVI). In this article, we review the technical aspects of TAVI development with a look at the future. Durability, low thrombogenicity, good hydrodynamics, biocompatibility, low catheter profile, and deployment stability are the attributes of an ideal TAVI device. Two main design types exist-balloon-expandable and self-expanding prostheses. Balloon-expandable prostheses use a cobalt-chromium alloy frame providing high radial strength and radiopacity, while the self-expanding prostheses use a nickel-titanium (Nitinol) alloy frame, which expands to its original shape once unsheathed and heated to the body temperature. The valve is sewn onto the frame and consists of the porcine or bovine pericardium, which is specially treated to prevent calcinations and prolong durability. The lower part of the frame can be covered by polyethylene terephthalate fabric or a pericardial skirt, providing better sealing between the frame and aortic annulus. The main future challenges lie in achieving lower rates of paravalvular leaks and new pacemaker implantations following the procedure, lower delivery system profiles, more precise positioning, longer durability, and a good hemodynamic profile. Patient-specific design and the use of autologous tissue might solve these issues.
Collapse
Affiliation(s)
| | - Matjaz Bunc
- Department of Cardiology, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia
| |
Collapse
|
8
|
VAN Kampen A, Kofler M, Meyer A, Gerber M, Sündermann SH, VAN Praet KM, Akansel S, Hommel M, Falk V, Kempfert J. Aortic valve replacement via right anterolateral minithoracotomy: preventing adverse events during the initial learning curve. THE JOURNAL OF CARDIOVASCULAR SURGERY 2022; 63:85-90. [PMID: 34825793 DOI: 10.23736/s0021-9509.21.11981-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Despite excellent outcomes and reduced invasiveness, the right anterolateral thoracotomy approach for aortic valve replacement (RALT-AVR) has not been broadly adopted. This study provides results regarding the initial experience and learning curve of a single surgeon performing this procedure. METHODS Periprocedural details and postoperative outcomes of the first 100 consecutive patients who underwent RALT-AVR at our institution were retrospectively analyzed. We conducted a cumulative sum analysis of surgical failure, defined as occurrence of 30-day-mortality, surgical revision for bleeding, conversion to sternotomy, 3rd degree heart block, paravalvular leakage, postoperative stroke or mean transvalvular gradient >20 mmHg. RESULTS The cohort was of low surgical risk (mean EuroSCORE II 1.31%±0.85, mean STS PROM 1.45%±0.97), 58% were males. Median cross-clamp time was 67.5 (57.8-76) min, median CPB time 105 (91.8-119) min, and median operation time 164.5 (144.5-183.2) min. There were no conversions to full sternotomy, 4 cases of revision for bleeding and 2 pacemaker implantations for 3rd degree heart block. Prosthesis function was good (median ΔPmean 10.9 [7.4-13.6] mmHg). Thirty-day-mortality was 0%. The log-likelihood graph never crossed the upper boundary, and after a steady decrease, crossed the lower boundary at 93 patients. CONCLUSIONS RALT-AVR can be performed with acceptable procedural times and satisfactory outcomes. For a well-trained surgeon, adapting to this new procedure does not expose patients to an increased risk, when patient selection and procedural planning are applied appropriately. Cumulative sum failure analysis is an appropriate tool to monitor the transition from standard AVR to the technically more demanding RALT-AVR.
Collapse
Affiliation(s)
- Antonia VAN Kampen
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany -
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany -
- University Clinic of Cardiac Surgery, Leipzig Heart Center, Leipzig, Germany -
| | - Markus Kofler
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Alexander Meyer
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Maria Gerber
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Simon H Sündermann
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Department of Cardiovascular Surgery, Charité University Hospital, Berlin, Germany
| | - Karel M VAN Praet
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Serdar Akansel
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Matthias Hommel
- Department of Anesthesiology, German Heart Center Berlin, Berlin, Germany
| | - Volkmar Falk
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Department of Cardiovascular Surgery, Charité University Hospital, Berlin, Germany
- Department of Health Sciences and Technology, Translational Cardiovascular Technologies, Institute of Translational Medicine, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Jörg Kempfert
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Department of Cardiovascular Surgery, Charité University Hospital, Berlin, Germany
| |
Collapse
|
9
|
Krüger N, Meyer A, Tautz L, Hüllebrand M, Wamala I, Pullig M, Kofler M, Kempfert J, Sündermann S, Falk V, Hennemuth A. Cascaded neural network-based CT image processing for aortic root analysis. Int J Comput Assist Radiol Surg 2022; 17:507-519. [PMID: 35066774 PMCID: PMC8873075 DOI: 10.1007/s11548-021-02554-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 12/22/2021] [Indexed: 01/03/2023]
Abstract
Purpose Careful assessment of the aortic root is paramount to select an appropriate prosthesis for transcatheter aortic valve implantation (TAVI). Relevant information about the aortic root anatomy, such as the aortic annulus diameter, can be extracted from pre-interventional CT. In this work, we investigate a neural network-based approach for segmenting the aortic root as a basis for obtaining these parameters. Methods To support valve prosthesis selection, geometric measures of the aortic root are extracted from the patient’s CT scan using a cascade of convolutional neural networks (CNNs). First, the image is reduced to the aortic root, valve, and left ventricular outflow tract (LVOT); within that subimage, the aortic valve and ascending aorta are segmented; and finally, the region around the aortic annulus. From the segmented annulus region, we infer the annulus orientation using principal component analysis (PCA). The area-derived diameter of the annulus is approximated based on the segmentation of the aortic root and LVOT and the plane orientation resulting from the PCA. Results The cascade of CNNs was trained using 90 expert-annotated contrast-enhanced CT scans routinely acquired for TAVI planning. Segmentation of the aorta and valve within the region of interest achieved an F1 score of 0.94 on the test set of 36 patients. The area-derived diameter within the annulus region was determined with a mean error below 2 mm between the automatic measurement and the diameter derived from annotations. The calculated diameters and resulting errors are comparable to published results of alternative approaches. Conclusions The cascaded neural network approach enabled the assessment of the aortic root with a relatively small training set. The processing time amounts to 30 s per patient, facilitating time-efficient, reproducible measurements. An extended training data set, including different levels of calcification or special cases (e.g., pre-implanted valves), could further improve this method’s applicability and robustness.
Collapse
Affiliation(s)
- Nina Krüger
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
- German Heart Center Berlin, Berlin, Germany.
| | - Alexander Meyer
- German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | | | - Markus Hüllebrand
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Fraunhofer MEVIS, Bremen, Germany
| | - Isaac Wamala
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Heart Center Berlin, Berlin, Germany
| | - Marius Pullig
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Markus Kofler
- German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Jörg Kempfert
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Simon Sündermann
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Volkmar Falk
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Department of Health Science and Technology, Swiss Federal Institute of Technology, Zurich, Switzerland
- Darmstadt University of Applied Sciences, Darmstadt, Germany
| | - Anja Hennemuth
- Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Heart Center Berlin, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Fraunhofer MEVIS, Bremen, Germany
| |
Collapse
|
10
|
Van Praet KM, Kempfert J, Jacobs S, Stamm C, Akansel S, Kofler M, Sündermann SH, Nazari Shafti TZ, Jakobs K, Holzendorf S, Unbehaun A, Falk V. Mitral valve surgery: current status and future prospects of the minimally invasive approach. Expert Rev Med Devices 2021; 18:245-260. [PMID: 33624569 DOI: 10.1080/17434440.2021.1894925] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Introduction: During the past five years the approach to procedural planning, operative techniques and perfusion strategies for minimally invasive mitral valve surgery (MIMVS) has evolved. With the goal to provide a maximum of patient safety the procedure has been modified according to individual patient characteristics and is largely based on preoperative imaging.Areas covered: In this review article we describe the important factors in image based therapy planning and simulation, different access strategies, the operative key-steps, a rationale use of devices, and highlight a few future developments in the field of MIMVS. Published studies were identified through pearl growing, citation chasing, a search of PubMed using the systematic review methods filter, and the authors' topic knowledge.Expert opinion: With the help of expert teams including surgeons specialized in mitral repair, anesthesiologists and perfusionists a broad spectrum of mitral valve pathologies and related pathologies can be treated with excellent functional outcomes. Avoiding procedure related complications is the key for success for any MIMVS program.
Collapse
Affiliation(s)
- Karel M Van Praet
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Jörg Kempfert
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Stephan Jacobs
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Christof Stamm
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Serdar Akansel
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Markus Kofler
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany
| | - Simon H Sündermann
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany.,Department of Cardiothoracic Surgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Timo Z Nazari Shafti
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany.,Berlin Institute of Health (BIH), Berlin, Germany
| | - Katharina Jakobs
- Institute for Anesthesiology, German Heart Center Berlin, Berlin, Germany
| | - Stefan Holzendorf
- Department of Perfusion, German Heart Center Berlin, Berlin, Germany
| | - Axel Unbehaun
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Volkmar Falk
- Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany.,Department of Cardiothoracic Surgery, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Institute of Health (BIH), Berlin, Germany.,Department of Health Sciences, ETH Zürich, Translational Cardiovascular Technologies, Switzerland
| |
Collapse
|