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Gomes B, Singh A, O'Sullivan JW, Schnurr TM, Goddard PC, Loong S, Amar D, Hughes JW, Kostur M, Haddad F, Salerno M, Foo R, Montgomery SB, Parikh VN, Meder B, Ashley EA. Genetic architecture of cardiac dynamic flow volumes. Nat Genet 2024; 56:245-257. [PMID: 38082205 DOI: 10.1038/s41588-023-01587-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 10/23/2023] [Indexed: 02/04/2024]
Abstract
Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.
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Affiliation(s)
- Bruna Gomes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Aditya Singh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Jack W O'Sullivan
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Theresia M Schnurr
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Pagé C Goddard
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Shaun Loong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - David Amar
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - J Weston Hughes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Mykhailo Kostur
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Francois Haddad
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Michael Salerno
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Roger Foo
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Stephen B Montgomery
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Victoria N Parikh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Benjamin Meder
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Euan A Ashley
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA.
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Polacin M, Geiger J, Burkhardt B, Callaghan FM, Valsangiacomo E, Kellenberger C. Quantitative evaluation of aortic valve regurgitation in 4D flow cardiac magnetic resonance: at which level should we measure? BMC Med Imaging 2022; 22:169. [PMID: 36167535 PMCID: PMC9513957 DOI: 10.1186/s12880-022-00895-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 09/08/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To find the best level to measure aortic flow for quantification of aortic regurgitation (AR) in 4D flow CMR. METHODS In 27 congenital heart disease patients with AR (67% male, 31 ± 16 years) two blinded observers measured antegrade, retrograde, net aortic flow volumes and regurgitant fractions at 6 levels in 4D flow: (1) below the aortic valve (AV), (2) at the AV, (3) at the aortic sinus, (4) at the sinotubular junction, (5) at the level of the pulmonary arteries (PA) and (6) below the brachiocephalic trunk. 2D phase contrast (2DPC) sequences were acquired at the level of PA. All patients received prior transthoracic echocardiography (TTE) with AR severity grading according to a recommended multiparametric approach. RESULTS After assigning 2DPC measurements into AR grading, agreement between TTE AR grading and 2DPC was good (κ = 0.88). In 4D flow, antegrade flow was similar between the six levels (p = 0.87). Net flow was higher at level 1-2 than at levels 3-6 (p < 0.05). Retrograde flow and regurgitant fraction at level 1-2 were lower compared to levels 3-6 (p < 0.05). Reproducibility (inter-reader agreement: ICC 0.993, 95% CI 0.986-0.99; intra-reader agreement: ICC 0.982, 95%CI 0.943-0.994) as well as measurement agreement between 4D flow and 2DPC (ICC 0.994; 95%CI 0.989 - 0.998) was best at the level of PA. CONCLUSION For estimating severity of AR in 4D flow, best reproducibility along with best agreement with 2DPC measurements can be expected at the level of PA. Measurements at AV or below AV might underestimate AR.
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Affiliation(s)
- Malgorzata Polacin
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland. .,Department of Diagnostic Imaging, University Children`s Hospital, University of Zurich, Zurich, Switzerland.
| | - Julia Geiger
- Department of Diagnostic Imaging, University Children`s Hospital, University of Zurich, Zurich, Switzerland
| | - Barbara Burkhardt
- Division of Pediatric Cardiology, Pediatric Heart Center, University Children`s Hospital, University of Zurich, Zurich, Switzerland
| | - Fraser M Callaghan
- Center for MR Research, University Children's Hospital, University of Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital, University of Zurich, Zurich, Switzerland
| | - Emanuela Valsangiacomo
- Division of Pediatric Cardiology, Pediatric Heart Center, University Children`s Hospital, University of Zurich, Zurich, Switzerland
| | - Christian Kellenberger
- Department of Diagnostic Imaging, University Children`s Hospital, University of Zurich, Zurich, Switzerland
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Nardi F, Pino PG, De Luca L, Riccio C, Cipriani M, Corda M, Francese GM, Gabrielli D, Oliva F, Gulizia MM, Colivicchi F. ANMCO position paper: 2022 focused update of appropriate use criteria for multimodality imaging: aortic valve disease. Eur Heart J Suppl 2022; 24:C289-C297. [PMID: 35602253 PMCID: PMC9117909 DOI: 10.1093/eurheartj/suac027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
This document addresses the evaluation of the Appropriate Use Criteria (AUC) of multimodality imaging in the diagnosis and management of aortic valve disease. The goal of this AUC document is to provide a comprehensive resource for multimodality imaging in the context of aortic valve disease, encompassing multiple imaging modalities. Clinical scenarios are developed in a simple way to illustrate patient presentations encountered in everyday practice.
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Affiliation(s)
- Federico Nardi
- Cardiology Department, Ospedale Santo Spirito, Via Giolitti 2, Casale Monferrato 15033, AL, Italy
| | - Paolo Giuseppe Pino
- Consultant Cardiologist of the Echo-Lab, Ospedale Santo Spirito, Casale Monferrato, AL, Italy
| | - Leonardo De Luca
- Department of Cardio-Thoraco-Vascular, Azienda Ospedaliera San Camillo Forlanini, Roma, Italy
| | - Carmine Riccio
- Cardio-Vascular Department, AORN Sant'Anna and San Sebastiano, Caserta, Italy
| | - Manlio Cipriani
- Cardiology 2-Heart Failure and Transplants, Dipartimento Cardiotoracovascolare “A. De Gasperis”, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Marco Corda
- Cardiology Department, Azienda Ospedaliera G. Brotzu, Cagliari, Italy
| | - Giuseppina Maura Francese
- Cardiology Department, Ospedale Garibaldi-Nesima—Azienda Rilievo Nazionale e Alta Specializzazione “Garibaldi”, Catania, Italy
| | - Domenico Gabrielli
- Department of Cardio-Thoraco-Vascular, Azienda Ospedaliera San Camillo Forlanini, Roma, Italy
| | - Fabrizio Oliva
- Unit of Intensive Cardiological Care, Cardiology 1-Hemodynamics, Cardiothoracovascular Department “A. De Gasperis”, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Michele Massimo Gulizia
- Cardiology Department, Ospedale Garibaldi-Nesima—Azienda Rilievo Nazionale e Alta Specializzazione “Garibaldi”, Catania, Italy
- Fondazione per il Tuo cuore—Heart Care Foundation, Firenze, Italy
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Evangelista Masip A, Galian-Gay L, Guala A, Lopez-Sainz A, Teixido-Turà G, Ruiz Muñoz A, Valente F, Gutierrez L, Fernandez-Galera R, Casas G, Panaro A, Marigliano A, Huguet M, González-Alujas T, Rodriguez-Palomares J. Unraveling Bicuspid Aortic Valve Enigmas by Multimodality Imaging: Clinical Implications. J Clin Med 2022; 11:456. [PMID: 35054153 PMCID: PMC8778671 DOI: 10.3390/jcm11020456] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 01/09/2022] [Accepted: 01/13/2022] [Indexed: 12/13/2022] Open
Abstract
Multimodality imaging is the basis of the diagnosis, follow-up, and surgical management of bicuspid aortic valve (BAV) patients. Transthoracic echocardiography (TTE) is used in our clinical routine practice as a first line imaging for BAV diagnosis, valvular phenotyping and function, measurement of thoracic aorta, exclusion of other aortic malformations, and for the assessment of complications such are infective endocarditis and aortic. Nevertheless, TTE is less useful if we want to assess accurately other aortic segments such as mid-distal ascending aorta, where computed tomography (CT) and magnetic resonance (CMR) could improve the precision of aorta size measurement by multiplanar reconstructions. A major advantage of CT is its superior spatial resolution, which affords a better definition of valve morphology and calcification, accuracy, and reproducibility of ascending aorta size, and allows for coronary artery assessment. Moreover, CMR offers the opportunity of being able to evaluate aortic functional properties and blood flow patterns. In this setting, new developed sequences such as 4D-flow may provide new parameters to predict events during follow up. The integration of all multimodality information facilitates a comprehensive evaluation of morphologic and dynamic features, stratification of the risk, and therapy guidance of this cohort of patients.
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Affiliation(s)
- Arturo Evangelista Masip
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain
- Teknon Heart Institute-Quiron Salud, 08022 Barcelona, Spain; (A.P.); (A.M.); (M.H.)
| | - Laura Galian-Gay
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Andrea Guala
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Angela Lopez-Sainz
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Gisela Teixido-Turà
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Aroa Ruiz Muñoz
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Filipa Valente
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Laura Gutierrez
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Ruben Fernandez-Galera
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Guillem Casas
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Alejandro Panaro
- Teknon Heart Institute-Quiron Salud, 08022 Barcelona, Spain; (A.P.); (A.M.); (M.H.)
| | - Alba Marigliano
- Teknon Heart Institute-Quiron Salud, 08022 Barcelona, Spain; (A.P.); (A.M.); (M.H.)
| | - Marina Huguet
- Teknon Heart Institute-Quiron Salud, 08022 Barcelona, Spain; (A.P.); (A.M.); (M.H.)
| | - Teresa González-Alujas
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
| | - Jose Rodriguez-Palomares
- Departament de Cardiologia, Hospital Vall d’Hebron.CIBERCV, Universitat Autonoma de Barcelona, 08035 Barcelona, Spain; (L.G.-G.); (A.G.); (A.L.-S.); (G.T.-T.); (A.R.M.); (F.V.); (L.G.); (R.F.-G.); (G.C.); (T.G.-A.); (J.R.-P.)
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