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Crawley R, Kunze KP, Milidonis X, Highton J, McElroy S, Frey SM, Hoefler D, Karamanli C, Wong NCK, Backhaus SJ, Alskaf E, Neji R, Scannell CM, Plein S, Chiribiri A. High-resolution free-breathing automated quantitative myocardial perfusion by cardiovascular magnetic resonance for the detection of functionally significant coronary artery disease. Eur Heart J Cardiovasc Imaging 2024; 25:914-925. [PMID: 38525948 PMCID: PMC11210990 DOI: 10.1093/ehjci/jeae084] [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: 12/12/2023] [Revised: 03/15/2024] [Accepted: 03/17/2024] [Indexed: 03/26/2024] Open
Abstract
AIMS Current assessment of myocardial ischaemia from stress perfusion cardiovascular magnetic resonance (SP-CMR) largely relies on visual interpretation. This study investigated the use of high-resolution free-breathing SP-CMR with automated quantitative mapping in the diagnosis of coronary artery disease (CAD). Diagnostic performance was evaluated against invasive coronary angiography (ICA) with fractional flow reserve (FFR) measurement. METHODS AND RESULTS Seven hundred and three patients were recruited for SP-CMR using the research sequence at 3 Tesla. Of those receiving ICA within 6 months, 80 patients had either FFR measurement or identification of a chronic total occlusion (CTO) with inducible perfusion defects seen on SP-CMR. Myocardial blood flow (MBF) maps were automatically generated in-line on the scanner following image acquisition at hyperaemic stress and rest, allowing myocardial perfusion reserve (MPR) calculation. Seventy-five coronary vessels assessed by FFR and 28 vessels with CTO were evaluated at both segmental and coronary territory level. Coronary territory stress MBF and MPR were reduced in FFR-positive (≤0.80) regions [median stress MBF: 1.74 (0.90-2.17) mL/min/g; MPR: 1.67 (1.10-1.89)] compared with FFR-negative regions [stress MBF: 2.50 (2.15-2.95) mL/min/g; MPR 2.35 (2.06-2.54) P < 0.001 for both]. Stress MBF ≤ 1.94 mL/min/g and MPR ≤ 1.97 accurately detected FFR-positive CAD on a per-vessel basis (area under the curve: 0.85 and 0.96, respectively; P < 0.001 for both). CONCLUSION A novel scanner-integrated high-resolution free-breathing SP-CMR sequence with automated in-line perfusion mapping is presented which accurately detects functionally significant CAD.
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Affiliation(s)
- R Crawley
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - K P Kunze
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
- Magnetic Resonance Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | - X Milidonis
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
- DeepCamera MRG, CYENS Centre of Excellence, Nicosia, Cyprus
| | - J Highton
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
- Aival, London, UK
| | - S McElroy
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
- Magnetic Resonance Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | - S M Frey
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
| | - D Hoefler
- Department of Radiotherapy, University of Erlangen, Erlangen, Germany
| | - C Karamanli
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - N C K Wong
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - S J Backhaus
- Department of Cardiology, Campus Kerckhoff of the Justus-Liebig-University Giessen, Kerckhoff-Clinic, Bad Nauheim, Germany
| | - E Alskaf
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - R Neji
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - C M Scannell
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - S Plein
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - A Chiribiri
- School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London, SE1 7EH, UK
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Xu J, Zhuang B, Cui C, Yang W, He J, Wang X, Duan X, Zhou D, Wang Y, Zhu L, Sirajuddin A, Zhao S, Lu M. Adenosine Triphosphate Stress Myocardial Strain in Ischemic Heart Disease: An Animal Study with Histological Validation. Acad Radiol 2024; 31:221-232. [PMID: 37330355 DOI: 10.1016/j.acra.2023.05.020] [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: 04/12/2023] [Revised: 05/17/2023] [Accepted: 05/20/2023] [Indexed: 06/19/2023]
Abstract
RATIONALE AND OBJECTIVES It is still challenging for cardiac magnetic resonance (CMR) to detect ischemic heart disease (IHD) without the use of gadolinium contrast. We aimed to evaluate the potential value of adenosine triphosphate (ATP) stress myocardial strain derived from feature tracking (FT) as a novel method for detecting IHD in a swine model. MATERIALS AND METHODS CMR cines, myocardial perfusion imaging at rest and during ATP stress, and late gadolinium enhancement were obtained in both control and IHD swine. Normal, remote, ischemic, and infarcted myocardium were analyzed. The diagnostic accuracy of myocardial strain for infarction and ischemia was assessed using coronary angiography and pathology as reference. RESULTS Eleven IHD swine and five healthy control swine were enrolled in this study. Strain parameters, even at rest, were associated with myocardial ischemia and infarction(all p < 0.05). The area under receiver operating characteristic curve (AUC) values of all strain parameters for detecting infarcted myocardium exceeded 0.900 (all p < 0.05). The AUC values for detecting ischemic myocardium were as follows: 0.906 and 0.847 for stress and rest radial strain, 0.763 and 0.716 for stress and rest circumferential strain, 0.758 and 0.663 for stress and rest longitudinal strain (all p < 0.001). Heat maps demonstrated that all strain parameters showed mild to moderate correlations with the stress myocardial blood flow and myocardial perfusion reserve (all p < 0.05). CONCLUSION CMR-FT-derived ATP stress myocardial strain shows promise as a noninvasive method for detecting myocardial ischemia and infarction in an IHD swine model, with rest strain parameters offering potential as a needle-free diagnostic option.
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Affiliation(s)
- Jing Xu
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Baiyan Zhuang
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Chen Cui
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Wenjing Yang
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Jian He
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Xin Wang
- Department of Animal Experimental Center, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.W.)
| | - Xuejing Duan
- Department of Pathology, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.D.)
| | - Di Zhou
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Yining Wang
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Leyi Zhu
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Arlene Sirajuddin
- Department of Health and Human Services, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland (A.S.)
| | - Shihua Zhao
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.)
| | - Minjie Lu
- Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (J.X., B.Z., C.C., W.Y., J.H., D.Z., Y.W., L.Z., S.Z., M.L.); Key Laboratory of Cardiovascular Imaging (Cultivation), Chinese Academy of Medical Sciences, Beijing, China (M.L.).
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3
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Scott AD, Jackson T, Khalique Z, Gorodezky M, Pardoe B, Begum L, Bruno VD, Chowdhury RA, Ferreira PF, Nielles‐Vallespin S, Roehl M, McCarthy KP, Sarathchandra P, Rose JN, Doorly DJ, Pennell DJ, Ascione R, de Silva R, Firmin DN. Development of a cardiovascular magnetic resonance-compatible large animal isolated heart model for direct comparison of beating and arrested hearts. NMR IN BIOMEDICINE 2022; 35:e4692. [PMID: 35040195 PMCID: PMC9286060 DOI: 10.1002/nbm.4692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/21/2021] [Accepted: 01/07/2022] [Indexed: 06/02/2023]
Abstract
Cardiac motion results in image artefacts and quantification errors in many cardiovascular magnetic resonance (CMR) techniques, including microstructural assessment using diffusion tensor cardiovascular magnetic resonance (DT-CMR). Here, we develop a CMR-compatible isolated perfused porcine heart model that allows comparison of data obtained in beating and arrested states. Ten porcine hearts (8/10 for protocol optimisation) were harvested using a donor heart retrieval protocol and transported to the remote CMR facility. Langendorff perfusion in a 3D-printed chamber and perfusion circuit re-established contraction. Hearts were imaged using cine, parametric mapping and STEAM DT-CMR at cardiac phases with the minimum and maximum wall thickness. High potassium and lithium perfusates were then used to arrest the heart in a slack and contracted state, respectively. Imaging was repeated in both arrested states. After imaging, tissue was removed for subsequent histology in a location matched to the DT-CMR data using fiducial markers. Regular sustained contraction was successfully established in six out of 10 hearts, including the final five hearts. Imaging was performed in four hearts and one underwent the full protocol, including colocalised histology. The image quality was good and there was good agreement between DT-CMR data in equivalent beating and arrested states. Despite the use of autologous blood and dextran within the perfusate, T2 mapping results, DT-CMR measures and an increase in mass were consistent with development of myocardial oedema, resulting in failure to achieve a true diastolic-like state. A contiguous stack of 313 5-μm histological sections at and a 100-μm thick section showing cell morphology on 3D fluorescent confocal microscopy colocalised to DT-CMR data were obtained. A CMR-compatible isolated perfused beating heart setup for large animal hearts allows direct comparisons of beating and arrested heart data with subsequent colocalised histology, without the need for onsite preclinical facilities.
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Affiliation(s)
- Andrew D. Scott
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Tim Jackson
- Department of PerfusionRoyal Brompton HospitalLondonUK
| | - Zohya Khalique
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Margarita Gorodezky
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Ben Pardoe
- Department of PerfusionRoyal Brompton HospitalLondonUK
| | - Lale Begum
- Department of PerfusionRoyal Brompton HospitalLondonUK
| | - V. Domenico Bruno
- Translational Biomedical Research CentreUniversity of BristolBristolUK
- Bristol Heart InstituteUniversity Hospital Bristol NHS Foundation TrustBristolUK
| | - Rasheda A. Chowdhury
- National Heart and Lung InstituteImperial CollegeLondonUK
- Imperial Centre for Cardiac EngineeringImperial CollegeLondonUK
| | - Pedro F. Ferreira
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Sonia Nielles‐Vallespin
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Malte Roehl
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | | | - Padmini Sarathchandra
- National Heart and Lung InstituteImperial CollegeLondonUK
- Magdi Yacoub Institute, National Heart and Lung InstituteImperial CollegeLondonUK
| | - Jan N. Rose
- Department of AeronauticsImperial CollegeLondonUK
| | | | - Dudley J. Pennell
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Raimondo Ascione
- Translational Biomedical Research CentreUniversity of BristolBristolUK
- Bristol Heart InstituteUniversity Hospital Bristol NHS Foundation TrustBristolUK
| | - Ranil de Silva
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - David N. Firmin
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
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4
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Aboulgheit A, Potz BA, Scrimgeour LA, Karbasiafshar C, Shi G, Zhang Z, Machan JT, Schorl C, Brodsky AS, Braga K, Pfeiffer M, Gao M, Cummings O, Sodha NR, Abid MR, Sellke FW. Effects of High Fat Versus Normal Diet on Extracellular Vesicle-Induced Angiogenesis in a Swine Model of Chronic Myocardial Ischemia. J Am Heart Assoc 2021; 10:e017437. [PMID: 33559477 PMCID: PMC7955347 DOI: 10.1161/jaha.120.017437] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 10/12/2020] [Indexed: 12/20/2022]
Abstract
Background Mesenchymal stem cell-derived extracellular vesicles (EVs) promote angiogenesis in the ischemic myocardium. This study examines the difference in vascular density, myocardial perfusion, molecular signaling, and gene expression between normal diet (ND) and high fat diet (HFD) groups at baseline and following intramyocardial injection of EVs. Methods and Results Intact male Yorkshire swine fed either an ND (n=17) or HFD (n=14) underwent placement of an ameroid constrictor on the left circumflex coronary artery. Subsequently, animals received either intramyocardial injection of vehicle-saline as controls; (ND-controls n=7, HFD-controls, n=6) or EVs; (ND-EVs n=10, HFD-EVs n=8) into the ischemic territory. Five weeks later, myocardial function, perfusion, vascular density, cell signaling, and gene expression were examined. EVs improved indices of myocardial contractile function, myocardial perfusion, and arteriogenesis in both dietary cohorts. Interestingly, quantification of alpha smooth muscle actin demonstrated higher basal arteriolar density in HFD swine compared with their ND counterparts; whereas EVs were associated with increased CD31-labeled endothelial cell density only in the ND tissue, which approached significance. Levels of total endothelial nitric oxide synthase, FOXO1 (forkhead box protein O1) , transforming growth factor-β, phosphorylated VEGFR2 (vascular endothelial growth factor receptor 2), and phosphorylated MAPK ERK1/ERK2 (mitogen-activated protein kinase) were higher in ischemic myocardial lysates from ND-controls compared with HFD-controls. Conversely, HFD-control tissue showed increased expression of phosphorylated endothelial nitric oxide synthase, phosphorylated FOXO1, VEGFR2, and MAPK ERK1/ERK2 with respect to ND-controls. Preliminary gene expression studies indicate differential modulation of transcriptional activity by EVs between the 2 dietary cohorts. Conclusions HFD produces a profound metabolic disorder that dysregulates the molecular mechanisms of collateral vessel formation in the ischemic myocardium, which may hinder the therapeutic angiogenic effects of EVs.
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Affiliation(s)
- Ahmed Aboulgheit
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
| | - Brittany A. Potz
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
| | - Laura A. Scrimgeour
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
| | - Catherine Karbasiafshar
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
| | - Guangbin Shi
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
| | - Zhiqi Zhang
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
| | - Jason T. Machan
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
- Department of OrthopedicsAlpert Medical School of Brown UniversityProvidenceRI
- Biostatistics CoreLifespan Hospital SystemProvidenceRI
| | - Christoph Schorl
- Department of Molecular Biology, Cell Biology, BiochemistryGenomics CoreBrown UniversityProvidenceRI
| | - Alexander S. Brodsky
- Department of Pathology and Laboratory MedicineAlpert Medical School of Brown UniversityProvidenceRI
- Center for Computational Molecular BiologyBrown UniversityProvidenceRI
| | - Karla Braga
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
| | - Melissa Pfeiffer
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
| | - May Gao
- Cardiothoracic Surgery Division, Cardiovascular Research CenterRhode Island Hospital, Warren Alpert Medical School of Brown UniversityProvidenceRI
| | - Olivia Cummings
- Cardiothoracic Surgery Division, Cardiovascular Research CenterRhode Island Hospital, Warren Alpert Medical School of Brown UniversityProvidenceRI
| | - Neel R. Sodha
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
| | - M. Ruhul Abid
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
| | - Frank W. Sellke
- Division of Cardiothoracic SurgeryAlpert Medical School of Brown University and Rhode Island HospitalProvidenceRI
- Department of SurgeryAlpert Medical School of Brown UniversityProvidenceRI
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Colbert CM, Shao J, Hollowed JJ, Currier JW, Ajijola OA, Fishbein GA, Duarte-Vogel SM, Dharmakumar R, Hu P, Nguyen KL. 3D-Printed Coronary Implants Are Effective for Percutaneous Creation of Swine Models with Focal Coronary Stenosis. J Cardiovasc Transl Res 2020; 13:1033-1043. [PMID: 32394352 PMCID: PMC9667863 DOI: 10.1007/s12265-020-10018-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 04/28/2020] [Indexed: 01/17/2023]
Abstract
Reliable, closed-chest methods for creating large animal models of acute myocardial hypoperfusion are limited. We demonstrated the feasibility and efficacy of using magnetic resonance (MR)-compatible 3D-printed coronary implants for establishing swine models of myocardial hypoperfusion. We designed, manufactured, and percutaneously deployed implants in 13 swine to selectively create focal coronary stenosis. To test the efficacy of the implants to cause hypoperfusion or ischemia in the perfused territory, we evaluated regional wall motion, myocardial perfusion, and infarction using MR imaging. The overall swine survival rate was 85% (11 of 13). The implant retrieval rate was 92% (12 of 13). Fluoroscopic angiography confirmed focal stenosis. Cine and perfusion MRI showed regional wall motion abnormalities and inducible ischemia, respectively. Late gadolinium enhancement and histopathology showed no myocardial infarction. Our minimally invasive technique has promising applications for validation of new diagnostic methods in cardiac MR. Graphical abstract Our new minimally invasive, percutaneous method for creating swine models of acute focal coronary stenosis can be used for magnetic resonance imaging studies of myocardial ischemia. Comparable to existing methods in its efficacy and reliability, this rapid prototyping technique will allow researchers to more easily conduct translational cardiac imaging studies of coronary artery disease in large animal models.
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Affiliation(s)
- Caroline M Colbert
- Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jiaxin Shao
- Diagnostic Cardiovascular Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - John J Hollowed
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, 11301 Wilshire Blvd, MC 111E, Los Angeles, CA, 90073, USA
| | - Jesse W Currier
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, 11301 Wilshire Blvd, MC 111E, Los Angeles, CA, 90073, USA
| | - Olujimi A Ajijola
- UCLA Cardiac Arrhythmia Center and Division of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Gregory A Fishbein
- Department of Pathology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Sandra M Duarte-Vogel
- Division of Laboratory Animal Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Rohan Dharmakumar
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center and Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Peng Hu
- Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Diagnostic Cardiovascular Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Kim-Lien Nguyen
- Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Diagnostic Cardiovascular Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, 11301 Wilshire Blvd, MC 111E, Los Angeles, CA, 90073, USA.
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6
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Rahman H, Scannell CM, Demir OM, Ryan M, McConkey H, Ellis H, Masci PG, Perera D, Chiribiri A. High-Resolution Cardiac Magnetic Resonance Imaging Techniques for the Identification of Coronary Microvascular Dysfunction. JACC Cardiovasc Imaging 2020; 14:978-986. [PMID: 33248969 DOI: 10.1016/j.jcmg.2020.10.015] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 09/01/2020] [Accepted: 10/14/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVES This study assessed the ability to identify coronary microvascular dysfunction (CMD) in patients with angina and nonobstructive coronary artery disease (NOCAD) using high-resolution cardiac magnetic resonance (CMR) and hypothesized that quantitative perfusion techniques would have greater accuracy than visual analysis. BACKGROUND Half of all patients with angina are found to have NOCAD, while the presence of CMD portends greater morbidity and mortality, it now represents a modifiable therapeutic target. Diagnosis currently requires invasive assessment of coronary blood flow during angiography. With greater reliance on computed tomography coronary angiography as a first-line tool to investigate angina, noninvasive tests for diagnosing CMD warrant validation. METHODS Consecutive patients with angina and NOCAD were enrolled. Intracoronary pressure and flow measurements were acquired during rest and vasodilator-mediated hyperemia. CMR (3-T) was performed and analyzed by visual and quantitative techniques, including calculation of myocardial blood flow (MBF) during hyperemia (stress MBF), transmural myocardial perfusion reserve (MPR: MBFHYPEREMIA / MBFREST), and subendocardial MPR (MPRENDO). CMD was defined dichotomously as an invasive coronary flow reserve <2.5, with CMR readers blinded to this classification. RESULTS A total of 75 patients were enrolled (57 ± 10 years of age, 81% women). Among the quantitative perfusion indices, MPRENDO and MPR had the highest accuracy (area under the curve [AUC]: 0.90 and 0.88) with high sensitivity and specificity, respectively, both superior to visual assessment (both p < 0.001). Visual assessment identified CMD with 58% accuracy (41% sensitivity and 83% specificity). Quantitative stress MBF performed similarly to visual analysis (AUC: 0.64 vs. 0.60; p = 0.69). CONCLUSIONS High-resolution CMR has good accuracy at detecting CMD but only when analyzed quantitatively. Although omission of rest imaging and stress-only protocols make for quicker scans, this is at the cost of accuracy compared with integrating rest and stress perfusion. Quantitative perfusion CMR has an increasingly important role in the management of patients frequently encountered with angina and NOCAD.
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Affiliation(s)
- Haseeb Rahman
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre, King's College London, London, United Kingdom
| | - Cian M Scannell
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Ozan M Demir
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre, King's College London, London, United Kingdom
| | - Matthew Ryan
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre, King's College London, London, United Kingdom
| | - Hannah McConkey
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre, King's College London, London, United Kingdom
| | - Howard Ellis
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre, King's College London, London, United Kingdom
| | - Pier Giorgio Masci
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Divaka Perera
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre, King's College London, London, United Kingdom.
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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7
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Rahman H, Demir OM, Ryan M, McConkey H, Scannell C, Ellis H, Webb A, Chiribiri A, Perera D. Optimal Use of Vasodilators for Diagnosis of Microvascular Angina in the Cardiac Catheterization Laboratory. Circ Cardiovasc Interv 2020; 13:e009019. [PMID: 32519879 PMCID: PMC7299228 DOI: 10.1161/circinterventions.120.009019] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Among patients with angina and nonobstructive coronary artery disease, those with coronary microvascular dysfunction have a poor outcome. Coronary microvascular dysfunction is usually diagnosed by assessing flow reserve with an endothelium-independent vasodilator like adenosine, but the optimal diagnostic threshold is unclear. Furthermore, the incremental value of testing endothelial function has never been assessed before. We sought to determine what pharmacological thresholds correspond to exercise pathophysiology and myocardial ischemia in patients with coronary microvascular dysfunction.
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Affiliation(s)
- Haseeb Rahman
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
| | - Ozan M Demir
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
| | - Matthew Ryan
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
| | - Hannah McConkey
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
| | - Cian Scannell
- School of Biomedical Engineering and Imaging Sciences (C.S., A.C.), King's College London, United Kingdom
| | - Howard Ellis
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
| | - Andrew Webb
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences (C.S., A.C.), King's College London, United Kingdom
| | - Divaka Perera
- School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom
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Scannell CM, Veta M, Villa AD, Sammut EC, Lee J, Breeuwer M, Chiribiri A. Deep-Learning-Based Preprocessing for Quantitative Myocardial Perfusion MRI. J Magn Reson Imaging 2020; 51:1689-1696. [PMID: 31710769 PMCID: PMC7317373 DOI: 10.1002/jmri.26983] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 10/11/2019] [Accepted: 10/16/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Quantitative myocardial perfusion cardiac MRI can provide a fast and robust assessment of myocardial perfusion status for the noninvasive diagnosis of myocardial ischemia while being more objective than visual assessment. However, it currently has limited use in clinical practice due to the challenging postprocessing required, particularly the segmentation. PURPOSE To evaluate the efficacy of an automated deep learning (DL) pipeline for image processing prior to quantitative analysis. STUDY TYPE Retrospective. POPULATION In all, 175 (350 MRI scans; 1050 image series) clinical patients under both rest and stress conditions (135/10/30 training/validation/test). FIELD STRENGTH/SEQUENCE 3.0T/2D multislice saturation recovery T1 -weighted gradient echo sequence. ASSESSMENT Accuracy was assessed, as compared to the manual operator, through the mean square error of the distance between landmarks and the Dice similarity coefficient of the segmentation and bounding box detection. Quantitative perfusion maps obtained using the automated DL-based processing were compared to the results obtained with the manually processed images. STATISTICAL TESTS Bland-Altman plots and intraclass correlation coefficient (ICC) were used to assess the myocardial blood flow (MBF) obtained using the automated DL pipeline, as compared to values obtained by a manual operator. RESULTS The mean (SD) error in the detection of the time of peak signal enhancement in the left ventricle was 1.49 (1.4) timeframes. The mean (SD) Dice similarity coefficients for the bounding box and myocardial segmentation were 0.93 (0.03) and 0.80 (0.06), respectively. The mean (SD) error in the RV insertion point was 2.8 (1.8) mm. The Bland-Altman plots showed a bias of 2.6% of the mean MBF between the automated and manually processed MBF values on a per-myocardial segment basis. The ICC was 0.89, 95% confidence interval = [0.87, 0.90]. DATA CONCLUSION We showed high accuracy, compared to manual processing, for the DL-based processing of myocardial perfusion data leading to quantitative values that are similar to those achieved with manual processing. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1689-1696.
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Affiliation(s)
- Cian M. Scannell
- School of Biomedical Engineering and Imaging SciencesKing's College LondonUK
- Alan Turing Institute LondonUK
| | - Mitko Veta
- Department of Biomedical Engineering, Medical Image Analysis groupEindhoven University of TechnologyEindhovenThe Netherlands
| | - Adriana D.M. Villa
- School of Biomedical Engineering and Imaging SciencesKing's College LondonUK
| | - Eva C. Sammut
- School of Biomedical Engineering and Imaging SciencesKing's College LondonUK
- Bristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health ScienceUniversity of BristolUK
| | - Jack Lee
- School of Biomedical Engineering and Imaging SciencesKing's College LondonUK
| | - Marcel Breeuwer
- Department of Biomedical Engineering, Medical Image Analysis groupEindhoven University of TechnologyEindhovenThe Netherlands
- Philips Healthcare, BestThe Netherlands
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging SciencesKing's College LondonUK
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Milidonis X, Nazir MS, Schneider T, Capstick M, Drost S, Kok G, Pelevic N, Poelma C, Schaeffter T, Chiribiri A. Pixel-wise assessment of cardiovascular magnetic resonance first-pass perfusion using a cardiac phantom mimicking transmural myocardial perfusion gradients. Magn Reson Med 2020; 84:2871-2884. [PMID: 32426854 PMCID: PMC7611223 DOI: 10.1002/mrm.28296] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/05/2020] [Accepted: 04/02/2020] [Indexed: 01/31/2023]
Abstract
PURPOSE Cardiovascular magnetic resonance first-pass perfusion for the pixel-wise detection of coronary artery disease is rapidly becoming the clinical standard, yet no widely available method exists for its assessment and validation. This study introduces a novel phantom capable of generating spatially dependent flow values to enable assessment of new perfusion imaging methods at the pixel level. METHODS A synthetic multicapillary myocardial phantom mimicking transmural myocardial perfusion gradients was designed and manufactured with high-precision 3D printing. The phantom was used in a stationary flow setup providing reference myocardial perfusion rates and was scanned on a 3T system. Repeated first-pass perfusion MRI for physiological perfusion rates between 1 and 4 mL/g/min was performed using a clinical dual-sequence technique. Fermi function-constrained deconvolution was used to estimate pixel-wise perfusion rate maps. Phase contrast (PC)-MRI was used to obtain velocity measurements that were converted to perfusion rates for validation of reference values and cross-method comparison. The accuracy of pixel-wise maps was assessed against simulated reference maps. RESULTS PC-MRI indicated excellent reproducibility in perfusion rate (coefficient of variation [CoV] 2.4-3.5%) and correlation with reference values (R2 = 0.985) across the full physiological range. Similar results were found for first-pass perfusion MRI (CoV 3.7-6.2%, R2 = 0.987). Pixel-wise maps indicated a transmural perfusion difference of 28.8-33.7% for PC-MRI and 23.8-37.7% for first-pass perfusion, matching the reference values (30.2-31.4%). CONCLUSION The unique transmural perfusion pattern in the phantom allows effective pixel-wise assessment of first-pass perfusion acquisition protocols and quantification algorithms before their introduction into routine clinical use.
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Affiliation(s)
- Xenios Milidonis
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Torben Schneider
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.,Philips Healthcare, Guilford, United Kingdom
| | | | - Sita Drost
- Laboratory for Aero- and Hydrodynamics, Technische Universiteit Delft, Delft, Netherlands
| | | | | | - Christian Poelma
- Laboratory for Aero- and Hydrodynamics, Technische Universiteit Delft, Delft, Netherlands
| | | | - Amedeo Chiribiri
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
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Rahman H, Demir O, Ryan M, McConkey H, Ellis H, Scannell C, Chiribiri A, Webb A, Perera D. Mechanisms of exertional angina in patients with normal coronary arteries. Clin Med (Lond) 2020; 20:s44-s45. [PMID: 32409366 PMCID: PMC7243519 DOI: 10.7861/clinmed.20-2-s44] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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11
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Martens J, Panzer S, den Wijngaard J, Siebes M, Schreiber LM. Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study. Magn Reson Med 2019; 84:467-483. [DOI: 10.1002/mrm.28125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Revised: 11/19/2019] [Accepted: 11/20/2019] [Indexed: 12/22/2022]
Affiliation(s)
- Johannes Martens
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure CenterUniversity Hospitals Würzburg Germany
- Department of Cardiovascular Imaging Comprehensive Heart Failure Center University Hospitals Würzburg Germany
| | - Sabine Panzer
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure CenterUniversity Hospitals Würzburg Germany
- Department of Cardiovascular Imaging Comprehensive Heart Failure Center University Hospitals Würzburg Germany
| | - Jeroen den Wijngaard
- Department of Biomedical Engineering & Physics Amsterdam University Medical Center University of Amsterdam Amsterdam Cardiovascular Sciences Amsterdam Netherlands
- Department of Clinical Chemistry and Hematology Diakonessenhuis Utrecht Netherlands
| | - Maria Siebes
- Department of Biomedical Engineering & Physics Amsterdam University Medical Center University of Amsterdam Amsterdam Cardiovascular Sciences Amsterdam Netherlands
| | - Laura M. Schreiber
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure CenterUniversity Hospitals Würzburg Germany
- Department of Cardiovascular Imaging Comprehensive Heart Failure Center University Hospitals Würzburg Germany
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12
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Rahman H, Ryan M, Lumley M, Modi B, McConkey H, Ellis H, Scannell C, Clapp B, Marber M, Webb A, Chiribiri A, Perera D. Coronary Microvascular Dysfunction Is Associated With Myocardial Ischemia and Abnormal Coronary Perfusion During Exercise. Circulation 2019; 140:1805-1816. [PMID: 31707835 PMCID: PMC6882540 DOI: 10.1161/circulationaha.119.041595] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 10/15/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Coronary microvascular dysfunction (MVD) is defined by impaired flow augmentation in response to a pharmacological vasodilator in the presence of nonobstructive coronary artery disease. It is unknown whether diminished coronary vasodilator response correlates with abnormal exercise physiology or inducible myocardial ischemia. METHODS Patients with angina and nonobstructive coronary artery disease had simultaneous coronary pressure and flow velocity measured using a dual sensor-tipped guidewire during rest, supine bicycle exercise, and adenosine-mediated hyperemia. Microvascular resistance (MR) was calculated as coronary pressure divided by flow velocity. Wave intensity analysis quantified the proportion of accelerating wave energy (perfusion efficiency). Global myocardial blood flow and subendocardial:subepicardial perfusion ratio were quantified using 3-Tesla cardiac magnetic resonance imaging during hyperemia and rest; inducible ischemia was defined as hyperemic subendocardial:subepicardial perfusion ratio <1.0. Patients were classified as having MVD if coronary flow reserve <2.5 and controls if coronary flow reserve ≥2.5, with researchers blinded to the classification. RESULTS Eighty-five patients were enrolled (78% female, 57±10 years), 45 (53%) were classified as having MVD. Of the MVD group, 82% had inducible ischemia compared with 22% of controls (P<0.001); global myocardial perfusion reserve was 2.01±0.41 and 2.68±0.49 (P<0.001). In controls, coronary perfusion efficiency improved from rest to exercise and was unchanged during hyperemia (59±11% vs 65±14% vs 57±18%; P=0.02 and P=0.14). In contrast, perfusion efficiency decreased during both forms of stress in MVD (61±12 vs 44±10 vs 42±11%; both P<0.001). Among patients with a coronary flow reserve <2.5, 62% had functional MVD, with normal minimal MR (hyperemic MR<2.5 mmHg/cm/s), and 38% had structural MVD with elevated hyperemic MR. Resting MR was lower in those with functional MVD (4.2±1.0 mmHg/cm/s) than in those with structural MVD (6.9±1.7 mmHg/cm/s) or controls (7.3±2.2 mmHg/cm/s; both P<0.001). During exercise, the structural group had a higher systolic blood pressure (188±25 mmHg) than did those with functional MVD (161±27 mmHg; P=0.004) and controls (156±30 mmHg; P<0.001). Functional and structural MVD had similar stress myocardial perfusion and exercise perfusion efficiency values. CONCLUSION In patients with angina and nonobstructive coronary artery disease, diminished coronary flow reserve characterizes a cohort with inducible ischemia and a maladaptive physiological response to exercise. We have identified 2 endotypes of MVD with distinctive systemic vascular responses to exercise; whether endotypes have a different prognosis or require different treatments merits further investigation.
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Affiliation(s)
- Haseeb Rahman
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Matthew Ryan
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Matthew Lumley
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Bhavik Modi
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Hannah McConkey
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Howard Ellis
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Cian Scannell
- Biomedical Engineering & Imaging Sciences (A.C., C.S.), King’s College London, United Kingdom
| | - Brian Clapp
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Michael Marber
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Andrew Webb
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
| | - Amedeo Chiribiri
- Biomedical Engineering & Imaging Sciences (A.C., C.S.), King’s College London, United Kingdom
| | - Divaka Perera
- From The British Heart Foundation Centre of Research Excellence, Schools of Cardiovascular Medicine & Sciences (H.R., M.R., M.L., B.M., H.M., H.E., B.C., M.M., A.W., D.P.), King’s College London, United Kingdom
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Rasmussen LD, Winther S, Westra J, Isaksen C, Ejlersen JA, Brix L, Kirk J, Urbonaviciene G, Søndergaard HM, Hammid O, Schmidt SE, Knudsen LL, Madsen LH, Frost L, Petersen SE, Gormsen LC, Christiansen EH, Eftekhari A, Holm NR, Nyegaard M, Chiribiri A, Bøtker HE, Böttcher M. Danish study of Non-Invasive testing in Coronary Artery Disease 2 (Dan-NICAD 2): Study design for a controlled study of diagnostic accuracy. Am Heart J 2019; 215:114-128. [PMID: 31323454 DOI: 10.1016/j.ahj.2019.03.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 03/27/2019] [Indexed: 12/19/2022]
Abstract
BACKGROUND Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICAs) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has 3 equivalent main aims: (1) To examine the diagnostic precision of a sound-based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. (2) To compare the diagnostic accuracy of 3T cardiac magnetic resonance imaging (3T CMRI), 82rubidium positron emission tomography (82Rb-PET), and CT-derived fractional flow reserve (FFRCT) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. (3) To compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using 82Rb-PET as reference standard. METHODS Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to coronary CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule out obstructive CAD, patients will be examined by 3T CMRI 82Rb-PET, FFRCT, ICA, and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90% diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion. DISCUSSION The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in 3 different steps: risk stratification prior to coronary CTA, diagnostic strategy after coronary CTA, and invasive wireless QFR analysis as an alternative to ICA-FFR.
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14
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Gkontra P, El‐Bouri WK, Norton K, Santos A, Popel AS, Payne SJ, Arroyo AG. Dynamic Changes in Microvascular Flow Conductivity and Perfusion After Myocardial Infarction Shown by Image-Based Modeling. J Am Heart Assoc 2019; 8:e011058. [PMID: 30897998 PMCID: PMC6509718 DOI: 10.1161/jaha.118.011058] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 02/19/2019] [Indexed: 12/26/2022]
Abstract
Background Microcirculation is a decisive factor in tissue reperfusion inadequacy following myocardial infarction ( MI ). Nonetheless, experimental assessment of blood flow in microcirculation remains a bottleneck. We sought to model blood flow properties in coronary microcirculation at different time points after MI and to compare them with healthy conditions to obtain insights into alterations in cardiac tissue perfusion. Methods and Results We developed an image-based modeling framework that permitted feeding a continuum flow model with anatomical data previously obtained from the pig coronary microvasculature to calculate physiologically meaningful permeability tensors. The tensors encompassed the microvascular conductivity and were also used to estimate the arteriole-venule drop in pressure and myocardial blood flow. Our results indicate that the tensors increased in a bimodal pattern at infarcted areas on days 1 and 7 after MI while a nonphysiological decrease in arteriole-venule drop in pressure was observed; contrary, the tensors and the arteriole-venule drop in pressure on day 3 after MI , and in remote areas, were closer to values for healthy tissue. Myocardial blood flow calculated using the condition-dependent arteriole-venule drop in pressure decreased in infarcted areas. Last, we simulated specific modes of vascular remodeling, such as vasodilation, vasoconstriction, or pruning, and quantified their distinct impact on microvascular conductivity. Conclusions Our study unravels time- and region-dependent alterations of tissue perfusion related to the structural changes occurring in the coronary microvasculature due to MI . It also paves the way for conducting simulations in new therapeutic interventions in MI and for image-based microvascular modeling by applying continuum flow models in other biomedical scenarios.
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Affiliation(s)
- Polyxeni Gkontra
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)MadridSpain
- Biomedical Image Technologies (BIT), ETSI Telecomunicación,Universidad Politécnica de MadridMadridSpain
| | - Wahbi K. El‐Bouri
- Institute of Biomedical EngineeringDepartment of Engineering ScienceUniversity of OxfordUnited Kingdom
| | - Kerri‐Ann Norton
- Division of Science, Mathematics, and ComputingBard CollegeAnnandale‐on‐HudsonNY
| | - Andrés Santos
- Biomedical Image Technologies (BIT), ETSI Telecomunicación,Universidad Politécnica de MadridMadridSpain
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBERBBN)MadridSpain
| | - Aleksander S. Popel
- Department of Biomedical EngineeringSchool of MedicineJohns Hopkins UniversityBaltimoreMD
| | - Stephen J. Payne
- Institute of Biomedical EngineeringDepartment of Engineering ScienceUniversity of OxfordUnited Kingdom
| | - Alicia G. Arroyo
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)MadridSpain
- Centro de Investigaciones Biológicas (CIB‐CSIC)MadridSpain
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15
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Alves JR, de Queiroz RAB, Bär M, Dos Santos RW. Simulation of the Perfusion of Contrast Agent Used in Cardiac Magnetic Resonance: A Step Toward Non-invasive Cardiac Perfusion Quantification. Front Physiol 2019; 10:177. [PMID: 30949059 PMCID: PMC6436070 DOI: 10.3389/fphys.2019.00177] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 02/12/2019] [Indexed: 01/02/2023] Open
Abstract
This work presents a new mathematical model to describe cardiac perfusion in the myocardium as acquired by cardiac magnetic resonance (CMR) perfusion exams. The combination of first pass (or contrast-enhanced CMR) and late enhancement CMR is a widely used non-invasive exam that can identify abnormal perfused regions of the heart via the use of a contrast agent (CA). The exam provides important information to the diagnosis, management, and prognosis of ischemia and infarct: perfusion on different regions, the status of microvascular structures, the presence of fibrosis, and the relative volume of extracellular space. This information is obtained by inferring the spatiotemporal dynamics of the contrast in the myocardial tissue from the acquired images. The evaluation of these physiological parameters plays an important role in the assessment of myocardial viability. However, the nature of cardiac physiology poses great challenges in the estimation of these parameters. Briefly, these are currently estimated qualitatively via visual inspection of images and comparison of relative brightness between different regions of the heart. Therefore, there is a great urge for techniques that can help to quantify cardiac perfusion. In this work, we propose a new mathematical model based on multidomain flow in porous media. The model is based on a system of partial differential equations. Darcy's law is used to obtain the pressure and velocity distribution. CA dynamics is described by reaction-diffusion-advection equations in the intravascular space and in the interstitial space. The interaction of fibrosis and the CA is also considered. The new model treats the domains as anisotropic media and imposes a closed loop of intravascular flow, which is necessary to reproduce the recirculation of the CA. The model parameters were adjusted to reproduce clinical data. In addition, the model was used to simulate different scenarios: normal perfusion; endocardial ischemia due to stenosis in a coronary artery in the epicardium; and myocardial infarct. Therefore, the computational model was able to correlate anatomical features, stenosis and the presence of fibrosis, with functional ones, cardiac perfusion. Altogether, the results suggest that the model can support the process of non-invasive cardiac perfusion quantification.
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Affiliation(s)
- João R Alves
- Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
| | - Rafael A B de Queiroz
- Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
| | - Markus Bär
- Department of Mathematical Modeling and Data Analysis, Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | - Rodrigo W Dos Santos
- Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
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16
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Lehnert J, Wübbeler G, Kolbitsch C, Chiribiri A, Coquelin L, Ebrard G, Smith N, Schaeffter T, Elster C. Pixel-wise quantification of myocardial perfusion using spatial Tikhonov regularization. Phys Med Biol 2018; 63:215017. [PMID: 30372423 DOI: 10.1088/1361-6560/aae758] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Quantification of myocardial perfusion by contrast-enhanced cardiovascular magnetic resonance imaging (CMR) aims for an observer independent and reproducible risk assessment of cardiovascular disease. Currently, the data used for the pixel-wise analysis of cardiac perfusion are either filtered prior to a fitting procedure, which inherently reduces the spatial resolution of data; or all pixels are considered without any regularization or prior filtering, which yields an unstable fit in the presence of low signal-to-noise ratio. Here, we propose a new pixel-wise analysis based on spatial Tikhonov regularization which exploits the spatial smoothness of the data and ensures accurate quantification even for images with low signal-to-noise ratio. The regularization parameter is determined automatically by an L-curve criterion. We study the performance of our method on a numerical phantom and demonstrate that the method reduces significantly the root-mean square error in the perfusion estimate compared to a non-regularized fit. In patient data our method allows us to recover the myocardial perfusion and to distinguish between healthy and ischemic regions.
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Affiliation(s)
- Judith Lehnert
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany. Author to whom any correspondence should be addressed
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O'Doherty J, Sammut E, Schleyer P, Stirling J, Nazir MS, Marsden PK, Chiribiri A. Feasibility of simultaneous PET-MR perfusion using a novel cardiac perfusion phantom. Eur J Hybrid Imaging 2017; 1:4. [PMID: 29782598 PMCID: PMC5954708 DOI: 10.1186/s41824-017-0008-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Accepted: 09/01/2017] [Indexed: 01/29/2023] Open
Abstract
Background PET-MR scanners are beginning to be employed for quantitative myocardial perfusion imaging. In order to examine simultaneous perfusion calculations, this work describes a feasibility study of simultaneous PET-MR of gadolinium-based contrast agent (GBCA) and PET radiotracer in a novel cardiac perfusion phantom. Results [18F]F− and GBCA were injected simultaneously into a cardiac phantom using a range of ground-truth myocardial perfusion rates of 1 to 5 ml/g/min. PET quantification of K1 (ml/g/min) was performed using a single tissue compartment model. MR perfusion was calculated using a model-independent signal deconvolution technique. PET and MR signal traces from the phantom aorta and myocardial sections show true simultaneous PET and MR arterial input functions (AIF) and myocardial uptake respectively at each perfusion rate. Calculation of perfusion parameters showed both K1 and h(t = 0) (PET and MR perfusion parameters respectively) to be linearly related with the ground truth perfusion rate (PT), and also linearly related to each other (R2 = 0.99). The highest difference in perfusion values between K1 and PT was 16% at 1 ml/g/min, and the mean difference for all other perfusion rates was <3%. Conclusions The perfusion phantom allows accurate and reproducible simulation of the myocardial kinetics for simultaneous PET-MR imaging, and may find use in protocol design and development of PET-MR based quantification techniques and direct comparison of quantification of the two modalities.
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Affiliation(s)
- Jim O'Doherty
- 1Division of Imaging Sciences and Biomedical Engineering, PET Imaging Centre, King's College London, St. Thomas' Hospital, 1st Floor Lambeth Wing, St Thomas' Hospital, London, SE1 7EH UK
| | - Eva Sammut
- 2Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St. Thomas' Hospital, London, UK.,3Bristol Heart Institute, Bristol, UK
| | | | - James Stirling
- 1Division of Imaging Sciences and Biomedical Engineering, PET Imaging Centre, King's College London, St. Thomas' Hospital, 1st Floor Lambeth Wing, St Thomas' Hospital, London, SE1 7EH UK
| | - Muhummad Sohaib Nazir
- 2Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St. Thomas' Hospital, London, UK.,5Department of Cardiology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Paul K Marsden
- 1Division of Imaging Sciences and Biomedical Engineering, PET Imaging Centre, King's College London, St. Thomas' Hospital, 1st Floor Lambeth Wing, St Thomas' Hospital, London, SE1 7EH UK
| | - Amedeo Chiribiri
- 2Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St. Thomas' Hospital, London, UK.,5Department of Cardiology, Guy's and St Thomas' NHS Foundation Trust, London, UK
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Likhite D, Suksaranjit P, Adluru G, Wilson B, DiBella E. Estimating extraction fraction and blood flow by combining first-pass myocardial perfusion and T1 mapping results. Quant Imaging Med Surg 2017; 7:480-495. [PMID: 29184761 DOI: 10.21037/qims.2017.08.07] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Background Quantifying myocardial perfusion is complicated by the complexity of pharmacokinetic model being used and the reliability of perfusion parameter estimates. More complex modeling provides more information about the underlying physiology, but too many parameters in complex models introduce a new problem of reliable estimation. To overcome the problem of multiple parameters, we have developed a technique that combines knowledge from two different cardiac magnetic resonance (MR) imaging techniques: dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and T1 mapping. Using extracellular volume (ECV) estimates from T1 mapping may allow more robust model parameter estimates. Methods Simulations and human scans were performed. The myocardial perfusion scans used an ungated saturation recovery prepared TurboFLASH pulse sequence. Four short-axis (SA) slices were acquired after a single saturation pulse with a saturation recovery time of ~25 ms before the first slice. Gadoteridol was injected and ~240 frames were acquired over a minute with shallow breathing and no electrocardiograph (ECG) gating. This was followed 20±5 minutes later by an injection of regadenoson to induce hyperemia. The data were acquired using an under-sampled golden angle radial acquisition. Modified look-locker inversion recovery (MOLLI) T1 mapping was performed in 3 slices pre- and post-contrast. The pre- and post-contrast T1 maps were used for ECV estimation. Quantification of perfusion was done using a 4-parameter model with additional information about ECV supplied during model fitting. Phase contrast scans of the coronary sinus (CS) were acquired at rest and immediately after the stress perfusion acquisition to estimate global flow. Results Without ECV information, the 5-parameter model fails to converge to a unique solution and often gives incorrect estimates for the perfusion parameters. The myocardial blood flow (MBF) estimates during rest and stress were 0.9±0.1 and 2.3±0.6 mL/min/g, respectively. The extraction fraction estimates were 0.49±0.04 and 0.34±0.05 during rest and stress, respectively. Conclusions These results show that it is possible to successfully fit a dynamic perfusion model with an extraction fraction parameter by using information from T1 mapping scans. This hybrid approach is especially important when the 5-parameter model alone fails to converge on a unique solution. This work is a good example of exploiting information overlaps between various cardiac MR imaging techniques.
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Affiliation(s)
- Devavrat Likhite
- Department of Radiology and Imaging Sciences, Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT, USA
| | | | - Ganesh Adluru
- Department of Radiology and Imaging Sciences, Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT, USA
| | - Brent Wilson
- Division of Cardiology, University of Utah, Salt Lake City, UT, USA
| | - Edward DiBella
- Department of Radiology and Imaging Sciences, Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT, USA.,Department of Bioengineering, University of Utah, Salt Lake City, UT, USA
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19
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Pelgrim GJ, Das M, van Tuijl S, van Assen M, Prinzen FW, Stijnen M, Oudkerk M, Wildberger JE, Vliegenthart R. Validation of myocardial perfusion quantification by dynamic CT in an ex-vivo porcine heart model. Int J Cardiovasc Imaging 2017; 33:1821-1830. [PMID: 28536897 PMCID: PMC5682851 DOI: 10.1007/s10554-017-1171-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 05/17/2017] [Indexed: 12/23/2022]
Abstract
To test the accuracy of quantification of myocardial perfusion imaging (MPI) using computed tomography (CT) in ex-vivo porcine models. Five isolated porcine hearts were perfused according to Langendorff. Hearts were perfused using retrograde flow through the aorta and blood flow, blood pressure and heart rate were monitored throughout the experiment. An inflatable cuff was placed around the circumflex (Cx) artery to create stenosis grades which were monitored using a pressure wire, analysing perfusion at several fractional flow reserve values of 1.0, 0.7, 0.5, 0.3, and total occlusion. Second-generation dual-source CT was used to acquire dynamic MPI in shuttle mode with 350 mAs/rot at 100 kVp. CT MPI was performed using VPCT myocardium software, calculating myocardial blood flow (MBF, ml/100 ml/min) for segments perfused by Cx artery and non-Cx myocardial segments. Microspheres were successfully infused at three stenosis grades in three of the five hearts. Heart rate ranged from 75 to 134 beats per minute. Arterial blood flow ranged from 0.5 to 1.4 l min and blood pressure ranged from 54 to 107 mmHg. MBF was determined in 400 myocardial segments of which 115 were classified as ‘Cx-territory’. MBF was significantly different between non-Cx and Cx segments at stenosis grades with an FFR ≤0.70 (Mann–Whitney U test, p < 0.05). MBF showed a moderate correlation with microsphere MBF for the three individual hearts (Pearson correlation 0.62–0.76, p < 0.01). CT MPI can be used to determine regional differences in myocardial perfusion parameters, based on severity of coronary stenosis. Significant differences in MBF could be measured between non-ischemic and ischemic segments.
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Affiliation(s)
- Gert Jan Pelgrim
- Center for Medical Imaging - North East Netherlands, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box EB44, 9713 GZ, Groningen, The Netherlands
| | - Marco Das
- Department of Radiology and Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, The Netherlands
| | | | - Marly van Assen
- Center for Medical Imaging - North East Netherlands, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box EB44, 9713 GZ, Groningen, The Netherlands
| | - Frits W Prinzen
- Department of Physiology, Maastricht University, Maastricht, The Netherlands
| | | | - Matthijs Oudkerk
- Center for Medical Imaging - North East Netherlands, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box EB44, 9713 GZ, Groningen, The Netherlands
| | - Joachim E Wildberger
- Department of Radiology and Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, The Netherlands
| | - Rozemarijn Vliegenthart
- Center for Medical Imaging - North East Netherlands, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box EB44, 9713 GZ, Groningen, The Netherlands.
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Hoffman JIE. The history of the microsphere method for measuring blood flows with special reference to myocardial blood flow: a personal memoir. Am J Physiol Heart Circ Physiol 2017; 312:H705-H710. [PMID: 28130341 DOI: 10.1152/ajpheart.00834.2016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 01/09/2017] [Accepted: 01/19/2017] [Indexed: 11/22/2022]
Abstract
We use many types of equipment and technologies to make our measurements but give little thought to how they developed. Evolution was once described as a series of recoils from blind alleys, and this is exemplified by the gradual development of the microsphere method of measuring blood flows. The microsphere method is one of the most frequently used methods for measuring blood flow to organs and portions of organs. The method can measure myocardial blood flow with reasonable accuracy (within 10%) down to samples weighing >50 mg but probably will not do so for samples weighing 1-10 mg. Microspheres with diameters from 10 to 15 μm provide the best compromise between accurate flow measurement and retention in tissue. Radioactive labels have been almst entirely replaced by fluorescent labels, but colored microspheres and neutron-activated labels are also used.NEW & NOTEWORTHY The contributions of the various individuals who developed the microsphere method of measuring regional blood flows and how these advances took place are brought to light in this paper.
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Affiliation(s)
- Julien I E Hoffman
- Department of Pediatrics, University of California, San Francisco, California
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21
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Villa ADM, Sammut E, Zarinabad N, Carr-White G, Lee J, Bettencourt N, Razavi R, Nagel E, Chiribiri A. Microvascular ischemia in hypertrophic cardiomyopathy: new insights from high-resolution combined quantification of perfusion and late gadolinium enhancement. J Cardiovasc Magn Reson 2016; 18:4. [PMID: 26767610 PMCID: PMC4714488 DOI: 10.1186/s12968-016-0223-8] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2015] [Accepted: 01/05/2016] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Microvascular ischemia is one of the hallmarks of hypertrophic cardiomyopathy (HCM) and has been associated with poor outcome. However, myocardial fibrosis, seen on cardiovascular magnetic resonance (CMR) as late gadolinium enhancement (LGE), can be responsible for rest perfusion defects in up to 30% of patients with HCM, potentially leading to an overestimation of the ischemic burden. We investigated the effect of left ventricle (LV) scar on the total LV ischemic burden using novel high-resolution perfusion analysis techniques in conjunction with LGE quantification. METHODS 30 patients with HCM and unobstructed epicardial coronary arteries underwent CMR with Fermi constrained quantitative perfusion analysis on segmental and high-resolution data. The latter were corrected for the presence of fibrosis on a pixel-by-pixel basis. RESULTS High-resolution quantification proved more sensitive for the detection of microvascular ischemia in comparison to segmental analysis. Areas of LGE were associated with significant reduction of myocardial perfusion reserve (MPR) leading to an overestimation of the total ischemic burden on non-corrected perfusion maps. Using a threshold MPR of 1.5, the presence of LGE caused an overestimation of the ischemic burden of 28%. The ischemic burden was more severe in patients with fibrosis, also after correction of the perfusion maps, in keeping with more severe disease in this subgroup. CONCLUSIONS LGE is an important confounder in the assessment of the ischemic burden in patients with HCM. High-resolution quantitative analysis with LGE correction enables the independent evaluation of microvascular ischemia and fibrosis and should be used when evaluating patients with HCM.
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Affiliation(s)
- Adriana D M Villa
- Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St Thomas' Hospital, London, UK.
| | - Eva Sammut
- Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St Thomas' Hospital, London, UK.
| | - Niloufar Zarinabad
- Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St Thomas' Hospital, London, UK.
| | | | - Jack Lee
- Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St Thomas' Hospital, London, UK.
| | | | - Reza Razavi
- Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St Thomas' Hospital, London, UK.
| | - Eike Nagel
- DZHK Centre for Cardiovascular Imaging, University Hospital Frankfurt / Main, Frankfurt am Main, Germany.
| | - Amedeo Chiribiri
- Division of Imaging Sciences, King's College London, Wellcome Trust/EPSRC Medical Engineering Centre, St Thomas' Hospital, London, UK.
- Division of Imaging Sciences and Biomedical Engineering, King's College London, The Rayne Institute - 4th Floor Lambeth Wing, St Thomas' Hospital, SE1 7EH, London, UK.
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Chiribiri A, Villa ADM, Sammut E, Breeuwer M, Nagel E. Perfusion dyssynchrony analysis. Eur Heart J Cardiovasc Imaging 2015; 17:1414-1423. [PMID: 26705485 PMCID: PMC5155575 DOI: 10.1093/ehjci/jev326] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 11/08/2015] [Indexed: 11/14/2022] Open
Abstract
AIMS We sought to describe perfusion dyssynchrony analysis specifically to exploit the high temporal resolution of stress perfusion CMR. This novel approach detects differences in the temporal distribution of the wash-in of contrast agent across the left ventricular wall. METHODS AND RESULTS Ninety-eight patients with suspected coronary artery disease (CAD) were retrospectively identified. All patients had undergone perfusion CMR at 3T and invasive angiography with fractional flow reserve (FFR) of lesions visually judged >50% stenosis. Stress images were analysed using four different perfusion dyssynchrony indices: the variance and coefficient of variation of the time to maximum signal upslope (V-TTMU and C-TTMU) and the variance and coefficient of variation of the time to peak myocardial signal enhancement (V-TTP and C-TTP). Patients were classified according to the number of vessels with haemodynamically significant CAD indicated by FFR <0.8. All indices of perfusion dyssynchrony were capable of identifying the presence of significant CAD. C-TTP >10% identified CAD with sensitivity 0.889, specificity 0.857 (P < 0.0001). All indices correlated with the number of diseased vessels. C-TTP >12% identified multi-vessel disease with sensitivity 0.806, specificity 0.657 (P < 0.0001). C-TTP was also the dyssynchrony index with the best inter- and intra-observer reproducibility. Perfusion dyssynchrony indices showed weak correlation with other invasive and non-invasive measurements of the severity of ischaemia, including FFR, visual ischaemic burden, and MPR. CONCLUSION These findings suggest that perfusion dyssynchrony analysis is a robust novel approach to the analysis of first-pass perfusion and has the potential to add complementary information to aid assessment of CAD.
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Affiliation(s)
- Amedeo Chiribiri
- Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Adriana D M Villa
- Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Eva Sammut
- Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Marcel Breeuwer
- Philips Healthcare, Imaging Systems-MR Eindhoven, The Netherlands.,Eindhoven University of Technology, Biomedical Engineering, Biomedical Image Analysis, Eindhoven, The Netherlands
| | - Eike Nagel
- Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.,DZHK Centre for Cardiovascular Imaging, University Hospital Frankfurt/Main, Frankfurt am Main, Germany
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