1
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Sharrack N, Brown LA, Farley J, Wahab A, Jex N, Thirunavukarasu S, Chowdhary A, Gorecka M, Javed W, Xue H, Levelt E, Dall'Armellina E, Kellman P, Garg P, Greenwood JP, Plein S, Swoboda PP. Occult coronary microvascular dysfunction and ischaemic heart disease in patients with diabetes and heart failure. J Cardiovasc Magn Reson 2024:101073. [PMID: 39096970 DOI: 10.1016/j.jocmr.2024.101073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 07/03/2024] [Accepted: 07/26/2024] [Indexed: 08/05/2024] Open
Abstract
BACKGROUND Patients with diabetes (DM) and heart failure (HF) have worse outcomes than normoglycaemic HF patients. Cardiovascular magnetic resonance (CMR) can identify ischaemic heart disease (IHD) and quantify coronary microvascular dysfunction (CMD) using myocardial perfusion reserve (MPR). We aimed to quantify extent of silent IHD and CMD in patients with DM presenting with HF. METHODS Prospectively recruited outpatients undergoing assessment into the aetiology of HF underwent inline quantitative perfusion CMR for calculation of stress and rest myocardial blood flow (MBF) and MPR. Exclusions included angina or history of IHD. Patients were followed up (median 3.0 years) for major adverse cardiovascular events (MACE). RESULTS Final analysis included 343 patients (176 normoglycaemic, 84 with pre-diabetes and 83 with DM). Prevalence of silent IHD was highest in DM (31%), then pre-diabetes (20%) then normoglycaemia (17%). Stress MBF was lowest in DM (1.53±0.52), then pre-diabetes (1.59±0.54) then normoglycaemia (1.83±0.62). MPR was lowest in DM (2.37±0.85) then pre-diabetes (2.41±0.88) then normoglycaemia (2.61±0.90). During follow up 45 patients experienced at least one MACE. On univariate Cox regression analysis MPR and presence of silent IHD were both associated with MACE. However, after correction for HbA1c, age and left ventricular ejection fraction the associations were no longer significant. CONCLUSIONS Patients with DM and HF had higher prevalence of silent IHD, more evidence of CMD and worse cardiovascular outcomes than their non-diabetic counterparts. These findings highlight the potential value of CMR for assessment of silent IHD and CMD in patients with DM presenting with HF.
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Affiliation(s)
- Noor Sharrack
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Louise Ae Brown
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Jonathan Farley
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Ali Wahab
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Nicholas Jex
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Sharmaine Thirunavukarasu
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Amrit Chowdhary
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Miroslawa Gorecka
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Wasim Javed
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Hui Xue
- National Institutes for Health, National Heart, Lung, and Blood Institute, Bethesda, United States of America
| | - Eylem Levelt
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Erica Dall'Armellina
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter Kellman
- National Institutes for Health, National Heart, Lung, and Blood Institute, Bethesda, United States of America
| | - Pankaj Garg
- Cardiovascular and Metabolic Medicine Group, Norwich Medical School, University of East Anglia, Norwich, UK
| | - John P Greenwood
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Sven Plein
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter P Swoboda
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
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2
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Zhao L, Chen BH, Tang H, Wang YY, Gu ZY, An DA, Wu LM, Xue S. The association between cardiac T2*BOLD and quantitative flow ratio (QFR) in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease. LA RADIOLOGIA MEDICA 2024; 129:1184-1196. [PMID: 38997567 DOI: 10.1007/s11547-024-01847-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 07/01/2024] [Indexed: 07/14/2024]
Abstract
BACKGROUND T2*BOLD is based on myocardial deoxyhemoglobin content to reflect the state of myocardial oxygenation. Quantitative flow ratio is a tool for assessing coronary blood flow based on invasive coronary angiography. PURPOSE This study aimed to evaluate the correlation between T2*BOLD and QFR in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease. METHODS Fifty patients with MVCAD with at least 1 significant coronary artery stenosis (diameter stenosis > 50%) and 21 healthy control subjects underwent coronary angiography combined with QFR measurements and cardiovascular magnetic resonance (CMR). QFR ≤ 0.80 was considered to indicate the presence of hemodynamic obstruction. RESULTS Totally 60 (54%) obstructive vessels had hemodynamic change. Between stenotic coronary arteries (QFR ≤ 0.8) and normal vessels, T2*BOLD showed AUCs of 0.97, 0.69, and 0.91 for left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries and PI displayed AUCs of 0.89, 0.77 and 0.90 (all p > 0.05, except for LAD). The AUCs of T2*BOLD between stenotic coronary arteries (QFR > 0.8) and normal vessels were 0.86, 0.72, and 0.85 for LAD, LCX and RCA; while, PI showed AUCs of 0.93, 0.86, and 0.88, respectively (p > 0.05). Moreover, T2*BOLD displayed AUCs of 0.96, 0.74, and 0.91 for coronary arteries as before between coronary arteries with stenosis (QFR ≤ 0.8 and > 0.8), but the mean PI of LAD, LCX and RCA showed no significant differences between them. CONCLUSION T2* BOLD and QFR have good correlation in diagnosing stenotic coronary arteries with hemodynamic changes in patients with stable multi-vessel CAD. T2* BOLD is superior to semi-quantitative perfusion imaging in analyzing myocardial ischemia without stress.
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Affiliation(s)
- Lei Zhao
- Department of Cardiovascular Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China
| | - Bing-Hua Chen
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China
| | - Hui Tang
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China
| | - Yong-Yi Wang
- Department of Cardiovascular Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China
| | - Zi-Yi Gu
- Department of Cardiovascular Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China
| | - Dong-Aolei An
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China
| | - Lian-Ming Wu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China.
| | - Song Xue
- Department of Cardiovascular Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, People's Republic of China.
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3
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Włodarczak S, Rola P, Jastrzębski A, Turkiewicz K, Korda A, Włodarczak P, Barycki M, Kulczycki JJ, Furtan Ł, Włodarczak A, Lesiak M. Safety and Effectiveness of Coronary Sinus Reducer in the Therapy of Refractory Angina Pectoris-Mid-Term Results of the Real-Life Cohort. J Clin Med 2024; 13:4413. [PMID: 39124680 PMCID: PMC11313317 DOI: 10.3390/jcm13154413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 07/07/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
Background: Despite continuous improvements in revascularization techniques, refractory angina without potential revascularization options remains a relevant clinical issue with significant impact on the patient's quality of life. Recently, a novel device, the Coronary Sinus Reducer (CSR), has been introduced into clinical practice as a therapeutic option for patients with disabling angina pectoris. In this single-center, observational study, we evaluated the mid-term (3-month) safety and efficacy of the CSR in a real-world cohort. Methods: The study population consisted of 55 patients with refractory angina without potential revascularization options, who were predominantly men (87.3%) with a high cardiovascular risk factor burden and advanced angina (baseline CCS angina class 3.15 ± 0.6). In terms of procedure safety, all patients underwent successful device deployment with only one periprocedural complication. Results: At the 3-month follow-up, we observed a statistically significant improvement in angina control measured CCS class and SAQ-7 total questionnaire along with increased abolition of physical limitation-6-MWT (233.3 ± 107.1 vs. 305.2 ± 126.8; p < 0.0001). Additionally, we observed significant improvement in terms of quality of life measurements SF-36, the EQ-5D-5L questionnaire, and the EQ-VAS. Conclusions: Our real-world data suggest that CSR implantation is a relatively safe procedure and appears to be particularly effective in relieving angina symptoms and improving quality of life in subjects with refractory angina.
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Affiliation(s)
- Szymon Włodarczak
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Piotr Rola
- Department of Cardiology, Provincial Specialized Hospital, 59-200 Legnica, Poland; (P.R.); (M.B.); (Ł.F.)
| | - Artur Jastrzębski
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Karol Turkiewicz
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Andrzej Korda
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Piotr Włodarczak
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Mateusz Barycki
- Department of Cardiology, Provincial Specialized Hospital, 59-200 Legnica, Poland; (P.R.); (M.B.); (Ł.F.)
| | - Jan Jakub Kulczycki
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Łukasz Furtan
- Department of Cardiology, Provincial Specialized Hospital, 59-200 Legnica, Poland; (P.R.); (M.B.); (Ł.F.)
| | - Adrian Włodarczak
- Department of Cardiology, Copper Health Centre (MCZ), 59-300 Lubin, Poland; (A.J.); (K.T.); (A.K.); (P.W.); (J.J.K.); (A.W.)
| | - Maciej Lesiak
- 1st Department of Cardiology, University of Medical Sciences, 61-701 Poznan, Poland;
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4
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Sliwicka O, Oostveen LJ, Swiderska Chadaj Z, van Everdingen WM, Michielsen K, Gommers J, Brink M, Snoeren M, Salah K, Peters-Bax L, Stille T, Habets J, Sechopoulos I. Radiation dose reduction of 50% in dynamic myocardial CT perfusion with skipped beat acquisition: a retrospective study. Acta Radiol 2024; 65:724-734. [PMID: 38630492 DOI: 10.1177/02841851241240446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
BACKGROUND Dynamic myocardial computed tomography perfusion (CTP) is a novel imaging technique that increases the applicability of CT for cardiac imaging; however, the scanning requires a substantial radiation dose. PURPOSE To investigate the feasibility of dose reduction in dynamic CTP by comparing all-heartbeat acquisitions to periodic skipping of heartbeats. MATERIAL AND METHODS We retrieved imaging data of 38 dynamic CTP patients and created new datasets with every fourth, third or second beat (Skip1:4, Skip1:3, Skip1:2, respectively) removed. Seven observers evaluated the resulting images and perfusion maps for perfusion deficits. The mean blood flow (MBF) in each of the 16 myocardial segments was compared per skipped-beat level, normalized by the respective MBF for the full dose, and averaged across patients. The number of segments/cases whose MBF was <1.0 mL/g/min were counted. RESULTS Out of 608 segments in 38 cases, the total additional number of false-negative (FN) segments over those present in the full-dose acquisitions and the number of additional false-positive cases were shown as acquisition (segment [%], case): Skip1:4: 7 (1.2%, 1); Skip1:3: 12 (2%, 3), and Skip1:2: 5 (0.8%, 2). The variability in quantitative MBF analysis in the repeated analysis for the reference condition resulted in 8 (1.3%) additional FN segments. The normalized results show a comparable MBF across all segments and patients, with relative mean MBFs as 1.02 ± 0.16, 1.03 ± 0.25, and 1.06 ± 0.30 for the Skip1:4, Skip1:3, and Skip1:2 protocols, respectively. CONCLUSION Skipping every second beat acquisition during dynamic myocardial CTP appears feasible and may result in a radiation dose reduction of 50%. Diagnostic performance does not decrease after removing 50% of time points in dynamic sequence.
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Affiliation(s)
- Olga Sliwicka
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Luuk J Oostveen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | | | - Koen Michielsen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jessie Gommers
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Monique Brink
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Miranda Snoeren
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Khibar Salah
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Liesbeth Peters-Bax
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tip Stille
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jesse Habets
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Radiology, Haaglanden Medical Center, The Hague, The Netherlands
| | - Ioannis Sechopoulos
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Technical Medicine Center, University of Twente, Enschede, The Netherlands
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5
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Foley MJ, Rajkumar CA, Ahmed-Jushuf F, Simader FA, Chotai S, Pathimagaraj RH, Mohsin M, Salih A, Wang D, Dixit P, Davies JR, Keeble TR, Cosgrove C, Spratt JC, O'Kane PD, De Silva R, Hill JM, Nijjer SS, Sen S, Petraco R, Mikhail GW, Khamis R, Kotecha T, Harrell FE, Kellman P, Francis DP, Howard JP, Cole GD, Shun-Shin MJ, Al-Lamee RK. Coronary sinus reducer for the treatment of refractory angina (ORBITA-COSMIC): a randomised, placebo-controlled trial. Lancet 2024; 403:1543-1553. [PMID: 38604209 DOI: 10.1016/s0140-6736(24)00256-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/04/2024] [Accepted: 02/07/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The coronary sinus reducer (CSR) is proposed to reduce angina in patients with stable coronary artery disease by improving myocardial perfusion. We aimed to measure its efficacy, compared with placebo, on myocardial ischaemia reduction and symptom improvement. METHODS ORBITA-COSMIC was a double-blind, randomised, placebo-controlled trial conducted at six UK hospitals. Patients aged 18 years or older with angina, stable coronary artery disease, ischaemia, and no further options for treatment were eligible. All patients completed a quantitative adenosine-stress perfusion cardiac magnetic resonance scan, symptom and quality-of-life questionnaires, and a treadmill exercise test before entering a 2-week symptom assessment phase, in which patients reported their angina symptoms using a smartphone application (ORBITA-app). Patients were randomly assigned (1:1) to receive either CSR or placebo. Both participants and investigators were masked to study assignment. After the CSR implantation or placebo procedure, patients entered a 6-month blinded follow-up phase in which they reported their daily symptoms in the ORBITA-app. At 6 months, all assessments were repeated. The primary outcome was myocardial blood flow in segments designated ischaemic at enrolment during the adenosine-stress perfusion cardiac magnetic resonance scan. The primary symptom outcome was the number of daily angina episodes. Analysis was done by intention-to-treat and followed Bayesian methodology. The study is registered with ClinicalTrials.gov, NCT04892537, and completed. FINDINGS Between May 26, 2021, and June 28, 2023, 61 patients were enrolled, of whom 51 (44 [86%] male; seven [14%] female) were randomly assigned to either the CSR group (n=25) or the placebo group (n=26). Of these, 50 patients were included in the intention-to-treat analysis (24 in the CSR group and 26 in the placebo group). 454 (57%) of 800 imaged cardiac segments were ischaemic at enrolment, with a median stress myocardial blood flow of 1·08 mL/min per g (IQR 0·77-1·41). Myocardial blood flow in ischaemic segments did not improve with CSR compared with placebo (difference 0·06 mL/min per g [95% CrI -0·09 to 0·20]; Pr(Benefit)=78·8%). The number of daily angina episodes was reduced with CSR compared with placebo (OR 1·40 [95% CrI 1·08 to 1·83]; Pr(Benefit)=99·4%). There were two CSR embolisation events in the CSR group, and no acute coronary syndrome events or deaths in either group. INTERPRETATION ORBITA-COSMIC found no evidence that the CSR improved transmural myocardial perfusion, but the CSR did improve angina compared with placebo. These findings provide evidence for the use of CSR as a further antianginal option for patients with stable coronary artery disease. FUNDING Medical Research Council, Imperial College Healthcare Charity, National Institute for Health and Care Research Imperial Biomedical Research Centre, St Mary's Coronary Flow Trust, British Heart Foundation.
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Affiliation(s)
- Michael J Foley
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | - Christopher A Rajkumar
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | | | | | - Shayna Chotai
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Rachel H Pathimagaraj
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | - Muhammad Mohsin
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Ahmed Salih
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Danqi Wang
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Prithvi Dixit
- National Heart and Lung Institute, Imperial College London, London, UK
| | - John R Davies
- Essex Cardiothoracic Centre, Mid and South Essex NHS Foundation Trust, Basildon, UK; Medical Technology Research Centre, Anglia Ruskin University School of Medicine, Chelmsford, UK
| | - Tom R Keeble
- Essex Cardiothoracic Centre, Mid and South Essex NHS Foundation Trust, Basildon, UK; Medical Technology Research Centre, Anglia Ruskin University School of Medicine, Chelmsford, UK
| | - Claudia Cosgrove
- St George's University Hospitals NHS Foundation Trust, London, UK; St George's, University of London, London, UK
| | - James C Spratt
- St George's University Hospitals NHS Foundation Trust, London, UK; St George's, University of London, London, UK
| | - Peter D O'Kane
- University Hospitals of Dorset NHS Foundation Trust, Bournemouth, UK
| | - Ranil De Silva
- The Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Jonathan M Hill
- The Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | | | - Sayan Sen
- Imperial College Healthcare NHS Trust, London, UK
| | | | | | - Ramzi Khamis
- Imperial College Healthcare NHS Trust, London, UK
| | | | - Frank E Harrell
- Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Peter Kellman
- Department of Health and Human Services, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Darrel P Francis
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | - James P Howard
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | - Graham D Cole
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | - Matthew J Shun-Shin
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK
| | - Rasha K Al-Lamee
- National Heart and Lung Institute, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK.
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6
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Karagodin I, Wang S, Wang H, Singh A, Gutbrod J, Landeras L, Patel H, Alvi N, Tang M, Benovoy M, Janich MA, Benjamin HJ, Chung JH, Patel AR. Myocardial Blood Flow Quantified Using Stress Cardiac Magnetic Resonance After Mild COVID-19 Infection. JACC. ADVANCES 2024; 3:100834. [PMID: 38433786 PMCID: PMC10906962 DOI: 10.1016/j.jacadv.2024.100834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/22/2023] [Accepted: 09/07/2023] [Indexed: 03/05/2024]
Abstract
BACKGROUND Severe COVID-19 infection is known to alter myocardial perfusion through its effects on the endothelium and microvasculature. However, the majority of patients with COVID-19 infection experience only mild symptoms, and it is unknown if their myocardial perfusion is altered after infection. OBJECTIVES The authors aimed to determine if there are abnormalities in myocardial blood flow (MBF), as measured by stress cardiac magnetic resonance (CMR), in individuals after a mild COVID-19 infection. METHODS We conducted a prospective, comparative study of individuals who had a prior mild COVID-19 infection (n = 30) and matched controls (n = 26) using stress CMR. Stress and rest myocardial blood flow (sMBF, rMBF) were quantified using the dual sequence technique. Myocardial perfusion reserve was calculated as sMBF/rMBF. Unpaired t-tests were used to test differences between the groups. RESULTS The median time interval between COVID-19 infection and CMR was 5.6 (IQR: 4-8) months. No patients with the COVID-19 infection required hospitalization. Symptoms including chest pain, shortness of breath, syncope, and palpitations were more commonly present in the group with prior COVID-19 infection than in the control group (57% vs 7%, P < 0.001). No significant differences in rMBF (1.08 ± 0.27 mL/g/min vs 0.97 ± 0.29 mL/g/min, P = 0.16), sMBF (3.08 ± 0.79 mL/g/min vs 3.06 ± 0.89 mL/g/min, P = 0.91), or myocardial perfusion reserve (2.95 ± 0.90 vs 3.39 ± 1.25, P = 0.13) were observed between the groups. CONCLUSIONS This study suggests that there are no significant abnormalities in rest or stress myocardial perfusion, and thus microvascular function, in individuals after mild COVID-19 infection.
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Affiliation(s)
- Ilya Karagodin
- Department of Medicine, NorthShore University Health System in Evanston, Chicago, Illinois, USA
| | - Shuo Wang
- Division of Cardiovascular Medicine, The University of Virginia Health System, Charlottesville, Virginia, USA
| | | | - Amita Singh
- Department of Cardiology, Central Dupage Hospital, Winfield, Illinois, USA
| | - Joseph Gutbrod
- Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Luis Landeras
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Hena Patel
- Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Nazia Alvi
- Department of Cardiology, Advent Health Heart and Vascular Institute, Chicago, Illinois, USA
| | - Maxine Tang
- Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | | | | | - Holly J. Benjamin
- Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Jonathan H. Chung
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Amit R. Patel
- Division of Cardiovascular Medicine, The University of Virginia Health System, Charlottesville, Virginia, USA
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7
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Foley MJ, Rajkumar CA, Ahmed-Jushuf F, Simader F, Pathimagaraj RH, Nijjer S, Sen S, Petraco R, Clesham G, Johnson T, Harrell FE, Kellman P, Francis D, Shun-Shin M, Howard J, Cole GD, Al-Lamee R. A double-blind, randomised, placebo-controlled trial of the coronary sinus Reducer in refractory angina: design and rationale of the ORBITA-COSMIC trial. EUROINTERVENTION 2024; 20:e216-e223. [PMID: 38214677 PMCID: PMC10836388 DOI: 10.4244/eij-d-23-00567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/12/2023] [Indexed: 01/13/2024]
Abstract
The coronary sinus Reducer (CSR) is an hourglass-shaped device which creates an artificial stenosis in the coronary sinus. Whilst placebo-controlled data show an improvement in angina, these results are unreplicated and are the subject of further confirmatory research. The mechanism of action of this unintuitive therapy is unknown. The Coronary Sinus Reducer Objective Impact on Symptoms, MRI Ischaemia, and Microvascular Resistance (ORBITA-COSMIC) trial is a randomised, placebo-controlled, double-blind trial investigating the efficacy of the CSR. Patients with (i) established epicardial coronary artery disease, (ii) angina on maximally tolerated antianginal medication, (iii) evidence of myocardial ischaemia and (iv) no further options for percutaneous coronary intervention or coronary artery bypass grafting will be enrolled. Upon enrolment, angina and quality-of-life questionnaires, treadmill exercise testing and quantitative stress perfusion cardiac magnetic resonance (CMR) imaging will be performed. Participants will record their symptoms daily on a smartphone application throughout the trial. After a 2-week symptom assessment phase, participants will be randomised in the cardiac catheterisation laboratory to CSR or a placebo procedure. After 6 months of blinded follow-up, all prerandomisation tests will be repeated. A prespecified subgroup will undergo invasive coronary physiology assessment at prerandomisation and follow-up. The primary outcome is stress myocardial blood flow on CMR. Secondary outcomes include angina frequency, quality of life and treadmill exercise time. (ClinicalTrials.gov: NCT04892537).
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Affiliation(s)
- Michael J Foley
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Christopher A Rajkumar
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Fiyyaz Ahmed-Jushuf
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Florentina Simader
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Rachel H Pathimagaraj
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Sukhjinder Nijjer
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Sayan Sen
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Ricardo Petraco
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | | | - Thomas Johnson
- Bristol Heart Institute, University Hospitals Bristol NHS Foundation Trust, Bristol, United Kingdom
| | - Frank E Harrell
- Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA
| | - Darrel Francis
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Matthew Shun-Shin
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - James Howard
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Graham D Cole
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Rasha Al-Lamee
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
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8
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Wang Y, Yin X. Modelling coronary flow and myocardial perfusion by integrating a structured-tree coronary flow model and a hyperelastic left ventricle model. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107928. [PMID: 38000321 DOI: 10.1016/j.cmpb.2023.107928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/02/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND AND OBJECTIVE There is an increasing demand to establish integrated computational models that facilitate the exploration of coronary circulation in physiological and pathological contexts, particularly concerning interactions between coronary flow dynamics and myocardial motion. The field of cardiology has also demonstrated a trend toward personalised medicine, where these integrated models can be instrumental in integrating patient-specific data to improve therapeutic outcomes. Notably, incorporating a structured-tree model into such integrated models is currently absent in the literature, which presents a promising prospect. Thus, the goal here is to develop a novel computational framework that combines a 1D structured-tree model of coronary flow in human coronary vasculature with a 3D left ventricle model utilising a hyperelastic constitutive law, enabling the physiologically accurate simulation of coronary flow dynamics. METHODS We adopted detailed geometric information from previous studies of both coronary vasculature and left ventricle to construct the coronary flow model and the left ventricle model. The structured-tree model for coronary flow was expanded to encompass the effect of time-varying intramyocardial pressure on intramyocardial blood vessels. Simultaneously, the left ventricle model served as a robust foundation for the calculation of intramyocardial pressure and subsequent quantitative evaluation of myocardial perfusion. A one-way coupling framework between the two models was established to enable the evaluation and examination of coronary flow dynamics and myocardial perfusion. RESULTS Our predicted coronary flow waveforms aligned well with published experimental data. Our model precisely captured the phasic pattern of coronary flow, including impeded or even reversed flow during systole. Moreover, our assessment of coronary flow, considering both globally and regionally averaged intramyocardial pressure, demonstrated that elevated intramyocardial pressure corresponds to increased impeding effects on coronary flow. Furthermore, myocardial blood flow simulated from our model was comparable with MRI perfusion data at rest, showcasing the capability of our model to predict myocardial perfusion. CONCLUSIONS The integrated model introduced in this study presents a novel approach to achieving physiologically accurate simulations of coronary flow and myocardial perfusion. It holds promise for its clinical applicability in diagnosing insufficient myocardial perfusion.
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Affiliation(s)
- Yingjie Wang
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom.
| | - Xueqing Yin
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
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9
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Kim YC, Kim K, Choe YH. Automatic calculation of myocardial perfusion reserve using deep learning with uncertainty quantification. Quant Imaging Med Surg 2023; 13:7936-7949. [PMID: 38106294 PMCID: PMC10722070 DOI: 10.21037/qims-23-840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/22/2023] [Indexed: 12/19/2023]
Abstract
Background Myocardial perfusion reserve index (MPRI) in magnetic resonance imaging (MRI) is an important indicator of ischemia, and its measurement typically involves manual procedures. The purposes of this study were to develop a fully automatic method for estimating the MPRI and to evaluate its performance. Methods The method consisted of segmenting the myocardium in dynamic contrast-enhanced (DCE) myocardial perfusion MRI data using Monte Carlo dropout U-Net, dividing the myocardium into segments based on landmark localization with machine learning, and estimating the MPRI after the calculation of the left ventricular and myocardial contrast upslopes. The proposed method was compared with a reference method, which involved manual adjustments of the myocardial contours and upslope ranges. Results In test subjects, MPRIs measured by the proposed technique correlated with those by the manual reference in segmental assessment [intraclass correlation coefficient (ICC) =0.75, 95% CI: 0.70-0.79, P<0.001]. The automatic and reference MPRI values showed a mean difference of -0.02 and 95% limits of agreement of (-0.86, 0.82). Conclusions The proposed automatic method is based on deep learning segmentation and machine learning landmark detection for MPRI measurements in DCE perfusion MRI. It holds the potential to efficiently and quantitatively assess myocardial ischemia without any user's interaction.
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Affiliation(s)
- Yoon-Chul Kim
- Division of Digital Healthcare, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju, Republic of Korea
| | - Kyurae Kim
- Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Yeon Hyeon Choe
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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10
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Chen W, Ni M, Huang H, Cong H, Fu X, Gao W, Yang Y, Yu M, Song X, Liu M, Yuan Z, Zhang B, Wang Z, Wang Y, Chen Y, Zhang C, Zhang Y. Chinese expert consensus on the diagnosis and treatment of coronary microvascular diseases (2023 Edition). MedComm (Beijing) 2023; 4:e438. [PMID: 38116064 PMCID: PMC10729292 DOI: 10.1002/mco2.438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/11/2023] [Accepted: 11/16/2023] [Indexed: 12/21/2023] Open
Abstract
Since the four working groups of the Chinese Society of Cardiology issued first expert consensus on coronary microvascular diseases (CMVD) in 2017, international consensus documents on CMVD have increased rapidly. Although some of these documents made preliminary recommendations for the diagnosis and treatment of CMVD, they did not provide classification of recommendations and levels of evidence. In order to summarize recent progress in the field of CMVD, standardize the methods and procedures of diagnosis and treatment, and identify the scientific questions for future research, the four working groups of the Chinese Society of Cardiology updated the 2017 version of the Chinese expert consensus on CMVD and adopted a series of measures to ensure the quality of this document. The current consensus has raised a new classification of CMVD, summarized new epidemiological findings for different types of CMVD, analyzed key pathological and molecular mechanisms, evaluated classical and novel diagnostic technologies, recommended diagnostic pathways and criteria, and therapeutic strategies and medications, for patients with CMVD. In view of the current progress and knowledge gaps of CMVD, future directions were proposed. It is hoped that this expert consensus will further expedite the research progress of CMVD in both basic and clinical scenarios.
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Affiliation(s)
- Wenqiang Chen
- The National Key Laboratory for Innovation and Transformation of Luobing TheoryThe Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical ScienceDepartment of CardiologyQilu Hospital of Shandong UniversityJinanShandongChina
| | - Mei Ni
- The National Key Laboratory for Innovation and Transformation of Luobing TheoryThe Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical ScienceDepartment of CardiologyQilu Hospital of Shandong UniversityJinanShandongChina
| | - He Huang
- Department of CardiologySir Run Run Shaw Hospital affiliated with Zhejiang University School of MedicineHangzhouChina
| | - Hongliang Cong
- Department of CardiologyTianjin Chest Hospital, Tianjin UniversityTianjinChina
| | - Xianghua Fu
- Department of CardiologyThe Second Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
| | - Wei Gao
- Department of CardiologyPeking University Third HospitalBeijingChina
| | - Yuejin Yang
- Department of CardiologyFuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Mengyue Yu
- Department of CardiologyFuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Xiantao Song
- Department of CardiologyBeijing Anzhen Hospital, Capital Medical UniversityBeijingChina
| | - Meilin Liu
- Department of GeriatricsPeking University First HospitalBeijingChina
| | - Zuyi Yuan
- Department of CardiologyThe First Affiliated Hospital of Xian Jiaotong UniversityXianChina
| | - Bo Zhang
- Department of CardiologyFirst Affiliated Hospital, Dalian Medical UniversityDalianLiaoningChina
| | - Zhaohui Wang
- Department of CardiologyUnion Hospital, Tongji Medical College, Huazhong University of Science and TechnologyWuhanChina
| | - Yan Wang
- Department of CardiologyXiamen Cardiovascular Hospital, Xiamen UniversityXiamenChina
| | - Yundai Chen
- Senior Department of Cardiology, Sixth Medical Center of Chinese PLA General Hospital, Beijing, China; for the Basic Research Group, Atherosclerosis and Coronary Heart Disease Group, Interventional Cardiology Group, and Women's Heart Health Group of the Chinese Society of Cardiology
| | - Cheng Zhang
- The National Key Laboratory for Innovation and Transformation of Luobing TheoryThe Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical ScienceDepartment of CardiologyQilu Hospital of Shandong UniversityJinanShandongChina
| | - Yun Zhang
- The National Key Laboratory for Innovation and Transformation of Luobing TheoryThe Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical ScienceDepartment of CardiologyQilu Hospital of Shandong UniversityJinanShandongChina
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11
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Black SM, Maclean C, Barrientos PH, Ritos K, Kazakidi A. Reconstruction and Validation of Arterial Geometries for Computational Fluid Dynamics Using Multiple Temporal Frames of 4D Flow-MRI Magnitude Images. Cardiovasc Eng Technol 2023; 14:655-676. [PMID: 37653353 PMCID: PMC10602980 DOI: 10.1007/s13239-023-00679-x] [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: 05/16/2022] [Accepted: 08/08/2023] [Indexed: 09/02/2023]
Abstract
PURPOSE Segmentation and reconstruction of arterial blood vessels is a fundamental step in the translation of computational fluid dynamics (CFD) to the clinical practice. Four-dimensional flow magnetic resonance imaging (4D Flow-MRI) can provide detailed information of blood flow but processing this information to elucidate the underlying anatomical structures is challenging. In this study, we present a novel approach to create high-contrast anatomical images from retrospective 4D Flow-MRI data. METHODS For healthy and clinical cases, the 3D instantaneous velocities at multiple cardiac time steps were superimposed directly onto the 4D Flow-MRI magnitude images and combined into a single composite frame. This new Composite Phase-Contrast Magnetic Resonance Angiogram (CPC-MRA) resulted in enhanced and uniform contrast within the lumen. These images were subsequently segmented and reconstructed to generate 3D arterial models for CFD. Using the time-dependent, 3D incompressible Reynolds-averaged Navier-Stokes equations, the transient aortic haemodynamics was computed within a rigid wall model of patient geometries. RESULTS Validation of these models against the gold standard CT-based approach showed no statistically significant inter-modality difference regarding vessel radius or curvature (p > 0.05), and a similar Dice Similarity Coefficient and Hausdorff Distance. CFD-derived near-wall hemodynamics indicated a significant inter-modality difference (p > 0.05), though these absolute errors were small. When compared to the in vivo data, CFD-derived velocities were qualitatively similar. CONCLUSION This proof-of-concept study demonstrated that functional 4D Flow-MRI information can be utilized to retrospectively generate anatomical information for CFD models in the absence of standard imaging datasets and intravenous contrast.
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Affiliation(s)
| | - Craig Maclean
- Research and Development, Terumo Aortic, Glasgow, UK
| | - Pauline Hall Barrientos
- Clinical Physics, Queen Elizabeth University Hospital, NHS Greater Glasgow & Clyde, Glasgow, UK
| | - Konstantinos Ritos
- Department of Mechanical and Aerospace Engineering, Glasgow, UK
- Department of Mechanical Engineering, University of Thessaly, Volos, Greece
| | - Asimina Kazakidi
- Department of Biomedical Engineering, University of Strathclyde, Glasgow, UK.
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12
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Alves JR, Berg LA, Gaio ED, Rocha BM, de Queiroz RAB, dos Santos RW. A Hybrid Model for Cardiac Perfusion: Coupling a Discrete Coronary Arterial Tree Model with a Continuous Porous-Media Flow Model of the Myocardium. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1229. [PMID: 37628259 PMCID: PMC10453666 DOI: 10.3390/e25081229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/18/2023] [Accepted: 07/27/2023] [Indexed: 08/27/2023]
Abstract
This paper presents a novel hybrid approach for the computational modeling of cardiac perfusion, combining a discrete model of the coronary arterial tree with a continuous porous-media flow model of the myocardium. The constructive constrained optimization (CCO) algorithm captures the detailed topology and geometry of the coronary arterial tree network, while Poiseuille's law governs blood flow within this network. Contrast agent dynamics, crucial for cardiac MRI perfusion assessment, are modeled using reaction-advection-diffusion equations within the porous-media framework. The model incorporates fibrosis-contrast agent interactions and considers contrast agent recirculation to simulate myocardial infarction and Gadolinium-based late-enhancement MRI findings. Numerical experiments simulate various scenarios, including normal perfusion, endocardial ischemia resulting from stenosis, and myocardial infarction. The results demonstrate the model's efficacy in establishing the relationship between blood flow and stenosis in the coronary arterial tree and contrast agent dynamics and perfusion in the myocardial tissue. The hybrid model enables the integration of information from two different exams: computational fractional flow reserve (cFFR) measurements of the heart coronaries obtained from CT scans and heart perfusion and anatomy derived from MRI scans. The cFFR data can be integrated with the discrete arterial tree, while cardiac perfusion MRI data can be incorporated into the continuum part of the model. This integration enhances clinical understanding and treatment strategies for managing cardiovascular disease.
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Affiliation(s)
- João R. Alves
- Department of Education, Federal Institute of Education, Science and Technology of Mato Grosso, Sorriso 78895-150, Brazil
| | - Lucas A. Berg
- Department of Computer Science, Federal Univesity of Juiz de Fora, Juiz de Fora 36036-900, Brazil (E.D.G.); (B.M.R.)
- Department of Computer Science, University of Oxford, Oxford OX3 7LD, UK
| | - Evandro D. Gaio
- Department of Computer Science, Federal Univesity of Juiz de Fora, Juiz de Fora 36036-900, Brazil (E.D.G.); (B.M.R.)
| | - Bernardo M. Rocha
- Department of Computer Science, Federal Univesity of Juiz de Fora, Juiz de Fora 36036-900, Brazil (E.D.G.); (B.M.R.)
| | | | - Rodrigo W. dos Santos
- Department of Computer Science, Federal Univesity of Juiz de Fora, Juiz de Fora 36036-900, Brazil (E.D.G.); (B.M.R.)
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13
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Brown LAE, Gulsin GS, Onciul SC, Broadbent DA, Yeo JL, Wood AL, Saunderson CED, Das A, Jex N, Chowdhary A, Thirunavukarasu S, Sharrack N, Knott KD, Levelt E, Swoboda PP, Xue H, Greenwood JP, Moon JC, Adlam D, McCann GP, Kellman P, Plein S. Sex- and age-specific normal values for automated quantitative pixel-wise myocardial perfusion cardiovascular magnetic resonance. Eur Heart J Cardiovasc Imaging 2023; 24:426-434. [PMID: 36458882 PMCID: PMC10029853 DOI: 10.1093/ehjci/jeac231] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 10/21/2022] [Indexed: 12/05/2022] Open
Abstract
AIMS Recently developed in-line automated cardiovascular magnetic resonance (CMR) myocardial perfusion mapping has been shown to be reproducible and comparable with positron emission tomography (PET), and can be easily integrated into clinical workflows. Bringing quantitative myocardial perfusion CMR into routine clinical care requires knowledge of sex- and age-specific normal values in order to define thresholds for disease detection. This study aimed to establish sex- and age-specific normal values for stress and rest CMR myocardial blood flow (MBF) in healthy volunteers. METHODS AND RESULTS A total of 151 healthy volunteers recruited from two centres underwent adenosine stress and rest myocardial perfusion CMR. In-line automatic reconstruction and post processing of perfusion data were implemented within the Gadgetron software framework, creating pixel-wise perfusion maps. Rest and stress MBF were measured, deriving myocardial perfusion reserve (MPR) and were subdivided by sex and age. Mean MBF in all subjects was 0.62 ± 0.13 mL/g/min at rest and 2.24 ± 0.53 mL/g/min during stress. Mean MPR was 3.74 ± 1.00. Compared with males, females had higher rest (0.69 ± 0.13 vs. 0.58 ± 0.12 mL/g/min, P < 0.01) and stress MBF (2.41 ± 0.47 vs. 2.13 ± 0.54 mL/g/min, P = 0.001). Stress MBF and MPR showed significant negative correlations with increasing age (r = -0.43, P < 0.001 and r = -0.34, P < 0.001, respectively). CONCLUSION Fully automated in-line CMR myocardial perfusion mapping produces similar normal values to the published CMR and PET literature. There is a significant increase in rest and stress MBF, but not MPR, in females and a reduction of stress MBF and MPR with advancing age, advocating the use of sex- and age-specific reference ranges for diagnostic use.
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Affiliation(s)
- Louise A E Brown
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Gaurav S Gulsin
- Department of Cardiovascular Sciences, University of Leicester and Cardiovascular Theme, NIHR Leicester Biomedical Research Centre, Glenfield Hospital, UK
| | - Sebastian C Onciul
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - David A Broadbent
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
- Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Jian L Yeo
- Department of Cardiovascular Sciences, University of Leicester and Cardiovascular Theme, NIHR Leicester Biomedical Research Centre, Glenfield Hospital, UK
| | - Alice L Wood
- Department of Cardiovascular Sciences, University of Leicester and Cardiovascular Theme, NIHR Leicester Biomedical Research Centre, Glenfield Hospital, UK
| | - Christopher E D Saunderson
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Arka Das
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Nicholas Jex
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Amrit Chowdhary
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Sharmaine Thirunavukarasu
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Noor Sharrack
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Kristopher D Knott
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, UK
| | - Eylem Levelt
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Peter P Swoboda
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD, USA
| | - John P Greenwood
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - James C Moon
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, UK
| | - David Adlam
- Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Gerry P McCann
- Department of Cardiovascular Sciences, University of Leicester and Cardiovascular Theme, NIHR Leicester Biomedical Research Centre, Glenfield Hospital, UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD, USA
| | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre (MCRC) and Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
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14
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Li XM, Jiang L, Min CY, Yan WF, Shen MT, Liu XJ, Guo YK, Yang ZG. Myocardial Perfusion Imaging by Cardiovascular Magnetic Resonance: Research Progress and Current Implementation. Curr Probl Cardiol 2023; 48:101665. [PMID: 36828047 DOI: 10.1016/j.cpcardiol.2023.101665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 02/17/2023] [Indexed: 02/24/2023]
Abstract
Cardiovascular diseases pose a significant health and economic burden worldwide, with coronary artery disease still recognized as a major problem. It is closely associated with hypertension, diabetes, obesity, smoking, lack of exercise, poor diet, and excessive alcohol consumption, which may lead to macro- and microvascular abnormalities in the heart. Coronary artery stenosis reduces the local supply of oxygen and nutrients to the myocardium and results in reduced levels of myocardial perfusion, which can lead to more severe conditions and irreversible damage to myocardial tissues. Therefore, accurate evaluation of myocardial perfusion abnormalities in patients with these risk factors is critical. As technology advances, magnetic resonance myocardial perfusion imaging has become more accurate at evaluating the myocardial microcirculation and has shown a powerful ability to detect myocardial ischemia. The purpose of this review is to summarize the principle, research progress of acquisition and analysis, and clinical implementation of cardiovascular magnetic resonance (CMR) myocardial perfusion imaging.
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Affiliation(s)
- Xue-Ming Li
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Laboratory of Cardiovascular Diseases, Regenerative Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Jiang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chen-Yan Min
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei-Feng Yan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Meng-Ting Shen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiao-Jing Liu
- Laboratory of Cardiovascular Diseases, Regenerative Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying-Kun Guo
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhi-Gang Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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15
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Leo I, Nakou E, Artico J, Androulakis E, Wong J, Moon JC, Indolfi C, Bucciarelli-Ducci C. Strengths and weaknesses of alternative noninvasive imaging approaches for microvascular ischemia. J Nucl Cardiol 2023; 30:227-238. [PMID: 35918590 DOI: 10.1007/s12350-022-03066-6] [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: 04/03/2022] [Accepted: 06/19/2022] [Indexed: 11/26/2022]
Abstract
Structural and functional abnormalities of coronary microvasculature are highly prevalent in several clinical settings and often associated with worse clinical outcomes. Therefore, there is a growing interest in the detection and treatment of this, often overlooked, disease. Coronary angiography allows the assessment of the Coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR). However, the measurement of these parameters is not always feasible because of limited technical availability and the need for a cardiac catheterization with a small but real risk of potential complications. Recent advances in non-invasive imaging techniques allow the assessment of coronary microvascular function with good accuracy and reproducibility. The objective of this review is to discuss the strengths and weaknesses of alternative non-invasive approaches used in the diagnosis of coronary microvascular dysfunction (CMD), highlighting the most recent advances for each imaging modality.
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Affiliation(s)
- Isabella Leo
- Royal Brompton and Harefield Hospitals, Guys's and St Thomas' NHS Foundation Trust, London, UK
- Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | - Eleni Nakou
- Royal Brompton and Harefield Hospitals, Guys's and St Thomas' NHS Foundation Trust, London, UK
| | - Jessica Artico
- Institute of Cardiovascular Science, University College London, Gower Street, London, UK
- St Bartholomew's Hospital, Barts Heart Centre, West Smithfield, London, UK
| | - Emmanouil Androulakis
- Royal Brompton and Harefield Hospitals, Guys's and St Thomas' NHS Foundation Trust, London, UK
| | - Joyce Wong
- Royal Brompton and Harefield Hospitals, Guys's and St Thomas' NHS Foundation Trust, London, UK
| | - James C Moon
- Institute of Cardiovascular Science, University College London, Gower Street, London, UK
- St Bartholomew's Hospital, Barts Heart Centre, West Smithfield, London, UK
| | - Ciro Indolfi
- Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
- Mediterranea Cardiocentro, Naples, Italy
| | - Chiara Bucciarelli-Ducci
- Royal Brompton and Harefield Hospitals, Guys's and St Thomas' NHS Foundation Trust, London, UK.
- Faculty of Life Sciences and Medicine, School of Biomedical Engineering and Imaging Sciences, King's College University, London, UK.
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16
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Scannell CM, Alskaf E, Sharrack N, Razavi R, Ourselin S, Young AA, Plein S, Chiribiri A. AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2023; 4:12-21. [PMID: 36743875 PMCID: PMC9890084 DOI: 10.1093/ehjdh/ztac074] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 10/23/2022] [Indexed: 12/12/2022]
Abstract
Aims One of the major challenges in the quantification of myocardial blood flow (MBF) from stress perfusion cardiac magnetic resonance (CMR) is the estimation of the arterial input function (AIF). This is due to the non-linear relationship between the concentration of gadolinium and the MR signal, which leads to signal saturation. In this work, we show that a deep learning model can be trained to predict the unsaturated AIF from standard images, using the reference dual-sequence acquisition AIFs (DS-AIFs) for training. Methods and results A 1D U-Net was trained, to take the saturated AIF from the standard images as input and predict the unsaturated AIF, using the data from 201 patients from centre 1 and a test set comprised of both an independent cohort of consecutive patients from centre 1 and an external cohort of patients from centre 2 (n = 44). Fully-automated MBF was compared between the DS-AIF and AI-AIF methods using the Mann-Whitney U test and Bland-Altman analysis. There was no statistical difference between the MBF quantified with the DS-AIF [2.77 mL/min/g (1.08)] and predicted with the AI-AIF (2.79 mL/min/g (1.08), P = 0.33. Bland-Altman analysis shows minimal bias between the DS-AIF and AI-AIF methods for quantitative MBF (bias of -0.11 mL/min/g). Additionally, the MBF diagnosis classification of the AI-AIF matched the DS-AIF in 669/704 (95%) of myocardial segments. Conclusion Quantification of stress perfusion CMR is feasible with a single-sequence acquisition and a single contrast injection using an AI-based correction of the AIF.
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Affiliation(s)
- Cian M Scannell
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.,Department of Biomedical Engineering, Eindhoven University of Technology, Gemini-Zuid, Groene Loper 5, 5612 Eindhoven, The Netherlands
| | - Ebraham Alskaf
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Noor Sharrack
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Reza Razavi
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Alistair A Young
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Sven Plein
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.,Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK
| | - Amedeo Chiribiri
- School of Biomedical Engineering & Imaging Sciences, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
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17
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Bazmpani MA, Nikolaidou C, Papanastasiou CA, Ziakas A, Karamitsos TD. Cardiovascular Magnetic Resonance Parametric Mapping Techniques for the Assessment of Chronic Coronary Syndromes. J Cardiovasc Dev Dis 2022; 9:jcdd9120443. [PMID: 36547440 PMCID: PMC9782163 DOI: 10.3390/jcdd9120443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 11/29/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
The term chronic coronary syndromes encompasses a variety of clinical presentations of coronary artery disease (CAD), ranging from stable angina due to epicardial coronary artery disease to microvascular coronary dysfunction. Cardiac magnetic resonance (CMR) imaging has an established role in the diagnosis, prognostication and treatment planning of patients with CAD. Recent advances in parametric mapping CMR techniques have added value in the assessment of patients with chronic coronary syndromes, even without the need for gadolinium contrast administration. Furthermore, quantitative perfusion CMR techniques have enabled the non-invasive assessment of myocardial blood flow and myocardial perfusion reserve and can reliably identify multivessel coronary artery disease and microvascular dysfunction. This review summarizes the clinical applications and the prognostic value of the novel CMR parametric mapping techniques in the setting of chronic coronary syndromes and discusses their strengths, pitfalls and future directions.
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Affiliation(s)
- Maria Anna Bazmpani
- Department of First Cardiology, Aristotle University of Thessaloniki School of Medicine, AHEPA University Hospital, 54636 Thessaloniki, Greece
| | | | - Christos A. Papanastasiou
- Department of First Cardiology, Aristotle University of Thessaloniki School of Medicine, AHEPA University Hospital, 54636 Thessaloniki, Greece
| | - Antonios Ziakas
- Department of First Cardiology, Aristotle University of Thessaloniki School of Medicine, AHEPA University Hospital, 54636 Thessaloniki, Greece
| | - Theodoros D. Karamitsos
- Department of First Cardiology, Aristotle University of Thessaloniki School of Medicine, AHEPA University Hospital, 54636 Thessaloniki, Greece
- Correspondence: ; Tel.: +30-2310994832; Fax: +30-2310994673
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18
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Pons-Lladó G, Kellman P. State-of-the-Art of Myocardial Perfusion by CMR: A Practical View. Rev Cardiovasc Med 2022; 23:325. [PMID: 39077124 PMCID: PMC11267340 DOI: 10.31083/j.rcm2310325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 08/30/2022] [Accepted: 08/31/2022] [Indexed: 07/31/2024] Open
Abstract
Ischemic heart disease (IHD) outstands among diseases threatening public health. Essential for its management are the continuous advances in medical and interventional therapies, although a prompt and accurate diagnosis and prognostic stratification are equally important. Besides information on the anatomy of coronary arteries, well covered nowadays by invasive and non-invasive angiographic techniques, there are also other components of the disease with clinical impact, as the presence of myocardial necrosis, the extent of pump function impairment, and the presence and extent of inducible myocardial ischemia, that must be considered in every patient. Cardiovascular Magnetic Resonance (CMR) is a multiparametric diagnostic imaging technique that provides reliable information on these issues. Regarding the detection and grading of inducible ischemia in particular, the technique has been widely adopted in the form of myocardial perfusion sequences under vasodilator stress, which is the subject of this review. While the analysis of images is conventionally performed by visual inspection of dynamic first-pass studies, with the inherent dependency on the operator capability, the recent introduction of a reliable application of quantitative perfusion (QP) represents a significant advance in the field. QP is based on a dual-sequence strategy for conversion of signal intensities into contrast agent concentration units and includes a full automatization of processes such as myocardial blood flow (MBF) calculation (in mL/min/g), generation of a pixel-wise flow mapping, myocardial segmentation, based on machine learning, and allocation of MBF values to myocardial segments. The acquisition of this protocol during induced vasodilation and at rest gives values of stress/rest MBF (in mL/min/g) and myocardial perfusion reserve (MPR), both global and per segment. Dual-sequence QP has been successfully validated against different reference methods, and its prognostic value has been shown in large longitudinal studies. The fact of the whole process being automated, without operator interaction, permits to conceive new interesting scenarios of integration of CMR into systems of entirely automated diagnostic workflow in patients with IHD.
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Affiliation(s)
- Guillem Pons-Lladó
- Head (Emeritus), Cardiac Imaging Unit, Cardiology Department, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Clínica Creu Banca, 08034 Barcelona, Spain
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA
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19
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He B, Chen Y, Wang L, Yang Y, Xia C, Zheng J, Gao F. Compact MR-compatible ergometer and its application in cardiac MR under exercise stress: A preliminary study. Magn Reson Med 2022; 88:1927-1936. [PMID: 35649186 PMCID: PMC9545047 DOI: 10.1002/mrm.29311] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 04/29/2022] [Accepted: 05/02/2022] [Indexed: 02/05/2023]
Abstract
Purpose To develop a compact MR‐compatible ergometer for exercise stress and to initially evaluate the reproducibility of myocardial native T1 and myocardial blood flow (MBF) measurements during exercise stress performed on this ergometer. Methods The compact ergometer consists of exercise, workload, and data processing components. The exercise stress can be achieved by pedaling on a pair of cylinders at a predefined frequency with adjustable resistances. Ten healthy subjects were recruited to perform cardiac MRI scans twice in a 3.0T MR scanner, at different days to assess reproducibility. Myocardial native T1 and MBF were acquired at rest and during a moderate exercise. The reproducibility of the two tests was determined by the intra‐group correlation coefficient (ICC) and coefficient of variation (CoV). Results The mean exercise intensity in this pilot study was 45 Watts (W), with an exercise duration of 5 min. Stress induced a significant increase in systolic blood pressure (from 113 ± 11 mmHg to 141 ± 12, P < 0.05) and maximal increase in heart rate by 74 ± 19%. The rate pressure product increased two‐fold (P < 0.001). Excellent reproducibility was demonstrated in native T1 during the exercise (CoV = 3.0%), whereas the reproducibility of MBF and myocardial perfusion reserve during the exercise was also good (CoV = 10.7% and 8.8%, respectively). Conclusion This pilot study demonstrated that it is possible to acquire reproducible measurements of myocardial native T1 and MBF during the exercise stress in healthy volunteers using our new compact ergometer. Click here for author‐reader discussions
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Affiliation(s)
- Bo He
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Molecular Imaging Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yushu Chen
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Lei Wang
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Molecular Imaging Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yang Yang
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Chunchao Xia
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Jie Zheng
- Mallinckrodt Institute of Radiology, Washington University in St Louis, St. Louis, Missouri, USA
| | - Fabao Gao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Molecular Imaging Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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20
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Nagueh SF, Phelan D, Abraham T, Armour A, Desai MY, Dragulescu A, Gilliland Y, Lester SJ, Maldonado Y, Mohiddin S, Nieman K, Sperry BW, Woo A. Recommendations for Multimodality Cardiovascular Imaging of Patients with Hypertrophic Cardiomyopathy: An Update from the American Society of Echocardiography, in Collaboration with the American Society of Nuclear Cardiology, the Society for Cardiovascular Magnetic Resonance, and the Society of Cardiovascular Computed Tomography. J Am Soc Echocardiogr 2022; 35:533-569. [PMID: 35659037 DOI: 10.1016/j.echo.2022.03.012] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Hypertrophic cardiomyopathy (HCM) is defined by the presence of left ventricular hypertrophy in the absence of other potentially causative cardiac, systemic, syndromic, or metabolic diseases. Symptoms can be related to a range of pathophysiologic mechanisms including left ventricular outflow tract obstruction with or without significant mitral regurgitation, diastolic dysfunction with heart failure with preserved and heart failure with reduced ejection fraction, autonomic dysfunction, ischemia, and arrhythmias. Appropriate understanding and utilization of multimodality imaging is fundamental to accurate diagnosis as well as longitudinal care of patients with HCM. Resting and stress imaging provide comprehensive and complementary information to help clarify mechanism(s) responsible for symptoms such that appropriate and timely treatment strategies may be implemented. Advanced imaging is relied upon to guide certain treatment options including septal reduction therapy and mitral valve repair. Using both clinical and imaging parameters, enhanced algorithms for sudden cardiac death risk stratification facilitate selection of HCM patients most likely to benefit from implantable cardioverter-defibrillators.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Saidi Mohiddin
- Inherited/Acquired Myocardial Diseases, Barts Health NHS Trust, St Bartholomew's Hospital, London, UK
| | - Koen Nieman
- Cardiovascular Medicine and Radiology (CV Imaging), Stanford University Medical Center, CA
| | - Brett W Sperry
- Saint Luke's Mid America Heart Institute, Kansas City, MO
| | - Anna Woo
- Toronto General Hospital, Toronto, Canada
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21
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Fan L, Hong K, Hsu LY, Carr JC, Allen BD, Lee DC, Kim D. Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI. Magn Reson Med 2022; 88:832-839. [PMID: 35377476 PMCID: PMC9321550 DOI: 10.1002/mrm.29240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/04/2022] [Accepted: 02/28/2022] [Indexed: 11/07/2022]
Abstract
Purpose The purpose of this study was to determine an optimal saturation‐recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject. Methods We scanned 18 subjects (mean age = 59 ± 14 years, 9/9 males/females) to acquire resting perfusion data and 1 additional subject (age = 38 years, male) to obtain stress‐rest perfusion data using a 5‐fold accelerated pulse sequence with radial k‐space sampling and applied k‐space weighted image contrast (KWIC) filters on the same k‐space data to retrospectively reconstruct five AIF images with effective TS ranging from 10 to 21.2 ms (2.8 ms steps). Undersampled images were reconstructed using a compressed sensing framework with temporal‐total‐variation and temporal‐principal‐component as 2 orthogonal sparsifying transforms. The image processing steps included, same motion correction across five different AIF images, signal normalization by the proton‐density‐weighted‐image, signal‐to‐T1 conversion using a Bloch equation, T1‐to‐gadolinium‐concentration conversion assuming fast water exchange, T2* correction to the AIF, and gadolinium‐concentration to myocardial blood flow (MBF) conversion based on a Fermi model. Results Among five TS values, the shortest TS (10 ms) produced significantly (P < 0.05) higher peak AIF and lower resting MBF (13.73 mM, 0.73 mL g−1 min−1) than 12.8 ms (11.24 mM, 0.89 mL g−1 min−1), 15.6 ms (9.56 mM, 1.05 mL g−1 min−1), 18.4 ms (8.55 mM, 1.17 mL g−1 min−1), and 21.2 ms (7.95 mM, 1.27 mL g−1 min−1). Similarly, shorter TS reduced underestimation of AIF (or overestimation of MBF) for both during stress and at rest, but this effect was canceled in myocardial‐perfusion‐reserve (MPR). Conclusion This study demonstrates that TS of 10 ms reduces the underestimation of AIF and, hence, the overestimation of MBF compared with longer TS values (12.8‐21.2 ms).
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Affiliation(s)
- Lexiaozi Fan
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
| | - Kyungpyo Hong
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Li-Yueh Hsu
- Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland, USA
| | - James C Carr
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Bradley D Allen
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel C Lee
- Division of Cardiology, Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Kim
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
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22
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Seraphim A, Dowsing B, Rathod KS, Shiwani H, Patel K, Knott KD, Zaman S, Johns I, Razvi Y, Patel R, Xue H, Jones DA, Fontana M, Cole G, Uppal R, Davies R, Moon JC, Kellman P, Manisty C. Quantitative Myocardial Perfusion Predicts Outcomes in Patients With Prior Surgical Revascularization. J Am Coll Cardiol 2022; 79:1141-1151. [PMID: 35331408 PMCID: PMC9034686 DOI: 10.1016/j.jacc.2021.12.037] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/23/2021] [Accepted: 12/29/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Patients with previous coronary artery bypass graft (CABG) surgery typically have complex coronary disease and remain at high risk of adverse events. Quantitative myocardial perfusion indices predict outcomes in native vessel disease, but their prognostic performance in patients with prior CABG is unknown. OBJECTIVES In this study, we sought to evaluate whether global stress myocardial blood flow (MBF) and perfusion reserve (MPR) derived from perfusion mapping cardiac magnetic resonance (CMR) independently predict adverse outcomes in patients with prior CABG. METHODS This was a retrospective analysis of consecutive patients with prior CABG referred for adenosine stress perfusion CMR. Perfusion mapping was performed in-line with automated quantification of MBF. The primary outcome was a composite of all-cause mortality and major adverse cardiovascular events defined as nonfatal myocardial infarction and unplanned revascularization. Associations were evaluated with the use of Cox proportional hazards models after adjusting for comorbidities and CMR parameters. RESULTS A total of 341 patients (median age 67 years, 86% male) were included. Over a median follow-up of 638 days (IQR: 367-976 days), 81 patients (24%) reached the primary outcome. Both stress MBF and MPR independently predicted outcomes after adjusting for known prognostic factors (regional ischemia, infarction). The adjusted hazard ratio (HR) for 1 mL/g/min of decrease in stress MBF was 2.56 (95% CI: 1.45-4.35) and for 1 unit of decrease in MPR was 1.61 (95% CI: 1.08-2.38). CONCLUSIONS Global stress MBF and MPR derived from perfusion CMR independently predict adverse outcomes in patients with previous CABG. This effect is independent from the presence of regional ischemia on visual assessment and the extent of previous infarction.
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Affiliation(s)
- Andreas Seraphim
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom. https://twitter.com/andreas_sera
| | - Benjamin Dowsing
- Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - Krishnaraj S Rathod
- Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - Hunain Shiwani
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - Kush Patel
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - Kristopher D Knott
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Sameer Zaman
- Imperial College London, Imperial College, Healthcare NHS Trust, South Kensington, London, United Kingdom
| | - Ieuan Johns
- Imperial College London, Imperial College, Healthcare NHS Trust, South Kensington, London, United Kingdom
| | | | | | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Daniel A Jones
- Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - Marianna Fontana
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Royal Free Hospital, London, United Kingdom
| | | | - Rakesh Uppal
- Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom; William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - Rhodri Davies
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - James C Moon
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Charlotte Manisty
- Institute of Cardiovascular Science, University College London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
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23
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Seraphim A, Knott KD, Augusto JB, Menacho K, Tyebally S, Dowsing B, Bhattacharyya S, Menezes LJ, Jones DA, Uppal R, Moon JC, Manisty C. Non-invasive Ischaemia Testing in Patients With Prior Coronary Artery Bypass Graft Surgery: Technical Challenges, Limitations, and Future Directions. Front Cardiovasc Med 2022; 8:795195. [PMID: 35004905 PMCID: PMC8733203 DOI: 10.3389/fcvm.2021.795195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 11/25/2021] [Indexed: 01/09/2023] Open
Abstract
Coronary artery bypass graft (CABG) surgery effectively relieves symptoms and improves outcomes. However, patients undergoing CABG surgery typically have advanced coronary atherosclerotic disease and remain at high risk for symptom recurrence and adverse events. Functional non-invasive testing for ischaemia is commonly used as a gatekeeper for invasive coronary and graft angiography, and for guiding subsequent revascularisation decisions. However, performing and interpreting non-invasive ischaemia testing in patients post CABG is challenging, irrespective of the imaging modality used. Multiple factors including advanced multi-vessel native vessel disease, variability in coronary hemodynamics post-surgery, differences in graft lengths and vasomotor properties, and complex myocardial scar morphology are only some of the pathophysiological mechanisms that complicate ischaemia evaluation in this patient population. Systematic assessment of the impact of these challenges in relation to each imaging modality may help optimize diagnostic test selection by incorporating clinical information and individual patient characteristics. At the same time, recent technological advances in cardiac imaging including improvements in image quality, wider availability of quantitative techniques for measuring myocardial blood flow and the introduction of artificial intelligence-based approaches for image analysis offer the opportunity to re-evaluate the value of ischaemia testing, providing new insights into the pathophysiological processes that determine outcomes in this patient population.
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Affiliation(s)
- Andreas Seraphim
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Kristopher D Knott
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Joao B Augusto
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Katia Menacho
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Sara Tyebally
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom
| | - Benjamin Dowsing
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Sanjeev Bhattacharyya
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom
| | - Leon J Menezes
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom
| | - Daniel A Jones
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - Rakesh Uppal
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - James C Moon
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Charlotte Manisty
- Department of Cardiac Imaging, Barts Health National Health System Trust, London, United Kingdom.,Institute of Cardiovascular Science, University College London, London, United Kingdom
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24
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Abouelnour A, Gori T. Vasomotor Dysfunction in Patients with Ischemia and Non-Obstructive Coronary Artery Disease: Current Diagnostic and Therapeutic Strategies. Biomedicines 2021; 9:biomedicines9121774. [PMID: 34944590 PMCID: PMC8698648 DOI: 10.3390/biomedicines9121774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/15/2021] [Accepted: 11/23/2021] [Indexed: 11/16/2022] Open
Abstract
Many patients who present with symptoms or objective evidence of ischemia have no or non-physiologically-significant disease on invasive coronary angiography. The diagnosis of ischemic heart disease is thus often dismissed, and patients receive false reassurance or other diagnoses are pursued. We now know that a significant proportion of these patients have coronary microvascular dysfunction and/or vasospastic disease as the underlying pathophysiology of their clinical presentation. Making the correct diagnosis of such abnormalities is important not only because they impact the quality of life, with recurring symptoms and unnecessary repeated testing, but also because they increase the risk for adverse cardiovascular events. The mainstay of diagnosis remains an invasive comprehensive physiologic assessment, which further allows stratifying these patients into appropriate “endotypes”. It has been shown that tailoring treatment to the patient’s assigned endotype improves symptoms and quality of life. In addition to the conventional drugs used in chronic stable angina, multiple newer agents are being investigated. Moreover, innovative non-pharmacologic and interventional therapies are emerging to provide a bail-out in refractory cases. Many of these novel therapies fail to show consistent benefits, but others show quite promising results.
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Affiliation(s)
- Amr Abouelnour
- Zentrum für Kardiologie, Kardiologie I, und Deutsches Zentrum für Herz und Kreislauf Forschung, University Medical Center Mainz, 55131 Standort Rhein-Main, Germany;
- Cardiovascular Institute, Assiut University, Assiut 71515, Egypt
| | - Tommaso Gori
- Zentrum für Kardiologie, Kardiologie I, und Deutsches Zentrum für Herz und Kreislauf Forschung, University Medical Center Mainz, 55131 Standort Rhein-Main, Germany;
- Correspondence:
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25
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Preda A, Liberale L, Montecucco F. Imaging techniques for the assessment of adverse cardiac remodeling in metabolic syndrome. Heart Fail Rev 2021; 27:1883-1897. [PMID: 34796433 DOI: 10.1007/s10741-021-10195-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/11/2021] [Indexed: 12/23/2022]
Abstract
Metabolic syndrome (MetS) includes different metabolic conditions (i.e. abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, decreased HDL cholesterol, and/or hypertension) that concour in the development of cardiovascular disease and diabetes. MetS individuals often show adverse cardiac remodeling and myocardial dysfunction even in the absence of overt coronary artery disease or valvular affliction. Diastolic impairment and hypertrophy are hallmarks of MetS-related cardiac remodeling and represent the leading cause of heart failure with preserved ejection fraction (HFpEF). Altered cardiomyocyte function, increased neurohormonal tone, interstitial fibrosis, coronary microvascular dysfunction, and a myriad of metabolic abnormalities have all been implicated in the development and progression of adverse cardiac remodeling related to MetS. However, despite the enormous amount of literature produced on this argument, HF remains a leading cause of morbidity and mortality in such population. The early detection of initial adverse cardiac remodeling would enable the optimal implementation of effective therapies aiming at preventing the progression of the disease to the symptomatic phase. Beyond conventional imaging techniques, such as echocardiography, cardiac tomography, and magnetic resonance, novel post-processing tools and techniques provide information on the biological processes that underlie metabolic heart disease. In this review, we summarize the pathophysiology of MetS-related cardiac remodeling and illustrate the relevance of state-of-the-art multimodality cardiac imaging to identify and quantify the degree of myocardial involvement, prognosticate long-term clinical outcome, and potentially guide therapeutic strategies.
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Affiliation(s)
| | - Luca Liberale
- First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, 6 viale Benedetto XV, 16132, Genoa, Italy.,Center for Molecular Cardiology, University of Zürich, Schlieren, Switzerland.,IRCCS Ospedale Policlinico San Martino Genoa-Italian Cardiovascular Network, Genoa, Italy
| | - Fabrizio Montecucco
- First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, 6 viale Benedetto XV, 16132, Genoa, Italy. .,IRCCS Ospedale Policlinico San Martino Genoa-Italian Cardiovascular Network, Genoa, Italy.
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26
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Franks R, Plein S, Chiribiri A. Clinical Application of Dynamic Contrast Enhanced Perfusion Imaging by Cardiovascular Magnetic Resonance. Front Cardiovasc Med 2021; 8:768563. [PMID: 34778420 PMCID: PMC8585782 DOI: 10.3389/fcvm.2021.768563] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 09/27/2021] [Indexed: 12/12/2022] Open
Abstract
Functionally significant coronary artery disease impairs myocardial blood flow and can be detected non-invasively by myocardial perfusion imaging. While multiple myocardial perfusion imaging modalities exist, the high spatial and temporal resolution of cardiovascular magnetic resonance (CMR), combined with its freedom from ionising radiation make it an attractive option. Dynamic contrast enhanced CMR perfusion imaging has become a well-validated non-invasive tool for the assessment and risk stratification of patients with coronary artery disease and is recommended by international guidelines. This article presents an overview of CMR perfusion imaging and its clinical application, with a focus on chronic coronary syndromes, highlighting its strengths and challenges, and discusses recent advances, including the emerging role of quantitative perfusion analysis.
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Affiliation(s)
- Russell Franks
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Sven Plein
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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27
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Das A, Kelly C, Teh I, Nguyen C, Brown LAE, Chowdhary A, Jex N, Thirunavukarasu S, Sharrack N, Gorecka M, Swoboda PP, Greenwood JP, Kellman P, Moon JC, Davies RH, Lopes LR, Joy G, Plein S, Schneider JE, Dall'Armellina E. Phenotyping hypertrophic cardiomyopathy using cardiac diffusion magnetic resonance imaging: the relationship between microvascular dysfunction and microstructural changes. Eur Heart J Cardiovasc Imaging 2021; 23:352-362. [PMID: 34694365 PMCID: PMC8863073 DOI: 10.1093/ehjci/jeab210] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/16/2021] [Indexed: 01/05/2023] Open
Abstract
Aims Microvascular dysfunction in hypertrophic cardiomyopathy (HCM) is predictive of clinical decline, however underlying mechanisms remain unclear. Cardiac diffusion tensor imaging (cDTI) allows in vivo characterization of myocardial microstructure by quantifying mean diffusivity (MD), fractional anisotropy (FA) of diffusion, and secondary eigenvector angle (E2A). In this cardiac magnetic resonance (CMR) study, we examine associations between perfusion and cDTI parameters to understand the sequence of pathophysiology and the interrelation between vascular function and underlying microstructure. Methods and results Twenty HCM patients underwent 3.0T CMR which included: spin-echo cDTI, adenosine stress and rest perfusion mapping, cine-imaging, and late gadolinium enhancement (LGE). Ten controls underwent cDTI. Myocardial perfusion reserve (MPR), MD, FA, E2A, and wall thickness were calculated per segment and further divided into subendocardial (inner 50%) and subepicardial (outer 50%) regions. Segments with wall thickness ≤11 mm, MPR ≥2.2, and no visual LGE were classified as ‘normal’. Compared to controls, ‘normal’ HCM segments had increased MD (1.61 ± 0.09 vs. 1.46 ± 0.07 × 10−3 mm2/s, P = 0.02), increased E2A (60 ± 9° vs. 38 ± 12°, P < 0.001), and decreased FA (0.29 ± 0.04 vs. 0.35 ± 0.02, P = 0.002). Across all HCM segments, subendocardial regions had higher MD and lower MPR than subepicardial (MDendo 1.61 ± 0.08 × 10−3 mm2/s vs. MDepi 1.56 ± 0.18 × 10−3 mm2/s, P = 0.003, MPRendo 1.85 ± 0.83, MPRepi 2.28 ± 0.87, P < 0.0001). Conclusion In HCM patients, even in segments with normal wall thickness, normal perfusion, and no scar, diffusion is more isotropic than in controls, suggesting the presence of underlying cardiomyocyte disarray. Increased E2A suggests the myocardial sheetlets adopt hypercontracted angulation in systole. Increased MD, most notably in the subendocardium, is suggestive of regional remodelling which may explain the reduced subendocardial blood flow.
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Affiliation(s)
- Arka Das
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Christopher Kelly
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Christopher Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, 55 Fruit St, Boston, MA 02114, USA.,A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, 55 Fruit St, Boston, MA 02114, USA.,Department of Medicine, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Centre, 116 N Robertson Blvd, Los Angeles, CA 90048, USA
| | - Louise A E Brown
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Amrit Chowdhary
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Nicholas Jex
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Sharmaine Thirunavukarasu
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Noor Sharrack
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Miroslawa Gorecka
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Peter P Swoboda
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - John P Greenwood
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, 31 Center Dr, Bethesda, MD 20892, USA
| | - James C Moon
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Rhodri H Davies
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Luis R Lopes
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK.,Centre for Heart Muscle Disease, Institute of Cardiovascular Science, University College London, Gower St, London WC1E 6BT, UK
| | - George Joy
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Sven Plein
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Jürgen E Schneider
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Erica Dall'Armellina
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
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28
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Kotecha T, Monteagudo JM, Martinez-Naharro A, Chacko L, Brown J, Knight D, Knott KD, Hawkins P, Moon JC, Plein S, Xue H, Kellman P, Lockie T, Patel N, Rakhit R, Fontana M. Quantitative cardiovascular magnetic resonance myocardial perfusion mapping to assess hyperaemic response to adenosine stress. Eur Heart J Cardiovasc Imaging 2021; 22:273-281. [PMID: 33188683 DOI: 10.1093/ehjci/jeaa252] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Indexed: 11/13/2022] Open
Abstract
AIMS Assessment of hyperaemia during adenosine stress cardiovascular magnetic resonance (CMR) remains a clinical challenge with lack of a gold-standard non-invasive clinical marker to confirm hyperaemic response. This study aimed to validate maximum stress myocardial blood flow (SMBF) measured using quantitative perfusion mapping for assessment of hyperaemic response and compare this to current clinical markers of adenosine stress. METHODS AND RESULTS Two hundred and eighteen subjects underwent adenosine stress CMR. A derivation cohort (22 volunteers) was used to identify a SMBF threshold value for hyperaemia. This was tested in a validation cohort (37 patients with suspected coronary artery disease) who underwent invasive coronary physiology assessment on the same day as CMR. A clinical cohort (159 patients) was used to compare SMBF to other physiological markers of hyperaemia [splenic switch-off (SSO), heart rate response (HRR), and blood pressure (BP) fall]. A minimum SMBF threshold of 1.43 mL/g/min was derived from volunteer scans. All patients in the coronary physiology cohort demonstrated regional maximum SMBF (SMBFmax) >1.43 mL/g/min and invasive evidence of hyperaemia. Of the clinical cohort, 93% had hyperaemia defined by perfusion mapping compared to 71% using SSO and 81% using HRR. There was no difference in SMBFmax in those with or without SSO (2.58 ± 0.89 vs. 2.54 ± 1.04 mL/g/min, P = 0.84) but those with HRR had significantly higher SMBFmax (2.66 1.86 mL/g/min, P < 0.001). HRR >15 bpm was superior to SSO in predicting adequate increase in SMBF (AUC 0.87 vs. 0.62, P < 0.001). CONCLUSION Adenosine-induced increase in myocardial blood flow is accurate for confirmation of hyperaemia during stress CMR studies and is superior to traditional, clinically used markers of adequate stress such as SSO and BP response.
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Affiliation(s)
- Tushar Kotecha
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiology, Royal Free Hospital, Pond Street, London, UK
| | | | - Ana Martinez-Naharro
- Department of Cardiology, Royal Free Hospital, Pond Street, London, UK.,Division of Medicine, University College London, London, UK
| | - Liza Chacko
- Department of Cardiology, Royal Free Hospital, Pond Street, London, UK.,Division of Medicine, University College London, London, UK
| | - James Brown
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiology, Royal Free Hospital, Pond Street, London, UK
| | - Daniel Knight
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiology, Royal Free Hospital, Pond Street, London, UK
| | - Kristopher D Knott
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiovascular Magnetic Resonance, Barts Heart Centre, London, UK
| | - Philip Hawkins
- Department of Cardiology, Royal Free Hospital, Pond Street, London, UK.,Division of Medicine, University College London, London, UK
| | - James C Moon
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiovascular Magnetic Resonance, Barts Heart Centre, London, UK
| | - Sven Plein
- Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Hui Xue
- Medical Signal and Imaging Processing Program, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter Kellman
- Medical Signal and Imaging Processing Program, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tim Lockie
- Department of Cardiology, Royal Free Hospital, Pond Street, London, UK
| | - Niket Patel
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiology, Royal Free Hospital, Pond Street, London, UK
| | - Roby Rakhit
- Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiology, Royal Free Hospital, Pond Street, London, UK
| | - Marianna Fontana
- Department of Cardiology, Royal Free Hospital, Pond Street, London, UK.,Division of Medicine, University College London, London, UK
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29
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Kero T, Johansson E, Engström M, Eggers KM, Johansson L, Ahlström H, Lubberink M. Evaluation of quantitative CMR perfusion imaging by comparison with simultaneous 15O-water-PET. J Nucl Cardiol 2021; 28:1252-1266. [PMID: 31313066 PMCID: PMC8421320 DOI: 10.1007/s12350-019-01810-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 05/28/2019] [Indexed: 02/04/2023]
Abstract
BACKGROUND We assessed the quantitative accuracy of cardiac perfusion measurements using dynamic contrast-enhanced MRI with simultaneous 15O-water PET as reference with a fully integrated PET-MR scanner. METHODS 15 patients underwent simultaneous DCE MRI and 15O-water PET scans at rest and adenosine-stress on an integrated PET-MR scanner. Correlation and agreement between MRI- and PET-based global and regional MBF values were assessed using correlation and Bland-Altman analysis. RESULTS Three subjects were excluded due to technical problems. Global mean (± SD) MBF values at rest and stress were 0.97 ± 0.27 and 3.19 ± 0.70 mL/g/min for MRI and 1.02 ± 0.28 and 3.13 ± 1.16 mL/g/min for PET (P = 0.66 and P = 0.81). The correlations between global and regional MRI- and PET-based MBF values were strong (r = 0.86 and r = 0.75). The biases were negligible for both global and regional MBF comparisons (0.01 and 0.00 mL/min/g for both), but the limits of agreement were wide for both global and regional MBF, with larger variability for high MBF-values. CONCLUSION The correlation between simultaneous MBF measurements with DCE MRI and 15O-water PET measured in an integrated PET-MRI was strong but the agreement was only moderate indicating that MRI-based quantitative MBF measurements is not ready for clinical introduction.
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Affiliation(s)
- Tanja Kero
- Medical Imaging Centre, Uppsala University Hospital, 75185, Uppsala, Sweden.
- Department of Surgical Sciences/Radiology, Uppsala University, Uppsala, Sweden.
| | | | | | - Kai M Eggers
- Department of Cardiology, Uppsala University Hospital, Uppsala, Sweden
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Håkan Ahlström
- Medical Imaging Centre, Uppsala University Hospital, 75185, Uppsala, Sweden
- Department of Surgical Sciences/Radiology, Uppsala University, Uppsala, Sweden
- Antaros Medical, BioVenture Hub, Mölndal, Sweden
| | - Mark Lubberink
- Medical Physics, Uppsala University Hospital, Uppsala, Sweden
- Department of Surgical Sciences/Radiology, Uppsala University, Uppsala, Sweden
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30
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Bechsgaard DF, Prescott E. Coronary Microvascular Dysfunction: A Practical Approach to Diagnosis and Management. Curr Atheroscler Rep 2021; 23:54. [PMID: 34268637 DOI: 10.1007/s11883-021-00947-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE OF REVIEW The purpose of this review is to provide an overview of diagnostic and treatment considerations in patients with coronary microvascular dysfunction (CMD) in the absence of obstructive coronary artery disease (CAD). RECENT FINDINGS The prevalence of obstructive CAD in unselected patient populations referred for evaluation of angina is less than 10%. A significant proportion of patients with angina and no obstructive CAD have CMD, a condition associated with impaired cardiovascular prognosis. Non-invasive and invasive evaluation of coronary microvascular function is feasible and widely available, yet CMD is underdiagnosed and undertreated. A patient-tailored treatment approach guided by coronary microvascular testing shows promising results for patient-reported outcomes of symptom burden and quality of life. Coronary microvascular testing should be considered in angina patients with no obstructive CAD, before other causes of chest pain are explored. A patient-tailored treatment approach guided by a complete evaluation of epicardial anatomy and macro-and microvascular function may help optimize treatment strategy and prevent unnecessary medical interventions. More research is needed to establish the long-term effect of patient-tailored therapies on risk reduction in CMD.
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Affiliation(s)
- Daria Frestad Bechsgaard
- Department of Cardiology, North Zealand University Hospital, University of Copenhagen, Dyrehavevej 29, 3400, Hillerød, Denmark.
| | - Eva Prescott
- Department of Cardiology, Bispebjerg University Hospital, University of Copenhagen, Bispebjerg Bakke 23, 2400, Copenhagen, Denmark
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31
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Paddock S, Tsampasian V, Assadi H, Mota BC, Swift AJ, Chowdhary A, Swoboda P, Levelt E, Sammut E, Dastidar A, Broncano Cabrero J, Del Val JR, Malcolm P, Sun J, Ryding A, Sawh C, Greenwood R, Hewson D, Vassiliou V, Garg P. Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review. Front Cardiovasc Med 2021; 8:682027. [PMID: 34307496 PMCID: PMC8292630 DOI: 10.3389/fcvm.2021.682027] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/04/2021] [Indexed: 01/05/2023] Open
Abstract
Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy—both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.
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Affiliation(s)
- Sophie Paddock
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.,Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Vasiliki Tsampasian
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Hosamadin Assadi
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Bruno Calife Mota
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Andrew J Swift
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Amrit Chowdhary
- Multidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter Swoboda
- Multidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Eylem Levelt
- Multidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Eva Sammut
- Bristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, Bristol, United Kingdom
| | - Amardeep Dastidar
- Bristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, Bristol, United Kingdom
| | - Jordi Broncano Cabrero
- Cardiothoracic Imaging Unit, Hospital San Juan De Dios, Ressalta, HT Medica, Córdoba, Spain
| | - Javier Royuela Del Val
- Cardiothoracic Imaging Unit, Hospital San Juan De Dios, Ressalta, HT Medica, Córdoba, Spain
| | - Paul Malcolm
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Julia Sun
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Alisdair Ryding
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Chris Sawh
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Richard Greenwood
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - David Hewson
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Vassilios Vassiliou
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Pankaj Garg
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.,Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
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32
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Daviller C, Boutelier T, Giri S, Ratiney H, Jolly MP, Vallée JP, Croisille P, Viallon M. Direct Comparison of Bayesian and Fermi Deconvolution Approaches for Myocardial Blood Flow Quantification: In silico and Clinical Validations. Front Physiol 2021; 12:483714. [PMID: 33912066 PMCID: PMC8072361 DOI: 10.3389/fphys.2021.483714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 03/08/2021] [Indexed: 11/13/2022] Open
Abstract
Cardiac magnetic resonance myocardial perfusion imaging can detect coronary artery disease and is an alternative to single-photon emission computed tomography or positron emission tomography. However, the complex, non-linear MR signal and the lack of robust quantification of myocardial blood flow have hindered its widespread clinical application thus far. Recently, a new Bayesian approach was developed for brain imaging and evaluation of perfusion indexes (Kudo et al., 2014). In addition to providing accurate perfusion measurements, this probabilistic approach appears more robust than previous approaches, particularly due to its insensitivity to bolus arrival delays. We assessed the performance of this approach against a well-known and commonly deployed model-independent method based on the Fermi function for cardiac magnetic resonance myocardial perfusion imaging. The methods were first evaluated for accuracy and precision using a digital phantom to test them against the ground truth; next, they were applied in a group of coronary artery disease patients. The Bayesian method can be considered an appropriate model-independent method with which to estimate myocardial blood flow and delays. The digital phantom comprised a set of synthetic time-concentration curve combinations generated with a 2-compartment exchange model and a realistic combination of perfusion indexes, arterial input dynamics, noise and delays collected from the clinical dataset. The myocardial blood flow values estimated with the two methods showed an excellent correlation coefficient (r2 > 0.9) under all noise and delay conditions. The Bayesian approach showed excellent robustness to bolus arrival delays, with a similar performance to Fermi modeling when delays were considered. Delays were better estimated with the Bayesian approach than with Fermi modeling. An in vivo analysis of coronary artery disease patients revealed that the Bayesian approach had an excellent ability to distinguish between abnormal and normal myocardium. The Bayesian approach was able to discriminate not only flows but also delays with increased sensitivity by offering a clearly enlarged range of distribution for the physiologic parameters.
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Affiliation(s)
- Clément Daviller
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS, UMR 5220, U1294, Lyon, France
| | - Timothé Boutelier
- Department of Research and Innovation, Olea Medical, La Ciotat, France
| | - Shivraman Giri
- Siemens Medical Solutions USA, Inc., Boston, MA, United States
| | - Hélène Ratiney
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS, UMR 5220, U1294, Lyon, France
| | | | - Jean-Paul Vallée
- Division of Radiology, Faculty of Medicine, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | - Pierre Croisille
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS, UMR 5220, U1294, Lyon, France.,Department of Radiology, CHU de Saint-Etienne, University of Lyon, UJM-Saint-Etienne, Saint-Étienne, France
| | - Magalie Viallon
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS, UMR 5220, U1294, Lyon, France.,Department of Radiology, CHU de Saint-Etienne, University of Lyon, UJM-Saint-Etienne, Saint-Étienne, France
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33
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Brown LAE, Saunderson CED, Das A, Craven T, Levelt E, Knott KD, Dall’Armellina E, Xue H, Moon JC, Greenwood JP, Kellman P, Swoboda PP, Plein S. A comparison of standard and high dose adenosine protocols in routine vasodilator stress cardiovascular magnetic resonance: dosage affects hyperaemic myocardial blood flow in patients with severe left ventricular systolic impairment. J Cardiovasc Magn Reson 2021; 23:37. [PMID: 33731141 PMCID: PMC7971951 DOI: 10.1186/s12968-021-00714-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 01/26/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Adenosine stress perfusion cardiovascular magnetic resonance (CMR) is commonly used in the assessment of patients with suspected ischaemia. Accepted protocols recommend administration of adenosine at a dose of 140 µg/kg/min increased up to 210 µg/kg/min if required. Conventionally, adequate stress has been assessed using change in heart rate, however, recent studies have suggested that these peripheral measurements may not reflect hyperaemia and can be blunted, in particular, in patients with heart failure. This study looked to compare stress myocardial blood flow (MBF) and haemodynamic response with different dosing regimens of adenosine during stress perfusion CMR in patients and healthy controls. METHODS 20 healthy adult subjects were recruited as controls to compare 3 adenosine perfusion protocols: standard dose (140 µg/kg/min for 4 min), high dose (210 µg/kg/min for 4 min) and long dose (140 µg/kg/min for 8 min). 60 patients with either known or suspected coronary artery disease (CAD) or with heart failure and different degrees of left ventricular (LV) dysfunction underwent adenosine stress with standard and high dose adenosine within the same scan. All studies were carried out on a 3 T CMR scanner. Quantitative global myocardial perfusion and haemodynamic response were compared between doses. RESULTS In healthy controls, no significant difference was seen in stress MBF between the 3 protocols. In patients with known or suspected CAD, and those with heart failure and mild systolic impairment (LV ejection fraction (LVEF) ≥ 40%) no significant difference was seen in stress MBF between standard and high dose adenosine. In those with LVEF < 40%, there was a significantly higher stress MBF following high dose adenosine compared to standard dose (1.33 ± 0.46 vs 1.10 ± 0.47 ml/g/min, p = 0.004). Non-responders to standard dose adenosine (defined by an increase in heart rate (HR) < 10 bpm) had a significantly higher stress HR following high dose (75 ± 12 vs 70 ± 14 bpm, p = 0.034), but showed no significant difference in stress MBF. CONCLUSIONS Increasing adenosine dose from 140 to 210 µg/kg/min leads to increased stress MBF in patients with significantly impaired LV systolic function. Adenosine dose in clinical perfusion assessment may need to be increased in these patients.
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Affiliation(s)
- Louise A. E. Brown
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Christopher E. D. Saunderson
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Arka Das
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Thomas Craven
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Eylem Levelt
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Kristopher D. Knott
- The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London, UK
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD USA
| | - Erica Dall’Armellina
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD USA
| | - James C. Moon
- The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London, UK
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD USA
| | - John P. Greenwood
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Peter Kellman
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
- The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London, UK
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD USA
| | - Peter P. Swoboda
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
| | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds, LS2 9JT UK
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Fidock B, Archer G, Barker N, Elhawaz A, Al-Mohammad A, Rothman A, Hose R, Hall IR, Grech E, Briffa N, Lewis N, van der Geest RJ, Zhang JM, Zhong L, Swift AJ, Wild JM, De Gárate E, Bucciarelli-Ducci C, Bax JJ, Plein S, Myerson S, Garg P. Standard and emerging CMR methods for mitral regurgitation quantification. Int J Cardiol 2021; 331:316-321. [PMID: 33548381 PMCID: PMC8040969 DOI: 10.1016/j.ijcard.2021.01.066] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 01/04/2021] [Accepted: 01/27/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND There are several methods to quantify mitral regurgitation (MR) by cardiovascular magnetic resonance (CMR). The interoperability of these methods and their reproducibility remains undetermined. OBJECTIVE To determine the agreement and reproducibility of different MR quantification methods by CMR across all aetiologies. METHODS Thirty-five patients with MR were recruited (primary MR = 12, secondary MR = 10 and MVR = 13). Patients underwent CMR, including cines and four-dimensional flow (4D flow). Four methods were evaluated: MRStandard (left ventricular stroke volume - aortic forward flow by phase contrast), MRLVRV (left ventricular stroke volume - right ventricular stroke volume), MRJet (direct jet quantification by 4D flow) and MRMVAV (mitral forward flow by 4D flow - aortic forward flow by 4D flow). For all cases and MR types, 520 MR volumes were recorded by these 4 methods for intra-/inter-observer tests. RESULTS In primary MR, MRMVAV and MRLVRV were comparable to MRStandard (P > 0.05). MRJet resulted in significantly higher MR volumes when compared to MRStandard (P < 0.05) In secondary MR and MVR cases, all methods were comparable. In intra-observer tests, MRMVAV demonstrated least bias with best limits of agreement (bias = -0.1 ml, -8 ml to 7.8 ml, P = 0.9) and best concordance correlation coefficient (CCC = 0.96, P < 0.01). In inter-observer tests, for primary MR and MVR, least bias and highest CCC were observed for MRMVAV. For secondary MR, bias was lowest for MRJet (-0.1 ml, PNS). CONCLUSION CMR methods of MR quantification demonstrate agreement in secondary MR and MVR. In primary MR, this was not observed. Across all types of MR, MRMVAV quantification demonstrated the highest reproducibility and consistency.
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Affiliation(s)
| | | | | | | | - Abdallah Al-Mohammad
- University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | | | - Rod Hose
- University of Sheffield, Sheffield, UK
| | - Ian R Hall
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Ever Grech
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Norman Briffa
- University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Nigel Lewis
- University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | | | | | | | | | | | | | | | - Jeroen J Bax
- Leiden University Medical Centre, Leiden, the Netherlands
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35
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Jacobs M, Benovoy M, Chang LC, Corcoran D, Berry C, Arai AE, Hsu LY. Automated Segmental Analysis of Fully Quantitative Myocardial Blood Flow Maps by First-Pass Perfusion Cardiovascular Magnetic Resonance. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:52796-52811. [PMID: 33996344 PMCID: PMC8117952 DOI: 10.1109/access.2021.3070320] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows fully quantitative pixel-wise myocardial blood flow (MBF) assessment, with proven diagnostic value for coronary artery disease. Segmental analysis requires manual segmentation of the myocardium. This work presents a fully automatic method of segmenting the left ventricular myocardium from MBF pixel maps, validated on a retrospective dataset of 247 clinical CMR perfusion studies, each including rest and stress images of three slice locations, performed on a 1.5T scanner. Pixel-wise MBF maps were segmented using an automated pipeline including region growing, edge detection, principal component analysis, and active contours to segment the myocardium, detect key landmarks, and divide the myocardium into sectors appropriate for analysis. Automated segmentation results were compared against a manually defined reference standard using three quantitative metrics: Dice coefficient, Cohen Kappa and myocardial border distance. Sector-wise average MBF and myocardial perfusion reserve (MPR) were compared using Pearson's correlation coefficient and Bland-Altman Plots. The proposed method segmented stress and rest MBF maps of 243 studies automatically. Automated and manual myocardial segmentation had an average (± standard deviation) Dice coefficient of 0.86 ± 0.06, Cohen Kappa of 0.86 ± 0.06, and Euclidian distances of 1.47 ± 0.73 mm and 1.02 ± 0.51 mm for the epicardial and endocardial border, respectively. Automated and manual sector-wise MBF and MPR values correlated with Pearson's coefficient of 0.97 and 0.92, respectively, while Bland-Altman analysis showed bias of 0.01 and 0.07 ml/g/min. The validated method has been integrated with our fully automated MBF pixel mapping pipeline to aid quantitative assessment of myocardial perfusion CMR.
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Affiliation(s)
- Matthew Jacobs
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, DC 20064, USA
| | - Mitchel Benovoy
- Circle Cardiovascular Imaging Inc., Calgary, AB T2P 3T6, Canada
| | - Lin-Ching Chang
- Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, DC 20064, USA
| | - David Corcoran
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8QQ, U.K
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Glasgow G81 4DY, U.K
| | - Colin Berry
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8QQ, U.K
- West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Glasgow G81 4DY, U.K
| | - Andrew E Arai
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Li-Yueh Hsu
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA
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Kawel-Boehm N, Hetzel SJ, Ambale-Venkatesh B, Captur G, Francois CJ, Jerosch-Herold M, Salerno M, Teague SD, Valsangiacomo-Buechel E, van der Geest RJ, Bluemke DA. Reference ranges ("normal values") for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update. J Cardiovasc Magn Reson 2020; 22:87. [PMID: 33308262 PMCID: PMC7734766 DOI: 10.1186/s12968-020-00683-3] [Citation(s) in RCA: 260] [Impact Index Per Article: 65.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 10/26/2020] [Indexed: 01/06/2023] Open
Abstract
Cardiovascular magnetic resonance (CMR) enables assessment and quantification of morphological and functional parameters of the heart, including chamber size and function, diameters of the aorta and pulmonary arteries, flow and myocardial relaxation times. Knowledge of reference ranges ("normal values") for quantitative CMR is crucial to interpretation of results and to distinguish normal from disease. Compared to the previous version of this review published in 2015, we present updated and expanded reference values for morphological and functional CMR parameters of the cardiovascular system based on the peer-reviewed literature and current CMR techniques. Further, databases and references for deep learning methods are included.
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Affiliation(s)
- Nadine Kawel-Boehm
- Department of Radiology, Kantonsspital Graubuenden, Loestrasse 170, 7000, Chur, Switzerland
- Institute for Diagnostic, Interventional and Pediatric Radiology (DIPR), Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, InselspitalBern, Switzerland
| | - Scott J Hetzel
- Department of Biostatistics and Medical Informatics, University of Wisconsin, 610 Walnut St, Madison, WI, 53726, USA
| | - Bharath Ambale-Venkatesh
- Department of Radiology, Johns Hopkins University, 600 N Wolfe Street, Baltimore, MD, 21287, USA
| | - Gabriella Captur
- MRC Unit of Lifelong Health and Ageing At UCL, 5-19 Torrington Place, Fitzrovia, London, WC1E 7HB, UK
- Inherited Heart Muscle Conditions Clinic, Royal Free Hospital NHS Foundation Trust, Hampstead, London, NW3 2QG, UK
| | - Christopher J Francois
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, Madison, WI, 53792, USA
| | - Michael Jerosch-Herold
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA
| | - Michael Salerno
- Cardiovascular Division, University of Virginia Health System, 1215 Lee Street, Charlottesville, VA, 22908, USA
| | - Shawn D Teague
- Department of Radiology, National Jewish Health, 1400 Jackson St, Denver, CO, 80206, USA
| | - Emanuela Valsangiacomo-Buechel
- Division of Paediatric Cardiology, University Children's Hospital Zurich, Steinwiesstrasse 75, 8032, Zurich, Switzerland
| | - Rob J van der Geest
- Department of Radiology, Leiden University Medical Center, Albinusdreef 2, 2333ZA, Leiden, The Netherlands
| | - David A Bluemke
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, Madison, WI, 53792, USA.
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Kwong RY, Chandrashekhar Y. The Higher You Climb, the Better the View: Quantitative CMR Perfusion Mapping for CAD. JACC Cardiovasc Imaging 2020; 13:2700-2702. [DOI: 10.1016/j.jcmg.2020.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Mathew RC, Bourque JM, Salerno M, Kramer CM. Cardiovascular Imaging Techniques to Assess Microvascular Dysfunction. JACC Cardiovasc Imaging 2020; 13:1577-1590. [PMID: 31607665 PMCID: PMC7148179 DOI: 10.1016/j.jcmg.2019.09.006] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 08/02/2019] [Accepted: 09/03/2019] [Indexed: 02/08/2023]
Abstract
The understanding of microvascular dysfunction without evidence of epicardial coronary artery disease pales in comparison with that of obstructive epicardial coronary artery disease. A primary limitation in the past had been the lack of development of noninvasive methods of detecting and quantifying microvascular dysfunction. This limitation has particularly affected the ability to study the pathophysiology, morbidity, and treatment of this disease. More recently, almost all of the noninvasive cardiac imaging modalities have been used to quantify blood flow and advance understanding of microvascular dysfunction.
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Affiliation(s)
- Roshin C Mathew
- Department of Medicine (Cardiology), University of Virginia Health System, Charlottesville, Virginia
| | - Jamieson M Bourque
- Department of Medicine (Cardiology), University of Virginia Health System, Charlottesville, Virginia; Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - Michael Salerno
- Department of Medicine (Cardiology), University of Virginia Health System, Charlottesville, Virginia; Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia; Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Christopher M Kramer
- Department of Medicine (Cardiology), University of Virginia Health System, Charlottesville, Virginia; Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia.
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Poli FE, Gulsin GS, March DS, Abdelaty AM, Parke KS, Wormleighton JV, McCann GP, Burton JO, Graham-Brown MP. The reliability and feasibility of non-contrast adenosine stress cardiovascular magnetic resonance T1 mapping in patients on haemodialysis. J Cardiovasc Magn Reson 2020; 22:43. [PMID: 32507107 PMCID: PMC7278072 DOI: 10.1186/s12968-020-00634-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 05/08/2020] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Identifying coronary artery disease (CAD) in patients with end-stage renal disease (ESRD) is challenging. Adenosine stress native T1 mapping with cardiovascular magnetic resonance (CMR) may accurately detect obstructive CAD and microvascular dysfunction in the general population. This study assessed the feasibility and reliability of adenosine stress native T1 mapping in patients on haemodialysis. METHODS The feasibility of undertaking rest and adenosine stress native T1 mapping using the single-shot Modified Look-Locker inversion recovery (MOLLI) sequence was assessed in 58 patients on maintenance haemodialysis using 3 T CMR. Ten patients underwent repeat stress CMR within 2 weeks for assessment of test-retest reliability of native T1, stress T1 and delta T1 (ΔT1). Interrater and intrarater agreement were assessed in 10 patients. Exploratory analyses were undertaken to assess associations between clinical variables and native T1 values in 51 patients on haemodialysis. RESULTS Mean age of participants was 55 ± 15 years, 46 (79%) were male, and median dialysis vintage was 21 (8; 48) months. All patients completed the scan without complications. Mean native T1 rest, stress and ΔT1 were 1261 ± 57 ms, 1297 ± 50 ms and 2.9 ± 2.5%, respectively. Interrater and intrarater agreement of rest T1, stress T1 and ΔT1 were excellent, with intraclass correlation coefficients (ICC) > 0.9 for all. Test-retest reliability of rest and stress native T1 were excellent or good (CoV 1.2 and 1.5%; ICC, 0.79 and 0.69, respectively). Test-retest reliability of ΔT1 was moderate to poor (CoV 27.4%, ICC 0.55). On multivariate analysis, CAD, diabetes mellitus and resting native T1 time were independent determinants of ΔT1 (β = - 0.275, p = 0.019; β = - 0.297, p = 0.013; β = - 0.455; p < 0.001, respectively). CONCLUSIONS Rest and adenosine stress native T1 mapping is feasible and well-tolerated amongst patients with ESRD on haemodialysis. Although rater agreement of the technique is excellent, test-retest reliability of ΔT1 is moderate to poor. Prospective studies should evaluate the relationship between this technique and established methods of CAD assessment and association with outcomes.
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Affiliation(s)
- Federica E Poli
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK
| | - Gaurav S Gulsin
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Daniel S March
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK
- John Walls Renal Unit, University Hospitals Leicester NHS Trust, Leicester, UK
| | - Ahmed Msek Abdelaty
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK
| | - Kelly S Parke
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Joanne V Wormleighton
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Gerry P McCann
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - James O Burton
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK
- John Walls Renal Unit, University Hospitals Leicester NHS Trust, Leicester, UK
- National Centre for Sport and Exercise Medicine, School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | - Matthew Pm Graham-Brown
- Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE1 9HN, UK.
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK.
- John Walls Renal Unit, University Hospitals Leicester NHS Trust, Leicester, UK.
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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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Knott KD, Seraphim A, Augusto JB, Xue H, Chacko L, Aung N, Petersen SE, Cooper JA, Manisty C, Bhuva AN, Kotecha T, Bourantas CV, Davies RH, Brown LA, Plein S, Fontana M, Kellman P, Moon JC. The Prognostic Significance of Quantitative Myocardial Perfusion: An Artificial Intelligence-Based Approach Using Perfusion Mapping. Circulation 2020; 141:1282-1291. [PMID: 32078380 PMCID: PMC7176346 DOI: 10.1161/circulationaha.119.044666] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 01/23/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND Myocardial perfusion reflects the macro- and microvascular coronary circulation. Recent quantitation developments using cardiovascular magnetic resonance perfusion permit automated measurement clinically. We explored the prognostic significance of stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR, the ratio of stress to rest MBF). METHODS A 2-center study of patients with both suspected and known coronary artery disease referred clinically for perfusion assessment. Image analysis was performed automatically using a novel artificial intelligence approach deriving global and regional stress and rest MBF and MPR. Cox proportional hazard models adjusting for comorbidities and cardiovascular magnetic resonance parameters sought associations of stress MBF and MPR with death and major adverse cardiovascular events (MACE), including myocardial infarction, stroke, heart failure hospitalization, late (>90 day) revascularization, and death. RESULTS A total of 1049 patients were included with a median follow-up of 605 (interquartile range, 464-814) days. There were 42 (4.0%) deaths and 188 MACE in 174 (16.6%) patients. Stress MBF and MPR were independently associated with both death and MACE. For each 1 mL·g-1·min-1 decrease in stress MBF, the adjusted hazard ratios for death and MACE were 1.93 (95% CI, 1.08-3.48, P=0.028) and 2.14 (95% CI, 1.58-2.90, P<0.0001), respectively, even after adjusting for age and comorbidity. For each 1 U decrease in MPR, the adjusted hazard ratios for death and MACE were 2.45 (95% CI, 1.42-4.24, P=0.001) and 1.74 (95% CI, 1.36-2.22, P<0.0001), respectively. In patients without regional perfusion defects on clinical read and no known macrovascular coronary artery disease (n=783), MPR remained independently associated with death and MACE, with stress MBF remaining associated with MACE only. CONCLUSIONS In patients with known or suspected coronary artery disease, reduced MBF and MPR measured automatically inline using artificial intelligence quantification of cardiovascular magnetic resonance perfusion mapping provides a strong, independent predictor of adverse cardiovascular outcomes.
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Affiliation(s)
- Kristopher D. Knott
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Andreas Seraphim
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Joao B. Augusto
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (H.X., P.K.)
| | - Liza Chacko
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Royal Free Hospital, London, United Kingdom (L.C., T.K., M.F.)
| | - Nay Aung
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
- William Harvey Research Institute, Queen Mary University of London, United Kingdom (N.A., S.E.P., J.A.C.)
| | - Steffen E. Petersen
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
- William Harvey Research Institute, Queen Mary University of London, United Kingdom (N.A., S.E.P., J.A.C.)
| | - Jackie A. Cooper
- William Harvey Research Institute, Queen Mary University of London, United Kingdom (N.A., S.E.P., J.A.C.)
| | - Charlotte Manisty
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Anish N. Bhuva
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Tushar Kotecha
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Royal Free Hospital, London, United Kingdom (L.C., T.K., M.F.)
| | - Christos V. Bourantas
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Rhodri H. Davies
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
| | - Louise A.E. Brown
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, United Kingdom (L.A.E.B., S.P.)
| | - Sven Plein
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, United Kingdom (L.A.E.B., S.P.)
| | - Marianna Fontana
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Royal Free Hospital, London, United Kingdom (L.C., T.K., M.F.)
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (H.X., P.K.)
| | - James C. Moon
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., A.S., J.B.A., L.C., C.M., A.N.B., T.K., C.V.B., R.H.D., M.F., J.C.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (K.D.K., A.S., J.B.A., N.A., S.E.P., C.M., A.N.B., C.V.B., R.H.D., J.C.M.)
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Schulz-Menger J, Bluemke DA, Bremerich J, Flamm SD, Fogel MA, Friedrich MG, Kim RJ, von Knobelsdorff-Brenkenhoff F, Kramer CM, Pennell DJ, Plein S, Nagel E. Standardized image interpretation and post-processing in cardiovascular magnetic resonance - 2020 update : Society for Cardiovascular Magnetic Resonance (SCMR): Board of Trustees Task Force on Standardized Post-Processing. J Cardiovasc Magn Reson 2020; 22:19. [PMID: 32160925 PMCID: PMC7066763 DOI: 10.1186/s12968-020-00610-6] [Citation(s) in RCA: 472] [Impact Index Per Article: 118.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 02/17/2020] [Indexed: 01/04/2023] Open
Abstract
With mounting data on its accuracy and prognostic value, cardiovascular magnetic resonance (CMR) is becoming an increasingly important diagnostic tool with growing utility in clinical routine. Given its versatility and wide range of quantitative parameters, however, agreement on specific standards for the interpretation and post-processing of CMR studies is required to ensure consistent quality and reproducibility of CMR reports. This document addresses this need by providing consensus recommendations developed by the Task Force for Post-Processing of the Society for Cardiovascular Magnetic Resonance (SCMR). The aim of the Task Force is to recommend requirements and standards for image interpretation and post-processing enabling qualitative and quantitative evaluation of CMR images. Furthermore, pitfalls of CMR image analysis are discussed where appropriate. It is an update of the original recommendations published 2013.
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Affiliation(s)
- Jeanette Schulz-Menger
- Department of Cardiology and Nephrology, Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrueck Center for Molecular Medicine, and HELIOS Klinikum Berlin Buch, Schwanebecker Chaussee 50, 13125, Berlin, Germany.
| | - David A Bluemke
- University of Wisconsin School of Medicine and Public Health, Madison, USA
| | - Jens Bremerich
- Department of Radiology of the University Hospital Basel, Basel, Switzerland
| | - Scott D Flamm
- Imaging, and Heart and Vascular Institutes, Cleveland Clinic, Cleveland, OH, USA
| | - Mark A Fogel
- Department of Radiology, Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Matthias G Friedrich
- Departments of Medicine and Diagnostic Radiology, McGill University, Montreal, QC, Canada
| | - Raymond J Kim
- Duke Cardiovascular Magnetic Resonance Center, and Departments of Medicine and Radiology, Duke University Medical Center, Durham, NC, USA
| | | | - Christopher M Kramer
- Departments of Medicine and Radiology and the Cardiovascular Imaging Center, University of Virginia Health System, Charlottesville, VA, USA
| | | | - Sven Plein
- Leeds Institute for Genetics Health and Therapeutics & Leeds Multidisciplinary Cardiovascular Research Centre, University of Leeds, Leeds, UK
| | - Eike Nagel
- Institute for Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site RheinMain, University Hospital Frankfurt, Frankfurt am Main, Germany
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Abstract
Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging, whereas PET is the clinical reference standard for the quantification of myocardial perfusion. MRI does not involve exposure to ionizing radiation, similar to echocardiography, which can be performed at the bedside. CT perfusion imaging is not frequently used but CT offers coronary angiography data, and invasive catheter-based methods can measure coronary flow and pressure. Technical improvements to the quantification of pathophysiological parameters of myocardial ischaemia can be achieved. Clinical consensus recommendations on the appropriateness of each technique were derived following a European quantitative cardiac imaging meeting and using a real-time Delphi process. SPECT using new detectors allows the quantification of myocardial blood flow and is now also suited to patients with a high BMI. PET is well suited to patients with multivessel disease to confirm or exclude balanced ischaemia. MRI allows the evaluation of patients with complex disease who would benefit from imaging of function and fibrosis in addition to perfusion. Echocardiography remains the preferred technique for assessing ischaemia in bedside situations, whereas CT has the greatest value for combined quantification of stenosis and characterization of atherosclerosis in relation to myocardial ischaemia. In patients with a high probability of needing invasive treatment, invasive coronary flow and pressure measurement is well suited to guide treatment decisions. In this Consensus Statement, we summarize the strengths and weaknesses as well as the future technological potential of each imaging modality.
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Scannell CM, Chiribiri A, Villa ADM, Breeuwer M, Lee J. Hierarchical Bayesian myocardial perfusion quantification. Med Image Anal 2020; 60:101611. [PMID: 31760191 PMCID: PMC6880627 DOI: 10.1016/j.media.2019.101611] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 11/07/2019] [Accepted: 11/08/2019] [Indexed: 01/25/2023]
Abstract
Myocardial blood flow can be quantified from dynamic contrast-enhanced magnetic resonance (MR) images through the fitting of tracer-kinetic models to the observed imaging data. The use of multi-compartment exchange models is desirable as they are physiologically motivated and resolve directly for both blood flow and microvascular function. However, the parameter estimates obtained with such models can be unreliable. This is due to the complexity of the models relative to the observed data which is limited by the low signal-to-noise ratio, the temporal resolution, the length of the acquisitions and other complex imaging artefacts. In this work, a Bayesian inference scheme is proposed which allows the reliable estimation of the parameters of the two-compartment exchange model from myocardial perfusion MR data. The Bayesian scheme allows the incorporation of prior knowledge on the physiological ranges of the model parameters and facilitates the use of the additional information that neighbouring voxels are likely to have similar kinetic parameter values. Hierarchical priors are used to avoid making a priori assumptions on the health of the patients. We provide both a theoretical introduction to Bayesian inference for tracer-kinetic modelling and specific implementation details for this application. This approach is validated in both in silico and in vivo settings. In silico, there was a significant reduction in mean-squared error with the ground-truth parameters using Bayesian inference as compared to using the standard non-linear least squares fitting. When applied to patient data the Bayesian inference scheme returns parameter values that are in-line with those previously reported in the literature, as well as giving parameter maps that match the independant clinical diagnosis of those patients.
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Affiliation(s)
- Cian M Scannell
- School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; The Alan Turing Institute London, United Kingdom.
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom.
| | - Adriana D M Villa
- School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom.
| | - Marcel Breeuwer
- Philips Healthcare, Best, the Netherlands; Department of Biomedical Engineering, Medical Image Analysis group, Eindhoven University of Technology, Eindhoven, the Netherlands.
| | - Jack Lee
- School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom.
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Xue H, Brown LA, Nielles-Vallespin S, Plein S, Kellman P. Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation. Magn Reson Med 2020; 83:712-730. [PMID: 31441550 PMCID: PMC8400845 DOI: 10.1002/mrm.27954] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 06/27/2019] [Accepted: 07/27/2019] [Indexed: 02/03/2023]
Abstract
PURPOSE Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization. METHODS Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g). RESULTS Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50). CONCLUSIONS An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.
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Affiliation(s)
- Hui Xue
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Louise A.E. Brown
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | | | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter Kellman
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
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Manning WJ. Journal of Cardiovascular Magnetic Resonance: 2017/2018 in review. J Cardiovasc Magn Reson 2019; 21:79. [PMID: 31884956 PMCID: PMC6936125 DOI: 10.1186/s12968-019-0594-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/14/2022] Open
Abstract
There were 89 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 76 original research papers, 4 reviews, 5 technical notes, 1 guideline, and 3 corrections. The volume was down slightly from 2017 with a corresponding 15% decrease in manuscript submissions from 405 to 346 and thus reflects a slight increase in the acceptance rate from 25 to 26%. The decrease in submissions for the year followed the initiation of the increased author processing charge (APC) for Society for Cardiovascular Magnetic Resonance (SCMR) members for manuscripts submitted after June 30, 2018. The quality of the submissions continues to be high. The 2018 JCMR Impact Factor (which is published in June 2019) was slightly lower at 5.1 (vs. 5.46 for 2017; as published in June 2018. The 2018 impact factor means that on average, each JCMR published in 2016 and 2017 was cited 5.1 times in 2018. Our 5 year impact factor was 5.82.In accordance with Open-Access publishing guidelines of BMC, the JCMR articles are published on-line in a continuus fashion in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful for the JCMR audience to annually summarize the publications into broad areas of interest or themes, so that readers can view areas of interest in a single article in relation to each other and contemporaneous JCMR publications. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, as in the past two years, I have used this publication to also convey information regarding the editorial process and as a "State of our JCMR."This is the 12th year of JCMR as an open-access publication with BMC (formerly known as Biomed Central). The timing of the JCMR transition to the open access platform was "ahead of the curve" and a tribute to the vision of Dr. Matthias Friedrich, the SCMR Publications Committee Chair and Dr. Dudley Pennell, the JCMR editor-in-chief at the time. The open-access system has dramatically increased the reading and citation of JCMR publications and I hope that you, our authors, will continue to send your very best, high quality manuscripts to JCMR for consideration. It takes a village to run a journal and I thank our very dedicated Associate Editors, Guest Editors, Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner. These efforts have allowed the JCMR to continue as the premier journal of our field. This entire process would also not be possible without the dedication and efforts of our managing editor, Diana Gethers. Finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 4th year as your editor-in-chief. It has been a tremendous experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!
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Affiliation(s)
- Warren J Manning
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
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Nickander J, Themudo R, Thalén S, Sigfridsson A, Xue H, Kellman P, Ugander M. The relative contributions of myocardial perfusion, blood volume and extracellular volume to native T1 and native T2 at rest and during adenosine stress in normal physiology. J Cardiovasc Magn Reson 2019; 21:73. [PMID: 31767018 PMCID: PMC6876099 DOI: 10.1186/s12968-019-0585-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 10/22/2019] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Both ischemic and non-ischemic heart disease can cause disturbances in the myocardial blood volume (MBV), myocardial perfusion and the myocardial extracellular volume fraction (ECV). Recent studies suggest that native myocardial T1 mapping can detect changes in MBV during adenosine stress without the use of contrast agents. Furthermore, native T2 mapping could also potentially be used to quantify changes in myocardial perfusion and/or MBV. Therefore, the aim of this study was to explore the relative contributions of myocardial perfusion, MBV and ECV to native T1 and native T2 at rest and during adenosine stress in normal physiology. METHODS Healthy subjects (n = 41, 26 ± 5 years, 51% females) underwent 1.5 T cardiovascular magnetic resonance (CMR) scanning. Quantitative myocardial perfusion [ml/min/g] and MBV [%] maps were computed from first pass perfusion imaging at adenosine stress (140 microg/kg/min infusion) and rest following an intravenous contrast bolus (0.05 mmol/kg, gadobutrol). Native T1 and T2 maps were acquired before and during adenosine stress. T1 maps at rest and stress were also acquired following a 0.2 mmol/kg cumulative intravenous contrast dose, rendering rest and stress ECV maps [%]. Myocardial T1, T2, perfusion, MBV and ECV values were measured by delineating a region of interest in the midmural third of the myocardium. RESULTS During adenosine stress, there was an increase in myocardial native T1, native T2, perfusion, MBV, and ECV (p ≤ 0.001 for all). Myocardial perfusion, MBV and ECV all correlated with both native T1 and native T2, respectively (R2 = 0.35 to 0.61, p < 0.001 for all). Multivariate linear regression revealed that ECV and perfusion together best explained the change in native T2 (ECV beta 0.21, p = 0.02, perfusion beta 0.66, p < 0.001, model R2 = 0.64, p < 0.001), and native T1 (ECV beta 0.50, p < 0.001, perfusion beta 0.43, p < 0.001, model R2 = 0.69, p < 0.001). CONCLUSIONS Myocardial native T1, native T2, perfusion, MBV, and ECV all increase during adenosine stress. Changes in myocardial native T1 and T2 during adenosine stress in normal physiology can largely be explained by the combined changes in myocardial perfusion and ECV. TRIAL REGISTRATION Clinicaltrials.gov identifier NCT02723747. Registered March 16, 2016.
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Affiliation(s)
- Jannike Nickander
- Department of Clinical Physiology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
| | - Raquel Themudo
- Department of Clinical Physiology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
- Department of Radiology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
| | - Simon Thalén
- Department of Clinical Physiology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
| | - Andreas Sigfridsson
- Department of Clinical Physiology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD USA
| | - Martin Ugander
- Department of Clinical Physiology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden
- Kolling Institute, Royal North Shore Hospital, and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia
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Nazir MS, Gould SM, Milidonis X, Reyes E, Ismail TF, Neji R, Roujol S, O’Doherty J, Xue H, Barrington SF, Schaeffter T, Razavi R, Marsden P, Kellman P, Plein S, Chiribiri A. Simultaneous 13N-Ammonia and gadolinium first-pass myocardial perfusion with quantitative hybrid PET-MR imaging: a phantom and clinical feasibility study. Eur J Hybrid Imaging 2019; 3:15. [PMID: 31544170 PMCID: PMC6718374 DOI: 10.1186/s41824-019-0062-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 07/15/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Positron emission tomography (PET) is the non-invasive reference standard for myocardial blood flow (MBF) quantification. Hybrid PET-MR allows simultaneous PET and cardiac magnetic resonance (CMR) acquisition under identical experimental and physiological conditions. This study aimed to determine feasibility of simultaneous 13N-Ammonia PET and dynamic contrast-enhanced CMR MBF quantification in phantoms and healthy volunteers. METHODS Images were acquired using a 3T hybrid PET-MR scanner. Phantom study: MBF was simulated at different physiological perfusion rates and a protocol for simultaneous PET-MR perfusion imaging was developed. Volunteer study: five healthy volunteers underwent adenosine stress. 13N-Ammonia and gadolinium were administered simultaneously. PET list mode data was reconstructed using ordered subset expectation maximisation. CMR MBF was quantified using Fermi function-constrained deconvolution of arterial input function and myocardial signal. PET MBF was obtained using a one-tissue compartment model and image-derived input function. RESULTS Phantom study: PET and CMR MBF measurements demonstrated high repeatability with intraclass coefficients 0.98 and 0.99, respectively. There was high correlation between PET and CMR MBF (r = 0.98, p < 0.001) and good agreement (bias - 0.85 mL/g/min; 95% limits of agreement 0.29 to - 1.98). Volunteer study: Mean global stress MBF for CMR and PET were 2.58 ± 0.11 and 2.60 ± 0.47 mL/g/min respectively. On a per territory basis, there was moderate correlation (r = 0.63, p = 0.03) and agreement (bias - 0.34 mL/g/min; 95% limits of agreement 0.49 to - 1.18). CONCLUSION Simultaneous MBF quantification using hybrid PET-MR imaging is feasible with high test repeatability and good to moderate agreement between PET and CMR. Future studies in coronary artery disease patients may allow cross-validation of techniques.
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Affiliation(s)
- Muhummad Sohaib Nazir
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Sarah-May Gould
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Xenios Milidonis
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Eliana Reyes
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Tevfik F. Ismail
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Radhouene Neji
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
- Siemens Healthcare Limited, Sir William Siemens Square, Frimley, Camberley, GU16 8QD UK
| | - Sébastien Roujol
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Jim O’Doherty
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Hui Xue
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD USA
| | - Sally F. Barrington
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Tobias Schaeffter
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | - Reza Razavi
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Paul Marsden
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD USA
| | - Sven Plein
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, LIGHT Laboratories, Clarendon Way, University of Leeds, Leeds, LS2 9JT UK
| | - Amedeo Chiribiri
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, Westminster Bridge, 4th Floor Lambeth Wing, London, SE1 7EH UK
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Knott KD, Augusto JB, Nordin S, Kozor R, Camaioni C, Xue H, Hughes RK, Manisty C, Brown LAE, Kellman P, Ramaswami U, Hughes D, Plein S, Moon JC. Quantitative Myocardial Perfusion in Fabry Disease. Circ Cardiovasc Imaging 2019; 12:e008872. [PMID: 31269811 DOI: 10.1161/circimaging.119.008872] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Fabry disease (FD) is an X-linked lysosomal storage disease resulting in tissue accumulation of sphingolipids. Key myocardial processes that lead to adverse outcomes in FD include storage, hypertrophy, inflammation, and fibrosis. These are quantifiable by multiparametric cardiovascular magnetic resonance. Recent developments in cardiovascular magnetic resonance perfusion mapping allow rapid in-line perfusion quantification permitting broader clinical application, including the assessment of microvascular dysfunction. We hypothesized that microvascular dysfunction in FD would be associated with storage, fibrosis, and edema. METHODS A prospective, observational study of 44 FD patients (49 years, 43% male, 24 [55%] with left ventricular hypertrophy [LVH]) and 27 healthy controls with multiparametric cardiovascular magnetic resonance including vasodilator stress perfusion mapping. Myocardial blood flow (MBF) was measured and its associations with other processes investigated. RESULTS Compared with LVH- FD, LVH+ FD had higher left ventricular ejection fraction (73% versus 68%), more late gadolinium enhancement (85% versus 15%), and a lower stress MBF (1.76 versus 2.36 mL/g per minute). The reduction in stress MBF was more pronounced in the subendocardium than subepicardium. LVH- FD had lower stress MBF than controls (2.36 versus 3.00 mL/g per minute; P=0.002). Across all FD, late gadolinium enhancement and low native T1 were independently associated with reduced stress MBF. On a per-segment basis, stress MBF was independently associated with wall thickness, T2, extracellular volume fraction, and late gadolinium enhancement. CONCLUSIONS FD patients have reduced perfusion, particularly in the subendocardium with greater reductions with LVH, storage, edema, and scar. Perfusion is reduced even without LVH suggesting it is an early disease marker.
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Affiliation(s)
- Kristopher D Knott
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Joao B Augusto
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Sabrina Nordin
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Rebecca Kozor
- Sydney Medical School, University of Sydney, Australia (R.K.)
| | - Claudia Camaioni
- Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Hui Xue
- Medical Signal and Image Processing, National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD (H.X., P.K.)
| | - Rebecca K Hughes
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Charlotte Manisty
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
| | - Louise A E Brown
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, United Kingdom (L.A.E.B., S.P.)
| | - Peter Kellman
- Medical Signal and Image Processing, National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD (H.X., P.K.)
| | - Uma Ramaswami
- Lysosomal Storage Disorder Unit, Royal Free Hospital, London, United Kingdom (U.R., D.H.)
| | - Derralyn Hughes
- Lysosomal Storage Disorder Unit, Royal Free Hospital, London, United Kingdom (U.R., D.H.)
| | - Sven Plein
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, United Kingdom (L.A.E.B., S.P.)
| | - James C Moon
- Institute of Cardiovascular Science, University College London, United Kingdom (K.D.K., J.B.A., S.N., R.K.H., C.M., J.C.M.).,Advanced Cardiac Imaging, Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London, United Kingdom (K.D.K., J.B.A., S.N., C.C., R.K.H., C.M., J.C.M.)
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50
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Jerosch-Herold M, Slomka P. Myocardial Blood Flow Quantification With Dynamic Contrast-Enhanced Computed Tomography. Circ Cardiovasc Imaging 2019; 12:e009431. [DOI: 10.1161/circimaging.119.009431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
| | - Piotr Slomka
- Artificial Intelligence in Medicine Program, Cedars-Sinai Medical Center, Los Angeles, CA (P.S.)
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