Stress Perfusion Cardiac Magnetic Resonance in Long-Standing Non-Infarcted Chronic Coronary Syndrome with Preserved Systolic Function
Abstract
:1. Introduction
2. Materials and Methods
2.1. Cardiac Magnetic Resonance Imaging Protocol
2.2. Study Outcomes and Patient’s Follow-Up
2.3. Statistical Analysis
3. Results
3.1. Patient Characteristics
3.2. Chronic Coronary Syndrome Characteristics
3.3. Association with Outcomes
4. Discussion
CCS and Outcome Association
- spCMR findings result as good predictors of clinical evolution of CCS patients beyond symptoms and CAD extension. The probability of developing MACE was about 90% when ischemia was detected, with a high prevalence of HF syndrome during follow-up.
- CMR-related strain confirms its ability to stage myocardial damage, which could translate into a critical ability to predict disease progression [99,100]. Among CCS patients with ischemia and no other conventional imaging predictor, GLS resulted highly impaired with a good correlation with the ischemic burden. This correlation proves GLS (an indicator of global function) as effective in describing the real impact of ischemia on cardiac function beyond the localized distribution of ischemic damage [101].
- Despite GLS significantly differing between ischemic and non-ischemic CCS patients, GCS and GRS results were impaired when compared to a healthy population. Actually, in our series, GCS showed a stable early impairment compared to healthy volunteers. GCS impairment is indeed more likely related to a transmural injury/advanced disease, while GLS resulted most sensitive to a subendocardial/early injury [99]. On the other hand, the lack of a significant difference of GRS between ischemic and non-ischemic longstanding CCS patients could be explained by a relatively preserved compensating mechanism offered by circumferential fibers, since radial strain is tethered with other longitudinal and circumferential fibers and no radially oriented fibers are disposed within the myocardium.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Knuuti, J.; Wijns, W.; Saraste, A.; Capodanno, D.; Barbato, E.; Funck-Brentano, C.; Prescott, E.; Storey, R.F.; Deaton, C.; Cuisset, T.; et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC). Eur. Heart J. 2020, 41, 407–477. [Google Scholar] [CrossRef] [PubMed]
- Danad, I.; Szymonifka, J.; Twisk, J.W.; Nørgaard, B.; Zarins, C.K.; Knaapen, P.; Min, J.K. Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: A meta-analysis. Eur. Heart J. 2016, 38, 991–998. [Google Scholar] [CrossRef] [PubMed]
- Esposito, A.; Gallone, G.; Palmisano, A.; Marchitelli, L.; Catapano, F.; Francone, M. The current landscape of imaging recommendations in cardiovascular clinical guidelines: Toward an imaging-guided precision medicine. Radiol. Med. 2020, 125, 1013–1023. [Google Scholar] [CrossRef] [PubMed]
- Ciancarella, P.; Ciliberti, P.; Santangelo, T.P.; Secchi, F.; Stagnaro, N.; Secinaro, A. Noninvasive imaging of congenital cardiovascular defects. Radiol. Med. 2020, 125, 1167–1185. [Google Scholar] [CrossRef] [PubMed]
- La Grutta, L.; Toia, P.; Grassedonio, E.; Pasta, S.; Albano, D.; Agnello, F.; Maffei, E.; Cademartiri, F.; Bartolotta, T.V.; Galia, M.; et al. TAVI imaging: Over the echocardiography. Radiol. Med. 2020, 125, 1148–1166. [Google Scholar] [CrossRef]
- Takehara, Y. 4D Flow when and how? Radiol. Med. 2020, 125, 838–850. [Google Scholar] [CrossRef]
- Palmisano, A.; Darvizeh, F.; Cundari, G.; Rovere, G.; Ferrandino, G.; Nicoletti, V.; Cilia, F.; De Vizio, S.; Palumbo, R.; Esposito, A.; et al. Advanced cardiac imaging in athlete’s heart: Unravelling the grey zone between physiologic adaptation and pathology. Radiol. Med. 2021, 126, 1518–1531. [Google Scholar] [CrossRef]
- Schicchi, N.; Fogante, M.; Palumbo, P.; Agliata, G.; Pirani, P.E.; Di Cesare, E.; Giovagnoni, A. The sub-millisievert era in CTCA: The technical basis of the new radiation dose approach. Radiol. Med. 2020, 125, 1024–1039. [Google Scholar] [CrossRef]
- Ledda, R.E.; Milanese, G.; Cademartiri, F.; Maffei, E.; Benedetti, G.; Goldoni, M.; Silva, M.; Sverzellati, N. Association of hepatic steatosis with epicardial fat volume and coronary artery disease in symptomatic patients. Radiol. Med. 2021, 126, 652–660. [Google Scholar] [CrossRef]
- Hoffmann, U.; Truong, Q.A.; Schoenfeld, D.A.; Chou, E.T.; Woodard, P.K.; Nagurney, J.T.; Pope, J.H.; Hauser, T.H.; White, C.S.; Weiner, S.; et al. Coronary CT Angiography versus Standard Evaluation in Acute Chest Pain. N. Engl. J. Med. 2012, 367, 299–308. [Google Scholar] [CrossRef] [Green Version]
- Douglas, P.S.; Hoffmann, U.; Patel, M.R.; Mark, D.B.; Al-Khalidi, H.R.; Cavanaugh, B.; Cole, J.; Dolor, R.; Fordyce, C.B.; Huang, M.; et al. Outcomes of Anatomical versus Functional Testing for Coronary Artery Disease. N. Engl. J. Med. 2015, 372, 1291–1300. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hoffmann, U.; Ferencik, M.; Udelson, J.E.; Picard, M.H.; Truong, Q.A.; Patel, M.R.; Huang, M.; Pencina, M.; Mark, D.B.; Heitner, J.F.; et al. Prognostic Value of Noninvasive Cardiovascular Testing in Patients With Stable Chest Pain. Circulation 2017, 135, 2320–2332. [Google Scholar] [CrossRef] [PubMed]
- Newby, D.E.; Williams, M.C.; Dweck, M.R. Forget Ischemia: It’s All About the Plaque. Circulation 2021, 144, 1039–1041. [Google Scholar] [CrossRef] [PubMed]
- Reynolds, H.R.; Picard, M.H.; Spertus, J.A.; Peteiro, J.; Sendon, J.L.L.; Senior, R.; El-Hajjar, M.C.; Celutkiene, J.; Shapiro, M.D.; Pellikka, P.A.; et al. Natural History of Patients With Ischemia and No Obstructive Coronary Artery Disease. Circulation 2021, 144, 1008–1023. [Google Scholar] [CrossRef]
- Reynolds, H.R.; Shaw, L.J.; Min, J.K.; Page, C.B.; Berman, D.S.; Chaitman, B.R.; Picard, M.H.; Kwong, R.Y.; O’Brien, S.M.; Huang, Z.; et al. Outcomes in the ISCHEMIA Trial Based on Coronary Artery Disease and Ischemia Severity. Circulation 2021, 144, 1024–1038. [Google Scholar] [CrossRef]
- Pezel, T.; Silva, L.M.; Bau, A.A.; Teixiera, A.; Jerosch-Herold, M.; Coelho-Filho, O.R. What Is the Clinical Impact of Stress CMR After the ISCHEMIA Trial? Front. Cardiovasc. Med. 2021, 8, 683434. [Google Scholar] [CrossRef]
- Velazquez, E.J.; Lee, K.L.; Jones, R.H.; Al-Khalidi, H.R.; Hill, J.A.; Panza, J.A.; Michler, R.E.; Bonow, R.O.; Doenst, T.; Petrie, M.C.; et al. Coronary-Artery Bypass Surgery in Patients with Ischemic Cardiomyopathy. N. Engl. J. Med. 2016, 374, 1511–1520. [Google Scholar] [CrossRef]
- Ge, Y.; Antiochos, P.; Steel, K.; Bingham, S.; Abdullah, S.; Chen, Y.-Y.; Mikolich, J.R.; Arai, A.E.; Bandettini, W.P.; Shanbhag, S.M.; et al. Prognostic Value of Stress CMR Perfusion Imaging in Patients With Reduced Left Ventricular Function. JACC Cardiovasc. Imaging 2020, 13, 2132–2145. [Google Scholar] [CrossRef]
- Patel, A.R.; Salerno, M.; Kwong, R.Y.; Singh, A.; Heydari, B.; Kramer, C.M. Stress Cardiac Magnetic Resonance Myocardial Perfusion Imaging. J. Am. Coll. Cardiol. 2021, 78, 1655–1668. [Google Scholar] [CrossRef]
- Pezel, T.; Garot, P.; Hovasse, T.; Unterseeh, T.; Champagne, S.; Kinnel, M.; Toupin, S.; Louvard, Y.; Morice, M.C.; Sanguineti, F.; et al. Vasodilatation stress cardiovascular magnetic resonance imaging: Feasibility, workflow and safety in a large prospective registry of more than 35,000 patients. Arch. Cardiovasc. Dis. 2021, 114, 490–503. [Google Scholar] [CrossRef]
- Pezel, T.; Unterseeh, T.; Garot, P.; Hovasse, T.; Kinnel, M.; Champagne, S.; Toupin, S.; Sanguineti, F.; Garot, J. Prognostic value of vasodilator stress perfusion cardiovascular magnetic resonance after inconclusive stress testing. J. Cardiovasc. Magn. Reson. 2021, 23, 89. [Google Scholar] [CrossRef] [PubMed]
- Pezel, T.; Unterseeh, T.; Garot, P.; Hovasse, T.; Sanguineti, F.; Toupin, S.; Morisset, S.; Champagne, S.; Garot, J. Long-Term Prognostic Value of Stress Cardiovascular Magnetic Resonance–Related Coronary Revascularization to Predict Death: A Large Registry With >200,000 Patient-Years of Follow-Up. Circ. Cardiovasc. Imaging 2021, 14, e012789. [Google Scholar] [CrossRef] [PubMed]
- Pavon, A.G.; Porretta, A.P.; Arangalage, D.; Domenichini, G.; Rutz, T.; Hugelshofer, S.; Pruvot, E.; Monney, P.; Pascale, P.; Schwitter, J. Feasibility of adenosine stress cardiovascular magnetic resonance perfusion imaging in patients with MR-conditional transvenous permanent pacemakers and defibrillators. J. Cardiovasc. Magn. Reson. 2022, 24, 1–11. [Google Scholar] [CrossRef]
- Lipinski, M.J.; McVey, C.M.; Berger, J.; Kramer, C.M.; Salerno, M. Prognostic Value of Stress Cardiac Magnetic Resonance Imaging in Patients With Known or Suspected Coronary Artery Disease: A Systematic Review and Meta-Analysis. J. Am. Coll. Cardiol. 2013, 62, 826–838. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Centonze, M.; Steidler, S.; Casagranda, G.; Alfonsi, U.; Spagnolli, F.; Rozzanigo, U.; Palumbo, D.; Faletti, R.; De Cobelli, F. Cardiac-CT and cardiac-MR cost-effectiveness: A literature review. Radiol. Med. 2020, 125, 1200–1207. [Google Scholar] [CrossRef] [PubMed]
- Buffa, V.; Di Renzi, P. CMR in the diagnosis of ischemic heart disease. Radiol. Med. 2020, 125, 1114–1123. [Google Scholar] [CrossRef]
- Desai, R.R.; Jha, S. Diagnostic Performance of Cardiac Stress Perfusion MRI in the Detection of Coronary Artery Disease Using Fractional Flow Reserve as the Reference Standard: A Meta-Analysis. Am. J. Roentgenol. 2013, 201, W245–W252. [Google Scholar] [CrossRef]
- Leiner, T.; Bogaert, J.; Friedrich, M.G.; Mohiaddin, R.; Muthurangu, V.; Myerson, S.; Powell, A.J.; Raman, S.V.; Pennell, D.J. SCMR Position Paper (2020) on clinical indications for cardiovascular magnetic resonance. J. Cardiovasc. Magn. Reson. 2020, 22, 1–37. [Google Scholar] [CrossRef]
- Klem, I.; Klein, M.; Khan, M.; Yang, E.Y.; Nabi, F.; Ivanov, A.; Bhatti, L.; Hayes, B.; Graviss, E.A.; Nguyen, D.T.; et al. Relationship of LVEF and Myocardial Scar to Long-Term Mortality Risk and Mode of Death in Patients With Nonischemic Cardiomyopathy. Circulation 2021, 143, 1343–1358. [Google Scholar] [CrossRef]
- Hachamovitch, R. Impact of ischemia and scar on therapeutic benefit of myocardial revascularization. Herz 2013, 38, 344–349. [Google Scholar] [CrossRef]
- Kwon, D.H.; Obuchowski, N.A.; Marwick, T.H.; Menon, V.; Griffin, B.; Flamm, S.D.; Hachamovitch, R. Jeopardized Myocardium Defined by Late Gadolinium Enhancement Magnetic Resonance Imaging Predicts Survival in Patients With Ischemic Cardiomyopathy: Impact of Revascularization. J. Am. Heart Assoc. 2018, 7, e009394. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Craft, J.; Li, Y.; Bhatti, S.; Cao, J.J. How to do left atrial late gadolinium enhancement: A review. Radiol. Med. 2021, 126, 1159–1169. [Google Scholar] [CrossRef] [PubMed]
- Palmisano, A.; Vignale, D.; Benedetti, G.; Del Maschio, A.; De Cobelli, F.; Esposito, A. Late iodine enhancement cardiac computed tomography for detection of myocardial scars: Impact of experience in the clinical practice. Radiol. Med. 2020, 125, 128–136. [Google Scholar] [CrossRef] [PubMed]
- Kip, K.E.; Hollabaugh, K.; Marroquin, O.C.; Williams, D.O. The Problem With Composite End Points in Cardiovascular Studies: The Story of Major Adverse Cardiac Events and Percutaneous Coronary Intervention. J. Am. Coll. Cardiol. 2008, 51, 701–707. [Google Scholar] [CrossRef] [Green Version]
- Boden, W.E.; O’Rourke, R.A.; Teo, K.K.; Hartigan, P.M.; Maron, D.J.; Kostuk, W.J.; Knudtson, M.; Dada, M.; Casperson, P.; Harris, C.L.; et al. Optimal Medical Therapy with or without PCI for Stable Coronary Disease. N. Engl. J. Med. 2007, 356, 1503–1516. [Google Scholar] [CrossRef] [Green Version]
- BARI 2D Study Group; Frye, R.L.; August, P.; Brooks, M.M.; Hardison, R.M.; Kelsey, S.F.; MacGregor, J.M.; Orchard, T.J.; Chaitman, B.R.; Genuth, S.M.; et al. A Randomized Trial of Therapies for Type 2 Diabetes and Coronary Artery Disease. N. Engl. J. Med. 2009, 360, 2503–2515. [Google Scholar] [CrossRef]
- Xie, J.X.; Winchester, D.E.; Phillips, L.M.; Hachamovitch, R.; Berman, D.S.; Blankstein, R.; Di Carli, M.F.; Miller, T.D.; Al-Mallah, M.H.; Shaw, L.J. The elusive role of myocardial perfusion imaging in stable ischemic heart disease: Is ISCHEMIA the answer? J. Nucl. Cardiol. 2017, 24, 1610–1618. [Google Scholar] [CrossRef]
- Mani, P.; Hachamovitch, R. Can Stress Cardiac Magnetic Resonance Identify Potential Survival Benefit With Revascularization in Stable Ischemic Heart Disease? JACC Cardiovasc. Imaging 2020, 13, 1687–1689. [Google Scholar] [CrossRef]
- Schwitter, J. The SPINS Trial: Building Evidence and a Consequence? J. Am. Coll. Cardiol. 2019, 74, 1756–1759. [Google Scholar] [CrossRef]
- Hendel, R.C.; Friedrich, M.G.; Schulz-Menger, J.; Zemmrich, C.; Bengel, F.; Berman, D.S.; Camici, P.G.; Flamm, S.D.; Le Guludec, D.; Kim, R.; et al. CMR First-Pass Perfusion for Suspected Inducible Myocardial Ischemia. JACC Cardiovasc. Imaging 2016, 9, 1338–1348. [Google Scholar] [CrossRef]
- Kwong, R.Y.; Ge, Y.; Steel, K.; Bingham, S.; Abdullah, S.; Fujikura, K.; Wang, W.; Pandya, A.; Chen, Y.-Y.; Mikolich, J.R.; et al. Cardiac Magnetic Resonance Stress Perfusion Imaging for Evaluation of Patients With Chest Pain. J. Am. Coll. Cardiol. 2019, 74, 1741–1755. [Google Scholar] [CrossRef] [PubMed]
- Gulati, M.; Levy, P.D.; Mukherjee, D.; Amsterdam, E.; Bhatt, D.L.; Birtcher, K.K.; Blankstein, R.; Boyd, J.; Bullock-Palmer, R.P.; Conejo, T.; et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2021, 144, 368–454. [Google Scholar] [CrossRef] [PubMed]
- Nagel, E.; Greenwood, J.P.; McCann, G.P.; Bettencourt, N.; Shah, A.M.; Hussain, S.T.; Perera, D.; Plein, S.; Bucciarelli-Ducci, C.; Paul, M.; et al. Magnetic Resonance Perfusion or Fractional Flow Reserve in Coronary Disease. N. Engl. J. Med. 2019, 380, 2418–2428. [Google Scholar] [CrossRef]
- Farzaneh-Far, A.; Borges-Neto, S. Ischemic Burden, Treatment Allocation, and Outcomes in Stable Coronary Artery Disease. Circ. Cardiovasc. Imaging 2011, 4, 746–753. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hachamovitch, R. Does Ischemia Burden in Stable Coronary Artery Disease Effectively Identify Revascularization Candidates? Circ. Cardiovasc. Imaging 2015, 8, 8. [Google Scholar] [CrossRef] [Green Version]
- Marcos-Garces, V.; Gavara, J.; Monmeneu, J.V.; Lopez-Lereu, M.P.; Bosch, M.J.; Merlos, P.; Perez, N.; Rios-Navarro, C.; De Dios, E.; Bonanad, C.; et al. Vasodilator Stress CMR and All-Cause Mortality in Stable Ischemic Heart Disease. JACC Cardiovasc. Imaging 2020, 13, 1674–1686. [Google Scholar] [CrossRef] [PubMed]
- Ge, Y.; Steel, K.; Antiochos, P.; Bingham, S.; Abdullah, S.; Mikolich, J.R.; Arai, A.E.; Bandettini, W.P.; Shanbhag, S.M.; Patel, A.R.; et al. Stress CMR in patients with obesity: Insights from the Stress CMR Perfusion Imaging in the United States (SPINS) registry. Eur. Heart J. Cardiovasc. Imaging 2021, 22, 518–527. [Google Scholar] [CrossRef]
- Galea, N.; Polizzi, G.; Gatti, M.; Cundari, G.; Figuera, M.; Faletti, R. Cardiovascular magnetic resonance (CMR) in restrictive cardiomyopathies. Radiol. Med. 2020, 125, 1072–1086. [Google Scholar] [CrossRef]
- Liguori, C.; Farina, D.; Vaccher, F.; Ferrandino, G.; Bellini, D.; Carbone, I. Myocarditis: Imaging up to date. Radiol. Med. 2020, 125, 1124–1134. [Google Scholar] [CrossRef]
- Palumbo, P.; Cannizzaro, E.; Di Cesare, A.; Bruno, F.; Schicchi, N.; Giovagnoni, A.; Splendiani, A.; Barile, A.; Masciocchi, C.; Di Cesare, E. Cardiac magnetic resonance in arrhythmogenic cardiomyopathies. Radiol. Med. 2020, 125, 1087–1101. [Google Scholar] [CrossRef]
- Palumbo, P.; Masedu, F.; De Cataldo, C.; Cannizzaro, E.; Bruno, F.; Pradella, S.; Arrigoni, F.; Valenti, M.; Splendiani, A.; Barile, A.; et al. Real-world clinical validity of cardiac magnetic resonance tissue tracking in primitive hypertrophic cardiomyopathy. Radiol. Med. 2021, 126, 1532–1543. [Google Scholar] [CrossRef] [PubMed]
- Pierpaolo, P.; Rolf, S.; Manuel, B.-P.; Davide, C.; Dresselaers, T.; Claus, P.; Bogaert, J. Left ventricular global myocardial strain assessment: Are CMR feature-tracking algorithms useful in the clinical setting? Radiol. Med. 2020, 125, 444–450. [Google Scholar] [CrossRef] [PubMed]
- Pradella, S.; Grazzini, G.; De Amicis, C.; Letteriello, M.; Acquafresca, M.; Miele, V. Cardiac magnetic resonance in hypertrophic and dilated cardiomyopathies. Radiol. Med. 2020, 125, 1056–1071. [Google Scholar] [CrossRef] [PubMed]
- Russo, V.; Lovato, L.; Ligabue, G. Cardiac MRI: Technical basis. Radiol. Med. 2020, 125, 1040–1055. [Google Scholar] [CrossRef]
- Hadamitzky, M.; Freissmuth, B.; Meyer, T.; Hein, F.; Kastrati, A.; Martinoff, S.; Schömig, A.; Hausleiter, J. Prognostic Value of Coronary Computed Tomographic Angiography for Prediction of Cardiac Events in Patients With Suspected Coronary Artery Disease. JACC Cardiovasc. Imaging 2009, 2, 404–411. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hadamitzky, M.; Distler, R.; Meyer, T.; Hein, F.; Kastrati, A.; Martinoff, S.; Schömig, A.; Hausleiter, J. Prognostic Value of Coronary Computed Tomographic Angiography in Comparison With Calcium Scoring and Clinical Risk Scores. Circ. Cardiovasc. Imaging 2011, 4, 16–23. [Google Scholar] [CrossRef] [Green Version]
- Andreini, D.; Pontone, G.; Mushtaq, S.; Bartorelli, A.L.; Bertella, E.; Antonioli, L.; Formenti, A.; Cortinovis, S.; Veglia, F.; Annoni, A.; et al. A Long-Term Prognostic Value of Coronary CT Angiography in Suspected Coronary Artery Disease. JACC Cardiovasc. Imaging 2012, 5, 690–701. [Google Scholar] [CrossRef] [Green Version]
- Motoyama, S.; Ito, H.; Sarai, M.; Kondo, T.; Kawai, H.; Nagahara, Y.; Harigaya, H.; Kan, S.; Anno, H.; Takahashi, H.; et al. Plaque Characterization by Coronary Computed Tomography Angiography and the Likelihood of Acute Coronary Events in Mid-Term Follow-Up. J. Am. Coll. Cardiol. 2015, 66, 337–346. [Google Scholar] [CrossRef] [Green Version]
- Nadjiri, J.; Hausleiter, J.; Jähnichen, C.; Will, A.; Hendrich, E.; Martinoff, S.; Hadamitzky, M. Incremental prognostic value of quantitative plaque assessment in coronary CT angiography during 5 years of follow up. J. Cardiovasc. Comput. Tomogr. 2016, 10, 97–104. [Google Scholar] [CrossRef]
- Marano, R.; Rovere, G.; Savino, G.; Flammia, F.C.; Carafa, M.R.P.; Steri, L.; Merlino, B.; Natale, L. CCTA in the diagnosis of coronary artery disease. Radiol. Med. 2020, 125, 1102–1113. [Google Scholar] [CrossRef]
- Valente, T.; Pignatiello, M.; Sica, G.; Bocchini, G.; Rea, G.; Cappabianca, S.; Scaglione, M. Hemopericardium in the acute clinical setting: Are we ready for a tailored management approach on the basis of MDCT findings? Radiol. Med. 2020, 126, 527–543. [Google Scholar] [CrossRef] [PubMed]
- Şeker, M. Prevalence and morphologic features of dual left anterior descending artery subtypes in coronary CT angiography. Radiol. Med. 2019, 125, 247–256. [Google Scholar] [CrossRef] [PubMed]
- Rovere, G.; Meduri, A.; Savino, G.; Flammia, F.C.; Piccolo, F.L.; Carafa, M.R.P.; Larici, A.R.; Natale, L.; Merlino, B.; Marano, R. Practical instructions for using drugs in CT and MR cardiac imaging. Radiol. Med. 2021, 126, 356–364. [Google Scholar] [CrossRef] [PubMed]
- Palumbo, P.; Cannizzaro, E.; Bruno, F.; Schicchi, N.; Fogante, M.; Agostini, A.; De Donato, M.C.; De Cataldo, C.; Giovagnoni, A.; Barile, A.; et al. Coronary artery disease (CAD) extension-derived risk stratification for asymptomatic diabetic patients: Usefulness of low-dose coronary computed tomography angiography (CCTA) in detecting high-risk profile patients. Radiol. Med. 2020, 125, 1249–1259. [Google Scholar] [CrossRef]
- Esposito, A.; Francone, M.; Andreini, D.; Buffa, V.; Cademartiri, F.; Carbone, I.; Clemente, A.; Guaricci, A.I.; Guglielmo, M.; Indolfi, C.; et al. SIRM—SIC appropriateness criteria for the use of Cardiac Computed Tomography. Part 1: Congenital heart diseases, primary prevention, risk assessment before surgery, suspected CAD in symptomatic patients, plaque and epicardial adipose tissue characterization, and functional assessment of stenosis. Radiol. Med. 2021, 126, 1236–1248. [Google Scholar] [CrossRef]
- De Rubeis, G.; Marchitelli, L.; Spano, G.; Catapano, F.; Cilia, F.; Galea, N.; Carbone, I.; Catalano, C.; Francone, M. Radiological outpatient’ visits to avoid inappropriate cardiac CT examinations: An 8-year experience report. Radiol. Med. 2021, 126, 214–220. [Google Scholar] [CrossRef]
- Pontone, G.; Di Cesare, E.; Castelletti, S.; De Cobelli, F.; De Lazzari, M.; Esposito, A.; Focardi, M.; Di Renzi, P.; Indolfi, C.; Lanzillo, C.; et al. Appropriate use criteria for cardiovascular magnetic resonance imaging (CMR): SIC—SIRM position paper part 1 (ischemic and congenital heart diseases, cardio-oncology, cardiac masses and heart transplant). Radiol. Med. 2021, 126, 365–379. [Google Scholar] [CrossRef]
- Motoyama, S.; Sarai, M.; Narula, J.; Ozaki, Y. Coronary CT angiography and high-risk plaque morphology. Cardiovasc. Interv. Ther. 2013, 28, 1–8. [Google Scholar] [CrossRef]
- Pontone, G.; Andreini, D.; Bartorelli, A.L.; Bertella, E.; Cortinovis, S.; Mushtaq, S.; Foti, C.; Annoni, A.; Formenti, A.; Baggiano, A.; et al. A Long-Term Prognostic Value of CT Angiography and Exercise ECG in Patients with Suspected CAD. JACC Cardiovasc. Imaging 2013, 6, 641–650. [Google Scholar] [CrossRef] [Green Version]
- Seitun, S.; Clemente, A.; Maffei, E.; Toia, P.; La Grutta, L.; Cademartiri, F. Prognostic value of cardiac CT. Radiol. Med. 2020, 125, 1135–1147. [Google Scholar] [CrossRef]
- Nakanishi, R.; Osawa, K.; Kurata, A.; Miyoshi, T. Role of coronary computed tomography angiography (CTA) post the ISCHEMIA trial: Precision prevention based on coronary CTA-derived coronary atherosclerosis. J. Cardiol. 2021. [Google Scholar] [CrossRef] [PubMed]
- Van Rosendael, A.R.; Bax, A.M.; van den Hoogen, I.J.; Smit, J.M.; Al’Aref, S.J.; Achenbach, S.; Al-Mallah, M.H.; Andreini, D.; Berman, D.S.; Budoff, M.J.; et al. Associations between dyspnoea, coronary atherosclerosis, and cardiovascular outcomes: Results from the long-term follow-up CONFIRM registry. Eur. Heart J. Cardiovasc. Imaging 2020, 23, 266–274. [Google Scholar] [CrossRef] [PubMed]
- Schicchi, N.; Mari, A.; Fogante, M.; Pirani, P.E.; Agliata, G.; Tosi, N.; Palumbo, P.; Cannizzaro, E.; Bruno, F.; Splendiani, A.; et al. In vivo radiation dosimetry and image quality of turbo-flash and retrospective dual-source CT coronary angiography. Radiol. Med. 2020, 125, 117–127. [Google Scholar] [CrossRef] [PubMed]
- Van Assen, M.; Muscogiuri, G.; Caruso, D.; Lee, S.J.; Laghi, A.; De Cecco, C.N. Artificial intelligence in cardiac radiology. Radiol. Med. 2020, 125, 1186–1199. [Google Scholar] [CrossRef]
- Scapicchio, C.; Gabelloni, M.; Barucci, A.; Cioni, D.; Saba, L.; Neri, E. A deep look into radiomics. Radiol. Med. 2021, 126, 1296–1311. [Google Scholar] [CrossRef]
- Nardone, V.; Reginelli, A.; Grassi, R.; Boldrini, L.; Vacca, G.; D’Ippolito, E.; Annunziata, S.; Farchione, A.; Belfiore, M.P.; Desideri, I.; et al. Delta radiomics: A systematic review. Radiol. Med. 2021, 126, 1571–1583. [Google Scholar] [CrossRef]
- Coppola, F.; Faggioni, L.; Regge, D.; Giovagnoni, A.; Golfieri, R.; Bibbolino, C.; Miele, V.; Neri, E.; Grassi, R. Artificial intelligence: Radiologists’ expectations and opinions gleaned from a nationwide online survey. Radiol. Med. 2021, 126, 63–71. [Google Scholar] [CrossRef]
- Cicero, G.; Ascenti, G.; Albrecht, M.H.; Blandino, A.; Cavallaro, M.; D’Angelo, T.; Carerj, M.L.; Vogl, T.J.; Mazziotti, S. Extra-abdominal dual-energy CT applications: A comprehensive overview. Radiol. Med. 2020, 125, 384–397. [Google Scholar] [CrossRef]
- Tonino, P.A.L.; De Bruyne, B.; Pijls, N.H.J.; Siebert, U.; Ikeno, F.; van’t Veer, M.; Klauss, V.; Manoharan, G.; Engstrøm, T.; Oldroyd, K.G.; et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N. Engl. J. Med. 2009, 360, 213–224. [Google Scholar] [CrossRef] [Green Version]
- Pijls, N.H.; Fearon, W.F.; Tonino, P.A.; Siebert, U.; Ikeno, F.; Bornschein, B.; Veer, M.V.; Klauss, V.; Manoharan, G.; Engstrøm, T.; et al. Fractional Flow Reserve Versus Angiography for Guiding Percutaneous Coronary Intervention in Patients With Multivessel Coronary Artery Disease: 2-Year Follow-Up of the FAME (Fractional Flow Reserve Versus Angiography for Multivessel Evaluation) Study. J. Am. Coll. Cardiol. 2010, 56, 177–184. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Bruyne, B.; Pijls, N.H.; Kalesan, B.; Barbato, E.; Tonino, P.A.; Piroth, Z.; Jagic, N.; Mobius-Winckler, S.; Rioufol, G.; Witt, N.; et al. Fractional Flow Reserve–Guided PCI versus Medical Therapy in Stable Coronary Disease. N. Engl. J. Med. 2012, 367, 991–1001. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Patel, M.R.; Jeremias, A.; Maehara, A.; Matsumura, M.; Zhang, Z.; Schneider, J.; Tang, K.; Talwar, S.; Marques, K.; Shammas, N.W.; et al. 1-Year Outcomes of Blinded Physiological Assessment of Residual Ischemia After Successful PCI. JACC Cardiovasc. Interv. 2022, 15, 52–61. [Google Scholar] [CrossRef] [PubMed]
- Zhang, D.; Lv, S.; Song, X.; Yuan, F.; Xu, F.; Zhang, M.; Yan, S.; Cao, X. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention: A meta-analysis. Heart 2015, 101, 455–462. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Xaplanteris, P.; Fournier, S.; Pijls, N.H.; Fearon, W.F.; Barbato, E.; Tonino, P.A.; Engstrøm, T.; Kääb, S.; Dambrink, J.-H.; Rioufol, G.; et al. Five-Year Outcomes with PCI Guided by Fractional Flow Reserve. N. Engl. J. Med. 2018, 379, 250–259. [Google Scholar] [CrossRef]
- Elgendy, I.Y.; Mahtta, D.; Pepine, C.J. Medical Therapy for Heart Failure Caused by Ischemic Heart Disease. Circ. Res. 2019, 124, 1520–1535. [Google Scholar] [CrossRef]
- Di Cesare, E.; Carerj, S.; Palmisano, A.; Carerj, M.L.; Catapano, F.; Vignale, D.; Di Cesare, A.; Milanese, G.; Sverzellati, N.; Francone, M.; et al. Multimodality imaging in chronic heart failure. Radiol. Med. 2021, 126, 231–242. [Google Scholar] [CrossRef]
- Masi, S.; Rizzoni, D.; Taddei, S.; Widmer, R.J.; Montezano, A.C.; Lüscher, T.F.; Schiffrin, E.L.; Touyz, R.M.; Paneni, F.; Lerman, A.; et al. Assessment and pathophysiology of microvascular disease: Recent progress and clinical implications. Eur. Heart J. 2021, 42, 2590–2604. [Google Scholar] [CrossRef]
- Crea, F.; Camici, P.G.; Merz, C.N.B. Coronary microvascular dysfunction: An update. Eur. Heart J. 2014, 35, 1101–1111. [Google Scholar] [CrossRef] [Green Version]
- Taqueti, V.R.; Solomon, S.D.; Shah, A.M.; Desai, A.S.; Groarke, J.D.; Osborne, M.; Hainer, J.; Bibbo, C.F.; Dorbala, S.; Blankstein, R.; et al. Coronary microvascular dysfunction and future risk of heart failure with preserved ejection fraction. Eur. Heart J. 2017, 39, 840–849. [Google Scholar] [CrossRef]
- Sechtem, U.; Brown, D.L.; Godo, S.; Lanza, G.A.; Shimokawa, H.; Sidik, N. Coronary microvascular dysfunction in stable ischaemic heart disease (non-obstructive coronary artery disease and obstructive coronary artery disease). Cardiovasc. Res. 2020, 116, 771–786. [Google Scholar] [CrossRef] [Green Version]
- Padro, T.; Manfrini, O.; Bugiardini, R.; Canty, J.; Cenko, E.; De Luca, G.; Duncker, D.J.; Eringa, E.C.; Koller, A.; Tousoulis, D.; et al. ESC Working Group on Coronary Pathophysiology and Microcirculation position paper on ‘coronary microvascular dysfunction in cardiovascular disease’. Cardiovasc. Res. 2020, 116, 741–755. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Corcoran, D.; Young, R.; Adlam, D.; McConnachie, A.; Mangion, K.; Ripley, D.; Cairns, D.; Brown, J.; Bucciarelli-Ducci, C.; Baumbach, A.; et al. Coronary microvascular dysfunction in patients with stable coronary artery disease: The CE-MARC 2 coronary physiology sub-study. Int. J. Cardiol. 2018, 266, 7–14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ford, T.; Stanley, B.; Good, R.; Rocchiccioli, P.; McEntegart, M.; Watkins, S.; Eteiba, H.; Shaukat, A.; Lindsay, M.; Robertson, K.; et al. Stratified Medical Therapy Using Invasive Coronary Function Testing in Angina. J. Am. Coll. Cardiol. 2018, 72, 2841–2855. [Google Scholar] [CrossRef] [PubMed]
- Ford, T.; Berry, C. How to Diagnose and Manage Angina Without Obstructive Coronary Artery Disease: Lessons from the British Heart Foundation CorMicA Trial. Interv. Cardiol. Rev. Res. Resour. 2019, 14, 76–82. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ford, T.; Ong, P.; Sechtem, U.; Beltrame, J.; Camici, P.G.; Crea, F.; Kaski, J.-C.; Merz, C.N.B.; Pepine, C.J.; Shimokawa, H.; et al. Assessment of Vascular Dysfunction in Patients Without Obstructive Coronary Artery Disease. JACC Cardiovasc. Interv. 2020, 13, 1847–1864. [Google Scholar] [CrossRef]
- Ford, T.J.; Stanley, B.; Sidik, N.; Good, R.; Rocchiccioli, P.; McEntegart, M.; Watkins, S.; Eteiba, H.; Shaukat, A.; Lindsay, M.; et al. 1-Year Outcomes of Angina Management Guided by Invasive Coronary Function Testing (CorMicA). JACC Cardiovasc. Interv. 2020, 13, 33–45. [Google Scholar] [CrossRef]
- Ford, T.J.; Corcoran, D.; Berry, C. Stable coronary syndromes: Pathophysiology, diagnostic advances and therapeutic need. Heart 2018, 104, 284–292. [Google Scholar] [CrossRef]
- Ford, T.J.; Corcoran, D.; Oldroyd, K.G.; McEntegart, M.; Rocchiccioli, P.; Watkins, S.; Brooksbank, K.; Padmanabhan, S.; Sattar, N.; Briggs, A.; et al. Rationale and design of the British Heart Foundation (BHF) Coronary Microvascular Angina (CorMicA) stratified medicine clinical trial. Am. Heart J. 2018, 201, 86–94. [Google Scholar] [CrossRef]
- Geyer, H.; Caracciolo, G.; Abe, H.; Wilansky, S.; Carerj, S.; Gentile, F.; Nesser, H.-J.; Khandheria, B.; Narula, J.; Sengupta, P.P. Assessment of Myocardial Mechanics Using Speckle Tracking Echocardiography: Fundamentals and Clinical Applications. J. Am. Soc. Echocardiogr. 2010, 23, 351–369. [Google Scholar] [CrossRef]
- Voigt, J.-U.; Cvijic, M. 2- and 3-Dimensional Myocardial Strain in Cardiac Health and Disease. JACC Cardiovasc. Imaging 2019, 12, 1849–1863. [Google Scholar] [CrossRef]
- Holmes, A.A.; Romero, J.; Levsky, J.M.; Haramati, L.B.; Phuong, N.; Rezai-Gharai, L.; Cohen, S.; Restrepo, L.; Ruiz-Guerrero, L.; Fisher, J.D.; et al. Circumferential strain acquired by CMR early after acute myocardial infarction adds incremental predictive value to late gadolinium enhancement imaging to predict late myocardial remodeling and subsequent risk of sudden cardiac death. J. Interv. Card. Electrophysiol. 2017, 50, 211–218. [Google Scholar] [CrossRef] [PubMed]
PO (No) | PO (Yes) | p-Value | ||
---|---|---|---|---|
All n (%) | 35 (100) | 23 (66) | 12 (34) | |
Sex (male) n (%) | 29 (83) | 21 (60) | 8 (23) | 0.089 |
Sex (female) n (%) | 6 (17) | 2 (6) | 4 (11) | |
Age (years) | 69 ± 9 | 67 ± 9 | 72 ± 7 | 0.122 |
EF (%) | 61 ± 8 | 60 ± 7 | 63 ± 10 | 0.415 |
Diabetes n (%) | 6 (17) | 3 (9) | 3 (9) | 0.329 |
Hypertension n (%) | 13 (37) | 9 (26) | 4 (11) | 0.517 |
Smoking habits n (%) | 8 (23) | 6 (17) | 2 (6) | 0.429 |
Familiarity for CHD n (%) | 10 (29) | 8 (23) | 2 (6) | 0.236 |
Dyslipidemia n (%) | 19 (54) | 12 (34) | 7 (20) | 0.505 |
Symptoms n (%) | 16 (46) | 6 (17) | 10 (29) | 0.002 ** |
Multivessel CAD n (%) | 21 (60) | 11 (31) | 10 (29) | 0.045 * |
Ischemia n (%) | 12 (34) | 3 (9) | 9 (26) | 0.0001 ** |
Ischemic burden (%) | 9 ±3 | 1 ± 2 | 7 ± 5 | 0.0001 ** |
CMR-Tissue Tracking CCS group | ||||
GLS (%) | −16 ± 2 | −17 ± 1 | −14 ± 2 | 0.0001 ** |
GCS (%) | −17 ± 3 | −17 ± 2 | −17 ± 4 | 0.489 |
GRS (%) | 28 ± 7 | 27 ± 6 | 29 ± 10 | 0.147 |
CMR-Tissue Tracking Healthy group | ||||
GLS (%) | −18 ± 1 | |||
GCS (%) | −20 ± 2 | |||
GRS (%) | 36 ± 6 |
Symptoms | Multivessel Disease | Ischemia | GLS Impairment | Ischemia and GLS Impairment | |
---|---|---|---|---|---|
No of patients | 16 (46) | 21 (60) | 12 (34) | 13 (37) | 8 (23) |
MACE n (%) | 10 (63) | 10 (48) | 9 (75) | 9 (69) | 8 (100) |
HF n (%) | 7 (44) | 6 (29) | 6 (50) | 5 (38) | 5 (63) |
no MACE or HF n (%) | 6 (37) | 11 (52) | 3 (25) | 4 (31) | 0 |
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Palumbo, P.; Cannizzaro, E.; Di Cesare, A.; Bruno, F.; Arrigoni, F.; Splendiani, A.; Barile, A.; Masciocchi, C.; Di Cesare, E. Stress Perfusion Cardiac Magnetic Resonance in Long-Standing Non-Infarcted Chronic Coronary Syndrome with Preserved Systolic Function. Diagnostics 2022, 12, 786. https://doi.org/10.3390/diagnostics12040786
Palumbo P, Cannizzaro E, Di Cesare A, Bruno F, Arrigoni F, Splendiani A, Barile A, Masciocchi C, Di Cesare E. Stress Perfusion Cardiac Magnetic Resonance in Long-Standing Non-Infarcted Chronic Coronary Syndrome with Preserved Systolic Function. Diagnostics. 2022; 12(4):786. https://doi.org/10.3390/diagnostics12040786
Chicago/Turabian StylePalumbo, Pierpaolo, Ester Cannizzaro, Annamaria Di Cesare, Federico Bruno, Francesco Arrigoni, Alessandra Splendiani, Antonio Barile, Carlo Masciocchi, and Ernesto Di Cesare. 2022. "Stress Perfusion Cardiac Magnetic Resonance in Long-Standing Non-Infarcted Chronic Coronary Syndrome with Preserved Systolic Function" Diagnostics 12, no. 4: 786. https://doi.org/10.3390/diagnostics12040786
APA StylePalumbo, P., Cannizzaro, E., Di Cesare, A., Bruno, F., Arrigoni, F., Splendiani, A., Barile, A., Masciocchi, C., & Di Cesare, E. (2022). Stress Perfusion Cardiac Magnetic Resonance in Long-Standing Non-Infarcted Chronic Coronary Syndrome with Preserved Systolic Function. Diagnostics, 12(4), 786. https://doi.org/10.3390/diagnostics12040786