Non-Invasive Diagnosis of Chronic Coronary Syndrome: History
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Coronary artery disease is still a major cause of death and morbidity worldwide. In the setting of chronic coronary disease, demonstration of inducible ischemia is mandatory to address treatment. Consequently, scientific and technological efforts were made in response to the request for non-invasive diagnostic tools with better sensitivity and specificity. Clinicians have at their disposal a wide range of stress-imaging techniques. Among others, stress cardiac magnetic resonance (S-CMR) and computed tomography perfusion (CTP) techniques both demonstrated their diagnostic efficacy and prognostic value in clinical trials when compared to other non-invasive ischemia-assessing techniques and invasive fractional flow reserve measurement techniques. 

  • coronary artery disease
  • cardiac coronary syndrome
  • stress imaging
  • cardiac computed tomography perfusion
  • stress magnetic cardiac resonance

1. Introduction

Coronary artery disease (CAD) represents a major cause of mortality and morbidity [1]; nowadays, it accounts for a considerable proportion of healthcare costs, which are expected to double by 2030 [2]. In 2019, the European Society of Cardiology (ESC) published guidelines on the diagnosis and management of chronic coronary syndrome (CCS), recommending diagnostic strategies that are predominantly based on cardiac imaging [3]. Indeed, non-invasive imaging methods provide detection of the disease and can guide therapy and predict outcomes [4].
However, while coronary computed tomographic angiography (CCTA) has a known high-negative predictive value in ruling out CAD, at the same time, it has limited accuracy in the diagnosis of hemodynamically significant coronary artery stenosis, especially those graded between 30% and 70%, as anatomical data alone are not predictive of inducible ischemia [5]. Therefore, an additional functional test is often required because both anatomic and functional information is needed to guide patient care and revascularization. Cardiac stress imaging techniques include, among others, nuclear perfusion, stress echocardiography, stress myocardial computed tomography perfusion (CTP), and stress cardiovascular magnetic resonance (S-CMR). These non-invasive functional imaging modalities can help in assessing significant myocardial ischemia, myocardium viability, and exercise capacity. The initial diagnostic workup should consider the performance and availability of each of the different imaging tests, as well as the patient profile.
S-CMR is a non-ionizing technique that can evaluate perfusion defects or ischemic wall motion abnormalities caused by pharmacological stress or even exercise. As will be explored later in more detail, several studies showed the high negative predictive value and high diagnostic accuracy of S-CMR to detect CAD compared to the gold standard techniques: angiographically determined luminal coronary stenosis and fractional flow reserve (FFR) [4]. The advantages of S-CMR are the lack of ionizing radiation and the relatively low cost. Nevertheless, S-CMR has disadvantages, such as its low availability and the high level of expertise required.

2. Stress Cardiac Magnetic Resonance

2.1. Why S-CMR

S-CMR is a functional non-invasive imaging test that has strongly consolidated its position in recent years, being able not only to highlight myocardial viability and cardiac function, but also to assess myocardial ischemia without the need for ionizing radiation [6].
Data from the multinational multicenter European Cardiovascular Magnetic Resonance registry demonstrated the safety of the procedure after analyzing the complications that occurred in 10,228 patients who underwent S-CMR. The results show that severe complications are extremely rare (0.07%), with only one patient suffering from anaphylactic shock due to adenosine. Mild complications were observed in 7.3% of the cases and manifestations included dyspnea, chest discomfort, ectopic beats attributed to the pharmacologic agent, and mild allergic reactions to Gadolinium-based contrast agents [7].
The diagnostic efficiency of S-CMR is believed to be a result of better contrast, as well as spatial and temporal resolution. This efficiency permits us to assess perfusion within the different myocardium layers and, consequently, to identify even subendocardial defects, in contrast to SPECT, where the poorer spatial resolution implies that ischemic segments are best identified in the context of a normally perfused myocardial segment. Moreover, CMR is not limited by attenuation artifacts or contamination of the myocardium by signal sources not related to myocardial perfusion that can mimic or disguise perfusion defects.
Moreover, S-CMR was shown to be an efficient diagnostic tool for significant in-stent restenosis: in two different studies, S-CMR showed a high diagnostic accuracy above 90% in detecting in-stent restenosis on a per-vessel level [8][9].
All of these data contributed to establishing S-CMR as a valuable diagnostic and prognostic tool to the point that it is currently recommended by international guidelines in the assessment of patients with known or suspected CAD [3][10].

2.2. How S-CMR

The S-CMR protocol, which should be performed according to the latest update of the S-CMR guidelines [11], consists of stress and rest phases, with final LGE sequences. In order to assess myocardial ischemia, S-CMR can be performed either using vasodilator drugs (dipyridamole, adenosine or regadenoson) or inotropic agents (dobutamine).
With the administration of a short half-life vasodilator stress agent, such as adenosine, perfusion defects can be outlined, while with long half-life vasodilator stress agent administration, such as dipyridamole and regadenoson, both perfusion defects and regional wall motion abnormalities (WMA) can be revealed. The depicted perfusion defect is a result of a “steal phenomenon” and loss of autoregulation mechanism induced by adminisering these drugs. Vasodilator agents should not be used in case of second-degree (type 2) or complete atrioventricular block, sinus bradycardia (<40 beats/min), low systolic blood pressure (<90 mmHg) or severe systemic arterial hypertension (>220/120 mmHg), active bronchoconstrictive or bronchospastic disease with regular use of inhalers, and known hypersensitivity to adenosine, dipyridamole, or regadenoson.
Moreover, S-CMR is able to show WMA mediated by an increase in heart rate after inotropic agent administration, such as dobutamine [12]. Dobutamine stress CMR should not be performed in patients with serious hypertension (>220/120 mmHg); unstable angina pectoris; uncontrolled heart failure; severe aortic stenosis; obstructive hypertrophic cardiomyopathy and complex cardiac arrhythmias, including uncontrolled atrial fibrillation; and in patients with myocarditis, endocarditis, or pericarditis [13]. Preliminary experiences also show promising results in ischemia assessment during physical exercise through use of a magnetic resonance compatible ergometer bicycle [14][15]. In clinical practice, vasodilator stress perfusion testing is the most common choice [11].
In the setting of ischemia in non-obstructive coronary disease, the CMR-derived myocardial perfusion reserve index (MPRI) also serves as a solid semiquantitative value representing the vasodilating capacity of small vessels, being defined as the ratio of stress to rest upslope normalized to the upslope of the left ventricular (LV) blood pool [16]. Liu et al. also defined, for MPRI, a cutoff threshold of 1.4 for the diagnosis of microvascular angina, with an accuracy of 92% [17]. More recently, a study showed that MPRI measured with S-CMR is an independent predictor of major adverse cardiovascular events (MACE). Patients with MPRI < 1.47 had a three-fold increased risk of MACE compared with those with MPRI > 1.47 [18].

2.3. When S-CMR

The selection of the preferred diagnostic tool to investigate CAD is guided by several factors, such as the pre-test probability of CAD, the patient’s comorbidities (renal function, presence of cardiac devices and arrhythmias, etc.) and the availability, expertise, and preference of each center. However, it is expected that for each test, there is a range of pre-test probability of significant CAD within which its performance is maximized. In their meta-analysis, Knuuti et al. defined the ranges of pre-test probability of CAD where the different techniques were able to rule in or rule out significant CAD by driving the post-test probabilities above 85% and below 15%, respectively. This method was performed for both anatomically and functionally significant CAD, taking as a reference standard ICA and invasive FFR, respectively [4]. From these data, it appears that S-CMR performs most effectively in the rule-in of patients with intermediate-to-high clinical likelihood of CAD, both for anatomically and functionally significant CAD. Moreover, it is known that revascularization decision-making requires the evaluation of ischemia in most patients, with functional imaging, including S-CMR, demonstrating an ability to reduce referrals for ICA compared with a strategy based on anatomical imaging [19]. Nonetheless, the Dan-NICAD trial showed low sensitivity (28–41%) of S-CMR in detecting hemodynamically significant CAD defined via invasive FFR in patients with suspected obstructive CAD based on CCTA [20]. These results are in contrast with the previous literature and might occur due to patient selection, as 61% of patients had angiographically intermediate lesions and the mean FFR of the study was close to the cut-off for hemodynamic significance (0.83).
Considering the data in the possession, S-CMR may be preferred in patients with a higher clinical likelihood of CAD or who were previously diagnosed with CAD. Current ESC guidelines on CCS published in 2019 received these data, making an important step forward in comparison to the previous version [3][21]. Similarly, 2018 ESC guidelines on myocardial revascularization and 2021 ESC guidelines on heart failure (HF) recommend the use of stress CMR for the evaluation of ischemic segments and myocardial viability in patients with heart failure and CAD to decide whether or not they should undergo myocardial revascularization (class IIb, level of evidence B) [22][23]. Eventually, the 2020 ESC guidelines on acute coronary syndrome without ST-elevation recommend using stress-CMR for patients with normal ECG and no elevation of high-sensitive troponin, but are still suspected as having acute coronary syndrome, before performing invasive tests (class I, level of evidence A) [24].

3. Myocardial Computed Tomography Perfusion

3.1. Why CTP

While the sensitivity of CCTA is excellent, the specificity of CCTA is unsatisfactory, with serious risk of an overestimation of the severity of CAD, especially in the intermediate range (40–80%) stenosis. Indeed, in their meta-analysis, Danad et al. found the sensitivity of CCTA to be 90%, while the specificity was only 39% in evaluating hemodynamically significant lesions, as defined by FFR measurement [25]. In contrast, other tests, such as stress echocardiography, SPECT, S-CMR, and PET, evaluate the presence of ischemia but fail in providing detailed information about anatomy, including atheroma burden and its composition. The EVINCI data demonstrated that a combination of anatomical and functional non-invasive tests avoided unnecessary ICA. Referring patients to an invasive procedure with the combination of positive CCTA and stress test also translated into a reduction in major adverse cardiovascular events (MACE) and cost-effectiveness [26][27].
Regarding the prognostic value of CTP, the combination of CCTA and CTP imaging resulted in a similar prediction of MACE at 2 years (defined as revascularization, myocardial infarction, hospitalization for chest pain or congestive heart failure, arrhythmia, or cardiac death), late MACE, and event-free survival to that obtained with the use of both SPECT and ICA [28]. Van Assen et al. also demonstrated that stress CTP has a higher prognostic value than coronary CTA or Fractional Flow Reserve Derived from CT (FFRCT) for the prediction of major adverse cardiac events [29].

3.2. How CTP

In the last few decades, CCT became the protagonist of dramatic evolutions in terms of technology, radiation dose and time of acquisition reduction, and overall performances. Currently, a 64-slice CT scanner is considered the minimum technology required for CTP imaging.
Similarly to other functional stress tests and according to the indications given by the Society of Cardiovascular Computer Tomography, CTP comprehends a series of rest and stress imaging acquisitions [30]. However, in this case, iodinate contrast agent is used and injected at a rate of at least 5 mL/s to achieve the enhancement in the first-pass arterial phase. Moreover, differently from S-CMR and SPECT, the rest scan in CTP is of key importance, as it represents the moment of evaluation of both coronary stenosis and myocardial perfusion, adding anatomical information to an otherwise functional evaluation.
Currently, two different techniques are available for CTP: static and dynamic CTP acquisitions.
Static CTP imaging acquires one single phase dataset during the first pass of the contrast agent in the myocardium, depicting the myocardial perfusion at one precise time point. This approach means that the timing of the scan acquisition is fundamental and requires careful assessment, with the objective being to acquire the images at the highest contrast-to-noise ratio difference between the normal and hypoperfused myocardium [31]. As per CCTA, CTP can be conducted via a retrospective ECG-gating or a prospective ECG-triggering method, without a definitive preference between the two options, even though the retrospective method allows for lower radiation dosing and smaller CT-detectors. The evaluation of the contrast enhancement is mainly performed qualitatively, with perfusion defects appearing hypodense compared to the surrounding normal myocardium, and usually being distributed at the subendocardium or transmural in nature. Similar to nuclear imaging, the comparison of stress and rest images allows for the distinction between inducible ischemia, if the hypo-attenuation is reversible at rest, and scar due to prior myocardial infarct, if the perfusion defect is fixed. Eventually, if the hypoperfusion at stress is still appreciated at rest, albeit reduced in extension, peri-infarct-ischemia can be diagnosed. Static CTP also allows a semi-quantitative evaluation, allowing for the measurement of the transmyocardial perfusion ratio, which is defined as the ratio of endocardial-to-epicardial attenuation.
Dynamic CTP consists of the acquisition of multiple imaging datasets at different time points during a 20–30-s-long inspiratory breath-hold. Dynamic CTP can be obtained via a prospective ECG-gated dynamic acquisition in the case of a CT scanner with a large coverage on the z-axis (256- or 320-detector-row) or, if detectors are narrower, an ECG-triggered axial shuttle mode technique with a second- or third-generation dual source CT scanner. The acquired images are used to create time-attenuation curves (TACs) for each voxel of the myocardium and the arterial input function (AIF), which are derived from the left ventricle or the thoracic aorta. Using a dedicated parametric deconvolution based on a two-compartment model of intra- and extra-vascular space to fit the TACs, dynamic CTP imaging enables absolute quantification of myocardial perfusion, such as myocardial blood flow (MBF, mL/100 mL/min), MBF ratio, and myocardial blood volume (mL/100 mL). Finally, through comparing MBF during stress and rest phases, an assessment of absolute coronary flow reserve may be obtained. The most appealing aspect of dynamic stress CTP is its quantitative approach, which makes reporting less operator-dependent and more reproducible compared to static stress CTP, especially in challenging settings, such as multivessel obstructive coronary disease or microcirculation dysfunction.
Compared to static CTP, the radiation exposure of a dynamic approach is higher, ranging between 8 and 9 mSv for the “shuttle-mode” technique and being 5 mSv for “whole-heart coverage” scanners. Notably, according to a recent pooled analysis on a per-patient basis, dual-energy and dynamic quantitative CTP tends to have a slightly higher sensitivity than static CTP imaging [32]. This finding may be related to higher detection of subtle perfusion defects.
Moreover, when compared to S-CMR, dynamic CTP shows similar diagnostic accuracy. For instance, de Knegt et al. [33] demonstrated that coronary computed tomography angiography (CCTA), visual stress cardiac magnetic resonance (S-CMR), and CCTA and relative computed tomography myocardial blood flow (CT-MBF) had better sensitivity compared to CCTA and visual computed tomography perfusion (CTP), with similar sensitivities for CCTA and visual s-CMR perfusion and CCTA and CT-MBF. Regarding specificity, there were no differences between these three techniques [33]. Similarly, in a meta-analysis by Takx et al., the diagnostic accuracy of dynamic CTP (AUC 0.93) was comparable with S-CMR (AUC 0.94) on a per-vessel level [34].

3.3. When CTP

An important limitation to myocardial CTP implementation is the heterogeneity within the literature of pharmacologic stress agents, imaging sequences, scanner types, acquisition protocols, post-processing, and interpretation of CTP results. Clinical adoption of myocardial CTP is further hindered by the absence of an expert consensus regarding when and how CTP should be performed. Since CCTA alone has a very high negative predictive value to exclude myocardial ischemia in the presence of no CAD or a non-obstructive stenosis (≤50% severity), selection of a myocardial CTP protocol should generally be reserved for a situation in which the presence of ischemia after performing CCTA is doubtful or known to be difficult to evaluate, such as coronary artery stenoses of unknown hemodynamic significance, severe coronary calcification, or coronary stents [35][36]. The Society of Cardiovascular Computed Tomography recommends adding CTP to standard CCTA if it is known that the presence and severity of ischemia would impact patient management [30]. This approach refers to cases with a high pre-test probability for obstructive CAD, including those patients with prior coronary intervention or significant calcification, as well as cases when there is a stenosis of indeterminate functional significance. Finally, CTP requires higher radiation and contrast doses and longer scan times. Hence, the use of CTP is limited in patients of young age or with kidney disease.

This entry is adapted from the peer-reviewed paper 10.3390/jcm12113793

References

  1. Malakar, A.K.; Choudhury, D.; Halder, B.; Paul, P.; Uddin, A.; Chakraborty, S. A review on coronary artery disease, its risk factors, and therapeutics. J. Cell. Physiol. 2019, 234, 16812–16823.
  2. 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.
  3. 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. Eur. Heart J. 2020, 41, 407–477.
  4. Knuuti, J.; Ballo, H.; Juarez-Orozco, L.E.; Saraste, A.; Kolh, P.; Rutjes, A.W.S.; Jüni, P.; Windecker, S.; Bax, J.J.; Wijns, W. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: A meta-analysis focused on post-test disease probability. Eur. Heart J. 2018, 39, 3322–3330.
  5. Mushtaq, S.; Conte, E.; Pontone, G.; Baggiano, A.; Annoni, A.; Formenti, A.; Mancini, M.E.; Guglielmo, M.; Muscogiuri, G.; Tanzilli, A.; et al. State-of-the-art-myocardial perfusion stress testing: Static CT perfusion. J. Cardiovasc. Comput. Tomogr. 2020, 14, 294–302.
  6. Patel, A.R.; Salerno, M.; Kwong, R.Y.; Singh, A.; Heydari, B.; Kramer, C.M. Stress Cardiac Magnetic Resonance Myocardial Perfusion Imaging: JACC Review Topic of the Week. J. Am. Coll. Cardiol. 2021, 78, 1655–1668.
  7. Bruder, O.; Wagner, A.; Lombardi, M.; Schwitter, J.; van Rossum, A.; Pilz, G.; Nothnagel, D.; Steen, H.; Petersen, S.; Nagel, E.; et al. European Cardiovascular Magnetic Resonance (EuroCMR) registry—multi national results from 57 centers in 15 countries. J. Cardiovasc. Magn. Reson. 2013, 15, 9.
  8. Heilmaier, C.; Bruder, O.; Meier, F.; Jochims, M.; Forsting, M.; Sabin, G.V.; Barkhausen, J.; Schlosser, T.W. Dobutamine stress cardiovascular magnetic resonance imaging in patients after invasive coronary revascularization with stent placement. Acta Radiol. 2009, 50, 1134–1141.
  9. Nanni, S.; Lovato, L.; Ghetti, G.; Vagnarelli, F.; Mineo, G.; Fattori, R.; Saia, F.; Marzocchi, A.; Marrozzini, C.; Zompatori, M.; et al. Utility of stress perfusion-cardiac magnetic resonance in follow-up of patients undergoing percutaneous coronary interventions of the left main coronary artery. Int. J. Cardiovasc. Imaging 2017, 33, 1589–1597.
  10. 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, 76.
  11. Kramer, C.M.; Barkhausen, J.; Bucciarelli-Ducci, C.; Flamm, S.D.; Kim, R.J.; Nagel, E. Standardized cardiovascular magnetic resonance imaging (CMR) protocols: 2020 update. J. Cardiovasc. Magn. Reson. 2020, 22, 17.
  12. Baessato, F.; Guglielmo, M.; Muscogiuri, G.; Baggiano, A.; Fusini, L.; Scafuri, S.; Babbaro, M.; Mollace, R.; Collevecchio, A.; Guaricci, A.I.; et al. Stress CMR in Known or Suspected CAD: Diagnostic and Prognostic Role. Biomed. Res. Int. 2021, 2021, 6678029.
  13. Baritussio, A.; Scatteia, A.; Dellegrottaglie, S.; Bucciarelli-Ducci, C. Evidence and Applicability of Stress Cardiovascular Magnetic Resonance in Detecting Coronary Artery Disease: State of the Art. J. Clin. Med. 2021, 10, 3279.
  14. Heiberg, J.; Asschenfeldt, B.; Maagaard, M.; Ringgaard, S. Dynamic bicycle exercise to assess cardiac output at multiple exercise levels during magnetic resonance imaging. Clin. Imaging 2017, 46, 102–107.
  15. Craven, T.P.; Jex, N.; Chew, P.G.; Higgins, D.M.; Bissell, M.M.; Brown, L.A.E.; Saunderson, C.E.D.; Das, A.; Chowdhary, A.; Dall’Armellina, E.; et al. Exercise cardiovascular magnetic resonance: Feasibility and development of biventricular function and great vessel flow assessment, during continuous exercise accelerated by Compressed SENSE: Preliminary results in healthy volunteers. Int. J. Cardiovasc. Imaging 2021, 37, 685–698.
  16. Pepine, C.J.; Anderson, R.D.; Sharaf, B.L.; Reis, S.E.; Smith, K.M.; Handberg, E.M.; Johnson, B.D.; Sopko, G.; Bairey Merz, C.N. Coronary microvascular reactivity to adenosine predicts adverse outcome in women evaluated for suspected ischemia results from the National Heart, Lung and Blood Institute WISE (Women’s Ischemia Syndrome Evaluation) study. J. Am. Coll. Cardiol. 2010, 55, 2825–2832.
  17. Liu, A.; Wijesurendra, R.S.; Liu, J.M.; Forfar, J.C.; Channon, K.M.; Jerosch-Herold, M.; Piechnik, S.K.; Neubauer, S.; Kharbanda, R.K.; Ferreira, V.M. Diagnosis of Microvascular Angina Using Cardiac Magnetic Resonance. J. Am. Coll. Cardiol. 2018, 71, 969–979.
  18. Zhou, W.; Lee, J.C.Y.; Leung, S.T.; Lai, A.; Lee, T.F.; Chiang, J.B.; Cheng, Y.W.; Chan, H.L.; Yiu, K.H.; Goh, V.K.; et al. Long-Term Prognosis of Patients With Coronary Microvascular Disease Using Stress Perfusion Cardiac Magnetic Resonance. JACC Cardiovasc. Imaging 2021, 14, 602–611.
  19. Greenwood, J.P.; Ripley, D.P.; Berry, C.; McCann, G.P.; Plein, S.; Bucciarelli-Ducci, C.; Dall’Armellina, E.; Prasad, A.; Bijsterveld, P.; Foley, J.R.; et al. Effect of Care Guided by Cardiovascular Magnetic Resonance, Myocardial Perfusion Scintigraphy, or NICE Guidelines on Subsequent Unnecessary Angiography Rates: The CE-MARC 2 Randomized Clinical Trial. JAMA 2016, 316, 1051–1060.
  20. Nissen, L.; Winther, S.; Westra, J.; Ejlersen, J.A.; Isaksen, C.; Rossi, A.; Holm, N.R.; Urbonaviciene, G.; Gormsen, L.C.; Madsen, L.H.; et al. Diagnosing coronary artery disease after a positive coronary computed tomography angiography: The Dan-NICAD open label, parallel, head to head, randomized controlled diagnostic accuracy trial of cardiovascular magnetic resonance and myocardial perfusion scintigraphy. Eur. Heart J. Cardiovasc. Imaging 2018, 19, 369–377.
  21. Montalescot, G.; Sechtem, U.; Achenbach, S.; Andreotti, F.; Arden, C.; Budaj, A.; Bugiardini, R.; Crea, F.; Cuisset, T.; Di Mario, C.; et al. 2013 ESC guidelines on the management of stable coronary artery disease: The Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur. Heart J. 2013, 34, 2949–3003.
  22. Neumann, F.J.; Sousa-Uva, M.; Ahlsson, A.; Alfonso, F.; Banning, A.P.; Benedetto, U.; Byrne, R.A.; Collet, J.P.; Falk, V.; Head, S.J.; et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. Eur. Heart J. 2019, 40, 87–165.
  23. McDonagh, T.A.; Metra, M.; Adamo, M.; Gardner, R.S.; Baumbach, A.; Böhm, M.; Burri, H.; Butler, J.; Čelutkienė, J.; Chioncel, O.; et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur. J. Heart Fail. 2022, 24, 4–131.
  24. Collet, J.P.; Thiele, H.; Barbato, E.; Barthélémy, O.; Bauersachs, J.; Bhatt, D.L.; Dendale, P.; Dorobantu, M.; Edvardsen, T.; Folliguet, T.; et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur. Heart J. 2021, 42, 1289–1367.
  25. Danad, I.; Szymonifka, J.; Twisk, J.W.R.; Norgaard, B.L.; 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. 2017, 38, 991–998.
  26. Neglia, D.; Liga, R.; Caselli, C.; Carpeggiani, C.; Lorenzoni, V.; Sicari, R.; Lombardi, M.; Gaemperli, O.; Kaufmann, P.A.; Scholte, A.; et al. Anatomical and functional coronary imaging to predict long-term outcome in patients with suspected coronary artery disease: The EVINCI-outcome study. Eur. Heart J. Cardiovasc. Imaging 2020, 21, 1273–1282.
  27. Lorenzoni, V.; Bellelli, S.; Caselli, C.; Knuuti, J.; Underwood, S.R.; Neglia, D.; Turchetti, G. Cost-effectiveness analysis of stand-alone or combined non-invasive imaging tests for the diagnosis of stable coronary artery disease: Results from the EVINCI study. Eur. J. Health Econ. 2019, 20, 1437–1449.
  28. Chen, M.Y.; Rochitte, C.E.; Arbab-Zadeh, A.; Dewey, M.; George, R.T.; Miller, J.M.; Niinuma, H.; Yoshioka, K.; Kitagawa, K.; Sakuma, H.; et al. Prognostic Value of Combined CT Angiography and Myocardial Perfusion Imaging versus Invasive Coronary Angiography and Nuclear Stress Perfusion Imaging in the Prediction of Major Adverse Cardiovascular Events: The CORE320 Multicenter Study. Radiology 2017, 284, 55–65.
  29. van Assen, M.; De Cecco, C.N.; Eid, M.; von Knebel Doeberitz, P.; Scarabello, M.; Lavra, F.; Bauer, M.J.; Mastrodicasa, D.; Duguay, T.M.; Zaki, B.; et al. Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease. J. Cardiovasc. Comput. Tomogr. 2019, 13, 26–33.
  30. Patel, A.R.; Bamberg, F.; Branch, K.; Carrascosa, P.; Chen, M.; Cury, R.C.; Ghoshhajra, B.; Ko, B.; Nieman, K.; Pugliese, F.; et al. Society of cardiovascular computed tomography expert consensus document on myocardial computed tomography perfusion imaging. J. Cardiovasc. Comput. Tomogr. 2020, 14, 87–100.
  31. Seitun, S.; De Lorenzi, C.; Cademartiri, F.; Buscaglia, A.; Travaglio, N.; Balbi, M.; Bezante, G.P. CT Myocardial Perfusion Imaging: A New Frontier in Cardiac Imaging. Biomed. Res. Int. 2018, 2018, 7295460.
  32. Danad, I.; Szymonifka, J.; Schulman-Marcus, J.; Min, J.K. Static and dynamic assessment of myocardial perfusion by computed tomography. Eur. Heart J. Cardiovasc. Imaging 2016, 17, 836–844.
  33. de Knegt, M.C.; Rossi, A.; Petersen, S.E.; Wragg, A.; Khurram, R.; Westwood, M.; Saberwal, B.; Mathur, A.; Nieman, K.; Bamberg, F.; et al. Stress myocardial perfusion with qualitative magnetic resonance and quantitative dynamic computed tomography: Comparison of diagnostic performance and incremental value over coronary computed tomography angiography. Eur. Heart J. Cardiovasc. Imaging 2020, 22, 1452–1462.
  34. Takx, R.A.; Blomberg, B.A.; El Aidi, H.; Habets, J.; de Jong, P.A.; Nagel, E.; Hoffmann, U.; Leiner, T. Diagnostic accuracy of stress myocardial perfusion imaging compared to invasive coronary angiography with fractional flow reserve meta-analysis. Circ. Cardiovasc. Imaging 2015, 8, e002666.
  35. Arbab-Zadeh, A.; Miller, J.M.; Rochitte, C.E.; Dewey, M.; Niinuma, H.; Gottlieb, I.; Paul, N.; Clouse, M.E.; Shapiro, E.P.; Hoe, J.; et al. Diagnostic accuracy of computed tomography coronary angiography according to pre-test probability of coronary artery disease and severity of coronary arterial calcification. The CORE-64 (Coronary Artery Evaluation Using 64-Row Multidetector Computed Tomography Angiography) International Multicenter Study. J. Am. Coll. Cardiol. 2012, 59, 379–387.
  36. Wykrzykowska, J.J.; Arbab-Zadeh, A.; Godoy, G.; Miller, J.M.; Lin, S.; Vavere, A.; Paul, N.; Niinuma, H.; Hoe, J.; Brinker, J.; et al. Assessment of in-stent restenosis using 64-MDCT: Analysis of the CORE-64 Multicenter International Trial. AJR Am. J. Roentgenol. 2010, 194, 85–92.
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