Bildgebende Belastungsdiagnostik des Herzens

Symptomatische Patienten mit Verdacht auf ein chronisches Koronarsyndrom sind häufig und die Kosten der diagnostischen Abklärung für das Gesundheitssystem erheblich. Bildgebende Verfahren stellen einen zentralen Teil der Diagnostik dar und ermöglichen sowohl Ausschluss eines CCS als auch den Nachweis einer hämodynamisch relevanten Stenose bzw. Myokardischämie. Folgend werden verschiedene Verfahren, deren Effektivität und Wirtschaftlichkeit vorgestellt.

Kernaussagen

• Die funktionellen bildgebenden Verfahren des Herzens haben einen maßgeblichen Stellenwert bei der Therapieentscheidung symptomatischer Patienten mit V. a. oder bereits bekanntem CCS.

• Sie sind entsprechend den aktuellen Leitlinien indiziert bei Patienten mit höherer klinischer Wahrscheinlichkeit für ein CCS oder bei bekanntem CCS, abhängig von lokaler Verfügbarkeit und Kompetenzen.

• Unter den im klinischen Umfeld relevanten Verfahren zeichnet sich die Stress-MRT durch ihre hohe diagnostische Genauigkeit aufgrund der guten räumlichen Auflösung und eine exzellente Narbenbildgebung aus.

• Die Stress-Echokardiografie, SPECT und PET-MPI sind weitere etablierte funktionelle Verfahren mit weitgehend vergleichbarer diagnostischer Genauigkeit.

• Insbesondere die Stress-Echokardiografie zeichnet sich durch die Möglichkeit der Erhebung weiterer relevanter Belastungsparameter des linken Ventrikels aus und kann als hoch verfügbare und kostengünstige Methode einen Mehrwert bieten.

• Im Bereich der ambulanten Versorgung spielt die SPECT aufgrund ihrer guten Standardisierung und Verfügbarkeit bisher die größte Rolle in Deutschland.

• Die PET-MPI und Perfusionsstress-CT haben eine exzellente diagnostische Aussagekraft aufgrund der Möglichkeit einer absoluten Quantifizierung der Perfusion, spielen in der klinischen Versorgung aktuell jedoch nur eine untergeordnete Rolle.

• Die CT hat methodisch das Potenzial, die morphologische und funktionelle Bildgebung mit der CT-Koronarangiografie und Perfusionsstress-CT zu vereinen.

Schlüsselwörter

Bildgebung - Diagnostik - CCS - Stress-MRT - Perfusionsstress-CT - fraktionierte Flussreserve - SPECT - PET - chronisches Koronarsyndrom

Publication History

Article published online:
01 July 2024

• Literatur

• 1 Knuuti J, Wijns W, Saraste A. et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J 2020; 41: 407-477 DOI: 10.1093/eurheartj/ehz425. (PMID: 31504439)
• 2 Saraste A, Barbato E, Capodanno D. et al. Imaging in ESC clinical guidelines: chronic coronary syndromes. Eur Heart J Cardiovasc Imaging 2019; 20: 1187-1197 DOI: 10.1093/ehjci/jez219. (PMID: 31642920)
• 3 Bundesärztekammer (BÄK), Kassenärztliche Bundesvereinigung (KBV), Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften (AWMF). Nationale VersorgungsLeitlinie Chronische KHK, Version 6.0. 2022 Accessed May 19, 2024 at: https://www.leitlinien.de/themen/khk
• 4 Lehmkuhl L, Krieghoff C, Gutberlet M. Neue Möglichkeiten der Ischämiediagnostik: CT-FFR und CT-Perfusion. Radiologie up2date 2017; 17: 307-320 DOI: 10.1055/s-0043-119184.
• 5 Nørgaard BL, Leipsic J, Gaur S. et al. Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: The NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am Coll Cardiol 2014; 63: 1145-1155 DOI: 10.1016/j.jacc.2013.11.043. (PMID: 24486266)
• 6 Foldyna B, Uhlig J, Gohmann R. et al. Quality and safety of coronary computed tomography angiography at academic and non-academic sites: insights from a large European registry (ESCR MR/CT Registry). Eur Radiol 2022; 32: 5246-5255 DOI: 10.1007/s00330-022-08639-0. (PMID: 35267087)
• 7 Uhlig J, Lücke C, Vliegenthart R. et al. Acute adverse events in cardiac MR imaging with gadolinium-based contrast agents: results from the European Society of Cardiovascular Radiology (ESCR) MRCT Registry in 72,839 patients. Eur Radiol 2019; 29: 3686-3695 DOI: 10.1007/s00330-019-06171-2. (PMID: 31041566)
• 8 Uhlig J, Al-Bourini O, Salgado R. et al. Gadolinium-based Contrast Agents for Cardiac MRI: Use of Linear and Macrocyclic Agents with Associated Safety Profile from 154 779 European Patients. Radiol Cardiothorac Imaging 2020; 2: e200102 DOI: 10.1148/ryct.2020200102. (PMID: 33778622)
• 9 Rossi A, Merkus D, Klotz E. et al. Stress myocardial perfusion: Imaging with multidetector CT. Radiology 2014; 270: 25-46 DOI: 10.1148/radiol.13112739. (PMID: 24354374)
• 10 Schelbert HR. Anatomy and physiology of coronary blood flow. J Nucl Cardiol 2010; 17: 545-554 DOI: 10.1007/s12350-010-9255-x. (PMID: 20521136)
• 11 Kramer CM, Barkhausen J, Bucciarelli-Ducci C. et al. Standardized cardiovascular magnetic resonance imaging (CMR) protocols: 2020 update. J Cardiovasc Magn Reson 2020; 22: 17 DOI: 10.1186/s12968-020-00607-1. (PMID: 32089132)
• 12 Nagel E, Greenwood JP, McCann GP. et al. Magnetic Resonance Perfusion or Fractional Flow Reserve in Coronary Disease. N Engl J Med 2019; 380: 2418-2428 DOI: 10.1056/NEJMoa1716734. (PMID: 31216398)
• 13 Pezel T, Unterseeh T, Garot P. et al. Prognostic value of vasodilator stress perfusion cardiovascular magnetic resonance after inconclusive stress testing. J Cardiovasc Magn Reson 2021; 23: 89 DOI: 10.1186/s12968-021-00785-6. (PMID: 34218805)
• 14 Peper J, Suchá D, Swaans M. et al. Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning. Br J Radiol 2020; 93: 20200349 DOI: 10.1259/bjr.20200349. (PMID: 32783626)
• 15 Azarine A, Scalbert F, Garçon P. Cardiac functional imaging. Presse Med 2022; 51: 104119 DOI: 10.1016/j.lpm.2022.104119. (PMID: 35321846)
• 16 Schwitter J, Wacker CM, van Rossum AC. et al. MR-IMPACT: comparison of perfusion-cardiac magnetic resonance with single-photon emission computed tomography for the detection of coronary artery disease in a multicentre, multivendor, randomized trial. Eur Heart J 2008; 29: 480-489 DOI: 10.1093/eurheartj/ehm617. (PMID: 18208849)
• 17 Schwitter J, Wacker CM, Wilke N. et al. MR-IMPACT II: Magnetic Resonance Imaging for Myocardial Perfusion Assessment in Coronary artery disease Trial: perfusion-cardiac magnetic resonance vs. single-photon emission computed tomography for the detection of coronary artery disease: a comparative multicentre, multivendor trial. Eur Heart J 2013; 34: 775-781 DOI: 10.1093/eurheartj/ehs022. (PMID: 22390914)
• 18 Greenwood JP, Maredia N, Younger JF. et al. Cardiovascular magnetic resonance and single-photon emission computed tomography for diagnosis of coronary heart disease (CE-MARC): a prospective trial. Lancet 2012; 379: 453-460 DOI: 10.1016/S0140-6736(11)61335-4. (PMID: 22196944)
• 19 Arai AE, Schulz-Menger J, Shah DJ. et al. Stress Perfusion Cardiac Magnetic Resonance vs SPECT Imaging for Detection of Coronary Artery Disease. J Am Coll Cardiol 2023; 82: 1828-1838 DOI: 10.1016/j.jacc.2023.08.046. (PMID: 37914512)
• 20 Min JY, Ko SM, Song IY. et al. Comparison of the Diagnostic Accuracies of 1.5T and 3T Stress Myocardial Perfusion Cardiovascular Magnetic Resonance for Detecting Significant Coronary Artery Disease. Korean J Radiol 2018; 19: 1007-1020 DOI: 10.3348/kjr.2018.19.6.1007. (PMID: 30386133)
• 21 Lockie T, Ishida M, Perera D. et al. High-resolution magnetic resonance myocardial perfusion imaging at 3.0-Tesla to detect hemodynamically significant coronary stenoses as determined by fractional flow reserve. J Am Coll Cardiol 2011; 57: 70-75 DOI: 10.1016/j.jacc.2010.09.019. (PMID: 21185504)
• 22 Glikson M, Nielsen JC, Kronborg MB. et al. 2021 ESC Guidelines on cardiac pacing and cardiac resynchronization therapy. Eur Heart J 2021; 42: 3427-34520 DOI: 10.1093/eurheartj/ehab364. (PMID: 34455430)
• 23 Sharma RK, Arbab-Zadeh A, Kishi S. et al. Incremental diagnostic accuracy of computed tomography myocardial perfusion imaging over coronary angiography stratified by pre-test probability of coronary artery disease and severity of coronary artery calcification: The CORE320 study. Int J Cardiol 2015; 201: 570-577 DOI: 10.1016/j.ijcard.2015.05.110. (PMID: 26334382)
• 24 Blankstein R, Shturman LD, Rogers IS. et al. Adenosine-induced stress myocardial perfusion imaging using dual-source cardiac computed tomography. J Am Coll Cardiol 2009; 54: 1072-1084 DOI: 10.1016/j.jacc.2009.06.014. (PMID: 19744616)
• 25 Chung HW, Ko SM, Hwang HK. et al. Diagnostic Performance of Coronary CT Angiography, Stress Dual-Energy CT Perfusion, and Stress Perfusion Single-Photon Emission Computed Tomography for Coronary Artery Disease: Comparison with Combined Invasive Coronary Angiography and Stress Perfusion Cardiac MRI. Korean J Radiol 2017; 18: 476-486 DOI: 10.3348/kjr.2017.18.3.476. (PMID: 28458600)
• 26 Huber AM, Leber V, Gramer BM. et al. Myocardium: Dynamic versus single-shot CT perfusion imaging. Radiology 2013; 269: 378-386 DOI: 10.1148/radiol.13121441. (PMID: 23788717)
• 27 Takx RAP, Blomberg BA, El Aidi H. et al. Diagnostic accuracy of stress myocardial perfusion imaging compared to invasive coronary angiography with fractional flow reserve meta-analysis. Circ Cardiovasc Imaging 2015; 8: e002666 DOI: 10.1161/CIRCIMAGING.114.002666. (PMID: 25596143)
• 28 Tanabe Y, Kurata A, Matsuda T. et al. Computed tomographic evaluation of myocardial ischemia. Jpn J Radiol 2020; 38: 411-433 DOI: 10.1007/s11604-020-00922-8. (PMID: 32026226)
• 29 Machida H, Tanaka I, Fukui R. et al. Current and Novel Imaging Techniques in Coronary CT. Radiographics 2015; 35: 991-1010 DOI: 10.1148/rg.2015140181. (PMID: 26046942)
• 30 Hulten E, Ahmadi A, Blankstein R. CT Assessment of Myocardial Perfusion and Fractional Flow Reserve. Prog Cardiovasc Dis 2015; 57: 623-631 DOI: 10.1016/j.pcad.2015.03.003. (PMID: 25770850)
• 31 Gutberlet M, Krieghoff C, Gohmann R. Werden die Karten der CT-Koronarangiographie mit der FFRCT neu gemischt?. Herz 2020; 45: 431-440 DOI: 10.1007/s00059-020-04944-w. (PMID: 32494946)
• 32 Min JK, Leipsic J, Pencina MJ. et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA 2012; 308: 1237-1245 DOI: 10.1001/2012.jama.11274. (PMID: 22922562)
• 33 Celeng C, Leiner T, Maurovich-Horvat P. et al. Anatomical and Functional Computed Tomography for Diagnosing Hemodynamically Significant Coronary Artery Disease: A Meta-Analysis. JACC Cardiovasc Imaging 2019; 12: 1316-1325 DOI: 10.1016/j.jcmg.2018.07.022. (PMID: 30219398)
• 34 Curzen N, Nicholas Z, Stuart B. et al. Fractional flow reserve derived from computed tomography coronary angiography in the assessment and management of stable chest pain: the FORECAST randomized trial. Eur Heart J 2021; 42: 3844-3852 DOI: 10.1093/eurheartj/ehab444. (PMID: 34269376)
• 35 Metz LD, Beattie M, Hom R. et al. The prognostic value of normal exercise myocardial perfusion imaging and exercise echocardiography: a meta-analysis. J Am Coll Cardiol 2007; 49: 227-237 DOI: 10.1016/j.jacc.2006.08.048. (PMID: 17222734)
• 36 de Jong MC, Genders TSS, van Geuns R-J. et al. Diagnostic performance of stress myocardial perfusion imaging for coronary artery disease: a systematic review and meta-analysis. Eur Radiol 2012; 22: 1881-1895 DOI: 10.1007/s00330-012-2434-1. (PMID: 22527375)
• 37 Knuuti J, Bengel F, Bax JJ. et al. Risks and benefits of cardiac imaging: an analysis of risks related to imaging for coronary artery disease. Eur Heart J 2014; 35: 633-638 DOI: 10.1093/eurheartj/eht512. (PMID: 24375074)
• 38 Trägårdh E, Tan SS, Bucerius J. et al. Systematic review of cost-effectiveness of myocardial perfusion scintigraphy in patients with ischaemic heart disease: A report from the cardiovascular committee of the European Association of Nuclear Medicine. Endorsed by the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging 2017; 18: 825-832 DOI: 10.1093/ehjci/jex095. (PMID: 28549119)
• 39 Lindner O, Schaefer WM, Silber S. et al. Myokard-Perfusions-SPECT 2021 in Deutschland: Ergebnisse der 9. Erhebung. Nuklearmedizin 2023; 62: 235-243 DOI: 10.1055/a-2084-7454.
• 40 Esteves FP, Raggi P, Folks RD. et al. Novel solid-state-detector dedicated cardiac camera for fast myocardial perfusion imaging: multicenter comparison with standard dual detector cameras. J Nucl Cardiol 2009; 16: 927-934 DOI: 10.1007/s12350-009-9137-2. (PMID: 19688410)
• 41 Kincl V, Kamínek M, Vašina J. et al. Feasibility of ultra low-dose thallium stress-redistribution protocol including prone imaging in obese patients using CZT camera. Int J Cardiovasc Imaging 2016; 32: 1463 DOI: 10.1007/s10554-016-0919-8. (PMID: 27250348)
• 42 Nakazato R, Tamarappoo BK, Kang X. et al. Quantitative upright-supine high-speed SPECT myocardial perfusion imaging for detection of coronary artery disease: correlation with invasive coronary angiography. J Nucl Med 2010; 51: 1724-1731 DOI: 10.2967/jnumed.110.078782. (PMID: 20956478)
• 43 Neill J, Prvulovich EM, Fish MB. et al. Initial multicentre experience of high-speed myocardial perfusion imaging: comparison between high-speed and conventional single-photon emission computed tomography with angiographic validation. Eur J Nucl Med Mol Imaging 2013; 40: 1084-1094 DOI: 10.1007/s00259-013-2399-6. (PMID: 23595108)
• 44 Parker MW, Iskandar A, Limone B. et al. Diagnostic accuracy of cardiac positron emission tomography versus single photon emission computed tomography for coronary artery disease: a bivariate meta-analysis. Circ Cardiovasc Imaging 2012; 5: 700-707 DOI: 10.1161/CIRCIMAGING.112.978270. (PMID: 23051888)
• 45 Zhou T, Yang L-F, Zhai J-L. et al. SPECT myocardial perfusion versus fractional flow reserve for evaluation of functional ischemia: a meta analysis. Eur J Radiol 2014; 83: 951-956 DOI: 10.1016/j.ejrad.2014.02.018. (PMID: 24666512)
• 46 Al-Mallah MH, Sitek A, Moore SC. et al. Assessment of myocardial perfusion and function with PET and PET/CT. J Nucl Cardiol 2010; 17: 498-513 DOI: 10.1007/s12350-010-9223-5. (PMID: 20379862)
• 47 Dorbala S, Hachamovitch R, Curillova Z. et al. Incremental prognostic value of gated Rb-82 positron emission tomography myocardial perfusion imaging over clinical variables and rest LVEF. JACC Cardiovasc Imaging 2009; 2: 846-854 DOI: 10.1016/j.jcmg.2009.04.009. (PMID: 19608135)
• 48 Dorbala S, Vangala D, Sampson U. et al. Value of vasodilator left ventricular ejection fraction reserve in evaluating the magnitude of myocardium at risk and the extent of angiographic coronary artery disease: a 82Rb PET/CT study. J Nucl Med 2007; 48: 349-358 (PMID: 17332611)
• 49 Hyafil F, Chequer R, Sorbets E. et al. Head-to-head comparison of the diagnostic performances of Rubidium-PET and SPECT with CZT camera for the detection of myocardial ischemia in a population of women and overweight individuals. J Nucl Cardiol 2020; 27: 755-768 DOI: 10.1007/s12350-018-01557-z. (PMID: 30574676)
• 50 Naya M, Murthy VL, Foster CR. et al. Prognostic interplay of coronary artery calcification and underlying vascular dysfunction in patients with suspected coronary artery disease. J Am Coll Cardiol 2013; 61: 2098-2106 DOI: 10.1016/j.jacc.2013.02.029. (PMID: 23524053)
• 51 Klein R, Renaud JM, Ziadi MC. et al. Intra- and inter-operator repeatability of myocardial blood flow and myocardial flow reserve measurements using rubidium-82 pet and a highly automated analysis program. J Nucl Cardiol 2010; 17: 600-616 DOI: 10.1007/s12350-010-9225-3. (PMID: 20387135)