Characterizing the Heart and the Myocardium With Photon-Counting CT.


Journal

Investigative radiology
ISSN: 1536-0210
Titre abrégé: Invest Radiol
Pays: United States
ID NLM: 0045377

Informations de publication

Date de publication:
01 07 2023
Historique:
medline: 14 6 2023
pubmed: 24 2 2023
entrez: 23 2 2023
Statut: ppublish

Résumé

Noninvasive cardiac imaging has rapidly evolved during the last decade owing to improvements in computed tomography (CT)-based technologies, among which we highlight the recent introduction of the first clinical photon-counting detector CT (PCD-CT) system. Multiple advantages of PCD-CT have been demonstrated, including increased spatial resolution, decreased electronic noise, and reduced radiation exposure, which may further improve diagnostics and may potentially impact existing management pathways. The benefits that can be obtained from the initial experiences with PCD-CT are promising. The implementation of this technology in cardiovascular imaging allows for the quantification of coronary calcium, myocardial extracellular volume, myocardial radiomics features, epicardial and pericoronary adipose tissue, and the qualitative assessment of coronary plaques and stents. This review aims to discuss these major applications of PCD-CT with a focus on cardiac and myocardial characterization.

Identifiants

pubmed: 36822653
doi: 10.1097/RLI.0000000000000956
pii: 00004424-202307000-00009
doi:

Types de publication

Review Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

505-514

Informations de copyright

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of interest and sources of funding: none declared.

Références

Willemink MJ, Grist TM. Counting photons: the next era for CT imaging? Radiology . 2022;303:139–140.
Rajendran K, Petersilka M, Henning A, et al. First clinical photon-counting detector CT system: technical evaluation. Radiology . 2022;303:130–138.
Willemink MJ, Persson M, Pourmorteza A, et al. Photon-counting CT: technical principles and clinical prospects. Radiology . 2018;289:293–312.
Leng S, Bruesewitz M, Tao S, et al. Photon-counting detector CT: system design and clinical applications of an emerging technology. Radiographics . 2019;39:729–743.
Sandstedt M, Marsh J Jr., Rajendran K, et al. Improved coronary calcification quantification using photon-counting-detector CT: an ex vivo study in cadaveric specimens. Eur Radiol . 2021;31:6621–6630.
Euler A, Higashigaito K, Mergen V, et al. High-pitch photon-counting detector computed tomography angiography of the aorta: intraindividual comparison to energy-integrating detector computed tomography at equal radiation dose. Invest Radiol . 2022;57:115–121.
Sartoretti T, Eberhard M, Nowak T, et al. Photon-counting multienergy computed tomography with spectrally optimized contrast media for plaque removal and stenosis assessment. Invest Radiol . 2021;56:563–570.
Zhou W, Michalak GJ, Weaver JM, et al. A universal protocol for abdominal CT examinations performed on a photon-counting detector CT system: a feasibility study. Invest Radiol . 2020;55:226–232.
Ren L, Huber N, Rajendran K, et al. Dual-contrast biphasic liver imaging with iodine and gadolinium using photon-counting detector computed tomography: an exploratory animal study. Invest Radiol . 2022;57:122–129.
Boccalini S, Si-Mohamed SA, Lacombe H, et al. First in-human results of computed tomography angiography for coronary stent assessment with a spectral photon counting computed tomography. Invest Radiol . 2022;57:212–221.
Jungblut L, Blüthgen C, Polacin M, et al. First performance evaluation of an artificial intelligence-based computer-aided detection system for pulmonary nodule evaluation in dual-source photon-counting detector CT at different low-dose levels. Invest Radiol . 2022;57:108–114.
Mannil M, Hickethier T, von Spiczak J, et al. Photon-counting CT: high-resolution imaging of coronary stents. Invest Radiol . 2018;53:143–149.
van der Werf NR, Si-Mohamed S, Rodesch PA, et al. Coronary calcium scoring potential of large field-of-view spectral photon-counting CT: a phantom study. Eur Radiol . 2022;32:152–162.
Si-Mohamed S, Boccalini S, Rodesch PA, et al. Feasibility of lung imaging with a large field-of-view spectral photon-counting CT system. Diagn Interv Imaging . 2021;102:305–312.
Willemink MJ, Varga-Szemes A, Schoepf UJ, et al. Emerging methods for the characterization of ischemic heart disease: ultrafast Doppler angiography, micro-CT, photon-counting CT, novel MRI and PET techniques, and artificial intelligence. Eur Radiol Exp . 2021;5:12.
Fink N, Schoepf UJ. Photon counting detectors—not only a technical breakthrough, but also a new era in patient care? Eur J Radiol . 2022;154:110435.
Knuuti J, Wijns W, Saraste A, 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 . 2019;41:407–477.
World Health Organization. The top 10 causes of death. 2020 https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death . Accessed December 23, 2022.
Agatston AS, Janowitz WR, Hildner FJ, et al. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol . 1990;15:827–832.
McCollough CH, Ulzheimer S, Halliburton SS, et al. Coronary artery calcium: a multi-institutional, multimanufacturer international standard for quantification at cardiac CT. Radiology . 2007;243:527–538.
Willemink MJ, Vliegenthart R, Takx RAP, et al. Coronary artery calcification scoring with state-of-the-art CT scanners from different vendors has substantial effect on risk classification. Radiology . 2014;273:695–702.
Visseren FLJ, Mach F, Smulders YM, et al. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice: developed by the Task Force for Cardiovascular Disease Prevention in Clinical Practice with representatives of the European Society of Cardiology and 12 medical societies with the special contribution of the European Association of Preventive Cardiology (EAPC). Eur Heart J . 2021;42:3227–3337.
D'Angelo T, Cicero G, Mazziotti S, et al. Dual energy computed tomography virtual monoenergetic imaging: technique and clinical applications. Br J Radiol . 2019;92:20180546.
Skoog S, Henriksson L, Gustafsson H, et al. Comparison of the Agatston score acquired with photon-counting detector CT and energy-integrating detector CT: ex vivo study of cadaveric hearts. Int J Cardiovasc Imaging . 2022;38:1145–1155.
Symons R, Sandfort V, Mallek M, et al. Coronary artery calcium scoring with photon-counting CT: first in vivo human experience. Int J Cardiovasc Imaging . 2019;35:733–739.
Eberhard M, Mergen V, Higashigaito K, et al. Coronary calcium scoring with first generation dual-source photon-counting CT-first evidence from phantom and in-vivo scans. Diagnostics (Basel) . 2021;11:1708.
Mergen V, Higashigaito K, Allmendinger T, et al. Tube voltage-independent coronary calcium scoring on a first-generation dual-source photon-counting CT-a proof-of-principle phantom study. Int J Cardiovasc Imaging . 2021.
van der Werf NR, van Gent M, Booij R, et al. Dose reduction in coronary artery calcium scoring using mono-energetic images from reduced tube voltage dual-source photon-counting CT data: a dynamic phantom study. Diagnostics (Basel) . 2021;11:2192.
van der Werf NR, Greuter MJW, Booij R, et al. Coronary calcium scores on dual-source photon-counting computed tomography: an adapted Agatston methodology aimed at radiation dose reduction. Eur Radiol . 2022;32:5201–5209.
Achenbach S, Ropers D, Holle J, et al. In-plane coronary arterial motion velocity: measurement with electron-beam CT. Radiology . 2000;216:457–463.
Husmann L, Leschka S, Desbiolles L, et al. Coronary artery motion and cardiac phases: dependency on heart rate—implications for CT image reconstruction. Radiology . 2007;245:567–576.
van der Werf NR, Willemink MJ, Willems TP, et al. Influence of heart rate on coronary calcium scores: a multi-manufacturer phantom study. Int J Cardiovasc Imaging . 2018;34:959–966.
Vonder M, van der Werf NR, Leiner T, et al. The impact of dose reduction on the quantification of coronary artery calcifications and risk categorization: a systematic review. J Cardiovasc Comput Tomogr . 2018;12:352–363.
Sandfort V, Persson M, Pourmorteza A, et al. Spectral photon-counting CT in cardiovascular imaging. J Cardiovasc Comput Tomogr . 2021;15:218–225.
Farhadi F, Rajagopal JR, Nikpanah M, et al. Review of technical advancements and clinical applications of photon-counting computed tomography in imaging of the thorax. J Thorac Imaging . 2021;36:84–94.
Gassert FG, Schacky CE, Müller-Leisse C, et al. Calcium scoring using virtual non-contrast images from a dual-layer spectral detector CT: comparison to true non-contrast data and evaluation of proportionality factor in a large patient collective. Eur Radiol . 2021;31:6193–6199.
Emrich T, Aquino G, Schoepf UJ, et al. Coronary computed tomography angiography-based calcium scoring: in vitro and in vivo validation of a novel virtual noniodine reconstruction algorithm on a clinical, first-generation dual-source photon counting-detector system. Invest Radiol . 2022;57:536–543.
von Ballmoos MW, Haring B, Juillerat P, et al. Meta-analysis: diagnostic performance of low-radiation-dose coronary computed tomography angiography. Ann Intern Med . 2011;154:413–420.
Haase R, Schlattmann P, Gueret P, et al. Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data. BMJ . 2019;365:l1945.
Knuuti J, Ballo H, Juarez-Orozco LE, et al. 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.
Maurovich-Horvat P, Bosserdt M, Kofoed KF, et alDISCHARGE Trial Group. CT or invasive coronary angiography in stable chest pain. N Engl J Med . 2022;386:1591–1602.
Song YB, Arbab-Zadeh A, Matheson MB, et al. Contemporary discrepancies of stenosis assessment by computed tomography and invasive coronary angiography. Circ Cardiovasc Imaging . 2019;12:e007720.
Habbel C, Hetterich H, Willner M, et al. Ex vivo assessment of coronary atherosclerotic plaque by grating-based phase-contrast computed tomography: correlation with optical coherence tomography. Invest Radiol . 2017;52:223–231.
Hetterich H, Willner M, Habbel C, et al. X-ray phase-contrast computed tomography of human coronary arteries. Invest Radiol . 2015;50:686–694.
Mehran R, Mintz GS, Hong MK, et al. Validation of the in vivo intravascular ultrasound measurement of in-stent neointimal hyperplasia volumes. J Am Coll Cardiol . 1998;32:794–799.
von Spiczak J, Mannil M, Peters B, et al. Photon counting computed tomography with dedicated sharp convolution kernels: tapping the potential of a new Technology for Stent Imaging. Invest Radiol . 2018;53:486–494.
Bratke G, Hickethier T, Bar-Ness D, et al. Spectral photon-counting computed tomography for coronary stent imaging: evaluation of the potential clinical impact for the delineation of in-stent restenosis. Invest Radiol . 2020;55:61–67.
Hoffmann U, Moselewski F, Nieman K, et al. Noninvasive assessment of plaque morphology and composition in culprit and stable lesions in acute coronary syndrome and stable lesions in stable angina by multidetector computed tomography. J Am Coll Cardiol . 2006;47:1655–1662.
Karanasos A, Ligthart JM, Witberg KT, et al. Calcified nodules: an underrated mechanism of coronary thrombosis? JACC Cardiovasc Imaging . 2012;5:1071–1072.
Maurovich-Horvat P, Ferencik M, Voros S, et al. Comprehensive plaque assessment by coronary CT angiography. Nat Rev Cardiol . 2014;11:390–402.
Maurovich-Horvat P, Hoffmann U, Vorpahl M, et al. The napkin-ring sign: CT signature of high-risk coronary plaques? JACC Cardiovasc Imaging . 2010;3:440–444.
Motoyama S, Kondo T, Sarai M, et al. Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol . 2007;50:319–326.
Williams MC, Kwiecinski J, Doris M, et al. Low-attenuation noncalcified plaque on coronary computed tomography angiography predicts myocardial infarction: results from the Multicenter SCOT-HEART Trial (Scottish computed tomography of the HEART). Circulation . 2020;141:1452–1462.
Meah MN, Tzolos E, Wang K-L, et al. Plaque burden and 1-year outcomes in acute chest pain. JACC Cardiovasc Imaging . 0.
Szilveszter B, Vattay B, Bossoussou M, et al. CAD-RADS may underestimate coronary plaque progression as detected by serial CT angiography. Eur Heart J Cardiovasc Imaging . 2022;23:1530–1539.
Benson JC, Rajendran K, Lane JI, et al. A new frontier in temporal bone imaging: photon-counting detector CT demonstrates superior visualization of critical anatomic structures at reduced radiation dose. AJNR Am J Neuroradiol . 2022;43:579–584.
Mergen V, Sartoretti T, Baer-Beck M, et al. Ultra-high-resolution coronary CT angiography with photon-counting detector CT: feasibility and image characterization. Invest Radiol . 2022;57:780–788.
Rajagopal JR, Farhadi F, Richards T, et al. Evaluation of coronary plaques and stents with conventional and photon-counting CT: benefits of high-resolution photon-counting CT. Radiol Cardiothorac Imaging . 2021;3:e210102.
de Graaf FR, Schuijf JD, van Velzen JE, et al. Diagnostic accuracy of 320-row multidetector computed tomography coronary angiography to noninvasively assess in-stent restenosis. Invest Radiol . 2010;45:331–340.
Si-Mohamed SA, Boccalini S, Lacombe H, et al. Coronary CT angiography with photon-counting CT: first-in-human results. Radiology . 2022;303:303–313.
Mergen V, Eberhard M, Manka R, et al. First in-human quantitative plaque characterization with ultra-high resolution coronary photon-counting CT angiography. Front Cardiovasc Med . 2022;9:981012.
Scully PR, Bastarrika G, Moon JC, et al. Myocardial extracellular volume quantification by cardiovascular magnetic resonance and computed tomography. Curr Cardiol Rep . 2018;20:15.
Pucci A, Aimo A, Musetti V, et al. Amyloid deposits and fibrosis on left ventricular endomyocardial biopsy correlate with extracellular volume in cardiac amyloidosis. J Am Heart Assoc . 2021;10:e020358.
Everett RJ, Treibel TA, Fukui M, et al. Extracellular myocardial volume in patients with aortic stenosis. J Am Coll Cardiol . 2020;75:304–316.
Dorbala S, Ando Y, Bokhari S, et al. ASNC/AHA/ASE/EANM/HFSA/ISA/SCMR/SNMMI expert consensus recommendations for multimodality imaging in cardiac amyloidosis: part 1 of 2-evidence base and standardized methods of imaging. Circ Cardiovasc Imaging . 2021;14:e000029.
Beltrami CA, Finato N, Rocco M, et al. Structural basis of end-stage failure in ischemic cardiomyopathy in humans. Circulation . 1994;89:151–163.
Weber KT, Brilla CG. Pathological hypertrophy and cardiac interstitium. Fibrosis and renin-angiotensin-aldosterone system. Circulation . 1991;83:1849–1865.
Whittaker P, Boughner DR, Kloner RA. Analysis of healing after myocardial infarction using polarized light microscopy. Am J Pathol . 1989;134:879–893.
Díez J, Querejeta R, López B, et al. Losartan-dependent regression of myocardial fibrosis is associated with reduction of left ventricular chamber stiffness in hypertensive patients. Circulation . 2002;105:2512–2517.
Kellman P, Wilson JR, Xue H, et al. Extracellular volume fraction mapping in the myocardium, part 1: evaluation of an automated method. J Cardiovasc Magn Reson . 2012;14:63.
Scully PR, Patel KP, Saberwal B, et al. Identifying cardiac amyloid in aortic stenosis: ECV quantification by CT in TAVR patients. JACC Cardiovasc Imaging . 2020;13:2177–2189.
Puntmann VO, Carr-White G, Jabbour A, et al. Native T1 and ECV of noninfarcted myocardium and outcome in patients with coronary artery disease. J Am Coll Cardiol . 2018;71:766–778.
Treibel TA, Fridman Y, Bering P, et al. Extracellular volume associates with outcomes more strongly than native or post-contrast myocardial T1. JACC Cardiovasc Imaging . 2020;13(1 pt 1):44–54.
Croisille P, Revel D, Saeed M. Contrast agents and cardiac MR imaging of myocardial ischemia: from bench to bedside. Eur Radiol . 2006;16:1951–1963.
Judd RM, Atalay MK, Rottman GA, et al. Effects of myocardial water exchange on T1 enhancement during bolus administration of MR contrast agents. Magn Reson Med . 1995;33:215–223.
Nacif MS, Kawel N, Lee JJ, et al. Interstitial myocardial fibrosis assessed as extracellular volume fraction with low-radiation-dose cardiac CT. Radiology . 2012;264:876–883.
Bandula S, White SK, Flett AS, et al. Measurement of myocardial extracellular volume fraction by using equilibrium contrast-enhanced CT: validation against histologic findings. Radiology . 2013;269:396–403.
Jablonowski R, Wilson MW, Do L, et al. Multidetector CT measurement of myocardial extracellular volume in acute patchy and contiguous infarction: validation with microscopic measurement. Radiology . 2015;274:370–378.
Lee HJ, Im DJ, Youn JC, et al. Myocardial extracellular volume fraction with dual-energy equilibrium contrast-enhanced cardiac CT in nonischemic cardiomyopathy: a prospective comparison with cardiac MR imaging. Radiology . 2016;280:49–57.
Abadia AF, Aquino GJ, Schoepf UJ, et al. Automated dual-energy computed tomography-based extracellular volume estimation for myocardial characterization in patients with ischemic and nonischemic cardiomyopathy. J Thorac Imaging . 2022;37:307–314.
Abadia AF, van Assen M, Martin SS, et al. Myocardial extracellular volume fraction to differentiate healthy from cardiomyopathic myocardium using dual-source dual-energy CT. J Cardiovasc Comput Tomogr . 2020;14:162–167.
Oda S, Emoto T, Nakaura T, et al. Myocardial late iodine enhancement and extracellular volume quantification with dual-layer spectral detector dual-energy cardiac CT. Radiol Cardiothorac Imaging . 2019;1:e180003.
Ohta Y, Kitao S, Yunaga H, et al. Myocardial delayed enhancement CT for the evaluation of heart failure: comparison to MRI. Radiology . 2018;288:682–691.
Mergen V, Sartoretti T, Klotz E, et al. Extracellular volume quantification with cardiac late enhancement scanning using dual-source photon-counting detector CT. Invest Radiol . 2022;57:406–411.
Emoto T, Oda S, Kidoh M, et al. Myocardial extracellular volume quantification using cardiac computed tomography: a comparison of the dual-energy iodine method and the standard subtraction method. Acad Radiol . 2021;28:e119–e126.
Kolossváry M, Kellermayer M, Merkely B, et al. Cardiac computed tomography radiomics: a comprehensive review on radiomic techniques. J Thorac Imaging . 2018;33:26–34.
Xu P, Xue Y, Schoepf UJ, et al. Radiomics: the next frontier of cardiac computed tomography. Circ Cardiovasc Imaging . 2021;14:e011747.
Yip SSF, Aerts HJWL. Applications and limitations of radiomics. Phys Med Biol . 2016;61:R150–R166.
Ayx I, Tharmaseelan H, Hertel A, et al. Comparison study of myocardial radiomics feature properties on energy-integrating and photon-counting detector CT. Diagnostics (Basel) . 2022;12:1294.
Ayx I, Tharmaseelan H, Hertel A, et al. Myocardial radiomics texture features associated with increased coronary calcium score—first results of a photon-counting CT. Diagnostics (Basel) . 2022;12:1663.
Zhou Z, Ren L, Rajendran K, et al. Simultaneous dual-contrast imaging using energy-integrating detector multi-energy CT: an in vivo feasibility study. Med Phys . 2022;49:1458–1467.
Tao S, Rajendran K, McCollough CH, et al. Feasibility of multi-contrast imaging on dual-source photon counting detector (PCD) CT: an initial phantom study. Med Phys . 2019;46:4105–4115.
Muenzel D, Daerr H, Proksa R, et al. Simultaneous dual-contrast multi-phase liver imaging using spectral photon-counting computed tomography: a proof-of-concept study. Eur Radiol Exp . 2017;1:25.
Dangelmaier J, Bar-Ness D, Daerr H, et al. Experimental feasibility of spectral photon-counting computed tomography with two contrast agents for the detection of endoleaks following endovascular aortic repair. Eur Radiol . 2018;28:3318–3325.
Symons R, Cork TE, Lakshmanan MN, et al. Dual-contrast agent photon-counting computed tomography of the heart: initial experience. Int J Cardiovasc Imaging . 2017;33:1253–1261.
Symons R, Krauss B, Sahbaee P, et al. Photon-counting CT for simultaneous imaging of multiple contrast agents in the abdomen: an in vivo study. Med Phys . 2017;44:5120–5127.
Cormode DP, Roessl E, Thran A, et al. Atherosclerotic plaque composition: analysis with multicolor CT and targeted gold nanoparticles. Radiology . 2010;256:774–782.
Hedgire S, Baliyan V, Zucker EJ, et al. Perivascular epicardial fat stranding at coronary CT angiography: a marker of acute plaque rupture and spontaneous coronary artery dissection. Radiology . 2018;287:808–815.
Libby P. Mechanisms of acute coronary syndromes and their implications for therapy. N Engl J Med . 2013;368:2004–2013.
Antonopoulos AS, Sanna F, Sabharwal N, et al. Detecting human coronary inflammation by imaging perivascular fat. Sci Transl Med . 2017;9:eaal2658.
Oikonomou EK, Marwan M, Desai MY, et al. Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data. Lancet . 2018;392:929–939.
Pontone G, Rossi A, Guglielmo M, et al. Clinical applications of cardiac computed tomography: a consensus paper of the European Association of Cardiovascular Imaging—part II. Eur Heart J Cardiovasc Imaging . 2022;23:e136–e161.
Mergen V, Ried E, Allmendinger T, et al. Epicardial adipose tissue attenuation and fat attenuation index: phantom study and in vivo measurements with photon-counting detector CT. AJR Am J Roentgenol . 2021;218:822–829.
Vattay B, Boussoussou M, Bartykowszki A, et al. The impact of virtual monoenergetic image energy levels on pericoronary adipose tissue attenuation using dual-source photon-counting detector computed tomography. J Cardiovasc Comput Tomogr . 2022;16(4 suppl):S14.

Auteurs

Akos Varga-Szemes (A)

From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston.

Bálint Szilveszter (B)

Heart and Vascular Center, Semmelweis University, Budapest, Hungary.

Niels R van der Werf (NR)

Philips Healthcare, Best, the Netherlands.

Domenico Mastrodicasa (D)

Stanford University School of Medicine, Department of Radiology, California.

Pál Maurovich-Horvat (P)

Medical Imaging Centre, Semmelweis University, Budapest, Hungary.

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