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Muscogiuri G, Guaricci AI, Soldato N, Cau R, Saba L, Siena P, Tarsitano MG, Giannetta E, Sala D, Sganzerla P, Gatti M, Faletti R, Senatieri A, Chierchia G, Pontone G, Marra P, Rabbat MG, Sironi S. Multimodality Imaging of Sudden Cardiac Death and Acute Complications in Acute Coronary Syndrome. J Clin Med 2022; 11:jcm11195663. [PMID: 36233531 PMCID: PMC9573273 DOI: 10.3390/jcm11195663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 09/07/2022] [Accepted: 09/22/2022] [Indexed: 11/23/2022] Open
Abstract
Sudden cardiac death (SCD) is a potentially fatal event usually caused by a cardiac arrhythmia, which is often the result of coronary artery disease (CAD). Up to 80% of patients suffering from SCD have concomitant CAD. Arrhythmic complications may occur in patients with acute coronary syndrome (ACS) before admission, during revascularization procedures, and in hospital intensive care monitoring. In addition, about 20% of patients who survive cardiac arrest develop a transmural myocardial infarction (MI). Prevention of ACS can be evaluated in selected patients using cardiac computed tomography angiography (CCTA), while diagnosis can be depicted using electrocardiography (ECG), and complications can be evaluated with cardiac magnetic resonance (CMR) and echocardiography. CCTA can evaluate plaque, burden of disease, stenosis, and adverse plaque characteristics, in patients with chest pain. ECG and echocardiography are the first-line tests for ACS and are affordable and useful for diagnosis. CMR can evaluate function and the presence of complications after ACS, such as development of ventricular thrombus and presence of myocardial tissue characterization abnormalities that can be the substrate of ventricular arrhythmias.
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Affiliation(s)
- Giuseppe Muscogiuri
- Department of Radiology, Istituto Auxologico Italiano IRCCS, San Luca Hospital, Piazzale Brescia 20, 20149 Milan, Italy
- School of Medicine, University of Milano-Bicocca, 20126 Milan, Italy
- Correspondence:
| | - Andrea Igoren Guaricci
- University Cardiology Unit, Department of Interdisciplinary Medicine, University of Bari, 70121 Bari, Italy
| | - Nicola Soldato
- University Cardiology Unit, Department of Interdisciplinary Medicine, University of Bari, 70121 Bari, Italy
| | - Riccardo Cau
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari-Polo di Monserrato, 09124 Cagliari, Italy
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari-Polo di Monserrato, 09124 Cagliari, Italy
| | - Paola Siena
- University Cardiology Unit, Department of Interdisciplinary Medicine, University of Bari, 70121 Bari, Italy
| | - Maria Grazia Tarsitano
- Department of Medical and Surgical Science, University Magna Grecia, 88100 Catanzaro, Italy
| | - Elisa Giannetta
- Department of Experimental Medicine, Sapienza University of Rome, Viale Regina Elena, 324, 00161 Rome, Italy
| | - Davide Sala
- Department of Cardiac, Neurological and Metabolic Sciences, San Luca Hospital, Istituto Auxologico Italiano IRCCS, 20149 Milan, Italy
| | - Paolo Sganzerla
- Department of Cardiac, Neurological and Metabolic Sciences, San Luca Hospital, Istituto Auxologico Italiano IRCCS, 20149 Milan, Italy
| | - Marco Gatti
- Radiology Unit, Department of Surgical Sciences, University of Turin, 10124 Turin, Italy
| | - Riccardo Faletti
- Radiology Unit, Department of Surgical Sciences, University of Turin, 10124 Turin, Italy
| | - Alberto Senatieri
- School of Medicine, University of Milano-Bicocca, 20126 Milan, Italy
| | | | | | - Paolo Marra
- School of Medicine, University of Milano-Bicocca, 20126 Milan, Italy
- Department of Radiology, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
| | - Mark G. Rabbat
- Division of Cardiology, Loyola University of Chicago, Chicago, IL 60611, USA
- Edward Hines Jr. VA Hospital, Hines, IL 60141, USA
| | - Sandro Sironi
- School of Medicine, University of Milano-Bicocca, 20126 Milan, Italy
- Department of Radiology, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
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Abstract
Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of myocardial abnormalities in acute and chronic settings. Myocardial edema, microvascular obstruction (MVO), intracardiac thrombus, intramyocardial hemorrhage, and late gadolinium enhancement of the myocardium are easily depicted using standard CMR sequences. In the acute setting, tissue characterization is mainly focused on assessment of ventricular thrombus and MVO, which are associated with poor prognosis. Conversely, in chronic ICM, it is important to depict late gadolinium enhancement and myocardial ischemia using stress perfusion sequences. Overall, with CMR's ability to accurately characterize myocardial tissue in acute and chronic ICM, it represents a valuable diagnostic and prognostic imaging method for treatment planning. In particular, tissue characterization abnormalities in the acute setting can provide information regarding the patients that may develop major adverse cardiac event and show the presence of ventricular thrombus; in the chronic setting, evaluation of viable myocardium can be fundamental for planning myocardial revascularization. In this review, the main findings on tissue characterization are illustrated in acute and chronic settings using qualitative and quantitative tissue characterization.
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Zahergivar A, Kocher M, Waltz J, Kabakus I, Chamberlin J, Akkaya S, Agha AM, Schoepf UJ, Burt JR. The diagnostic value of non-contrast magnetic resonance coronary angiography in the assessment of coronary artery disease: A systematic review and meta-analysis. Heliyon 2021; 7:e06386. [PMID: 33817362 PMCID: PMC8010401 DOI: 10.1016/j.heliyon.2021.e06386] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 12/28/2020] [Accepted: 02/24/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose The current literature reports a wide range of diagnostic accuracy of non-contrast magnetic resonance coronary angiography (NC-MRCA) for the assessment of coronary artery disease (CAD). We aimed to compare the clinical effectiveness of NC-MRCA with that of invasive coronary angiography (ICA) in patients with suspected CAD using a systematic review and meta-analysis. Methods Two investigators independently extracted 36 published manuscripts between 2010 and 2019. Databases including Medline, Web of Knowledge, Google Scholar, Scopus, and Cochrane were searched using pre-established keywords. Analysis of the data followed the PRISMA statement for reporting systematic reviews and meta-analyses and primary analysis followed the Mantel-Hansel methodology. Correctness of classification for detecting coronary artery stenosis ≥50% (CAS) was measured using ICA as the gold standard. Results A total of five studies met inclusion criteria, with a total of 417 patients and 2883 coronary segments. The pooled per patient sensitivity and specificity of NC-MRCA for CAS in suspected patients was 90.3% (95% CI 85.6–95.1%) and 77.9% (95% CI 69.5–86.3%). Pooled per vessel assessment of NC- MRCA revealed a sensitivity of 83.7% (95%CI 79.7–87.8%) and specificity of 90.0% (95%CI 86.7–93.4%). Per-segment assessment of NC-MRCA showed a pooled sensitivity of 81.6% (95% CI 76.8–86.4) and specificity of 97.0% (95% CI 95.5–98.5). Mild to moderate heterogeneity was noted in most diagnostic parameters with larger heterogeneity noted in the per-segment analyses. There was less heterogeneity in sensitivity and NPV than specificity and PPV. Conclusion According to this meta-analysis, non-contrast coronary MRA resulted in adequate screening in patients with suspected CAD with high sensitivity and specificity. This result was true for per-patient, per-vessel, and per-segment assessment.
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Affiliation(s)
- Aryan Zahergivar
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Madison Kocher
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Jeffrey Waltz
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Ismail Kabakus
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Jordan Chamberlin
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Selcuk Akkaya
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Ali M Agha
- Department of Internal Medicine, Division of Cardiology, Baylor College of Medicine, Houston, TX, USA
| | - U Joseph Schoepf
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Jeremy R Burt
- Department of Radiology, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC, USA
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Abstract
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role of AI to support cardiac radiologist in their day-to-day tasks, assisting in segmentation, quantification, and reporting tasks. In addition, AI algorithms can be also utilized to optimize image reconstruction and image quality. Since these algorithms will play an important role in the field of cardiac radiology, it is increasingly important for radiologists to be familiar with the potential applications of AI. The main focus of this article is to provide an overview of cardiac-related AI applications for CT and MRI studies, as well as non-imaging-based applications for reporting and image optimization.
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Abstract
The purpose of this article was to review the pathophysiology, imaging features, and imaging pitfalls of noncongenital ventricular septal defects (VSDs). Noncongenital VSDs can result from ischemic heart disease, trauma, infection, and iatrogenic causes. Ischemic VSDs typically involve the posterior descending or left anterior descending vascular territories and are commonly seen in the apical septum or basal-mid inferoseptum. VSDs can also occur in patients with infectious endocarditis or as a complication following cardiac surgery. Most of these involve the membranous portion of the interventricular septum. Traumatic VSDs are rare and commonly involve the mid to apical anteroseptum. Computed tomography and magnetic resonance imaging can accurately characterize the morphologic features of the defects and associated imaging findings.
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