Myocarditis and the Role of Cardiac Imaging

Matthew Sadler , Gautam Sen , Aamir Shamsi , Antonio Cannata , Daniel Bromage , Daniel Sado

British Journal of Hospital Medicine ›› 2026, Vol. 87 ›› Issue (2) : 50850

PDF (7022KB)
British Journal of Hospital Medicine ›› 2026, Vol. 87 ›› Issue (2) :50850 DOI: 10.31083/BJHM50850
Review
review-article
Myocarditis and the Role of Cardiac Imaging
Author information +
History +
PDF (7022KB)

Abstract

Myocarditis, an inflammatory condition of the myocardium, can present with a spectrum of clinical manifestations, ranging from mild symptoms to cardiogenic shock or death. While endomyocardial biopsy (EMB) remains the gold standard for diagnosis, its invasive nature and limited sensitivity have shifted focus toward non-invasive imaging, particularly cardiovascular magnetic resonance (CMR) imaging. CMR has emerged as a cornerstone in diagnosing myocarditis, offering high sensitivity and specificity through advanced tissue characterisation and functional assessment. Key CMR techniques include T1 and T2 mapping, which allow quantitative evaluation of myocardial injury, oedema, and fibrosis, alongside late gadolinium enhancement (LGE), which identifies predominantly necrosis and scar tissue. The revised 2018 Lake Louise Criteria have further standardised the diagnostic approach with integration of mapping for enhanced accuracy. However, emerging technologies, such as radiomics with machine learning techniques, show promise in improving diagnostic precision, risk stratification, and prognostication. This review explores the pathophysiology, clinical manifestations, and underlying causes of myocarditis, with a particular emphasis on the role of imaging modalities. It highlights the central importance of CMR in the diagnosis and management of myocarditis, while also underscoring the need for ongoing innovation and advancements to enhance patient outcomes.

Graphical abstract

Keywords

cardiac magnetic resonance imaging / myocarditis / inflammation / echocardiography / cardiac computed tomography

Cite this article

Download citation ▾
Matthew Sadler, Gautam Sen, Aamir Shamsi, Antonio Cannata, Daniel Bromage, Daniel Sado. Myocarditis and the Role of Cardiac Imaging. British Journal of Hospital Medicine, 2026, 87(2): 50850 DOI:10.31083/BJHM50850

登录浏览全文

4963

注册一个新账户 忘记密码

1. Introduction

Myocarditis, characterised by inflammation of the myocardium, was first identified as a distinct condition by German physician Dr Joseph Friedrich Sobernheim in 1837 [1]. It can be triggered by both infectious and non-infectious factors and may present in acute, subacute, or chronic forms. Signs and symptoms can range from chest pain, shortness of breath and palpitations, to fevers, peripheral oedema, fatigue and lethargy. In rare cases, it can lead to serious adverse outcomes such as decompensated heart failure, ventricular arrhythmias, cardiogenic shock, or death. Diagnosing myocarditis has traditionally been challenging due to its wide range of symptoms and the absence of specific biomarkers, and in addition, real-world diagnostic accuracy and coding of myocarditis can be poor [2]. While endomyocardial biopsy (EMB) has historically been the gold standard for diagnosis, the advent of cardiac imaging, particularly cardiovascular magnetic resonance (CMR) imaging, has facilitated a shift towards non-invasive diagnostic approaches in most cases [2, 3]. This review will examine the aetiology and clinical presentation of myocarditis, the role of various imaging modalities in its diagnosis with a focus on CMR, its inclusion in clinical guidelines, and potential future research directions.

2. Clinical Presentation and Aetiology

Patients with myocarditis can present acutely, subacutely or in the chronic phase. The acute phase is typified by myocardial oedema and inflammation with associated myocardial injury. Over a period of days to weeks, there is a transition into the subacute phase where the myocardial tissue begins to heal, and the presence of mixed inflammation and interstitial oedema is usually present. Over subsequent weeks, granulation tissue develops at sites of myocardial injury with collagen deposition replacing necrotic cardiomyocytes cleared by macrophage activity. The collagen matures into a heterogeneous scar tissue. Rarely, chronic myocarditis can occur where inflammation persists with coexistent healing.

Acute myocarditis is most frequently seen in the young (30–45 years old) and men (60–80%) [4]. The most common presentation of acute myocarditis is with chest pain (82–95%), and frequently it is associated with dyspnoea (19–49%) and fever (58–65%), with presentations of cardiogenic shock (fulminant myocarditis) being rare (3–9%) [5, 6, 7]. Recent evidence has shown that it is possible to quickly risk-stratify myocarditis patients with basic blood tests, where a neutrophil lymphocyte ratio of >4 is associated with a worse prognosis [8]. However, treatment strategies are largely supportive, with equipoise over immunomodulatory pharmacological therapies [9].

There is a wide range of triggers for myocarditis, ranging from infective to autoimmune, toxin, drug-induced and hypersensitivity causes [10] (Table 1, Ref. [11]). More recently, it has become evident that there is a genetic interplay with myocarditis, and some individuals are at heightened risk [12, 13]. In particular, genetic variants linked to arrhythmogenic cardiomyopathy (ACM) are associated with myocarditis. Described as the “hot phase” of ACM, such acute myocarditis is particularly observed in desmosomal ACM, with a typically more widespread mid-wall involvement on imaging, and in many cases, patients present with recurrent myocarditis episodes [14, 15].

3. Endomyocardial Biopsy and Histopathological Classification

Myocarditis is a non-ischemic inflammatory disease of the myocardium, defined by the presence of inflammation, cellular injury with leucocyte ingress, and myocyte necrosis [3, 16]. The gold standard for diagnosis is EMB, which provides histopathological detail about the pattern and aetiology of inflammation. Subsequently, myocarditis is classified by cell infiltrate, which includes eosinophilic, lymphocytic, lymphohistiocytic and neutrophilic infiltrates.

Eosinophilic myocarditis is identified by one of two separate histopathological patterns—mild patchy interstitial eosinophilic infiltrate or dense eosinophilic infiltrate with cardiomyocyte necrosis. Lymphocytic myocarditis is characterised most commonly by patchy infiltration of T lymphocytes in the myocardial interstitium. Lymphohistiocytic myocarditis can describe either granulomatous myocarditis, characterised by distinct epithelioid granulomas, or giant cell myocarditis, in which multinucleated giant cells are present. The latter is associated with diffuse inflammation and myocardial necrosis, whereas the former demonstrates patchy inflammation and granulomatous fibrosis, with sarcoidosis being the most common underlying aetiology. Lastly, neutrophilic myocarditis is a rare pattern seen in patients with bacterial involvement, either through sepsis/bacterial endocarditis, or very uncommonly, fungal infection.

Endomyocardial biopsy remains the reference standard for the diagnosis of myocarditis. However, in many countries, EMB is rarely performed, with only 3.6% of North American and 0.7% of United Kingdom (UK) suspected myocarditis cases undergoing EMB [17, 18]. EMB carries a risk of complications (1–5%), and in the UK, only 18% of National Health Service (NHS) trusts undertake this procedure [17]. It is often only performed in specific circumstances where the diagnosis remains uncertain, particularly if giant cell myocarditis is suspected, where its role can be pivotal, or when biopsy results would dramatically alter management, most commonly in new-onset heart failure. The decision to perform an EMB demands careful consideration, weighing the patient’s clinical condition against the expertise of the medical team and the balance of potential benefits and risks. In addition, biopsy has a relatively low sensitivity when compared with autopsy findings [19]. As a result of these limitations, the vast majority of clinical myocarditis diagnoses are made through non-invasive testing such as serology and cardiac imaging.

4. Imaging in Myocarditis

Cardiac imaging has become a cornerstone in the evaluation and diagnosis of myocarditis and its associated cardiac complications. Here, we will discuss various imaging modalities used in the assessment of patients with suspected myocarditis.

4.1 Echocardiography

In the majority of individuals, echocardiography is the first cardiac imaging medium utilised in the investigation of patients presenting with chest pain and breathlessness, the most common symptoms of myocarditis. Low cost, widely available and accessible, echocardiography provides a foundation for the exclusion of alternative pathologies (such as valvular or pericardial disease) and can give a rapid and accurate assessment of left and right ventricular function. However, the features of myocarditis on echocardiography are non-specific, and include left ventricular systolic dysfunction (LVSD), which can be global or more commonly regional (of the basal inferolateral wall), ventricular dilation, and pericardial effusion (in the context of perimyocarditis) [4]. Hypo or akinetic walls create substrate for ventricular thrombi, and these may be easily visible on 2D imaging, but if there is uncertainty, contrast should be considered to enhance diagnostic accuracy.

Contemporary methods, such as strain analysis (Fig. 1), which measure the displacement of tissue (pixels) and thus strain over the course of the cardiac cycle, can be helpful in cases of myocarditis owing to the inability of echocardiography to accurately characterise myocardial inflammation. Global longitudinal and radial strain correspond to areas of myocardial inflammation on biopsy [20] and, in both 2D and 3D imaging, have been correlated with regional changes of inflammation and late gadolinium enhancement (LGE) on CMR [21, 22].

4.2 Cardiac Computed Tomography and Coronary Angiography

Cardiac computed tomography (CT) usually does not play a significant role in the diagnosis of patients with potential myocarditis. In part, this is due to the exposure of a typically younger population to ionising radiation and the limited role that CT plays in tissue characterisation. Cardiac CT can be beneficial in excluding alternative causes of patients presenting with chest pain, especially if there is equipoise between myocardial infarction, aortic dissection, and myocarditis, due to its diagnostic accuracy in assessment of coronary artery and aortic disease [23]. More recent advancements in the field of cardiac CT include extracellular volume (ECV) mapping, iodine enhancement, and photon-counting, which correlate with cardiac magnetic resonance imaging (MRI) findings, and have been utilised in tissue characterisation and diagnosis of myocarditis [24, 25].

Patients with potential myocarditis often present with symptoms and findings mimicking acute coronary syndromes (elevated troponin levels, ischemic electrocardiographic [ECG] changes), and subsequently, invasive coronary angiography is commonly undertaken to exclude obstructive coronary lesions [26].

4.3 Cardiovascular Magnetic Resonance Imaging

Considered the non-invasive gold standard for myocardial diagnosis, CMR offers high sensitivity and specificity for the assessment of myocardial function, inflammation and scar, which together provide a comprehensive assessment of myocardial injury [27].

MRI-specific features associated with myocarditis include:

4.3.1 Myocardial Hyperaemia and Early Gadolinium Enhancement

Hyperaemia is identified through early gadolinium enhancement (EGE) following intravenous contrast, reflecting increased vascular permeability and cellular necrosis typical of inflamed myocardium. The EGE ratio, where a value of 4 against reference tissue (typically skeletal muscle) indicates pathology, suggests increased relative myocardial signal intensity by over 45%, a strong indicator of active inflammation. Although EGE initially featured in the 2009 Lake Louise Criteria (LLC) [28], its lower sensitivity and specificity, and variability in image quality, have limited its standalone diagnostic utility, leading to its removal in the 2018 revised LLC. However, EGE can still provide complementary information on vascular changes in myocarditis [29].

4.3.2 Inflammation and T1 and T2 Parametric Mapping

The advantages of parametric mapping lie in the ability to provide spatial visualisation and quantification of myocardial tissue changes seen in myocarditis. This allows for better assessment of diffuse disease processes and the study of the evolution of the disease process. T1 mapping measures the longitudinal relaxation time (T1), which is frequently elevated in myocarditis due to oedema, necrosis, or interstitial expansion associated with inflammation (Fig. 2A,B). Native, pre-contrast, T1 mapping is particularly useful for detecting diffuse myocardial oedema or fibrosis that may not be apparent with conventional imaging. It is therefore sensitive, but lacks specificity for the assessment of oedema. T2 mapping quantifies transverse relaxation time (T2), and elevated values serve as a more specific marker for myocardial oedema (Fig. 2C,D). Extracellular volume (ECV) is derived from pre- and post-contrast T1 mapping values and reflects extracellular matrix expansion and is elevated in areas of oedema or scar [30]. Utilising the combination of these three values allows for a comprehensive assessment of areas of myocardial scar and oedema, with the presence of elevated ECV, T1 and T2 being associated with adverse events in myocarditis, including arrhythmia and cardiac mortality [31].

4.3.3 Necrosis and Fibrosis: Late Gadolinium Enhancement

Late gadolinium enhancement (LGE) uses T1-weighted inversion-recovery sequences following gadolinium contrast administration. It identifies focal areas of predominantly myocardial necrosis and fibrosis. In myocarditis, LGE typically appears in subepicardial or mid-wall patterns, often in the inferior/inferolateral segments of the left ventricle (Fig. 3). While signal intensity often diminishes in chronic stages, persistent LGE related to the formation of scar, making it the most reliable indicator of myocarditis in approximately 90% of cases [32], and a valuable marker for long-term prognosis, where presence of LGE in viral myocarditis, is associated with 8.4-fold increase in all-cause mortality, after adjusting for left ventricular function, New York Heart Association (NYHA) functional class and left ventricle end diastolic volumes [33].

4.3.4 Classical Imaging Findings in CMR for Myocarditis

The CMR appearance of myocarditis depends on the stage of the disease. In the acute phase, CMR typically shows marked myocardial oedema (elevated T2, T1, and ECV) reflecting active inflammation, and early or patchy LGE. Diagnostic sensitivity of CMR is greatest within the first 2–4 weeks after symptom onset, as oedema is most pronounced during this period [34].

In the subacute to chronic phase, myocardial inflammation and oedema generally subside, with normalisation of T1/T2 values. LGE often persists and becomes more organised, indicating progressive fibrosis and early scar formation.

In myocarditis, the LGE pattern most commonly seen is a subepicardial or mid-wall pattern along the basal to mid inferolateral and inferior segments [35]. A mid-wall LGE pattern in the interventricular septum, while less common, has prognostic implications, often associated with poorer outcomes, and it is important to consider a genetic aetiology in these cases, such as ACM [36]. In cases of fulminant myocarditis, imaging may show diffuse myocardial oedema, extensive LGE, and LVSD, where a left ventricular ejection fraction (LVEF) of <40% is associated with a 4-fold increased mortality [31]. The coexistence of pericardial enhancement points to concurrent pericarditis, particularly in the pericardium adjacent to the affected myocardial regions. Although LGE on CMR cannot, by itself, establish the aetiology of myocarditis and presentations are often heterogeneous, certain LGE patterns (Table 2; Ref. [37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47] ) are more typical of specific causes [48].

4.3.5 CMR Criteria for Diagnosing Myocarditis

The original LLC, introduced in 2009, provided foundational diagnostic criteria for acute myocarditis on CMR [28], requiring at least two of three findings: heightened T2-weighted myocardial signal, early gadolinium enhancement (EGE), and LGE in a non-ischemic distribution. With the advent and evolution of parametric mapping, the 2018 revised LLC incorporated T1 and T2 imaging, which enhances diagnostic sensitivity (73% vs. 88%, p = 0.03) while maintaining high specificity at 96% [49, 50]. The updated LLC requires that each of the two categories be satisfied, namely:

- The presence of a T1-based indicator of myocardial injury, such as non-ischemic LGE, increased native T1, or extracellular volume (ECV).

- A T2-based indicator of myocardial oedema such as regional elevated T2-signal intensity/increased T2 relaxation time or increased global T2 ratio (>2.0).

The combination of the above provides robust evidence of myocardial inflammation in patients with high clinical suspicion of myocarditis. Supportive criteria include evidence of pericardial inflammation or LVSD. However, one of the main drawbacks of parametric techniques is the requirement for local reference ranges, as values are scanner-specific and require local calibration, and thus should be interpreted accordingly [30].

4.3.6 Myocarditis—Protocol for Assessment

There are a variety of different protocols proposed to assess myocarditis. However, the Society for Cardiovascular Magnetic Resonance (SCMR) has published standardised protocols to ensure consistency in CMR studies [51].

The 2020 update emphasises sequences such as cine imaging for functional assessment, T2-weighted imaging for oedema detection, T1 mapping for fibrosis evaluation, and LGE for identifying necrosis or scar tissue, with the aim of streamlining CMR procedures and enhancing diagnostic accuracy. Myocarditis protocol recommendations are summarised below (Table 3).

4.3.7 Follow-Up Imaging and Prognostic Implications in Myocarditis Using Cardiac MRI

Longitudinal assessment of patients with myocarditis is important to monitor disease activity, guide return to exercise, especially in performance athletes, and assess cardiac function, which informs ongoing treatment and prognosis [52, 53]. Repeat imaging is typically performed 6 months after the index presentation, and in the majority of patients, left ventricular (LV) systolic function is either normal at baseline or resolves at follow-up [54]. Persistent LV systolic dysfunction, especially in the initial setting of fulminant myocarditis, relays a worse prognosis [55]. A strength of utilising follow-up CMR is the ability to characterise the myocardium, in particular oedema and fibrosis. There is uncertainty regarding the prognostic presence of persistent oedema on follow-up CMR, with reports of elevated values associated with improved prognosis, possibly relating to the potential for resolution and recovery [56], and others linking normalisation of T2 values with clinical recovery, suggesting a healed stage of the disease [57]. However, consensus lies with the persistent presence and extent of isolated LGE, suggesting scar formation, which is associated with worse outcomes such as ventricular arrhythmia, and necessitates longer-term follow-up [31, 34, 56].

4.3.8 Diagnostic Guidelines

Recognised by the 2021 European Society of Cardiology (ESC) heart failure guidelines, CMR is a first-line (or Class I) investigation for the investigation of suspected myocarditis, with a recommendation for follow-up imaging in those who have LVSD, arrhythmias or ECG abnormalities [58]. In addition, the American Heart Association (AHA) and American College of Cardiology (ACC) guidelines strengthen these recommendations, giving CMR a class 1B recommendation for evaluation of chest pain in suspected myocarditis [23]. The AHA/ACC guidelines, specifically, underscore MRI’s utility with LGE for differentiating myocarditis from other aetiologies of myocardial injury where coronary arteries are unobstructed (i.e., myocardial infarction with non-obstructive coronary arteries [MINOCA]) and when there is diagnostic uncertainty.

5. Novel Techniques and Specific Populations

5.1 Strain Analysis

Beyond traditional measures, strain analysis quantifies myocardial deformation by tracking the motion of tissue (pixels) throughout the cardiac cycle, offering sensitive detection of subtle functional changes, and can be applied across imaging modalities, including echocardiography and CMR. CMR offers new modalities to evaluate myocardial strain through feature tracking techniques, and is considered superior to strain via echocardiography, especially for regional abnormalities [59, 60].

CMR-derived myocardial strain analysis detects deformation, torsion, and synchrony impairments, which may be present even in myocarditis patients with normal ejection fraction [61]. Recent data underscore the enhanced diagnostic sensitivity and prognostic value of strain parameters, particularly global longitudinal strain (GLS), in myocarditis, with predictive utility extending beyond traditional measures such as LVEF and LGE [62]. GLS has been identified as an independent predictor of adverse cardiac outcomes, including mortality, ventricular arrhythmia, and heart failure hospitalisation, with a hazard ratio of 1.21 (95% confidence interval [CI]: 1.08–1.36, p = 0.001) [63]. Furthermore, incorporating GLS into a multivariable predictive model significantly improved diagnostic accuracy [63].

5.2 Positron Emission Tomography (PET)

Positron emission tomography (PET) is not routinely employed for diagnosing acute myocarditis or chronic inflammatory cardiomyopathy. However, it can be a useful non-invasive diagnostic tool for stable patients who are unable to undergo CMR imaging or for those with suspected systemic autoimmune diseases affecting multiple organs.

F-fluoro-deoxy-glucose (FDG) cardiac PET/CT provides an assessment of myocardial inflammation through the use of increased FDG uptake. It requires patients to undergo dietary preparation through a low-carbohydrate/high-fat diet and fasting prior to the scan, to allow suppression of physiological FDG. Despite these precautions, 10–15% of cardiac PET scans may fail diagnostically due to inadequate suppression of physiological glucose uptake. FDG PET/CT has been found to be able to localise inflammation within the myocardium in case-based publications [64, 65], but lacks prospective randomised trials in its assessment of myocarditis diagnosis.

PET has gained particular utility in diagnosing and managing cardiac sarcoidosis (CS). The technique leverages the avid glucose uptake by active inflammatory cells within sarcoid granulomas. Cardiac PET is often combined with whole-body imaging to assess extracardiac involvement. A meta-analysis of 17 studies including 891 patients with suspected CS reported a sensitivity of 84% and a specificity of 83% for PET imaging [66]. Additionally, PET serves as a valuable modality for monitoring disease progression and evaluating response to immunosuppressive therapy. The usefulness of PET/CT is likely to grow, especially in multi-system conditions where it can give information for more than just the heart [67].

5.3 Radiomics

A relatively new field in medical science, radiomics uses image analysis to extract large volumes of quantitative features (texture, shape, and intensity) from medical imaging [68]. Such data can then be leveraged in combination with machine learning (ML) and artificial intelligence (AI) techniques to provide enhanced abilities in disease classification, prognosis, treatment response and early detection [69]. Cardiac MRI is an attractive avenue for radiomics due to the large volume of spatial data, including functional data and tissue characterisation, where a typical workflow incorporates the extraction of hundreds to thousands of quantitative features, followed by pattern analysis with ML techniques. One of the challenges arising in CMR assessment of myocarditis is differentiating it from focal myocardial infarction. Radiomic techniques such as texture analysis (TA), which involves assessing spatial variations in pixel intensity, have been utilised in T1 and T2 mapping for myocarditis, with TA demonstrating a sensitivity and specificity for the diagnosis of acute, infarct-like myocarditis that was significantly greater than the Lake Louise Criteria (area under the curve [AUC]: 0.88 vs. 0.62) [70]. In addition, radiomic and ML techniques have been used to predict a composite of death, heart failure hospitalisation, ventricular arrhythmia and recurrent myocarditis in patients with suspected myocarditis (AUC: 0.8) based on LGE features [71], and to identify varying patterns of CMR inflammation in ethnically diverse populations [72].

Incorporation of machine learning techniques into MRI assessment of myocarditis is in its relative infancy, and suffers from limited data sets, single-centre data, and heterogeneous methodologies [73]. However, these hurdles are likely to be overcome with the rapid development of AI platforms and technological advances, with the ability to share large volumes of data [74]. Further research is required to maximise the potential of AI in transforming diagnostic and prognostic approaches in myocarditis.

6. Conclusion

A multi-modality cardiac imaging approach is key in the workup of potential myocarditis. All patients should undergo echocardiography in the first instance, and where available, CMR is the next investigation of choice. It is important in establishing aetiology, excluding alternative diagnoses and aiding prognostication and risk stratification, along with guiding therapeutic decision making. There have been recent advancements in risk stratification in myocarditis; however, there remains considerable uncertainty regarding optimal treatment strategies and the timing of interventions, particularly with respect to immunomodulatory therapies. Improvements in current echocardiographic and CMR techniques, along with newer approaches like radiomics and strain, are poised to expand the diagnostic and prognostic capabilities, but further research is needed to refine risk assessment, clarify therapeutic approaches, and ultimately improve patient outcomes in this heterogeneous condition.

Key Points

Myocarditis often affects young patients, presents heterogeneously, and can range from mild symptoms to life-threatening complications.

Diagnosis remains challenging, and although biopsy remains the diagnostic gold standard, its low sensitivity, procedural risks, and limited availability have driven a shift toward non-invasive imaging, particularly cardiovascular magnetic resonance (CMR).

CMR is the preferred imaging modality for the assessment of myocarditis, incorporated into international guidelines, it allows for the dynamic assessment of cardiac function and detailed tissue characterisation.

Novel applications such as CMR-based strain, radiomics, and machine learning applied to MRI data show early promise in improving diagnostic precision and predicting outcomes.

Availability of Data and Materials

Not applicable.

References

[1]

Schölmerich P. Myocarditis — Cardiomyopathy Historic Survey and Definition. In Just H, Schuster HP (eds.) Myocarditis Cardiomyopathy (pp. 1–5). Springer: Berlin, Heidelberg. 1983. https://doi.org/10.1007/978-3-642-68608-5_1.

[2]

Roy R, Cannata A, Al-Agil M, Ferone E, Jordan A, To-Dang B, et al. Diagnostic accuracy, clinical characteristics, and prognostic differences of patients with acute myocarditis according to inclusion criteria. European Heart Journal. Quality of Care & Clinical Outcomes. 2024; 10: 366–378. https://doi.org/10.1093/ehjqcco/qcad061.

[3]

Aretz HT, Billingham ME, Edwards WD, Factor SM, Fallon JT, Fenoglio JJ, Jr, et al. Myocarditis. A histopathologic definition and classification. The American Journal of Cardiovascular Pathology. 1987; 1: 3–14.

[4]

Ammirati E, Frigerio M, Adler ED, Basso C, Birnie DH, Brambatti M, et al. Management of Acute Myocarditis and Chronic Inflammatory Cardiomyopathy: An Expert Consensus Document. Circulation. Heart Failure. 2020; 13: e007405. https://doi.org/10.1161/CIRCHEARTFAILURE.120.007405.

[5]

White JA, Hansen R, Abdelhaleem A, Mikami Y, Peng M, Rivest S, et al. Natural History of Myocardial Injury and Chamber Remodeling in Acute Myocarditis. Circulation. Cardiovascular Imaging. 2019; 12: e008614. https://doi.org/10.1161/CIRCIMAGING.118.008614.

[6]

Baritussio A, Schiavo A, Basso C, Giordani AS, Cheng CY, Pontara E, et al. Predictors of relapse, death or heart transplantation in myocarditis before the introduction of immunosuppression: negative prognostic impact of female gender, fulminant onset, lower ejection fraction and serum autoantibodies. European Journal of Heart Failure. 2022; 24: 1033–1044. https://doi.org/10.1002/ejhf.2496.

[7]

Cannata A, Bhatti P, Roy R, Al-Agil M, Daniel A, Ferone E, et al. Prognostic relevance of demographic factors in cardiac magnetic resonance-proven acute myocarditis: A cohort study. Frontiers in Cardiovascular Medicine. 2022; 9: 1037837. https://doi.org/10.3389/fcvm.2022.1037837.

[8]

Cannata A, Segev A, Madaudo C, Bobbio E, Baggio C, Schütze J, et al. Elevated Neutrophil-to-Lymphocyte Ratio Predicts Prognosis in Acute Myocarditis. JACC. Heart Failure. 2025; 13: 770–780. https://doi.org/10.1016/j.jchf.2024.11.003.

[9]

Ferone E, Segev A, Tempo E, Gentile P, Elsanhoury A, Baggio C, et al. Current Treatment and Immunomodulation Strategies in Acute Myocarditis. Journal of Cardiovascular Pharmacology. 2024; 83: 364–376. https://doi.org/10.1097/FJC.0000000000001542.

[10]

Brociek E, Tymińska A, Giordani AS, Caforio ALP, Wojnicz R, Grabowski M, et al. Myocarditis: Etiology, Pathogenesis, and Their Implications in Clinical Practice. Biology. 2023; 12: 874. https://doi.org/10.3390/biology12060874.

[11]

Bozkurt B, Kamat I, Hotez PJ. Myocarditis With COVID-19 mRNA Vaccines. Circulation. 2021; 144: 471–484. https://doi.org/10.1161/CIRCULATIONAHA.121.056135.

[12]

Cannata’ A, Artico J, Gentile P, Merlo M, Sinagra G. Myocarditis evolving in cardiomyopathy: when genetics and offending causes work together. European Heart Journal Supplements. 2019; 21: B90–B95. https://doi.org/10.1093/eurheartj/suz033.

[13]

Artico J, Merlo M, Delcaro G, Cannatà A, Gentile P, De Angelis G, et al. Lymphocytic Myocarditis: A Genetically Predisposed Disease? Journal of the American College of Cardiology. 2020; 75: 3098–3100. https://doi.org/10.1016/j.jacc.2020.04.048.

[14]

Lota AS, Hazebroek MR, Theotokis P, Wassall R, Salmi S, Halliday BP, et al. Genetic Architecture of Acute Myocarditis and the Overlap With Inherited Cardiomyopathy. Circulation. 2022; 146: 1123–1134. https://doi.org/10.1161/CIRCULATIONAHA.121.058457.

[15]

Ollitrault P, Al Khoury M, Troadec Y, Calcagno Y, Champ-Rigot L, Ferchaud V, et al. Recurrent acute myocarditis: An under-recognized clinical entity associated with the later diagnosis of a genetic arrhythmogenic cardiomyopathy. Frontiers in Cardiovascular Medicine. 2022; 9: 998883. https://doi.org/10.3389/fcvm.2022.998883.

[16]

Khawaja A, Bromage DI. The innate immune response in myocarditis. The International Journal of Biochemistry & Cell Biology. 2021; 134: 105973. https://doi.org/10.1016/j.biocel.2021.105973.

[17]

Asher A. A review of endomyocardial biopsy and current practice in England: out of date or underutilised? British Journal of Cardiology. 2017; 24: 108–112. https://doi.org/10.5837/bjc.2017.019.

[18]

Elbadawi A, Elgendy IY, Ha LD, Mentias A, Ogunbayo GO, Tahir MW, et al. National Trends and Outcomes of Endomyocardial Biopsy for Patients With Myocarditis: From the National Inpatient Sample Database. Journal of Cardiac Failure. 2018; 24: 337–341. https://doi.org/10.1016/j.cardfail.2018.03.013.

[19]

Chow LH, Radio SJ, Sears TD, McManus BM. Insensitivity of right ventricular endomyocardial biopsy in the diagnosis of myocarditis. Journal of the American College of Cardiology. 1989; 14: 915–920. https://doi.org/10.1016/0735-1097(89)90465-8.

[20]

Escher F, Kasner M, Kühl U, Heymer J, Wilkenshoff U, Tschöpe C, et al. New echocardiographic findings correlate with intramyocardial inflammation in endomyocardial biopsies of patients with acute myocarditis and inflammatory cardiomyopathy. Mediators of Inflammation. 2013; 2013: 875420. https://doi.org/10.1155/2013/875420.

[21]

Meindl C, Paulus M, Poschenrieder F, Zeman F, Maier LS, Debl K. Patients with acute myocarditis and preserved systolic left ventricular function: comparison of global and regional longitudinal strain imaging by echocardiography with quantification of late gadolinium enhancement by CMR. Clinical Research in Cardiology. 2021; 110: 1792–1800. https://doi.org/10.1007/s00392-021-01885-0.

[22]

Goody PR, Zimmer S, Öztürk C, Zimmer A, Kreuz J, Becher MU, et al. 3D-speckle-tracking echocardiography correlates with cardiovascular magnetic resonance imaging diagnosis of acute myocarditis - An observational study. International Journal of Cardiology. Heart & Vasculature. 2022; 41: 101081. https://doi.org/10.1016/j.ijcha.2022.101081.

[23]

Gulati M, Levy PD, Mukherjee D, Amsterdam E, Bhatt DL, Birtcher KK, et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021; 144: e368–e454. https://doi.org/10.1161/CIR.0000000000001029.

[24]

Bouleti C, Baudry G, Iung B, Arangalage D, Abtan J, Ducrocq G, et al. Usefulness of Late Iodine Enhancement on Spectral CT in Acute Myocarditis. JACC. Cardiovascular Imaging. 2017; 10: 826–827. https://doi.org/10.1016/j.jcmg.2016.09.013.

[25]

Gkizas C, Longere B, Sliwicka O, Musso AR, Lemesle G, Croisille C, et al. Photon-counting CT-derived extracellular volume in acute myocarditis: Comparison with cardiac MRI. Diagnostic and Interventional Imaging. 2025; 106: 255–263. https://doi.org/10.1016/j.diii.2025.03.001.

[26]

Martens P, Cooper LT, Tang WHW. Diagnostic Approach for Suspected Acute Myocarditis: Considerations for Standardization and Broadening Clinical Spectrum. Journal of the American Heart Association. 2023; 12: e031454. https://doi.org/10.1161/JAHA.123.031454.

[27]

Nagel E, Kwong RY, Chandrashekhar YS. CMR in Nonischemic Myocardial Inflammation: Solving the Problem of Diagnosing Myocarditis or Still Diagnostic Ambiguity? JACC. Cardiovascular Imaging. 2020; 13: 163–166. https://doi.org/10.1016/j.jcmg.2019.10.023.

[28]

Friedrich MG, Sechtem U, Schulz-Menger J, Holmvang G, Alakija P, Cooper LT, et al. Cardiovascular magnetic resonance in myocarditis: A JACC White Paper. Journal of the American College of Cardiology. 2009; 53: 1475–1487. https://doi.org/10.1016/j.jacc.2009.02.007.

[29]

Esposito A, Francone M, Faletti R, Centonze M, Cademartiri F, Carbone I, et al. Lights and shadows of cardiac magnetic resonance imaging in acute myocarditis. Insights into Imaging. 2016; 7: 99–110. https://doi.org/10.1007/s13244-015-0444-7.

[30]

Messroghli DR, Moon JC, Ferreira VM, Grosse-Wortmann L, He T, Kellman P, et al. Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI). Journal of Cardiovascular Magnetic Resonance. 2017; 19: 75. https://doi.org/10.1186/s12968-017-0389-8.

[31]

Gräni C, Eichhorn C, Bière L, Murthy VL, Agarwal V, Kaneko K, et al. Prognostic Value of Cardiac Magnetic Resonance Tissue Characterization in Risk Stratifying Patients With Suspected Myocarditis. Journal of the American College of Cardiology. 2017; 70: 1964–1976. https://doi.org/10.1016/j.jacc.2017.08.050.

[32]

Ferreira VM, Piechnik SK, Dall’Armellina E, Karamitsos TD, Francis JM, Ntusi N, et al. T(1) mapping for the diagnosis of acute myocarditis using CMR: comparison to T2-weighted and late gadolinium enhanced imaging. JACC. Cardiovascular Imaging. 2013; 6: 1048–1058. https://doi.org/10.1016/j.jcmg.2013.03.008.

[33]

Grün S, Schumm J, Greulich S, Wagner A, Schneider S, Bruder O, et al. Long-term follow-up of biopsy-proven viral myocarditis: predictors of mortality and incomplete recovery. Journal of the American College of Cardiology. 2012; 59: 1604–1615. https://doi.org/10.1016/j.jacc.2012.01.007.

[34]

Luetkens JA, Homsi R, Dabir D, Kuetting DL, Marx C, Doerner J, et al. Comprehensive Cardiac Magnetic Resonance for Short-Term Follow-Up in Acute Myocarditis. Journal of the American Heart Association. 2016; 5: e003603. https://doi.org/10.1161/JAHA.116.003603.

[35]

Sanchez Tijmes F, Thavendiranathan P, Udell JA, Seidman MA, Hanneman K. Cardiac MRI Assessment of Nonischemic Myocardial Inflammation: State of the Art Review and Update on Myocarditis Associated with COVID-19 Vaccination. Radiology. Cardiothoracic Imaging. 2021; 3: e210252. https://doi.org/10.1148/ryct.210252.

[36]

Aquaro GD, Perfetti M, Camastra G, Monti L, Dellegrottaglie S, Moro C, et al. Cardiac MR With Late Gadolinium Enhancement in Acute Myocarditis With Preserved Systolic Function: ITAMY Study. Journal of the American College of Cardiology. 2017; 70: 1977–1987. https://doi.org/10.1016/j.jacc.2017.08.044.

[37]

Sozzi FB, Gherbesi E, Faggiano A, Gnan E, Maruccio A, Schiavone M, et al. Viral Myocarditis: Classification, Diagnosis, and Clinical Implications. Frontiers in Cardiovascular Medicine. 2022; 9: 908663. https://doi.org/10.3389/fcvm.2022.908663.

[38]

Arvind B, Ojha V, Arava SK, Seth S, Ramakrishnan S. Diphtheritic myocarditis: An unusual and reversible cause of heart failure. Annals of Pediatric Cardiology. 2022; 15: 311–313. https://doi.org/10.4103/apc.apc_144_21.

[39]

Luo S, Dou WQ, Schoepf UJ, Varga-Szemes A, Pridgen WT, Zhang LJ. Cardiovascular magnetic resonance imaging in myocardial involvement of systemic lupus erythematosus. Trends in Cardiovascular Medicine. 2023; 33: 346–354. https://doi.org/10.1016/j.tcm.2022.02.002.

[40]

Giollo A, Dumitru RB, Swoboda PP, Plein S, Greenwood JP, Buch MH, et al. Cardiac magnetic resonance imaging for the detection of myocardial involvement in granulomatosis with polyangiitis. The International Journal of Cardiovascular Imaging. 2021; 37: 1053–1062. https://doi.org/10.1007/s10554-020-02066-2.

[41]

Omidi A, Weiss E, Trankle CR, Rosu-Bubulac M, Wilson JS. Quantitative assessment of radiotherapy-induced myocardial damage using MRI: a systematic review. Cardio-Oncology. 2023; 9: 24. https://doi.org/10.1186/s40959-023-00175-0.

[42]

Lee-Felker SA, Thomas M, Felker ER, Traina M, Salih M, Hernandez S, et al. Value of cardiac MRI for evaluation of chronic Chagas disease cardiomyopathy. Clinical Radiology. 2016; 71: 618.e1–618.e7. https://doi.org/10.1016/j.crad.2016.02.015.

[43]

Shibazaki S, Eguchi S, Endo T, Wakabayashi T, Araki M, Gu Y, et al. Eosinophilic Myocarditis due to Toxocariasis: Not a Rare Cause. Case Reports in Cardiology. 2016; 2016: 2586292. https://doi.org/10.1155/2016/2586292.

[44]

Yang S, Chen X, Li J, Sun Y, Song J, Wang H, et al. Late gadolinium enhancement characteristics in giant cell myocarditis. ESC Heart Failure. 2021; 8: 2320–2327. https://doi.org/10.1002/ehf2.13276.

[45]

Athwal PSS, Chhikara S, Ismail MF, Ismail K, Ogugua FM, Kazmirczak F, et al. Cardiovascular Magnetic Resonance Imaging Phenotypes and Long-term Outcomes in Patients With Suspected Cardiac Sarcoidosis. JAMA Cardiology. 2022; 7: 1057–1066. https://doi.org/10.1001/jamacardio.2022.2981.

[46]

Fan J, Wahab L, Nguyen V. Characteristic Cardiac Magnetic Resonance (CMR) Imaging Findings of Cocaine-Induced Myocardial Injury. Cureus. 2024; 16: e67072. https://doi.org/10.7759/cureus.67072.

[47]

de Frutos F, Ochoa JP, Fernández AI, Gallego-Delgado M, Navarro-Peñalver M, Casas G, et al. Late gadolinium enhancement distribution patterns in non-ischaemic dilated cardiomyopathy: genotype-phenotype correlation. European Heart Journal. Cardiovascular Imaging. 2023; 25: 75–85. https://doi.org/10.1093/ehjci/jead184.

[48]

Meier C, Eisenblätter M, Gielen S. Myocardial Late Gadolinium Enhancement (LGE) in Cardiac Magnetic Resonance Imaging (CMR)-An Important Risk Marker for Cardiac Disease. Journal of Cardiovascular Development and Disease. 2024; 11: 40. https://doi.org/10.3390/jcdd11020040.

[49]

Ferreira VM, Schulz-Menger J, Holmvang G, Kramer CM, Carbone I, Sechtem U, et al. Cardiovascular Magnetic Resonance in Nonischemic Myocardial Inflammation: Expert Recommendations. Journal of the American College of Cardiology. 2018; 72: 3158–3176. https://doi.org/10.1016/j.jacc.2018.09.072.

[50]

Luetkens JA, Faron A, Isaak A, Dabir D, Kuetting D, Feisst A, et al. Comparison of Original and 2018 Lake Louise Criteria for Diagnosis of Acute Myocarditis: Results of a Validation Cohort. Radiology. Cardiothoracic Imaging. 2019; 1: e190010. https://doi.org/10.1148/ryct.2019190010.

[51]

Kramer CM, Barkhausen J, Bucciarelli-Ducci C, Flamm SD, Kim RJ, Nagel E. Standardized cardiovascular magnetic resonance imaging (CMR) protocols: 2020 update. Journal of Cardiovascular Magnetic Resonance. 2020; 22: 17. https://doi.org/10.1186/s12968-020-00607-1.

[52]

Pelliccia A, Sharma S, Gati S, Bäck M, Börjesson M, Caselli S, et al. 2020 ESC Guidelines on sports cardiology and exercise in patients with cardiovascular disease. European Heart Journal. 2021; 42: 17–96. https://doi.org/10.1093/eurheartj/ehaa605.

[53]

Bohbot Y, Garot J, Hovasse T, Unterseeh T, Di Lena C, Boukefoussa W, et al. Clinical and Cardiovascular Magnetic Resonance Predictors of Early and Long-Term Clinical Outcome in Acute Myocarditis. Frontiers in Cardiovascular Medicine. 2022; 9: 886607. https://doi.org/10.3389/fcvm.2022.886607.

[54]

Ammirati E, Cipriani M, Lilliu M, Sormani P, Varrenti M, Raineri C, et al. Survival and Left Ventricular Function Changes in Fulminant Versus Nonfulminant Acute Myocarditis. Circulation. 2017; 136: 529–545. https://doi.org/10.1161/CIRCULATIONAHA.117.026386.

[55]

Ammirati E, Cipriani M, Moro C, Raineri C, Pini D, Sormani P, et al. Clinical Presentation and Outcome in a Contemporary Cohort of Patients With Acute Myocarditis: Multicenter Lombardy Registry. Circulation. 2018; 138: 1088–1099. https://doi.org/10.1161/CIRCULATIONAHA.118.035319.

[56]

Aquaro GD, Ghebru Habtemicael Y, Camastra G, Monti L, Dellegrottaglie S, Moro C, et al. Prognostic Value of Repeating Cardiac Magnetic Resonance in Patients With Acute Myocarditis. Journal of the American College of Cardiology. 2019; 74: 2439–2448. https://doi.org/10.1016/j.jacc.2019.08.1061.

[57]

Spieker M, Haberkorn S, Gastl M, Behm P, Katsianos S, Horn P, et al. Abnormal T2 mapping cardiovascular magnetic resonance correlates with adverse clinical outcome in patients with suspected acute myocarditis. Journal of Cardiovascular Magnetic Resonance. 2017; 19: 38. https://doi.org/10.1186/s12968-017-0350-x.

[58]

McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. European Heart Journal. 2021; 42: 3599–3726. https://doi.org/10.1093/eurheartj/ehab368.

[59]

Amzulescu MS, Langet H, Saloux E, Manrique A, Boileau L, Slimani A, et al. Head-to-Head Comparison of Global and Regional Two-Dimensional Speckle Tracking Strain Versus Cardiac Magnetic Resonance Tagging in a Multicenter Validation Study. Circulation. Cardiovascular Imaging. 2017; 10: e006530. https://doi.org/10.1161/CIRCIMAGING.117.006530.

[60]

Smiseth OA, Rider O, Cvijic M, Valkovič L, Remme EW, Voigt JU. Myocardial Strain Imaging: Theory, Current Practice, and the Future. JACC. Cardiovascular Imaging. 2025; 18: 340–381. https://doi.org/10.1016/j.jcmg.2024.07.011.

[61]

Eichhorn C, Greulich S, Bucciarelli-Ducci C, Sznitman R, Kwong RY, Gräni C. Multiparametric Cardiovascular Magnetic Resonance Approach in Diagnosing, Monitoring, and Prognostication of Myocarditis. JACC. Cardiovascular Imaging. 2022; 15: 1325–1338. https://doi.org/10.1016/j.jcmg.2021.11.017.

[62]

Porcari A, Merlo M, Baggio C, Gagno G, Cittar M, Barbati G, et al. Global longitudinal strain by CMR improves prognostic stratification in acute myocarditis presenting with normal LVEF. European Journal of Clinical Investigation. 2022; 52: e13815. https://doi.org/10.1111/eci.13815.

[63]

Fischer K, Obrist SJ, Erne SA, Stark AW, Marggraf M, Kaneko K, et al. Feature Tracking Myocardial Strain Incrementally Improves Prognostication in Myocarditis Beyond Traditional CMR Imaging Features. JACC. Cardiovascular Imaging. 2020; 13: 1891–1901. https://doi.org/10.1016/j.jcmg.2020.04.025.

[64]

Ozawa K, Funabashi N, Daimon M, Takaoka H, Takano H, Uehara M, et al. Determination of optimum periods between onset of suspected acute myocarditis and 18F-fluorodeoxyglucose positron emission tomography in the diagnosis of inflammatory left ventricular myocardium. International Journal of Cardiology. 2013; 169: 196–200. https://doi.org/10.1016/j.ijcard.2013.08.098.

[65]

Moriwaki K, Dohi K, Omori T, Tanimura M, Sugiura E, Nakamori S, et al. A Survival Case of Fulminant Right-Side Dominant Eosinophilic Myocarditis. International Heart Journal. 2017; 58: 459–462. https://doi.org/10.1536/ihj.16-338.

[66]

Miratashi Yazdi SN, Riahi F, Azizollahi S, Tooyserkani SH, Fesharaki S, Alaei M, et al. Exploring the latest advances in 18F-FDG PET/CT and cardiac magnetic resonance for imaging for cardiac sarcoidosis diagnosis. American Journal of Nuclear Medicine and Molecular Imaging. 2024; 14: 149–156. https://doi.org/10.62347/GIKK5707.

[67]

Slart RHJA, Bengel FM, Akincioglu C, Bourque JM, Chen W, Dweck MR, et al. Total-Body PET/CT Applications in Cardiovascular Diseases: A Perspective Document of the SNMMI Cardiovascular Council. Journal of Nuclear Medicine. 2024; 65: 607–616. https://doi.org/10.2967/jnumed.123.266858.

[68]

Mannil M, Eberhard M, von Spiczak J, Heindel W, Alkadhi H, Baessler B. Artificial Intelligence and Texture Analysis in Cardiac Imaging. Current Cardiology Reports. 2020; 22: 131. https://doi.org/10.1007/s11886-020-01402-1.

[69]

Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016; 278: 563–577. https://doi.org/10.1148/radiol.2015151169.

[70]

Baessler B, Luecke C, Lurz J, Klingel K, von Roeder M, de Waha S, et al. Cardiac MRI Texture Analysis of T1 and T2 Maps in Patients with Infarctlike Acute Myocarditis. Radiology. 2018; 289: 357–365. https://doi.org/10.1148/radiol.2018180411.

[71]

Shiri I, Baj G, Mohammadi Kazaj P, Balzer S, Schutze J, Valenzuela W, et al. Predicting major adverse cardiovascular events in suspected myocarditis patients using cmr late gadolinium enhancement radiomics: a time-to-event prognostication modeling. European Heart Journal. 2024; 45: ehae666.3419. https://doi.org/10.1093/eurheartj/ehae666.3419.

[72]

Ghareeb AN, Karim SA, Jani VP, Francis W, Van den Eynde J, Alkuwari M, et al. Patterns of cardiovascular magnetic resonance inflammation in acute myocarditis from South Asia and Middle East. International Journal of Cardiology. Heart & Vasculature. 2022; 40: 101029. https://doi.org/10.1016/j.ijcha.2022.101029.

[73]

Shyam-Sundar V, Harding D, Khan A, Abdulkareem M, Slabaugh G, Mohiddin SA, et al. Imaging for the diagnosis of acute myocarditis: can artificial intelligence improve diagnostic performance? Frontiers in Cardiovascular Medicine. 2024; 11: 1408574. https://doi.org/10.3389/fcvm.2024.1408574.

[74]

Khalifa M, Albadawy M. AI in diagnostic imaging: Revolutionising accuracy and efficiency. Computer Methods and Programs in Biomedicine Update. 2024; 5: 100146. https://doi.org/10.1016/j.cmpbup.2024.100146.

PDF (7022KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/