Comparison of myocardial fibrosis quantification methods by cardiovascular magnetic resonance imaging for risk stratification of patients with suspected myocarditis

Myocardial Fibrosis Quantification Methods by Cardiovascular Magnetic Resonance Imaging in Patients with Fabry Disease

Background/Objectives: The presence of late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in patients with Fabry disease (FD) is a predictor of adverse cardiac events. The aim of this study was to establish the most reliable and reproducible technique for quantifying LGE in patients with FD. Methods: Twenty FD patients with LGE who underwent CMR on the same scanner and LGE sequence were included. LGE quantifications were done using gray-scale thresholds of 2, 3, 4, 5 and 6 standard deviations (SD) above the mean signal intensity of the remote myocardium, the full width at half maximum method (FWHM), visual assessment with threshold (VAT) and the fully manual method (MM). Results: The mean amount of fibrosis varied between quantification techniques from 36 ± 19 at 2SD to 2 ± 2 g using the FWHM (p < 0.0001). Intraobserver reliability was excellent for most methods, except for the FWHM which was good (ICC 0.84; all p < 0.05). Interobserver reliability was excellent for VAT (ICC 0.94) and good for other techniques (all p < 0.05). Intraobserver reproducibility showed the lowest coefficient of variation (CV, 6%) at 5SD and at 2SD and VAT (35% and 38%) for interobserver reproducibility. The FWHM revealed the highest CV (63% and 94%) for both intra- and interobserver reproducibility. Conclusions: The available methods for LGE quantification demonstrate good to excellent intra- and interobserver reproducibility in patients with FD. The most reliable and reproducible techniques were VAT and 5SD, whereas the FWHM was the least reliable in the setting of our study. The total amount of LGE varies strongly with the quantification technique used.

Optimizing ventricular tachycardia ablation through imaging-based assessment of arrhythmic substrate: A comprehensive review and roadmap for the future

Ventricular tachycardia (VT) is a life-threatening heart rhythm and has long posed a complex challenge in the field of cardiology. Recent developments in advanced imaging modalities have aimed to improve comprehension of underlying arrhythmic substrate for VT. To this extent, high-resolution cardiac magnetic resonance (CMR) and cardiac computed tomography (CCT) have emerged as tools for accurately visualizing and characterizing scar tissue, fibrosis, and other critical structural abnormalities within the heart, providing novel insights into VT triggers and substrate. However, clinical implementation of knowledge derived from these advanced imaging techniques in improving VT treatment and guiding invasive therapeutic strategies continues to pose significant challenges. A pivotal concern lies in the absence of standardized imaging protocols and analysis methodologies, resulting in a large variance in data quality and consistency. Furthermore, the clinical significance and outcomes associated with VT substrate characterization through CMR and CCT remain dynamic and subject to ongoing evolution. This highlights the need for refinement of these techniques before their reliable integration into routine patient care can be realized. The primary objectives of this study are twofold: firstly, to provide a comprehensive overview of the studies conducted over the last 15 years, summarizing the current available literature on imaging-based assessment of VT substrate. Secondly, to critically analyze and evaluate the selected studies, with the aim of providing valuable insights that can inform current clinical practice and future research.

Cardiac magnetic resonance imaging (MRI) for detecting acute myocardial injury of fulminant myocarditis survivors after extracorporeal membrane oxygenation (ECMO) treatment in adults

AIMS

To detect the acute myocardial injury in fulminant myocarditis (FM) survivors after extracorporeal membrane oxygenation (ECMO) and to demonstrate its significant differences from non-FM patients by cardiac magnetic resonance (CMR).

MATERIALS AND METHODS

This retrospective study enrolled 59 patients with acute myocarditis (AM), including 35 non-FM patients, 24 FM patients, and 54 controls. The peak value of cardiac troponin T (cTnT) was recorded. Tissue parameters, including native T1, extracellular volume (ECV), late gadolinium-enhancement (LGE)%, and T2 by CMR were assessed.

RESULTS

The mean age was 35 ± 14 years, and 45.8% of the population were males in the AM group. Patients had higher levels of peak cTnT, peak NT-proBNP and peak C-reactive protein in the FM group (all p<0.05). Comparing with non-FM, the values of T1-based imaging parameters were significantly higher in the FM group (all p<0.05). In contrast, no difference was observed among the two groups in terms of T2 value (p=0.707). The septal area was more frequently involved in FM survivors after ECMO treatment, both in T1 and T2-based images. In addition, the cubic relationship was the relative best fit of LGE% against logcTnT and indicated that cTnT value exceeding 300ng/L exhibited a rapid upward trend of LGE%.

CONCLUSION

Comparing to non-FM, higher myocardial necrosis and fibrosis but similar edema determined by T1 and T2 based imaging was found in FM survivors after ECMO treatment. Furthermore, the inter-ventricular septal area was more frequently involved by acute myocardial injury in FM survivors after ECMO treatment. In addition, LGE% showed an overall increasing trend with cTnT values elevating with rapidly increasing with cTnT exceeding 300 ng/L.

Vitamin D Status and Cardiovascular Disease in College Athletes After SARS-CoV-2 Infection

OBJECTIVE

To evaluate the association between vitamin D status and CV disease after COVID-19 in college athletes.

DESIGN

Retrospective cohort study.

SETTING

National College Athletic Association Division-I college athletes from a single academic institution.

PATIENTS

A total of 157 athletes (60 female; median age: 20 years) from 9 sports with a positive SARS-CoV-2 test, cardiac magnetic resonance imaging (CMR), and vitamin D level.

INDEPENDENT VARIABLES

Serum 25-hydroxyvitamin D level (primary); age, sex (regression models).

MAIN OUTCOMES MEASURES

Differences in age, sex, race, ethnicity, myocarditis, pericarditis, and CMR metrics by vitamin D status were analyzed. Regression models were used to assess the relationship between vitamin D status and CMR metrics accounting for age and sex.

RESULTS

Low vitamin D (LVD) was found in 33 (21.0%) of athletes, particularly Black males (P < 0.001). Athletes with LVD had higher biventricular and lower mid-ventricular extracellular volumes, but these differences were not significant when corrected for age and sex. Athletes with LVD had higher left ventricle (LV) mass (P < 0.001) and LV mass index (P = 0.001) independent of age and sex. Differences in global circumferential strain were noted but are likely clinically insignificant. Vitamin D status did not associate with myocarditis and pericarditis (P = 0.544).

CONCLUSIONS

LVD is common in athletes, particularly in Black males. Although athletes with LVD had higher LV mass, cardiac function and tissue characterization did not differ by vitamin D status. Future studies are needed to determine if the differences in LV mass and LV mass index by vitamin D status are clinically significant. This study suggests that vitamin D status does not impact the development of myocarditis or pericarditis after COVID-19 infection.

Imaging of Cardiac Fibrosis: An Update, From the AJR Special Series on Imaging of Fibrosis

Myocardial fibrosis (MF) is defined as excessive production and deposition of extra-cellular matrix proteins that result in pathologic myocardial remodeling. Three types of MF have been identified: replacement fibrosis from tissue necrosis, reactive fibrosis from myocardial stress, and infiltrative interstitial fibrosis from progressive deposition of nondegradable material such as amyloid. Although echocardiography, nuclear medicine, and CT play important roles in the assessment of MF, MRI is pivotal in the evaluation of MF, with the late gadolinium enhancement (LGE) technique used as a primary end point. The LGE technique focuses on the pattern and distribution of gadolinium accumulation in the myocardium and assists in the diagnosis and establishment of the cause of both ischemic and nonischemic cardiomyopathy. LGE MRI also aids prognostication and risk stratification. In addition, LGE MRI is used to guide the management of patients considered for ablation for arrhythmias. Parametric mapping techniques, including T1 mapping and extracellular volume measurement, allow detection and quantification of diffuse fibrosis, which may not be detected by LGE MRI. These techniques also allow monitoring of disease progression and therapy response. This review provides an update on the imaging of MF, including prognostication and risk stratification tools, electrophysiologic considerations, and disease monitoring.

Comparative analysis of late gadolinium enhancement assessment techniques for monitoring fibrotic changes in myocarditis follow-up

OBJECTIVES

To compare the repeatability and interrelation of various late gadolinium enhancement (LGE) assessment techniques for monitoring fibrotic changes in myocarditis follow-up.

MATERIALS AND METHODS

LGE extent change between baseline and 3-month cardiovascular magnetic resonance (CMR) was compared in patients with acute myocarditis using the full width at half maximum (FWHM), gray-scale thresholds at 5 and 6 standard deviations (SD5 and SD6), visual assessment with threshold (VAT) and full manual (FM) techniques. In addition, visual presence score (VPS), visual transmurality score (VTS), and a simplified visual change score (VCS) were assessed. Intraclass-correlation (ICC) was used to evaluate repeatability, and methods were compared using Spearman's correlation.

RESULTS

Forty-seven patients (38 male, median age: 27 [IQR: 21; 38] years) were included. LGE extent change differed among quantitative techniques (p < 0.01), with variability in the proportion of patients showing LGE change during follow-up (FWHM: 62%, SD5: 74%, SD6: 66%, VAT: 43%, FM: 60%, VPS: 53%, VTS: 77%, VCS: 89%). Repeatability was highest with FWHM (ICC: 0.97) and lowest with SD5 (ICC: 0.89). Semiquantitative scoring had slightly lower values (VPS ICC: 0.81; VTS ICC: 0.71). VCS repeatability was excellent (ICC: 0.93). VPS and VTS correlated with quantitative techniques, while VCS was positively associated with VPS, VTS, VAT, and FM, but not with FWHM, SD5, and SD6.

CONCLUSION

FWHM offers the least observer-dependent LGE follow-up after myocarditis. VPS, VTS, and VCS are practical alternatives, showing reliable correlations with quantitative methods. Classification of patients exhibiting either stable or changing LGE relies on the assessment technique.

CLINICAL RELEVANCE STATEMENT

This study shows that LGE monitoring in myocarditis is technique-dependent; the FWHM method yields the most consistent fibrotic tracking results, with scoring-based techniques as reliable alternatives.

KEY POINTS

Recognition of fibrotic changes during myocarditis follow-up is significantly influenced by the choice of the quantification technique employed. The FWHM technique ensures highly repeatable tracking of myocarditis-related LGE changes. Segment-based visual scoring and the simplified visual change score offer practical, reproducible alternatives in resource-limited settings.

Quantitative Analysis of Radiation Therapy-Induced Cardiac and Aortic Sequelae in Patients With Lung Cancer via Magnetic Resonance Imaging: A Pilot Study

PURPOSE

The objective of this study was to quantify early radiation therapy (RT)-induced cardiac and aortic changes in patients with lung cancer using cardiac magnetic resonance imaging (MRI).

METHODS AND MATERIALS

Nine patients with lung cancer treated with RT completed MR scans at baseline (before RT) and at 3 and 6 months after RT completion. Cine, T1/T2, late gadolinium enhancement (LGE), and 4-dimensional flow MRIs were acquired to assess biological and mechanical cardiovascular changes globally (ie, over the entire left ventricle (LV) or aorta) and regionally (according to an American Heart Association model).

RESULTS

Regional metrics demonstrated multiple significant changes and dose-dependent responses. Notably, LGE showed changes at 3 and 6 months over septal and high-dose regions (P < .0458). Longitudinal strain changes were notable at septal and high-dose regions at 3 months and at septal regions at 6 months (P < .0469). Elevated T1/T2 signals (P < .0391) and changes in radial/circumferential strain at the septum (P < .0391) were observed at 3 months. Both T1/T2 signal and LGE were correlated with dose at 6 months (T1 signal also at 3 months), with significantly greater changes in regions receiving >50 Gy (P < .0331). LV dose was not correlated with LV strain changes (P > .1), but ascending aortic dose was correlated with strain changes at segments 1 and 2 of the LV (P < .0362). Global metrics identified only 2 significant responses: increase in LGE volume at 6 months and a reduction in ascending aortic circumferential strain at 3 months (P < .0356).

CONCLUSIONS

Early MR-based changes after RT occurred primarily in high-dose regions and the LV septal wall. Although several early signals resolved by 6 months, LGE and longitudinal strain changes persisted for at least 6 months. Dose-dependent responses/correlations were observed for T1/T2/LGE changes at 6 months, with the greatest effect in regions exposed to >50 Gy. Further investigations with larger cohorts and longer follow-up are warranted to confirm regional dose dependence and the association between aortic dose and LV strain observed in this pilot study.

Simultaneous Viability Assessment and Invasive Coronary Angiography Using a Therapeutic CT System in Chronic Myocardial Infarction Patients

PURPOSE

In a preclinical study using a swine myocardial infarction (MI) model, a delayed enhancement (DE)-multi-detector computed tomography (MDCT) scan was performed using a hybrid system alongside diagnostic invasive coronary angiography (ICA) without the additional use of a contrast agent, and demonstrated an excellent correlation in the infarct area compared with histopathologic specimens. In the present investigation, we evaluated the feasibility and diagnostic accuracy of a myocardial viability assessment by DE-MDCT using a hybrid system comprising ICA and MDCT alongside diagnostic ICA without the additional use of a contrast agent.

MATERIALS AND METHODS

We prospectively enrolled 13 patients (median age: 67 years) with a previous MI (>6 months) scheduled to undergo ICA. All patients underwent cardiac magnetic resonance (CMR) imaging before diagnostic ICA. MDCT viability scans were performed concurrently with diagnostic ICA without the use of additional contrast. The total myocardial scar volume per patient and average transmurality per myocardial segment measured by DE-MDCT were compared with those from DE-CMR.

RESULTS

The DE volume measured by MDCT showed an excellent correlation with the volume measured by CMR (r=0.986, p<0.0001). The transmurality per segment by MDCT was well-correlated with CMR (r=0.900, p<0.0001); the diagnostic performance of MDCT in differentiating non-viable from viable myocardium using a 50% transmurality criterion was good with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 87.5%, 99.5%, 87.5%, 99.5%, and 99.1%, respectively.

CONCLUSION

The feasibility of the DE-MDCT viability assessment acquired simultaneously with conventional ICA was proven in patients with chronic MI using DE-CMR as the reference standard.

Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization

BACKGROUND

Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images is usually straightforward, but diagnostic uncertainty arises when reporters are not sure whether the observed LGE is genuine or not. This uncertainty might be resolved by repetition (to remove artifact) or further acquisition of intersecting images, but this must take place before the scan finishes. Real-time quality assurance by humans is a complex task requiring training and experience, so being able to identify which images have an intermediate likelihood of LGE while the scan is ongoing, without the presence of an expert is of high value. This decision-support could prompt immediate image optimization or acquisition of supplementary images to confirm or refute the presence of genuine LGE. This could reduce ambiguity in reports.

METHODS

Short-axis, phase-sensitive inversion recovery late gadolinium images were extracted from our clinical cardiac magnetic resonance (CMR) database and shuffled. Two, independent, blinded experts scored each individual slice for "LGE likelihood" on a visual analog scale, from 0 (absolute certainty of no LGE) to 100 (absolute certainty of LGE), with 50 representing clinical equipoise. The scored images were split into two classes-either "high certainty" of whether LGE was present or not, or "low certainty." The dataset was split into training, validation, and test sets (70:15:15). A deep learning binary classifier based on the EfficientNetV2 convolutional neural network architecture was trained to distinguish between these categories. Classifier performance on the test set was evaluated by calculating the accuracy, precision, recall, F1-score, and area under the receiver operating characteristics curve (ROC AUC). Performance was also evaluated on an external test set of images from a different center.

RESULTS

One thousand six hundred and forty-five images (from 272 patients) were labeled and split at the patient level into training (1151 images), validation (247 images), and test (247 images) sets for the deep learning binary classifier. Of these, 1208 images were "high certainty" (255 for LGE, 953 for no LGE), and 437 were "low certainty". An external test comprising 247 images from 41 patients from another center was also employed. After 100 epochs, the performance on the internal test set was accuracy = 0.94, recall = 0.80, precision = 0.97, F1-score = 0.87, and ROC AUC = 0.94. The classifier also performed robustly on the external test set (accuracy = 0.91, recall = 0.73, precision = 0.93, F1-score = 0.82, and ROC AUC = 0.91). These results were benchmarked against a reference inter-expert accuracy of 0.86.

CONCLUSION

Deep learning shows potential to automate quality control of late gadolinium imaging in CMR. The ability to identify short-axis images with intermediate LGE likelihood in real-time may serve as a useful decision-support tool. This approach has the potential to guide immediate further imaging while the patient is still in the scanner, thereby reducing the frequency of recalls and inconclusive reports due to diagnostic indecision.

CMR Predictors of Favorable Outcome in Myocarditis: A Single-Center Experience

Background: Cardiovascular magnetic resonance (CMR) has emerged as the most accurate, non-invasive method to support the diagnosis of clinically suspected myocarditis and as a risk-stratification tool in patients with cardiomyopathies. We aim to assess the diagnostic and prognostic role of CMR at diagnosis in patients with myocarditis. Methods: We enrolled consecutive single-center patients with 2013 ESC consensus-based endomyocardial biopsy (EMB)-proven or clinically suspected myocarditis undergoing CMR at diagnosis. The pre-specified outcome was defined as NYHA class > I and echocardiographic left ventricular ejection fraction (LVEF) < 50% at follow-up. Results: We included 207 patients (74% male, median age 36 years; 25% EMB-proven). CMR showed the highest sensitivity in myocarditis with infarct-like presentation. Patients with EMB-proven myocarditis were more likely to have diffuse LGE and right ventricular LGE (p < 0.001), which was also more common among patients with arrhythmic presentation (p = 0.001). The outcome was met in 17 patients at any follow-up time point, more commonly in those with larger biventricular volumes (p < 0.001), CMR-based diagnosis of dilated cardiomyopathy (p < 0.001), and ischemic LGE (p = 0.005). Higher biventricular systolic function (p < 0.001) and greater LGE extent (p = 0.033) at diagnosis had a protective effect. Conclusions: In our single-center cohort of rigorously defined myocarditis patients, higher biventricular systolic function and greater LGE extent on CMR at diagnosis identified patients with better functional class and higher left ventricular ejection fraction at follow-up. Conversely, larger biventricular volumes, CMR-based DCM features, and the presence of an ischemic LGE pattern at diagnosis were predictors of worse functional class and LV systolic dysfunction at follow-up. Larger prospective studies are warranted to extend our findings to multi-center cohorts.

Left ventricular fibrosis in arrhythmic mitral valve prolapse: quantification and comparison of semi-automated techniques assessed by cardiac magnetic resonance

PURPOSE

Left ventricular (LV) fibrosis has a key role in arrhythmogenesis in patients with mitral valve prolapse (MVP). Cardiac magnetic resonance identifies LV fibrosis by using late gadolinium enhancement (LGE) technique. LGE assessment and quantification in patients with MVP lacks of standardization protocols.

METHODS

66 MVP patients with normal systolic function and without significant regurgitation were enrolled. Semi-automated gray-scale thresholding techniques using full width at half maximum (FWHM) and 2, 3 and 5 standard deviation (SD) above the remote myocardium were used and compared with the visual assessment, considered as the gold standard.

RESULTS

LGE was identified in 41 MVP patients (62%) and quantified. The mean quantity of LGE visually assessed was 2.40 ± 1.07% or 1.40 ± 0.82 g. With FWHM, LGE resulted 3.56 ± 1.23% or 1.99 ± 1.13 g. Using thresholding, the mean LGE quantity was 9.2 ± 3.1% or 4.82 ± 2.28 g for 2-SD, 5.72 ± 1.75% or 3.06 ± 1.47 g for 3-SD and 2.36 ± 0.99% or 1.29 ± 0.79 g for 5-SD. The 5-SD measurement in percentage demonstrated a good correlation with LGE quantification visually assessed (2.40 ± 1.07 vs. 2.363 ± 0.9909, p = 0.543). When compared with the gold standard, the 5-SD threshold quantification, both in percentage and in grams, revealed the least intra-observer (respectively, ICC: 0.976 and 0.966) and inter-observer variability (respectively ICC: 0.948 and 0.935).

CONCLUSION

The 5-SD gray-scale threshold technique in percentage revealed the best correlation with the visual assessment and an optimal reproducibility in MVP patient.

Cardiac Magnetic Resonance Imaging Findings and Clinical Features of COVID-19 Vaccine-Associated Myocarditis, Compared With Those of Other Types of Myocarditis

BACKGROUND

To compare the clinical and cardiac magnetic resonance (CMR) imaging findings of coronavirus disease 2019 (COVID-19) vaccine-associated myocarditis (VAM) with those of other types of myocarditis.

METHODS

From January 2020 to March 2022, a total of 39 patients diagnosed with myocarditis via CMR according to the Modified Lake Louise criteria were included in the present study. The patients were classified into two groups based on their vaccination status: COVID-19 VAM and other types of myocarditis not associated with COVID-19 vaccination. Clinical outcomes, including the development of clinically significant arrhythmias, sudden cardiac arrest, and death, and CMR imaging features were compared between COVID-19 VAM and other types of myocarditis.

RESULTS

Of the 39 included patients (mean age, 39 years ± 16.4 [standard deviation]; 23 men), 23 (59%) had COVID-19 VAM and 16 (41%) had other types of myocarditis. The occurrence of clinical adverse events did not differ significantly between the two groups. As per the CMR imaging findings, the presence and dominant pattern of late gadolinium enhancement did not differ significantly between the two groups. The presence of high native T1 or T2 values was not significantly different between the two groups. Although the native T1 and T2 values tended to be lower in COVID-19 VAM than in other types of myocarditis, there were no statistically significant differences between the native T1 and T2 values in the two groups.

CONCLUSION

The present study demonstrated that the CMR imaging findings and clinical outcomes of COVID-19 VAM did not differ significantly from those of other types of myocarditis during hospitalization.

Cardiovascular magnetic resonance (CMR) and positron emission tomography (PET) imaging in the diagnosis and follow-up of patients with acute myocarditis and chronic inflammatory cardiomyopathy : A review paper with practical recommendations on behalf of the European Society of Cardiovascular Radiology (ESCR)

Advanced cardiac imaging techniques such as cardiovascular magnetic resonance (CMR) and positron emission tomography (PET) are widely used in clinical practice in patients with acute myocarditis and chronic inflammatory cardiomyopathies (I-CMP). We aimed to provide a review article with practical recommendations from the European Society of Cardiovascular Radiology (ESCR), in order to guide physicians in the use and interpretation of CMR and PET in clinical practice both for acute myocarditis and follow-up in chronic forms of I-CMP.

Phenotyping of giant cell myocarditis versus cardiac sarcoidosis using cardiovascular magnetic resonance

BACKGROUND

Giant cell myocarditis (GCM) and cardiac sarcoidosis (CS) are rare inflammatory diseases of the myocardium with poor prognosis. Little is known about the cardiovascular magnetic resonance (CMR) appearance of GCM and the methods ability to distinguish the two rare entities from one another.

METHODS

We assessed a total of 40 patients with endomyocardial biopsy-proven GCM (n = 14) and CS (n = 26) concerning their clinical and CMR appearance in a blinded manner.

RESULTS

Patients with GCM and CS were of similar median age (55 vs 56 years), and a male predominance was observed in both groups. In GCM, median levels of troponin T (313 vs 31 ng/L, p < 0.001), and natriuretic peptides (6560 vs 676 pg/mL, p < 0.001) were higher than in CS, and the clinical outcome worse (p = 0.04). On CMR imaging, the observed alterations of left and right ventricular (LV/RV) dimensions and function were similar. GCM showed multifocal LV late gadolinium enhancement (LGE) with a similar longitudinal, circumferential, and radial distribution as in CS, including suggested signature imaging biomarkers of CS like the "hook sign" (71% vs 77%, p = 0.702). The median LV LGE enhanced volume was 17% and 22% in GCM and CS (p = 0.150), respectively. The number of RV segments with pathologically increased T2 signal and/or LGE were most extensive in GCM.

CONCLUSIONS

The CMR appearance of both GCM and CS is highly similar, making the differentiation between the two rare entities solely based on CMR challenging. This stands in contrast to the clinical appearance, which seems to be more severe in GCM.

Predictive value of cardiac magnetic resonance right ventricular longitudinal strain in patients with suspected myocarditis

BACKGROUND

Recent evidence underlined the importance of right (RV) involvement in suspected myocarditis. We aim to analyze the possible incremental prognostic value from RV global longitudinal strain (GLS) by CMR.

METHODS

Patients referred for CMR, meeting clinical criteria for suspected myocarditis and no other cardiomyopathy were enrolled in a dual-center register cohort study. Ejection fraction (EF), GLS and tissue characteristics were assessed in both ventricles to assess their association to first major adverse cardiovascular events (MACE) including hospitalization for heart failure (HF), ventricular tachycardia (VT), recurrent myocarditis and death.

RESULTS

Among 659 patients (62.8% male; 48.1 ± 16.1 years), RV GLS was impaired (> - 15.4%) in 144 (21.9%) individuals, of whom 76 (58%), 108 (77.1%), 27 (18.8%) and 40 (32.8%) had impaired right ventricular ejection fraction (RVEF), impaired left ventricular ejection fraction (LVEF), RV late gadolinium enhancement (LGE) or RV edema, respectively. After a median observation time of 3.7 years, 45 (6.8%) patients were hospitalized for HF, 42 (6.4%) patients died, 33 (5%) developed VT and 16 (2.4%) had recurrent myocarditis. Impaired RV GLS was associated with MACE (HR = 1.07, 95% CI 1.04-1.10; p < 0.001), HF hospitalization (HR = 1.17, 95% CI 1.12-1.23; p < 0.001), and death (HR = 1.07, 95% CI 1.02-1.12; p = 0.004), but not with VT and recurrent myocarditis in univariate analysis. RV GLS lost its association with outcomes, when adjusted for RVEF, LVEF, LV GLS and LV LGE extent.

CONCLUSION

RV strain is associated with MACE, HF hospitalization and death but has neither independent nor incremental prognostic value after adjustment for RV and LV function and tissue characteristics. Therefore, assessing RV GLS in the setting of myocarditis has only limited value.

Multimodality Cardiac Imaging in COVID

Infection with SARS-CoV-2, the virus that causes COVID, is associated with numerous potential secondary complications. Global efforts have been dedicated to understanding the myriad potential cardiovascular sequelae which may occur during acute infection, convalescence, or recovery. Because patients often present with nonspecific symptoms and laboratory findings, cardiac imaging has emerged as an important tool for the discrimination of pulmonary and cardiovascular complications of this disease. The clinician investigating a potential COVID-related complication must account not only for the relative utility of various cardiac imaging modalities but also for the risk of infectious exposure to staff and other patients. Extraordinary clinical and scholarly efforts have brought the international medical community closer to a consensus on the appropriate indications for diagnostic cardiac imaging during this protracted pandemic. In this review, we summarize the existing literature and reference major societal guidelines to provide an overview of the indications and utility of echocardiography, nuclear imaging, cardiac computed tomography, and cardiac magnetic resonance imaging for the diagnosis of cardiovascular complications of COVID.

COVID-19 mRNA Vaccines: The Molecular Basis of Some Adverse Events

Each injection of any known vaccine results in a strong expression of pro-inflammatory cytokines. This is the result of the innate immune system activation, without which no adaptive response to the injection of vaccines is possible. Unfortunately, the degree of inflammation produced by COVID-19 mRNA vaccines is variable, probably depending on genetic background and previous immune experiences, which through epigenetic modifications could have made the innate immune system of each individual tolerant or reactive to subsequent immune stimulations.We hypothesize that we can move from a limited pro-inflammatory condition to conditions of increasing expression of pro-inflammatory cytokines that can culminate in multisystem hyperinflammatory syndromes following COVID-19 mRNA vaccines (MIS-V). We have graphically represented this idea in a hypothetical inflammatory pyramid (IP) and we have correlated the time factor to the degree of inflammation produced after the injection of vaccines. Furthermore, we have placed the clinical manifestations within this hypothetical IP, correlating them to the degree of inflammation produced. Surprisingly, excluding the possible presence of an early MIS-V, the time factor and the complexity of clinical manifestations are correlated to the increasing degree of inflammation: symptoms, heart disease and syndromes (MIS-V).

Association between ECG parameters and late gadolinium enhancement along the course of myocarditis

PURPOSE

Numerous electrocardiogram (ECG) abnormalities and late gadolinium enhancement (LGE) in cardiac magnetic resonance imaging (CMR) have been related to poor prognosis in acute myocarditis. We evaluated whether ECG parameters are associated with the distribution and dynamic of LGE along the course of myocarditis.

METHODS

Fifty-one patients with CMR confirmed acute myocarditis were included who underwent CMR with LGE and 12-lead ECG at baseline and 3-month follow-up at our institution. The association between the presence, regional distribution and change of ECG parameters and LGE was investigated using linear regression analysis. LGE was quantified as visual presence score (VPS) and visual transmurality score (VTS).

RESULTS

Among many ECG parameters only > 1 mm ST-elevation (STE) was associated with VPS and VTS at baseline (β = 3.08 [95%CI: 1.75; 4.41], p = < 0.001 and β = 5.40 [95%CI: 1.92; 8.88], p = 0.004; respectively). STE was most frequent in lateral and inferior ECG-leads (48% and 31%) and it was associated with VPS and VTS in these localizations (p < 0.05 all), however no association between anterior-septal STE and LGE could be confirmed. At follow-up the regression of STE was associated with the regression of VPS and VTS in univariate analysis (β=-1.49 [95%CI: -2.41; -0.57], p = 0.003 and β=-4.87 [95%CI: -7.18; -2.56], p = 0.001, respectively), which remained significant for VTS using a multivariate model (β=-2.39 [95%CI: -3.32; -0.47], p = 0.019).

CONCLUSION

Although we demonstrated some promising associations between STE and LGE, the usability of ECG to estimate the territorial involvement and dynamical changes of LGE along the course of myocarditis is generally limited and cardiac magnetic resonance should be considered for this purpose.

The predictive role of right ventricular late gadolinium enhancement in patients with tetralogy of Fallot undergoing pulmonary valve replacement

BACKGROUND

Our purpose was to evaluate the correlations between right ventricular (RV) late gadolinium enhancement (LGE) at cardiac magnetic resonance (CMR) in patients with tetralogy of Fallot (ToF) scheduled for pulmonary valve replacement (PVR) and post-PVR functional data.

METHODS

We retrospectively reviewed ToF patients scheduled for PVR who underwent two CMR examinations at our institution, one before the procedure (CMR-0), including contrast-enhanced sequences, and one after the procedure (CMR-1). Functional left and RV data were obtained by segmenting short-axis stacks on both CMR examinations, and normalised variations were calculated by dividing differences between CMR-1 and CMR-0 by the intercurring time interval, whereas the RV scar burden was assessed on CMR-0 LGE sequences both semiquantitatively and quantitatively. Data were reported as median and interquartile range, differences were appraised with the Mann-Whitney U test, while correlations were assessed with Spearman's ρ.

RESULTS

Fifteen patients with a median age of 25 years (16-29), including 9 (60%) males, with a median time interval between CMR-0 and CMR-1 of 17 months (12-23), were retrospectively reviewed. The semiquantitative LGE score at CMR-0 was 7 (6-9), and LGE volume was 4.49 mL (3.70-5.78), covering 5.63% (4.92-7.00) of the RV. RV LGE score showed a moderate positive correlation with the normalised variation of RV stroke volume (ρ = 0.662, p = 0.007) and a borderline moderate positive correlation with the normalised variation of RV end-diastolic indexed volume (ρ = 0.513, p = 0.050).

CONCLUSIONS

The assessment of RV LGE before PVR may provide insights on post-PVR functional data, potentially facilitating a patient-tailored treatment pathway.

Optimization of null point in Look-Locker images for myocardial late gadolinium enhancement imaging using deep learning and a smartphone

OBJECTIVES

To determine the optimal inversion time (TI) from Look-Locker scout images using a convolutional neural network (CNN) and to investigate the feasibility of correcting TI using a smartphone.

METHODS

In this retrospective study, TI-scout images were extracted using a Look-Locker approach from 1113 consecutive cardiac MR examinations performed between 2017 and 2020 with myocardial late gadolinium enhancement. Reference TI null points were independently determined visually by an experienced radiologist and an experienced cardiologist, and quantitatively measured. A CNN was developed to evaluate deviation of TI from the null point and then implemented in PC and smartphone applications. Images on 4 K or 3-megapixel monitors were captured by a smartphone, and CNN performance on each monitor was determined. Optimal, undercorrection, and overcorrection rates using deep learning on the PC and smartphone were calculated. For patient analysis, TI category differences in pre- and post-correction were evaluated using the TI null point used in late gadolinium enhancement imaging.

RESULTS

For PC, 96.4% (772/749) of images were classified as optimal, with under- and overcorrection rates of 1.2% (9/749) and 2.4% (18/749), respectively. For 4 K images, 93.5% (700/749) of images were classified as optimal, with under- and overcorrection rates of 3.9% (29/749) and 2.7% (20/749), respectively. For 3-megapixel images, 89.6% (671/749) of images were classified as optimal, with under- and overcorrection rates of 3.3% (25/749) and 7.0% (53/749), respectively. On patient-based evaluations, subjects classified as within optimal range increased from 72.0% (77/107) to 91.6% (98/107) using the CNN.

CONCLUSIONS

Optimizing TI on Look-Locker images was feasible using deep learning and a smartphone.

KEY POINTS

• A deep learning model corrected TI-scout images to within optimal null point for LGE imaging. • By capturing the TI-scout image on the monitor with a smartphone, the deviation of the TI from the null point can be immediately determined. • Using this model, TI null points can be set to the same degree as that by an experienced radiological technologist.

Entropy of left ventricular late gadolinium enhancement and its prognostic value in hypertrophic cardiomyopathy a new CMR assessment method

PURPOSE

As a novel metric, entropy generated from late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) can be utilized to assess tissue heterogeneity. However, it is unknown if it can be utilized for risk stratification in hypertrophic cardiomyopathy (HCM). In addition, it is unknown if LGE entropy correlates with LGE mass%, which is commonly utilized for fibrosis assessment. This research was done to investigate these issues.

MATERIALS AND METHODS

Patients with HCM who underwent 3.0-T CMR between January 2015 and January 2020 were prospectively enrolled and classified into low- and high-risk groups according to the AHA/ACC risk stratification guideline for 2020. The LGE entropy was automatically estimated using a generic Python package algorithm. On CMR imaging, the LGE mass% was determined using the CVI 42 software. Endpoint events included sudden cardiac death (SCD), hospital readmission owing to heart failure, and implantable cardioverter defibrillator (ICD) treatment for ventricular arrhythmias.

RESULTS

A total of 109 HCM participants (70 males) were included. During the follow-up (23 ± 7 months), the patients in the high-risk group had higher LGE entropy (p < 0.001) and LGE mass% (p < 0.001) than those in the low-risk group, and patients with endpoint events had higher LGE entropy (p < 0.001) and LGE mass% (p < 0.001) than those without endpoint events. In all participants, there was a link between LGE entropy and LGE mass%, according to the Spearman rank correlation analysis (p < 0.001; r = 0.667). In ROC analysis, the area under the curve (AUC) of LGE entropy was 0.893 (95% CI, 0.794-0.993; P<0.001), AUC of LGE mass% was 0.826 (95% CI, 0.737-0.914; P<0.001), AUC of LVEF was 0.610 (95% CI, 0.473-0.748; P = 0.117) and AUC of 2020 AHA/ACC guideline for risk stratification was 0.716 (95% CI, 0.617-0.815; P = 0.002). According to Kaplan-Meier curves, HCM with a higher LGE entropy (≥cutoff value (<5.873) or ≥ thied tertile (5.540)) were more likely to experience the endpoint events. Following adjustment for the 2020 AHA/ACC guideline for risk categorization, LGE mass%, or decreased LVEF, Cox analysis showed that LGE entropy was independently linked with endpoint events.

CONCLUSIONS

The variability and extent of LGE pictures can be reflected by LGE entropy, which is a reliable, usable, and repeatable metric for risk classification in HCM. It is a prognostic indicator of endpoint events that is independent of other risk indicators.

Prognostic Value of Right Ventricular Function in Patients With Suspected Myocarditis Undergoing Cardiac Magnetic Resonance

BACKGROUND

Risk-stratification of myocarditis is based on functional parameters and tissue characterization of the left ventricle (LV), whereas right ventricular (RV) involvement remains mostly unrecognized.

OBJECTIVES

In this study, the authors sought to analyze the prognostic value of RV involvement in myocarditis by cardiac magnetic resonance (CMR).

METHODS

Patients meeting the recommended clinical criteria for suspected myocarditis were enrolled at 2 centers. Exclusion criteria were the evidence of coronary artery disease, pulmonary artery hypertension or structural cardiomyopathy. Biventricular ejection fraction, edema according to T2-weighted images, and late gadolinium enhancement (LGE) were linked to a composite end point of major adverse cardiovascular events (MACE), including heart failure hospitalization, ventricular arrhythmia, recurrent myocarditis, and death.

RESULTS

Among 1,125 consecutive patients, 736 (mean age: 47.8 ± 16.1 years) met the clinical diagnosis of suspected myocarditis and were followed for 3.7 years. Signs of RV involvement (abnormal right ventricular ejection fraction [RVEF], RV edema, and RV-LGE) were present in 188 (25.6%), 158 (21.5%), and 92 (12.5%) patients, respectively. MACE occurred in 122 patients (16.6%) and was univariably associated with left ventricular ejection fraction (LVEF), LV edema, LV-LGE, RV-LGE, RV edema, and RVEF. In a series of nesting multivariable Cox regression models, the addition of RVEF (HR_adj: 0.974 [95% CI: 0.956-0.993]; P = 0.006) improved prognostication (chi-square test = 89.5; P = 0.001 vs model 1; P = 0.006 vs model 2) compared with model 1 including only clinical variables (chi-square test = 28.54) and model 2 based on clinical parameters, LVEF, and LV-LGE extent (chi-square test = 78.93).

CONCLUSIONS

This study emphasizes the role of RV involvement in myocarditis and demonstrates the independent and incremental prognostic value of RVEF beyond clinical variables, CMR tissue characterization, and LV function. (Inflammatory Cardiomyopathy Bern Registry [FlamBER]; NCT04774549; CMR Features in Patients With Suspected Myocarditis [CMRMyo]; NCT03470571).

Subtyping based on immune cell fractions reveal heterogeneity of cardiac fibrosis in end-stage heart failure

Background

A central issue hindering the development of effective anti-fibrosis drugs for heart failure is the unclear interrelationship between fibrosis and the immune cells. This study aims at providing precise subtyping of heart failure based on immune cell fractions, elaborating their differences in fibrotic mechanisms, and proposing a biomarker panel for evaluating intrinsic features of patients' physiological statuses through subtype classification, thereby promoting the precision medicine for cardiac fibrosis.

Methods

We inferred immune cell type abundance of the ventricular samples by a computational method (CIBERSORTx) based on ventricular tissue samples from 103 patients with heart failure, and applied K-means clustering to divide patients into two subtypes based on their immune cell type abundance. We also designed a novel analytic strategy: Large-Scale Functional Score and Association Analysis (LAFSAA), to study fibrotic mechanisms in the two subtypes.

Results

Two subtypes of immune cell fractions: pro-inflammatory and pro-remodeling subtypes, were identified. LAFSAA identified 11 subtype-specific pro-fibrotic functional gene sets as the basis for personalised targeted treatments. Based on feature selection, a 30-gene biomarker panel (ImmunCard30) established for diagnosing patient subtypes achieved high classification performance, with the area under the receiver operator characteristic curve corresponding to 0.954 and 0.803 for the discovery and validation sets, respectively.

Conclusion

Patients with the two subtypes of cardiac immune cell fractions were likely having different fibrotic mechanisms. Patients' subtypes can be predicted based on the ImmunCard30 biomarker panel. We envision that our unique stratification strategy revealed in this study will unravel advance diagnostic techniques for personalised anti-fibrotic therapy.

Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data

BACKGROUND

The objective of the study was to investigate variability and agreement of the commonly used image processing method "n-SD from remote" and in particular for quantifying myocardial infarction by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR). LGE-CMR in tandem with the analysis method "n-SD from remote" represents the current reference standard for infarct quantification. This analytic method utilizes regions of interest (ROIs) and defines infarct as the tissue with a set number of standard deviations (SD) above the signal intensity of remote nulled myocardium. There is no consensus on what the set number of SD is supposed to be. Little is known about how size and location of ROIs and underlying signal properties in the LGE images affect results. Furthermore, the method is frequently used elsewhere in medical imaging often without careful validation. Therefore, the usage of the "n-SD" method warrants a thorough validation.

METHODS

Data from 214 patients from two multi-center cardioprotection trials were included. Infarct size from different remote ROI positions, ROI size, and number of standard deviations ("n-SD") were compared with reference core lab delineations.

RESULTS

Variability in infarct size caused by varying ROI position, ROI size, and "n-SD" was 47%, 48%, and 40%, respectively. The agreement between the "n-SD from remote" method and the reference infarct size by core lab delineations was low. Optimal "n-SD" threshold computed on a slice-by-slice basis showed high variability, n = 5.3 ± 2.2.

CONCLUSION

The "n-SD from remote" method is unreliable for infarct quantification due to high variability which depends on different placement and size of remote ROI, number "n-SD", and image signal properties related to the CMR-scanner and sequence used. Therefore, the "n-SD from remote" method should not be used, instead methods validated against an independent standard are recommended.

Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar

Reliable and robust simulation of individual patients using patient-specific models (PSMs) is one of the next frontiers for modeling and simulation (M&S) in healthcare. PSMs, which form the basis of digital twins, can be employed as clinical tools to, for example, assess disease state, predict response to therapy, or optimize therapy. They may also be used to construct virtual cohorts of patients, for in silico evaluation of medical product safety and/or performance. Methods and frameworks have recently been proposed for evaluating the credibility of M&S in healthcare applications. However, such efforts have generally been motivated by models of medical devices or generic patient models; how best to evaluate the credibility of PSMs has largely been unexplored. The aim of this paper is to understand and demonstrate the credibility assessment process for PSMs using patient-specific cardiac electrophysiological (EP) modeling as an exemplar. We first review approaches used to generate cardiac PSMs and consider how verification, validation, and uncertainty quantification (VVUQ) apply to cardiac PSMs. Next, we execute two simulation studies using a publicly available virtual cohort of 24 patient-specific ventricular models, the first a multi-patient verification study, the second investigating the impact of uncertainty in personalized and non-personalized inputs in a virtual cohort. We then use the findings from our analyses to identify how important characteristics of PSMs can be considered when assessing credibility with the approach of the ASME V&V40 Standard, accounting for PSM concepts such as inter- and intra-user variability, multi-patient and “every-patient” error estimation, uncertainty quantification in personalized vs non-personalized inputs, clinical validation, and others. The results of this paper will be useful to developers of cardiac and other medical image based PSMs, when assessing PSM credibility.

Patient-specific models are computational models that have been personalized using data from a patient. After decades of research, recent computational, data science and healthcare advances have opened the door to the fulfilment of the enormous potential of such models, from truly personalized medicine to efficient and cost-effective testing of new medical products. However, reliability (credibility) of patient-specific models is key to their success, and there are currently no general guidelines for evaluating credibility of patient-specific models. Here, we consider how frameworks and model evaluation activities that have been developed for generic (not patient-specific) computational models, can be extended to patient specific models. We achieve this through a detailed analysis of the activities required to evaluate cardiac electrophysiological models, chosen as an exemplar field due to its maturity and the complexity of such models. This is the first paper on the topic of reliability of patient-specific models and will help pave the way to reliable and trusted patient-specific modeling across healthcare applications.

The crucial role of cardiac MRI parameters in the prediction of outcomes in acute clinically suspected myocarditis: A functional and feature-tracking study

Background

The definitive diagnosis of myocarditis is made by endomyocardial biopsy, but it is an invasive method. Recent investigations have proposed that cardiac MRI parameters have both diagnostic and prognostic roles in assessing myocarditis. We aimed to evaluate the role of functional and feature-tracking (FT)-derived strain values in predicting major adverse cardiovascular events (MACE) in patients with acute myocarditis.

Methods and results

We evaluated 133 patients with acute myocarditis (74.4% men) between January 2016 and February 2021. During a mean follow-up of 31 ± 16 months, sixteen patients (12.03%) experienced MACE: three deaths (2.3%), nine ICD implantations (6.76%), and five cardiac transplantations (3.8%). The left ventricular ejection fraction (LVEF), the LV end-diastolic volume index (EDVI), and the LV global longitudinal strain (GLS) were the strongest predictors of MACE. Each 1-unit decline in LVEF and LVGLS or 1-unit rise in LVEDVI resulted in a 5, 24, and 2% increase in MACE, respectively. LVEF ≤36.46% and LVGLS ≤9% indicated MACE with 75% sensitivity and 74.4 and 73.5% specificity, respectively.

Conclusions

In a group of acute myocarditis patients with evidence of myocardial edema and late Gadolinium enhancement, LVEF and GLS were the strongest predictors of adverse cardiac events.

Using Multiparametric Cardiac Magnetic Resonance to Phenotype and Differentiate Biopsy-Proven Chronic from Healed Myocarditis and Dilated Cardiomyopathy

(1) Objectives: To discriminate biopsy-proven myocarditis (chronic vs. healed myocarditis) and to differentiate from dilated cardiomyopathy (DCM) using cardiac magnetic resonance (CMR). (2) Methods: A total of 259 consecutive patients (age 51 ± 15 years; 28% female) who underwent both endomyocardial biopsy (EMB) and CMR in the years 2008−2021 were evaluated. According to right-ventricular EMB results, patients were divided into either chronic (n = 130, 50%) or healed lymphocytic myocarditis (n = 60, 23%) or DCM (n = 69, 27%). The CMR protocol included functional, strain, and late gadolinium enhancement (LGE) imaging, T2w imaging, and T2 mapping. (3) Results: Left-ventricular ejection fraction (LV-EF) was higher, and the indexed end-diastolic volume (EDV) was lower in myocarditis patients (chronic: 42%, median 96 mL/m²; healed: 49%, 86 mL/m²) compared to the DCM patients (31%, 120 mL/m²), p < 0.0001. Strain analysis demonstrated lower contractility in DCM patients vs. myocarditis patients, p < 0.0001. Myocarditis patients demonstrated a higher LGE prevalence (68% chronic; 59% healed) than the DCM patients (45%), p = 0.01. Chronic myocarditis patients showed a higher myocardial edema prevalence and ratio (59%, median 1.3) than healed myocarditis (23%, 1.3) and DCM patients (13%, 1.0), p < 0.0001. T2 mapping revealed elevated values more frequently in chronic (90%) than in healed (21%) myocarditis and DCM (23%), p < 0.0001. T2 mapping yielded an AUC of 0.89 (sensitivity 90%, specificity 76%) in the discrimination of chronic from healed myocarditis and an AUC of 0.92 (sensitivity 86%, specificity 91%) in the discrimination of chronic myocarditis from DCM, both p < 0.0001. (4) Conclusions: Multiparametric CMR imaging, including functional parameters, LGE and T2 mapping, may allow differentiation of chronic from healed myocarditis and DCM and therefore help to optimize patient management in this clinical setting.

Cardiovascular magnetic resonance imaging patterns of acute COVID-19 mRNA vaccine-associated myocarditis in young male patients: A first single-center experience

Background

The risk of myocarditis after mRNA vaccination against COVID-19 has emerged recently. Current evidence suggests that young male patients are predominantly affected. In the majority of the cases, only mild symptoms were observed. However, little is known about cardiac magnetic resonance (CMR) imaging patterns in mRNA-related myocarditis and their differences when compared to classical viral myocarditis in the acute phase of inflammation.

Methods and results

In total, 10 mRNA vaccination-associated patients with myocarditis were retrospectively enrolled in this study and compared to 10 patients suffering from viral myocarditis, who were matched for age, sex, comorbidities, and laboratory markers. All patients (n = 20) were hospitalized and underwent a standardized clinical examination, as well as an echocardiography and a CMR. Both, clinical and imaging findings and, in particular, functional and volumetric CMR assessments, as well as detailed tissue characterization using late gadolinium enhancement and T1 + T2-weighted sequences, were compared between both groups. The median age of the overall cohort was 26 years (group 1: 25.5; group 2: 27.5; p = 0.57). All patients described chest pain as the leading reason for their initial presentation. CMR volumetric and functional parameters did not differ significantly between both groups. In all cases, the lateral left ventricular wall showed late gadolinium enhancement without significant differences in terms of the localization or in-depth tissue characterization (late gadolinium enhancement [LGE] enlargement: group 1: 5.4%; group 2: 6.5%; p = 0.14; T2 global/maximum value: group 1: 38.9/52 ms; group 2: 37.8/54.5 ms; p = 0.79 and p = 0.80).

Conclusion

This study yielded the first evidence that COVID-19 mRNA vaccine-associated myocarditis does not show specific CMR patterns during the very acute stage in the most affected patient group of young male patients. The observed imaging markers were closely related to regular viral myocarditis in our cohort. Additionally, we could not find any markers implying adverse outcomes in this relatively little number of patients; however, this has to be confirmed by future studies that will include larger sample sizes.

Impact of myocardial injury on regional left ventricular function in the course of acute myocarditis with preserved ejection fraction: insights from segmental feature tracking strain analysis using cine cardiac MRI

The aim of this study was to provide insights into myocardial adaptation over time in myocyte injury caused by acute myocarditis with preserved ejection fraction. The effect of myocardial injury, as defined by the presence of late gadolinium enhancement (LGE), on the change of left ventricular (LV) segmental strain parameters was evaluated in a longitudinal analysis. Patients with a first episode of acute myocarditis were enrolled retrospectively. Peak radial (PRS), longitudinal (PLS) and circumferential (PCS) LV segmental strain values at baseline and at follow-up were computed using feature tracking cine cardiac magnetic resonance imaging. The change of segmental strain values in LGE positive (LGE+) and LGE negative (LGE-) segments was compared over a course of 89 ± 20 days. In 24 patients, 100 LGE+ segments and 284 LGE- segments were analysed. Between LGE+ and LGE- segments, significant differences were found for the change of segmental PCS (p < 0.001) and segmental PRS (p = 0.006). LGE + segments showed an increase in contractility, indicating recovery, and LGE- segments showed a decrease in contractility, indicating normalisation after a hypercontractile state or impairment of an initially normal contracting segment. No significant difference between LGE+ and LGE- segments was found for the change in segmental PLS. In the course of acute myocarditis with preserved ejection fraction, regional myocardial function adapts inversely in segments with and without LGE. As these effects seem to counterbalance each other, global functional parameters might be of limited use in monitoring functional recovery of these patients.

Diagnostic performance of cardiac magnetic resonance segmental myocardial strain for detecting microvascular obstruction and late gadolinium enhancement in patients presenting after a ST-elevation myocardial infarction

Background

Microvascular obstruction (MVO) and Late Gadolinium Enhancement (LGE) assessed in cardiac magnetic resonance (CMR) are associated with adverse outcome in patients with ST-elevation myocardial infarction (STEMI). Our aim was to analyze the diagnostic performance of segmental strain for the detection of MVO and LGE.

Methods

Patients with anterior STEMI, who underwent additional CMR were enrolled in this sub-study of the CARE-AMI trial. Using CMR feature tracking (FT) segmental circumferential peak strain (SCS) was measured and the diagnostic performance of SCS to discriminate MVO and LGE was assessed in a derivation and validation cohort.

Results

Forty-eight STEMI patients (62 ± 12 years old), 39 (81%) males, who underwent CMR (i.e., mean 3.0 ± 1.5 days) after primary percutaneous coronary intervention (PCI) were included. All patients presented with LGE and in 40 (83%) patients, MVO was additionally present. Segments in all patients were visually classified and 146 (19%) segments showed MVO (i.e., LGE+/MVO+), 308 (40%) segments showed LGE and no MVO (i.e., LGE+/MVO–), and 314 (41%) segments showed no LGE (i.e., LGE–). Diagnostic performance of SCS for detecting MVO segments (i.e., LGE+/MVO+ vs. LGE+/MVO–, and LGE–) showed an AUC = 0.764 and SCS cut-off value was –11.2%, resulting in a sensitivity of 78% and a specificity of 67% with a positive predictive value (PPV) of 30% and a negative predictive value (NPV) of 94% when tested in the validation group. For LGE segments (i.e., LGE+/MVO+ and LGE+/MVO– vs. LGE–) AUC = 0.848 and SCS with a cut-off value of –13.8% yielded to a sensitivity of 76%, specificity of 74%, PPV of 81%, and NPV of 70%.

Conclusion

Segmental strain in STEMI patients was associated with good diagnostic performance for detection of MVO+ segments and very good diagnostic performance of LGE+ segments. Segmental strain may be useful as a potential contrast-free surrogate marker to improve early risk stratification in patients after primary PCI.

A multisystem, cardio-renal investigation of post-COVID-19 illness

The pathophysiology and trajectory of post-Coronavirus Disease 2019 (COVID-19) syndrome is uncertain. To clarify multisystem involvement, we undertook a prospective cohort study including patients who had been hospitalized with COVID-19 (ClinicalTrials.gov ID NCT04403607 ). Serial blood biomarkers, digital electrocardiography and patient-reported outcome measures were obtained in-hospital and at 28-60 days post-discharge when multisystem imaging using chest computed tomography with pulmonary and coronary angiography and cardio-renal magnetic resonance imaging was also obtained. Longer-term clinical outcomes were assessed using electronic health records. Compared to controls (n = 29), at 28-60 days post-discharge, people with COVID-19 (n = 159; mean age, 55 years; 43% female) had persisting evidence of cardio-renal involvement and hemostasis pathway activation. The adjudicated likelihood of myocarditis was 'very likely' in 21 (13%) patients, 'probable' in 65 (41%) patients, 'unlikely' in 56 (35%) patients and 'not present' in 17 (11%) patients. At 28-60 days post-discharge, COVID-19 was associated with worse health-related quality of life (EQ-5D-5L score 0.77 (0.23) versus 0.87 (0.20)), anxiety and depression (PHQ-4 total score 3.59 (3.71) versus 1.28 (2.67)) and aerobic exercise capacity reflected by predicted maximal oxygen utilization (20.0 (7.6) versus 29.5 (8.0) ml/kg/min) (all P < 0.01). During follow-up (mean, 450 days), 24 (15%) patients and two (7%) controls died or were rehospitalized, and 108 (68%) patients and seven (26%) controls received outpatient secondary care (P = 0.017). The illness trajectory of patients after hospitalization with COVID-19 includes persisting multisystem abnormalities and health impairments that could lead to substantial demand on healthcare services in the future.

Echocardiographic and Cardiac Magnetic Resonance Imaging-Derived Strains in Relation to Late Gadolinium Enhancement in Hypertrophic Cardiomyopathy

We compared speckle tracking echocardiography (STE) and feature tracking cardiovascular magnetic resonance (FT-CMR) in patients with hypertrophic cardiomyopathy (HC) with a varying extent of fibrosis as defined by late gadolinium enhancement to look at the level of agreement between methods and their ability to relate those to myocardial fibrosis. At 2 reference centers, 79 patients with HC and 16 volunteers (the control group) underwent STE and CMR with late gadolinium enhancement and FT-CMR. Patients were classified into 3 categories: no detectable, limited, and extensive fibrosis. Global longitudinal strain (GLS) and global radial strain (GRS) were derived using FT-CMR and STE. STE-derived GRS was decreased in all HC categories compared with the control group (p <0.001), whereas FT-CMR GRS was reduced only in patients with HC with fibrosis (p <0.05). Reduced STE-derived GLS was associated with extensive fibrosis (p <0.05) and a value less than -15.2% identified those with extensive fibrosis (sensitivity 79%, specificity 92%, area under the curve 0.863, 95% confidence interval [CI] 0.76 to 0.97, p <0.001). Inter-modality agreement was moderate for STE versus CMR-GLS (overall population intra-class correlation coefficient = 0.615, 95% CI 0.42 to 0.75, p <0.001; patients with HC 0.63, 0.42 to 0.76, p <0.001) and GRS (overall population intra-class correlation coefficient = 0.601, 95% CI 0.397 to 0.735, p <0.001). A low level of agreement for GRS was seen between methods in patients with HC. In conclusion, strain indexes measured using echocardiography and CMR are reduced in patients with HC compared with the control group and correlate well with the burden of myocardial fibrosis. Reduced STE-GLS can identify patients with extensive fibrosis, but whether there is an added value for risk stratification for sudden cardiac death remains to be determined.

Characteristics of COVID-19 Myocarditis With and Without Multisystem Inflammatory Syndrome

Multisystem inflammatory syndrome (MIS) is a severe complication described in a minority of patients with COVID-19. Myocarditis has been reported in patients with COVID-19, including MIS. In this study, we compared the clinical characteristics and cardiac magnetic resonance (CMR) findings of COVID-19 myocarditis in patients with and without MIS. In the 330 patients with COVID-19 who were referred for CMR at our institution between July 24, 2020, to March 31, 2021, 40 patients were identified as having myocarditis, MIS myocarditis (n = 21) and non-MIS myocarditis (n = 19). MIS myocarditis was characterized by global myocardial inflammation/edema with significantly elevated native T1, whereas only regional inflammation, and edema were noted in the non-MIS group. Distinct late gadolinium enhancement (LGE) patterns-inferior myocardial involvement in non-MIS myocarditis and septal involvement in MIS myocarditis-were identified. The LGE burden was comparable between the 2 groups (5.9% vs 6.6%, MIS vs non-MIS group, p = 0.83). Myocarditis was diagnosed more frequently by CMR in the MIS group (70% vs 6.3%, MIS vs non-MIS, p <0.001). In the 20 patients with a sequential CMR study at a median 102-day follow-up, 25% had persistent myocardial edema. The LGE burden improved over time, from a median of 5.0% (interquartile range 3.4% to 7.3%) to 3.2% (interquartile range 2.0% to 3.8%; p <0.001). In conclusion, MIS and non-MIS myocarditis exhibit distinct characteristics by CMR. Persistent LGE and edema were common at follow-up CMR examination in both groups.

Quantitative Myocardial Perfusion Predicts Outcomes in Patients With Prior Surgical Revascularization

BACKGROUND

Patients with previous coronary artery bypass graft (CABG) surgery typically have complex coronary disease and remain at high risk of adverse events. Quantitative myocardial perfusion indices predict outcomes in native vessel disease, but their prognostic performance in patients with prior CABG is unknown.

OBJECTIVES

In this study, we sought to evaluate whether global stress myocardial blood flow (MBF) and perfusion reserve (MPR) derived from perfusion mapping cardiac magnetic resonance (CMR) independently predict adverse outcomes in patients with prior CABG.

METHODS

This was a retrospective analysis of consecutive patients with prior CABG referred for adenosine stress perfusion CMR. Perfusion mapping was performed in-line with automated quantification of MBF. The primary outcome was a composite of all-cause mortality and major adverse cardiovascular events defined as nonfatal myocardial infarction and unplanned revascularization. Associations were evaluated with the use of Cox proportional hazards models after adjusting for comorbidities and CMR parameters.

RESULTS

A total of 341 patients (median age 67 years, 86% male) were included. Over a median follow-up of 638 days (IQR: 367-976 days), 81 patients (24%) reached the primary outcome. Both stress MBF and MPR independently predicted outcomes after adjusting for known prognostic factors (regional ischemia, infarction). The adjusted hazard ratio (HR) for 1 mL/g/min of decrease in stress MBF was 2.56 (95% CI: 1.45-4.35) and for 1 unit of decrease in MPR was 1.61 (95% CI: 1.08-2.38).

CONCLUSIONS

Global stress MBF and MPR derived from perfusion CMR independently predict adverse outcomes in patients with previous CABG. This effect is independent from the presence of regional ischemia on visual assessment and the extent of previous infarction.

Cardiac Magnetic Resonance in the Evaluation of COVID-19

Cardiovascular involvement following COVID-19 is heterogeneous, prevalent and is often missed by echocardiography and serum biomarkers (such as troponin I and brain natriuretic peptide). Cardiac magnetic resonance (CMR) is the gold standard non-invasive imaging modality to phenotype unique populations after COVID-19, such as competitive athletes with a heightened risk of sudden cardiac death, patients with multisystem inflammatory syndrome, and people suspected of having COVID-19 vaccine-induced myocarditis. This review summarises the key attributes of CMR, reviews the literature that has emerged for using CMR for people who may have COVID-19-related complications after COVID-19, and offers expert opinion regarding future avenues of investigation and the importance of reporting findings.

Diagnostic and Prognostic Value of Cardiovascular Magnetic Resonance in Neuromuscular Cardiomyopathies

Neuromuscular diseases (NMD) encompass a broad spectrum of diseases with variable type of cardiac involvement and there is lack of clinical data on Cardiovascular Magnetic Resonance (CMR) phenotypes or even prognostic value of CMR in NMD. We explored the diagnostic and prognostic value of CMR in NMD-related cardiomyopathies. The study included retrospective analysis of a cohort of 111 patients with various forms of NMD; mitochondrial: n = 14, Friedreich's ataxia (FA): n = 27, myotonic dystrophy: n = 27, Becker/Duchenne's muscular dystrophy (BMD/DMD): n = 15, Duchenne's carriers: n = 6, other: n = 22. Biventricular volumes and function and myocardial late gadolinium enhancement (LGE) pattern and extent were assessed by CMR. Patients were followed-up for the composite clinical endpoint of death, heart failure development or need for permanent pacemaker/intracardiac defibrillator. The major NMD subtypes, i.e. FA, mitochondrial, BMD/DMD, and myotonic dystrophy had significant differences in the incidence of LGE (56%, 21%, 62% & 30% respectively, chi² = 9.86, p = 0.042) and type of cardiomyopathy phenotype (chi² = 13.8, p = 0.008), extent/pattern (p = 0.006) and progression rate of LGE (p = 0.006). In survival analysis the composite clinical endpoint differed significantly between NMD subtypes (p = 0.031), while the subgroup with LGE + and LVEF < 50% had the worst prognosis (Log-rank p = 0.0034). We present data from a unique cohort of NMD patients and provide evidence on the incidence, patterns, and the prognostic value of LGE in NMD-related cardiomyopathy. LGE is variably present in NMD subtypes and correlates with LV remodelling, dysfunction, and clinical outcomes in patients with NMD.

Multiparametric Cardiovascular Magnetic Resonance Approach in Diagnosing, Monitoring, and Prognostication of Myocarditis

Myocarditis represents the entity of an inflamed myocardium and is a diagnostic challenge caused by its heterogeneous presentation. Contemporary noninvasive evaluation of patients with clinically suspected myocarditis using cardiac magnetic resonance (CMR) includes dimensions and function of the heart chambers, conventional T2-weighted imaging, late gadolinium enhancement, novel T1 and T2 mapping, and extracellular volume fraction calculation. CMR feature-tracking, texture analysis, and artificial intelligence emerge as potential modern techniques to further improve diagnosis and prognostication in this clinical setting. This review will describe the evidence surrounding different CMR methods and image postprocessing methods and highlight their values for clinical decision making, monitoring, and risk stratification across stages of this condition.

The Role of AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

Reproducibility and its confounders of CMR feature tracking myocardial strain analysis in patients with suspected myocarditis

Objectives

Cardiovascular magnetic resonance feature tracking (CMR-FT) is an emerging technique for assessing myocardial strain with valuable diagnostic and prognostic potential. However, the reproducibility of biventricular CMR-FT analysis in a large cardiovascular population has not been assessed. Also, evidence of confounders impacting reader reproducibility for CMR-FT in patients is unknown and currently limits the clinical implementation of this technique.

Methods

From a dual-center database of patients referred to CMR for suspected myocarditis, 125 patients were randomly selected to undergo biventricular CMR-FT analysis for 2-dimensional systolic and diastolic measures, with additional 3-dimensional analysis for the left ventricle. All image analysis was replicated by a single reader and by a second reader for intra- and inter-reader analysis (Circle Cardiovascular Imaging). Reliability was tested with intraclass correlation (ICC) tests, and the impact of imaging confounders on agreement was assessed through multivariable analysis.

Results

Left and right ventricular ejection fractions were reduced in 34% and 37% of the patients, respectively. Good to excellent reliability was shown for 2D (all ICC > 0.85) and 3D (all ICC > 0.70) peak strain and early diastolic strain rate for both ventricles in longitudinal orientation as well as circumferential orientations for the left ventricle. An increased slice number improved agreement while the presence of pericardial effusion compromised diastolic strain rate agreement, and arrhythmia compromised right ventricular agreement.

Conclusion

In a large clinical cohort, we could show CMR-FT yields excellent inter-reader and intra-reader reproducibility. Multi-parametric CMR-FT of the right and left ventricles appears to be a robust tool in cardiovascular patients referred to CMR.

Clinical trial registration.

ClinicalTrials.gov Identifier: NCT03470571, NCT04774549.

Key Points

• Cardiovascular magnetic resonance feature tracking (CMR-FT) is an emerging technique to measure myocardial strain in cardiovascular patients referred for CMR; however, the evaluation of its reproducibility in a large cohort has not yet been performed.

• In a large clinical cohort, CMR-FT yields excellent inter-reader and intra-reader reproducibility for both left and right ventricular systolic and diastolic parameters.

• Arrhythmia and pericardial effusion compromise agreement of select FT parameters, but poor ejection fraction does not.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08416-5.

Cardiovascular magnetic resonance evaluation of soldiers after recovery from symptomatic SARS-CoV-2 infection: a case-control study of cardiovascular post-acute sequelae of SARS-CoV-2 infection (CV PASC)

BACKGROUND

Myocarditis is a potential complication after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and a known cause of sudden cardiac death. Given the athletic demands of soldiers, identification of myocarditis and characterization of post-acute sequelae of SARS-CoV-2 infection with cardiovascular symptoms (CV PASC) may be critical to guide return-to-service. This study sought to evaluate the spectrum of cardiac involvement among soldiers with cardiopulmonary symptoms in the late convalescent phase of recovery from SARS-CoV-2 compared to a healthy soldier control group, and to determine the rate of progression to CV PASC.

METHODS

All soldiers referred for cardiovascular magnetic resonance (CMR) imaging for cardiopulmonary symptoms following COVID-19 were enrolled and matched by age, gender, and athletic phenotype 1:1 to soldiers undergoing CMR in the year prior to the first case of COVID-19 at our institution. Demographic, clinical, laboratory, and imaging parameters were compared between groups. The diagnosis of acute myocarditis was made using modified Lake Louise criteria. Wilcoxon rank sum and chi-squared tests were used for comparison of continuous and categorical variables, respectively.

RESULTS

Fifty soldier cases and 50 healthy soldier controls were included. The median time from SARS-CoV-2 detection to CMR was 71 days. The majority of cases experienced moderate symptoms (N = 43, 86%), while only 10% required hospitalization. The right ventricular (RV) ejection fraction (RVEF) was reduced in soldier cases compared to controls (51.0% vs. 53.2%, p = 0.012). Four cases were diagnosed with myocarditis (8%), 1 (2%) was diagnosed with Takotsubo cardiomyopathy, and 1 (2%) had new biventricular systolic dysfunction of unclear etiology. Isolated inferior RV septal insertion late gadolinium enhancement (LGE) was present in 8 cases and 8 controls (16% vs. 24%, p = 0.09). Seven of the 19 (37%) cases that completed an intermediate-term follow-up survey reported CV PASC at a median of 139 days of follow-up. Two of the 7 soldiers (29%) with CV PASC had a pathological clinical diagnosis (myocarditis) on CMR.

CONCLUSIONS

Cardiovascular pathology was diagnosed in 6 symptomatic soldiers (12%) after recovery from SARS-CoV-2, with myocarditis found in 4 (8%). RVEF was reduced in soldier cases compared to controls. CV PASC occurred in over one-third of soldiers surveyed, but did not occur in any soldiers with asymptomatic acute SARS-CoV-2 infection.

Is left atrial fibrosis an independent determinant of atrial fibrillation in mitral stenosis?

We prospectively studied whether left atrial (LA) fibrosis is a determinant of atrial fibrillation (AF) in mitral stenosis in patients who underwent balloon mitral valvotomy. There were 2 groups: Group A (n = 16), with AF and Group B (n = 27), without AF. Fibrosis was assessed by MRI. Patients underwent cardioversion before MRI. There were 27 females and 16 males, aged 29 ± 6 years. The LA areas in Groups A and B were 54.3 ± 4.4 mm² and 39.4 ± 2.3 mm² (p < 0.05) and the LA volume index was 46.2 ± 2.9 ml/m² vs 33 ± 3 ml/m² respectively (p < 0.0001). The presence of LA scarring was not statistically different in the two groups.

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy

BACKGROUND

Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to develop a contrast agent-free technology to replace LGE for faster and cheaper CMR scans.

METHODS

A CMR virtual native enhancement (VNE) imaging technology was developed using artificial intelligence. The deep learning model for generating VNE uses multiple streams of convolutional neural networks to exploit and enhance the existing signals in native T1 maps (pixel-wise maps of tissue T1 relaxation times) and cine imaging of cardiac structure and function, presenting them as LGE-equivalent images. The VNE generator was trained using generative adversarial networks. This technology was first developed on CMR datasets from the multicenter Hypertrophic Cardiomyopathy Registry, using hypertrophic cardiomyopathy as an exemplar. The datasets were randomized into 2 independent groups for deep learning training and testing. The test data of VNE and LGE were scored and contoured by experienced human operators to assess image quality, visuospatial agreement, and myocardial lesion burden quantification. Image quality was compared using a nonparametric Wilcoxon test. Intra- and interobserver agreement was analyzed using intraclass correlation coefficients (ICC). Lesion quantification by VNE and LGE were compared using linear regression and ICC.

RESULTS

A total of 1348 hypertrophic cardiomyopathy patients provided 4093 triplets of matched T1 maps, cines, and LGE datasets. After randomization and data quality control, 2695 datasets were used for VNE method development and 345 were used for independent testing. VNE had significantly better image quality than LGE, as assessed by 4 operators (n=345 datasets; P<0.001 [Wilcoxon test]). VNE revealed lesions characteristic of hypertrophic cardiomyopathy in high visuospatial agreement with LGE. In 121 patients (n=326 datasets), VNE correlated with LGE in detecting and quantifying both hyperintensity myocardial lesions (r=0.77-0.79; ICC=0.77-0.87; P<0.001) and intermediate-intensity lesions (r=0.70-0.76; ICC=0.82-0.85; P<0.001). The native CMR images (cine plus T1 map) required for VNE can be acquired within 15 minutes and producing a VNE image takes less than 1 second.

CONCLUSIONS

VNE is a new CMR technology that resembles conventional LGE but without the need for contrast administration. VNE achieved high agreement with LGE in the distribution and quantification of lesions, with significantly better image quality.

Extracellular volume-guided late gadolinium enhancement analysis for non-ischemic cardiomyopathy: The Women's Interagency HIV Study

BACKGROUND

Quantification of non-ischemic myocardial scar remains a challenge due to the patchy diffuse nature of fibrosis. Extracellular volume (ECV) to guide late gadolinium enhancement (LGE) analysis may achieve a robust scar assessment.

METHODS

Three cohorts of 80 non-ischemic-training, 20 non-ischemic-validation, and 10 ischemic-validation were prospectively enrolled and underwent 3.0 Tesla cardiac MRI. An ECV cutoff to differentiate LGE scar from non-scar was identified in the training cohort from the receiver-operating characteristic curve analysis, by comparing the ECV value against the visually-determined presence/absence of the LGE scar at the highest signal intensity (SI) area of the mid-left ventricle (LV) LGE. Based on the ECV cutoff, an LGE semi-automatic threshold of n-times of standard-deviation (n-SD) above the remote-myocardium SI was optimized in the individual cases ensuring correspondence between LGE and ECV images. The inter-method agreement of scar amount in comparison with manual (for non-ischemic) or full-width half-maximum (FWHM, for ischemic) was assessed. Intra- and inter-observer reproducibility were investigated in a randomly chosen subset of 40 non-ischemic and 10 ischemic cases.

RESULTS

The non-ischemic groups were all female with the HIV positive rate of 73.8% (training) and 80% (validation). The ischemic group was all male with reduced LV function. An ECV cutoff of 31.5% achieved optimum performance (sensitivity: 90%, specificity: 86.7% in training; sensitivity: 100%, specificity: 81.8% in validation dataset). The identified n-SD threshold varied widely (range 3 SD-18 SD), and was independent of scar amount (β = -0.01, p = 0.92). In the non-ischemic cohorts, results suggested that the manual LGE assessment overestimated scar (%) in comparison to ECV-guided analysis [training: 4.5 (3.2-6.4) vs. 0.92 (0.1-2.1); validation: 2.5 (1.2-3.7) vs. 0.2 (0-1.6); P < 0.01 for both]. Intra- and inter-observer analyses of global scar (%) showed higher reproducibility in ECV-guided than manual analysis with CCC = 0.94 and 0.78 versus CCC = 0.86 and 0.73, respectively (P < 0.01 for all). In ischemic validation, the ECV-guided LGE analysis showed a comparable scar amount and reproducibility with the FWHM.

CONCLUSIONS

ECV-guided LGE analysis is a robust scar quantification method for a non-ischemic cohort. Trial registration ClinicalTrials.gov; NCT00000797, retrospectively-registered 2 November 1999; NCT02501811, registered 15 July 2015.

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

Background

Conventional transthoracic echocardiography (TTE) does often not accurately reveal pathologies in patients with acute myocarditis and preserved left ventricular ejection fraction (LVEEF). Therefore, we investigated the diagnostic value of two-dimensional (2D) speckle tracking echocardiography compared to late gadolinium enhancement (LGE) by cardiac magnetic resonance (CMR) imaging in patients with acute myocarditis and normal global LVEF.

Methods and results

31 patients (group 1) with the diagnosis of acute myocarditis confirmed by CMR according to the Lake Louise criteria and 20 healthy controls (group 2) were analyzed including global longitudinal strain (GLS) and regional longitudinal strain (RLS) derived by the bull’s eye plot. Although preserved LVEF was present in both groups, GLS was significantly lower in patients with acute myocarditis (group 1: GLS − 19.1 ± 1.8% vs. group 2: GLS − 22.1 ± 1.7%, p < 0.001). Compared to controls, lower RLS values were detected predominantly in the lateral, inferolateral, and inferior segments in patients with acute myocarditis. Additionally RLS values were significantly lower in segments without LGE.

Conclusion

In patients with acute myocarditis and preserved LVEF, a significant reduction of GLS compared to healthy subjects was detected. Further RLS adds important information to the localization and extent of myocardial injury.

Graphic abstract

Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification

OBJECTIVES

The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification.

METHODS

Sixty patients (46 ± 17 years, 50% male) with suspected or known cardiomyopathy underwent CMR. Short-axis LGE images were reconstructed using the conventional reconstruction and a DL network (DLRecon) with tunable noise reduction (NR) levels from 0 to 100%. Image quality of standard LGE images and DLRecon images with 75% NR was scored using a 5-point scale (poor to excellent). In 30 patients with LGE, scar size was quantified using thresholding techniques with different standard deviations (SD) above remote myocardium, and using full width at half maximum (FWHM) technique in images with varying NR levels.

RESULTS

DLRecon images were of higher quality than standard LGE images (subjective quality score 3.3 ± 0.5 vs. 3.6 ± 0.7, p < 0.001). Scar size increased with increasing NR levels using the SD methods. With 100% NR level, scar size increased 36%, 87%, and 138% using 2SD, 4SD, and 6SD quantification method, respectively, compared to standard LGE images (all p values < 0.001). However, with the FWHM method, no differences in scar size were found (p = 0.06).

CONCLUSIONS

LGE image quality improved significantly using a DL-based reconstruction algorithm. However, this algorithm has an important impact on scar quantification depending on which quantification technique is used. The FWHM method is preferred because of its independency of NR. Clinicians should be aware of this impact on scar quantification, as DL-based reconstruction algorithms are being used.

KEY POINTS

• The image quality based on (subjective) visual assessment and image sharpness of late gadolinium enhancement images improved significantly using a deep learning-based reconstruction algorithm that aims to reconstruct high signal-to-noise images using a denoising technique. • Special care should be taken when scar size is quantified using thresholding techniques with different standard deviations above remote myocardium because of the large impact of these advanced image enhancement algorithms. • The full width at half maximum method is recommended to quantify scar size when deep learning algorithms based on noise reduction are used, as this method is the least sensitive to the level of noise and showed the best agreement with visual late gadolinium enhancement assessment.