Association Between Midwall Late Gadolinium Enhancement and Sudden Cardiac Death in Patients With Dilated Cardiomyopathy and Mild and Moderate Left Ventricular Systolic Dysfunction

The application of radiology for dilated cardiomyopathy diagnosis, treatment, and prognosis prediction: a bibliometric analysis

Background

Radiology plays a highly crucial role in the diagnosis, treatment, and prognosis prediction of dilated cardiomyopathy (DCM). Related research has increased rapidly over the past few years, but systematic analyses are lacking. This study thus aimed to provide a reference for further research by analyzing the knowledge field, development trends, and research hotspots of radiology in DCM using bibliometric methods.

Methods

Articles on the radiology of DCM published between 2002 and 2021 in the Web of Science Core Collection database (WoSCCd) were searched and analyzed. Data were retrieved and analyzed using CiteSpace V, VOSviewer, and Scimago Graphic software, and included the name, research institution, and nationality of authors; journals of publication; and the number of citations.

Results

A total of 4,257 articles were identified on radiology of DCM from WoSCCd. The number of articles published in this field has grown steadily from 2002 to 2021 and is expected to reach 392 annually by 2024. According to subfields, the number of papers published in cardiac magnetic resonance field increased steadily. The authors from the United States published the most (1,364 articles, 32.04%) articles. The author with the most articles published was Bax JJ (54 articles, 1.27%) from Leiden University Medical Center. The most cited article was titled "2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure", with 138 citations. Citation-based clustering showed that arrhythmogenic cardiomyopathy, T1 mapping, and endomyocardial biopsy are the current hots pots for research in DCM radiology. The most frequently occurring keyword was "dilated cardiomyopathy". The keyword-based clusters mainly included "late gadolinium enhancement", "congestive heart failure", "cardiovascular magnetic resonance", "sudden cardiac death", "ventricular arrhythmia", and "cardiac resynchronization therapy".

Conclusions

The United States and Northern Europe are the most influential countries in research on DCM radiology, with many leading distinguished research institutions. The current research hots pots are myocardial fibrosis, risk stratification of ventricular arrhythmia, the prognosis of cardiac resynchronization therapy (CRT) treatment, and subtype classification of DCM.

Phenotyping heart failure by cardiac magnetic resonance imaging of cardiac macro- and microscopic structure: state of the art review

Heart failure demographics have evolved in past decades with the development of improved diagnostics, therapies, and prevention. Cardiac magnetic resonance (CMR) has developed in a similar timeframe to become the gold-standard non-invasive imaging modality for characterizing diseases causing heart failure. CMR techniques to assess cardiac morphology and function have progressed since their first use in the 1980s. Increasingly efficient acquisition protocols generate high spatial and temporal resolution images in less time. This has enabled new methods of characterizing cardiac systolic and diastolic function such as strain analysis, exercise real-time cine imaging and four-dimensional flow. A key strength of CMR is its ability to non-invasively interrogate the myocardial tissue composition. Gadolinium contrast agents revolutionized non-invasive cardiac imaging with the late gadolinium enhancement technique. Further advances enabled quantitative parametric mapping to increase sensitivity at detecting diffuse pathology. Novel methods such as diffusion tensor imaging and artificial intelligence-enhanced image generation are on the horizon. Magnetic resonance spectroscopy (MRS) provides a window into the molecular environment of the myocardium. Phosphorus (31P) spectroscopy can inform the status of cardiac energetics in health and disease. Proton (1H) spectroscopy complements this by measuring creatine and intramyocardial lipids. Hyperpolarized carbon (13C) spectroscopy is a novel method that could further our understanding of dynamic cardiac metabolism. CMR of other organs such as the lungs may add further depth into phenotypes of heart failure. The vast capabilities of CMR should be deployed and interpreted in context of current heart failure challenges.

The Predictive Value of Myocardial Native T1 Mapping Radiomics in Dilated Cardiomyopathy: A Study in a Chinese Population

BACKGROUND

Investigation of the factors influencing dilated cardiomyopathy (DCM) prognosis is important as it could facilitate risk stratification and guide clinical decision-making.

PURPOSE

To assess the prognostic value of magnetic resonance imaging (MRI) radiomics analysis of native T1 mapping in DCM.

STUDY TYPE

Prospective.

SUBJECTS

Three hundred and thirty consecutive patients with non-ischemic DCM (mean age 48.42 ± 14.20 years, 247 males).

FIELD STRENGTH/SEQUENCE

Balanced steady-state free precession and modified Look-Locker inversion recovery T1 mapping sequences at 3 T.

ASSESSMENT

Clinical characteristics, conventional MRI parameters (ventricular volumes, function, and mass), native myocardial T1, and radiomics features extracted from native T1 mapping were obtained. The study endpoint was defined as all-cause mortality or heart transplantation. Models were developed based on 1) clinical data; 2) radiomics data based on T1 mapping; 3) clinical and conventional MRI data; 4) clinical, conventional MRI, and native T1 data; and 5) clinical, conventional MRI, and radiomics T1 mapping data. Each prediction model was trained according to follow-up results with AdaBoost, random forest, and logistic regression classifiers.

STATISTICAL TESTS

The predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1 score by 5-fold cross-validation.

RESULTS

During a median follow-up of 53.5 months (interquartile range, 41.6-69.5 months), 77 patients with DCM experienced all-cause mortality or heart transplantation. The random forest model based on radiomics combined with clinical and conventional MRI parameters achieved the best performance, with AUC and F1 score of 0.95 and 0.89, respectively.

DATA CONCLUSION

A machine-learning framework based on radiomics analysis of T1 mapping prognosis prediction in DCM.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

Impact of Cardiac Magnetic Resonance to Arrhythmic Risk Stratification in Nonischemic Cardiomyopathy

Left ventricular ejection fraction-based arrhythmic risk stratification in nonischemic cardiomyopathy (NICM) is insufficient and has led to the failure of primary prevention implantable cardioverter defibrillator trials, mainly due to the inability of selecting patients at high risk for sudden cardiac death (SCD). Cardiac magnetic resonance offers unique opportunities for tissue characterization and has gained a central role in arrhythmic risk stratification in NICM. The presence of myocardial scar, denoted by late gadolinium enhancement, is a significant, independent, and strong predictor of ventricular arrhythmias and SCD with high negative predictive value. T1 maps and extracellular volume fraction, which are able to quantify diffuse fibrosis, hold promise as complementary tools but need confirmatory results from large studies.

The Role of Cardiovascular Magnetic Resonance Imaging in Patients with Cardiac Arrhythmias

Cardiac arrhythmias are associated with significant morbidity, mortality and poor quality of life. Cardiovascular magnetic resonance (CMR) imaging, with its unsurpassed capability of non-invasive tissue characterisation, high accuracy, and reproducibility of measurements, plays an integral role in determining the underlying aetiology of cardiac arrhytmias. CMR can reliably diagnose previous myocardial infarction, non-ischemic cardiomyopathy, characterise congenital heart disease and valvular pathologies, and also detect the underlying substrate concealed on conventional investigations in a significant proportion of patients with arrhythmias. Determining the underlying substrate of arrhythmia is of paramount importance for treatment planning and prognosis. However, CMR imaging in patients with irregular heart rates can be problematic. Understanding the different ways to overcome the limitations of CMR in arrhythmia is essential for providing high-quality imaging, comprehensive information, and definitive answers in this diverse group of patients.

Impact of late gadolinium-enhanced cardiac MRI on arrhythmic and mortality outcomes in nonischemic dilated cardiomyopathy: updated systematic review and meta-analysis

Risk stratification based mainly on the impairment of left ventricular ejection fraction has limited performance in patients with nonischemic dilated cardiomyopathy (NIDCM). Evidence is rapidly growing for the impact of myocardial scar identified by late gadolinium enhancement (LGE) cardiac magnetic resonance imaging (CMR) on cardiovascular events. We aim to assess the prognostic value of LGE on long-term arrhythmic and mortality outcomes in patients with NIDCM. PubMed, Scopus, and Cochrane databases were searched from inception to January 21, 2022. Studies that included disease-specific subpopulations of NIDCM were excluded. Data were independently extracted and combined via random-effects meta-analysis using a generic inverse-variance strategy. Data from 60 studies comprising 15,217 patients were analyzed with a 3-year median follow-up. The presence of LGE was associated with major ventricular arrhythmic events (pooled OR: 3.99; 95% CI 3.08, 5.16), all-cause mortality (pooled OR: 2.14; 95% CI 1.81, 2.52), cardiovascular mortality (pooled OR 2.83; 95% CI 2.23, 3.60), and heart failure hospitalization (pooled OR: 2.53; 95% CI 1.78, 3.59). Real-world evidence suggests that the presence of LGE on CMR was a strong predictor of adverse long-term outcomes in patients with NIDCM. Scar assessment should be incorporated as a primary determinant in the patient selection criteria for primary prophylactic implantable cardioverter-defibrillator placement.

Nonspecific intraventricular conduction delay predicts the prognosis of dilated cardiomyopathy

PURPOSE

Left bundle branch block (LBBB) has been confirmed to be independently associated with adverse outcomes in dilated cardiomyopathy (DCM). However, prognostic data on nonspecific intraventricular conduction delay (NSIVCD) are still limited and conflicting. We aimed to evaluate the prognosis of DCM with NSIVCD.

METHODS

A total of 548 DCM patients who underwent cardiovascular magnetic resonance imaging (CMR) from January 2016 to December 2017 were consecutively enrolled. The cohort was divided into four groups: 87 with LBBB, 27 with RBBB, 61 with NSIVCD, and 373 without intraventricular conduction delay (IVCD). After a median follow-up of 58 months (interquartile range: 47-65), 123 patients reached the composite endpoints, which included cardiovascular death, heart transplantation, and malignant arrhythmias. The associations between different patterns of IVCD and the outcomes of DCM were analysed by Kaplan‒Meier analysis and Cox proportional hazards regression analysis.

RESULTS

Of 548 DCM patients, there were 398 males (72.6%), and the average age was 46 ± 15 years, ranging from 18 to 76 years. In Kaplan‒Meier analysis, patients with NSIVCD and LBBB showed higher event rates than patients without IVCD, while RBBB patients did not. By multivariate Cox regression analysis, LBBB, NSIVCD, NYHA class, left ventricular ejection fraction (LVEF), indexed left ventricular end-diastolic diameter (LVEDDI), percentage of late gadolinium enhancement mass (LGE%), and global longitudinal strain (GLS) were found to be independently associated with the outcomes of DCM.

CONCLUSIONS

In addition to LBBB, NSIVCD was an unfavourable prognostic marker in patients with DCM, independent of LVEDDI, NYHA class, LVEF, LGE%, and GLS.

Septal Midwall Late Gadolinium Enhancement in Ischemic Cardiomyopathy and Nonischemic Dilated Cardiomyopathy-Characteristics and Prognosis

Septal midwall late gadolinium enhancement (LGE) is a characteristic finding on cardiac magnetic resonance imaging (CMR) in nonischemic dilated cardiomyopathy (DCM) and is associated with adverse events. Its significance in ischemic cardiomyopathy (ICM) is unknown. With this multicenter observational study, we aimed to study the characteristics of septal midwall LGE and evaluate its prognostic value in ICM. A total of 1,084 patients with an impaired left ventricular (LV) ejection fraction (<50%) on LGE-CMR, either because of ICM (53%) or DCM, were included retrospectively. Septal midwall LGE was defined as midmyocardial stripe-like or patchy LGE in septal segments and was present in 10% of patients with ICM compared with 34% of patients with DCM (p <0.001). It was significantly associated with larger LV volumes and lower LV ejection fraction, irrespective of etiology. The primary endpoint was all-cause mortality and secondary endpoint was ventricular arrhythmias (VAs), including resuscitated cardiac arrest, sustained VA, and appropriate implantable cardioverter-defibrillator (ICD) therapy. During a median follow-up of 2.7 years, we found a significant association between septal midwall LGE and mortality in patients with DCM (hazard ratio [HR] 1.92, p = 0.03), but not in patients with ICM (HR 1.35, p = 0.39). Risk of VAs was significantly higher in patients with septal midwall LGE on CMR, both in DCM (HR 2.80, p <0.01) and in ICM (HR 2.70, p <0.01). In conclusion, septal midwall LGE, typically seen in DCM, was also present in 10% of patients with ICM and was associated with increased LV dilation and worse function, irrespective of etiology. When present, septal midwall LGE was associated with adverse outcome.

Dark-Blood Late Gadolinium Enhancement MRI Is Noninferior to Bright-Blood LGE in Non-Ischemic Cardiomyopathies

(1) Background and Objectives: Dark-blood late gadolinium enhancement has been shown to be a reliable cardiac magnetic resonance (CMR) method for assessing viability and depicting myocardial scarring in ischemic cardiomyopathy. The aim of this study was to evaluate dark-blood LGE imaging compared with conventional bright-blood LGE for the detection of myocardial scarring in non-ischemic cardiomyopathies. (2) Materials and Methods: Patients with suspected non-ischemic cardiomyopathy were prospectively enrolled in this single-centre study from January 2020 to March 2023. All patients underwent 1.5 T CMR with both dark-blood and conventional bright-blood LGE imaging. Corresponding short-axis stacks of both techniques were analysed for the presence, distribution, pattern, and localisation of LGE, as well as the quantitative scar size (%). (3) Results: 343 patients (age 44 ± 17 years; 124 women) with suspected non-ischemic cardiomyopathy were examined. LGE was detected in 123 of 343 cases (36%) with excellent inter-reader agreement (κ 0.97-0.99) for both LGE techniques. Dark-blood LGE showed a sensitivity of 99% (CI 98-100), specificity of 99% (CI 98-100), and an accuracy of 99% (CI 99-100) for the detection of non-ischemic scarring. No significant difference in total scar size (%) was observed. Dark-blood imaging with mean 5.35 ± 4.32% enhanced volume of total myocardial volume, bright-blood with 5.24 ± 4.28%, p = 0.84. (4) Conclusions: Dark-blood LGE imaging is non-inferior to conventional bright-blood LGE imaging in detecting non-ischemic scarring. Therefore, dark-blood LGE imaging may become an equivalent method for the detection of both ischemic and non-ischemic scars.

New perspectives in diagnosis and risk stratification of non-ischaemic dilated cardiomyopathy

Dilated cardiomyopathy is a primitive heart muscle condition, characterized by structural and functional abnormalities, in the absence of a specific cause sufficient to determine the disease. It is, though, an 'umbrella' term that describes the final common pathway of different pathogenic processes and gene-environment interactions. Performing an accurate diagnostic workup and appropriate characterization of the patient has a direct impact on the patient's outcome. The physician should adapt a multiparametric approach, including a careful anamnesis and physical examination and integrating imaging data and genetic testing. Aetiological characterization should be pursued, and appropriate arrhythmic risk stratification should be performed. Evaluations should be repeated thoroughly at follow-up, as the disease is dynamical over time and individual risk might evolve. The goal is an all-around characterization of the patient, a personalized medicine approach, in order to establish a diagnosis and therapy tailored for the individual patient.

From the phenotype to precision medicine: an update on the cardiomyopathies diagnostic workflow

Cardiomyopathies are disease of the cardiac muscle largely due to genetic alterations of proteins with 'structural' or 'functional' roles within the cardiomyocyte, going from the regulation of contraction-relaxation, metabolic and energetic processes to ionic fluxes. Modifications occurring to these proteins are responsible, in the vast majority of cases, for the phenotypic manifestations of the disease, including hypertrophic, dilated, arrhythmogenic and restrictive cardiomyopathies. Secondary nonhereditary causes to be excluded include infections, toxicity from drugs or alcohol or medications, hormonal imbalance and so on. Obtaining a phenotypic definition and an etiological diagnosis is becoming increasingly relevant and feasible, thanks to the availability of new tailored treatments and the diagnostic advancements made particularly in the field of genetics. This is, for example, the case for transthyretin cardiac amyloidosis, Fabry disease or dilated cardiomyopathies due to laminopathies. For these diseases, specific medications have been developed, and a more tailored arrhythmic risk stratification guides the implantation of a defibrillator. In addition, new medications directly targeting the altered protein responsible for the phenotype are becoming available (including the myosin inhibitors mavacantem and aficamten, monoclonal antibodies against Ras-MAPK, genetic therapies for sarcoglycanopathies), thus making a precision medicine approach less unrealistic even in the field of cardiomyopathies. For these reasons, a contemporary approach to cardiomyopathies must consider diagnostic algorithms founded on the clinical suspicion of the disease and developed towards a more precise phenotypic definition and etiological diagnosis, based on a multidisciplinary methodology putting together specialists from different disciplines, facilities for advanced imaging testing and genetic and anatomopathological competencies.

Aortic valve calcification and myocardial fibrosis determine outcome following transcatheter aortic valve replacement

AIMS

There is evidence to suggest that the subtype of aortic stenosis (AS), the degree of myocardial fibrosis (MF), and level of aortic valve calcification (AVC) are associated with adverse cardiac outcome in AS. Because little is known about their respective contribution, we sought to investigate their relative importance and interplay as well as their association with adverse cardiac events following transcatheter aortic valve replacement (TAVR).

METHODS AND RESULTS

One hundred consecutive patients with severe AS and indication for TAVR were prospectively enrolled between January 2017 and October 2018. Patients underwent transthoracic echocardiography, multidetector computed tomography, and left ventricular endomyocardial biopsies at the time of TAVR. The final study cohort consisted of 92 patients with a completed study protocol, 39 (42.4%) of whom showed a normal ejection fraction (EF) high-gradient (NEFHG) AS, 13 (14.1%) a low EF high-gradient (LEFHG) AS, 25 (27.2%) a low EF low-gradient (LEFLG) AS, and 15 (16.3%) a paradoxical low-flow, low-gradient (PLFLG) AS. The high-gradient phenotypes (NEFHG and LEFHG) showed the largest amount of AVC (807 ± 421 and 813 ± 281 mm³ , respectively) as compared with the low-gradient phenotypes (LEFLG and PLFLG; 503 ± 326 and 555 ± 594 mm³ , respectively, P < 0.05). Conversely, MF was most prevalent in low-output phenotypes (LEFLG > LEFHG > PLFLG > NEFHG, P < 0.05). This was paralleled by a greater cardiovascular (CV) mortality within 600 days after TAVR (LEFLG 28% > PLFLG 26.7% > LEFHG 15.4% > NEFHG 2.5%; P = 0.023). In patients with a high MF burden, a higher AVC was associated with a lower mortality following TAVR (P = 0.045, hazard ratio 0.261, 95% confidence interval 0.07-0.97).

CONCLUSIONS

MF is associated with adverse CV outcome following TAVR, which is most prevalent in low EF situations. In the presence of large MF burden, patients with large AVC have better outcome following TAVR. Conversely, worse outcome in large MF and relatively little AVC may be explained by a relative prominence of an underlying cardiomyopathy. The better survival rates in large AVC patients following TAVR indicate TAVR induced relief of severe AS-associated pressure overload with subsequently improved outcome.

Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI

Background

Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. We apply this strategy to train a deep learning (DL) model to classify the anatomical position of CMR images. This allows the automated removal of slices that do not contain the left ventricular (LV) myocardium.

Methods

Anonymised LV short-axis slices from 300 random scans (3,552 individual images) were extracted. Each image's anatomical position relative to the LV was labelled using two different strategies performed for 5 hours each: (I) 'one-image-at-a-time': each image labelled according to its position: 'too basal', 'LV', or 'too apical' individually by one of three experts; and (II) 'multiple-image-ranking': three independent experts ordered slices according to their relative position from 'most-basal' to 'most apical' in batches of eight until each image had been viewed at least 3 times. Two convolutional neural networks were trained for a three-way classification task (each model using data from one labelling strategy). The models' performance was evaluated by accuracy, F1-score, and area under the receiver operating characteristics curve (ROC AUC).

Results

After excluding images with artefact, 3,323 images were labelled by both strategies. The model trained using labels from the 'multiple-image-ranking strategy' performed better than the model using the 'one-image-at-a-time' labelling strategy (accuracy 86% vs. 72%, P=0.02; F1-score 0.86 vs. 0.75; ROC AUC 0.95 vs. 0.86). For expert clinicians performing this task manually the intra-observer variability was low (Cohen's κ=0.90), but the inter-observer variability was higher (Cohen's κ=0.77).

Conclusions

We present proof of concept that, given the same clinician labelling effort, comparing multiple images side-by-side using a 'multiple-image-ranking' strategy achieves ground truth labels for DL more accurately than by classifying images individually. We demonstrate a potential clinical application: the automatic removal of unrequired CMR images. This leads to increased efficiency by focussing human and machine attention on images which are needed to answer clinical questions.

The extent of late gadolinium enhancement predicts mortality, sudden death and major adverse cardiovascular events in patients with nonischaemic cardiomyopathy: a systematic review and meta-analysis

AIM

To conduct a systematic review and meta-analysis with the objective of evaluating the prognostic value of extent of myocardial fibrosis by late gadolinium-enhanced cardiac magnetic resonance imaging (CMR) in non-ischaemic dilated cardiomyopathy (NICM).

MATERIAL AND METHODS

The databases PubMed, EMBASE, and Google Scholar were searched for studies that investigated the prognostic value of quantification of late gadolinium enhancement (LGE) in patients with NICM. Unadjusted and adjusted hazard ratios (HRs) of uniformly defined predictors were pooled for meta-analysis.

RESULTS

Fourteen studies were retrieved from 884 publications for this systematic review and meta-analysis. In total, 4,336 patients (mean age 51.2 years; mean follow-up 35.1 months) were included in the analysis. Meta-analysis showed the extent of LGE was associated with an increased risk of all-cause mortality (HR: 1.07/1% LGE; 95% confidence interval [CI]: 1.03-1.11; p=0.0003), composite arrhythmic endpoint (HR: 1.09/1% LGE; 95% CI: 1.03-1.15; p=0.002) and major adverse cardiovascular events (MACE; HR: 1.06/1% LGE; 95% CI: 1.02-1.11; p=0.005). After adjusting for baseline characteristics, the higher extent of LGE remained associated with the risk of all-cause mortality (HR_adjusted: 1.07/1% LGE; 95% CI: 1.00-1.14; p=0.04), also strongly associated with the risk of composite arrhythmic endpoint (HR_adjusted: 1.07; 95% CI: 1.02-1.012; p=0.004) and MACE (HR_adjusted: 1.04; 95% CI: 1.01-1.08; p=0.005).

CONCLUSIONS

Extent of LGE in CMR predicts all-cause mortality, arrhythmic events, and MACE. Collectively, these findings emphasise that extent of LGE by CMR may have value for optimising current predictive models for clinical events or mortality in patients with NICM.

Cardiac MRI to Predict Sudden Cardiac Death Risk in Dilated Cardiomyopathy

Background Sudden cardiac death (SCD) is one of the leading causes of death in individuals with nonischemic dilated cardiomyopathy (DCM). However, the risk stratification of SCD events remains challenging in clinical practice. Purpose To determine whether myocardial tissue characterization with cardiac MRI could be used to predict SCD events and to explore a SCD stratification algorithm in nonischemic DCM. Materials and Methods In this prospective single-center study, adults with nonischemic DCM who underwent cardiac MRI between June 2012 and August 2020 were enrolled. SCD-related events included SCD, appropriate implantable cardioverter-defibrillator shock, and resuscitation after cardiac arrest. Competing risk regression analysis and Kaplan-Meier analysis were performed to identify the association of myocardial tissue characterization with outcomes. Results Among the 858 participants (mean age, 48 years; age range, 18-83 years; 603 men), 70 (8%) participants experienced SCD-related events during a median follow-up of 33.0 months. In multivariable competing risk analysis, late gadolinium enhancement (LGE) (hazard ratio [HR], 1.87; 95% CI: 1.07, 3.27; P = .03), native T1 (per 10-msec increase: HR, 1.07; 95% CI: 1.04, 1.11; P < .001), and extracellular volume fraction (per 3% increase: HR, 1.26; 95% CI: 1.11, 1.44; P < .001) were independent predictors of SCD-related events after adjustment of systolic blood pressure, atrial fibrillation, and left ventricular ejection fraction. An SCD risk stratification category was developed with a combination of native T1 and LGE. Participants with a native T1 value 4 or more SDs above the mean (1382 msec) had the highest annual SCD-related events rate of 9.3%, and participants with a native T1 value 2 SDs below the mean (1292 msec) and negative LGE had the lowest rate of 0.6%. This category showed good prediction ability (C statistic = 0.74) and could be used to discriminate SCD risk and competing heart failure risk. Conclusion Myocardial tissue characteristics derived from cardiac MRI were independent predictors of sudden cardiac death (SCD)-related events in individuals with nonischemic dilated cardiomyopathy and could be used to stratify participants according to different SCD risk categories. Clinical trial registration no. ChiCTR1800017058 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sakuma in this issue.

Cardiac MRI Risk Stratification for Dilated Cardiomyopathy with Left Ventricular Ejection Fraction of 35% or Higher

Background Studies over the past 15 years have demonstrated that a considerable number of patients with dilated cardiomyopathy (DCM) who died from sudden cardiac death (SCD) had a left ventricular (LV) ejection fraction (LVEF) of 35% or higher. Purpose To identify clinical and cardiac MRI risk factors for adverse events in patients with DCM and LVEF of 35% or higher. Materials and Methods In this retrospective study, consecutive patients with DCM and LVEF of 35% or higher who underwent cardiac MRI between January 2010 and December 2017 were included. The primary end point was a composite of SCD or aborted SCD. The secondary end point was a composite of all-cause mortality, heart transplant, or hospitalization for heart failure. The risk factors for the primary and secondary end points were identified with multivariable Cox analysis. Results A total of 466 patients with DCM and LVEF of 35% or higher (mean age, 44 years ± 14 [SD]; 358 men) were included. During a mean follow-up of 79 months ± 30 (SD) (range, 7-143 months), 40 patients reached the primary end point and 61 reached the secondary end point. In the adjusted analysis, age (hazard ratio [HR], 1.03 per year [95% CI: 1.00, 1.05]; P = .04), family history of SCD (HR, 3.4 [95% CI: 1.3, 8.8]; P = .01), New York Heart Association (NYHA) class III or IV (HR vs NYHA class I or II, 2.1 [95% CI: 1.1, 3.9]; P = .02), and myocardial scar at late gadolinium enhancement (LGE) MRI greater than or equal to 7.1% of the LV mass (HR, 4.4 [95% CI: 2.4, 8.3]; P < .001) were associated with SCD or aborted SCD. For the composite secondary end point, LGE greater than or equal to 7.1% of the LV mass (HR vs LGE <7.1%, 2.0 [95% CI: 1.2, 3.4]; P = .01), left atrial maximum volume index, and reduced global longitudinal strain were independent predictors. Conclusion For patients with dilated cardiomyopathy and left ventricular (LV) ejection fraction of 35% or higher, cardiac MRI-defined myocardial scar greater than or equal to 7.1% of the LV mass was associated with sudden cardiac death (SCD) or aborted SCD. © RSNA, 2022 Online supplemental material is available for this article.

Single cell and lineage tracing studies reveal the impact of CD34+ cells on myocardial fibrosis during heart failure

BACKGROUND

CD34⁺ cells have been used to treat the patients with heart failure, but the outcome is variable. It is of great significance to scrutinize the fate and the mechanism of CD34⁺ cell differentiation in vivo during heart failure and explore its intervention strategy.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) of the total non-cardiomyocytes and enriched Cd34-tdTomato⁺ lineage cells in the murine (male Cd34-CreERT2; Rosa26-tdTomato mice) pressure overload model (transverse aortic constriction, TAC), and total non-cardiomyocytes from human adult hearts. Then, in order to determine the origin of CD34⁺ cell that plays a role in myocardial fibrosis, bone marrow transplantation model was performed. Furthermore, to further clarify the role of CD34 + cells in myocardial remodeling in response to TAC injury, we generated Cd34-CreERT2; Rosa26-eGFP-DTA (Cre/DTA) mice.

RESULTS

By analyzing the transcriptomes of 59,505 single cells from the mouse heart and 22,537 single cells from the human heart, we illustrated the dynamics of cell landscape during the progression of heart hypertrophy, including CD34⁺ cells, fibroblasts, endothelial and immune cells. By combining genetic lineage tracing and bone marrow transplantation models, we demonstrated that non-bone-marrow-derived CD34⁺ cells give rise to fibroblasts and endothelial cells, while bone-marrow-derived CD34⁺ cell turned into immune cells only in response to pressure overload. Interestingly, partial depletion of CD34⁺ cells alleviated the severity of myocardial fibrosis with a significant improvement of cardiac function in Cd34-CreERT2; Rosa26-eGFP-DTA model. Similar changes of non-cardiomyocyte composition and cellular heterogeneity of heart failure were also observed in human patient with heart failure. Furthermore, immunostaining showed a double labeling of CD34 and fibroblast markers in human heart tissue. Mechanistically, our single-cell pseudotime analysis of scRNA-seq data and in vitro cell culture study revealed that Wnt-β-catenin and TGFβ1/Smad pathways are critical in regulating CD34⁺ cell differentiation toward fibroblasts.

CONCLUSIONS

Our study provides a cellular landscape of CD34⁺ cell-derived cells in the hypertrophy heart of human and animal models, indicating that non-bone-marrow-derived CD34⁺ cells differentiating into fibroblasts largely account for cardiac fibrosis. These findings may provide novel insights for the pathogenesis of cardiac fibrosis and have further potential therapeutic implications for the heart failure.

Diffuse myocardial fibrosis associates with incident ventricular arrhythmia in implantable cardioverter defibrillator recipients

Background

Diffuse myocardial fibrosis (DMF) quantified by extracellular volume (ECV) may represent a vulnerable phenotype and associate with life threatening ventricular arrhythmias more than focal myocardial fibrosis. This principle remains important because 1) risk stratification for implantable cardioverter defibrillators (ICD) remains challenging, and 2) DMF may respond to current or emerging medical therapies (reversible substrate).

Objectives

To evaluate the association between quantified by ECV in myocardium without focal fibrosis by late gadolinium enhancement (LGE) with time from ICD implantation to 1) appropriate shock, or 2) shock or anti-tachycardia pacing.

Methods

Among patients referred for cardiovascular magnetic resonance (CMR) without congenital disease, hypertrophic cardiomyopathy, or amyloidosis who received ICDs (n=215), we used Cox regression to associate ECV with incident ICD therapy.

Results

After a median of 2.9 (IQR 1.5-4.2) years, 25 surviving patients experienced ICD shock and 44 experienced shock or anti-tachycardia pacing. ECV ranged from 20.2% to 39.4%. No patient with ECV<25% experienced an ICD shock. ECV associated with both endpoints, e.g., hazard ratio 2.17 (95%CI 1.17-4.00) for every 5% increase in ECV, p=0.014 in a stepwise model for ICD shock adjusting for ICD indication, age, smoking, atrial fibrillation, and myocardial infarction, whereas focal fibrosis by LGE and global longitudinal strain (GLS) did not.

Conclusions

DMF measured by ECV associates with ventricular arrhythmias requiring ICD therapy in a dose-response fashion, even adjusting for potential confounding variables, focal fibrosis by LGE, and GLS. ECV-based risk stratification and DMF representing a therapeutic target to prevent ventricular arrhythmia warrant further investigation.

Artificial Intelligence in Cardiovascular CT and MR Imaging

The technological development of Artificial Intelligence (AI) has grown rapidly in recent years. The applications of AI to cardiovascular imaging are various and could improve the radiologists' workflow, speeding up acquisition and post-processing time, increasing image quality and diagnostic accuracy. Several studies have already proved AI applications in Coronary Computed Tomography Angiography and Cardiac Magnetic Resonance, including automatic evaluation of calcium score, quantification of coronary stenosis and plaque analysis, or the automatic quantification of heart volumes and myocardial tissue characterization. The aim of this review is to summarize the latest advances in the field of AI applied to cardiovascular CT and MR imaging.

DSP-Related Cardiomyopathy as a Distinct Clinical Entity? Emerging Evidence from an Italian Cohort

Variants in desmoplakin gene (DSP MIM *125647) have been usually associated with Arrhythmogenic Cardiomyopathy (ACM), or Dilated Cardiomyopathy (DCM) inherited in an autosomal dominant manner. A cohort of 18 probands, characterized as heterozygotes for DSP variants by a target Next Generation Sequencing (NGS) cardiomyopathy panel, was analyzed. Cardiological, genetic data, and imaging features were retrospectively collected. A total of 16 DSP heterozygous pathogenic or likely pathogenic variants were identified, 75% (n = 12) truncating variants, n = 2 missense variants, n = 1 splicing variant, and n = 1 duplication variant. The mean age at diagnosis was 40.61 years (IQR 31-47.25), 61% of patients being asymptomatic (n = 11, New York Heart Association (NYHA) class I) and 39% mildly symptomatic (n = 7, NYHA class II). Notably, 39% of patients (n = 7) presented with a clinical history of presumed myocarditis episodes, characterized by chest pain, myocardial enzyme release, 12-lead electrocardiogram abnormalities with normal coronary arteries, which were recurrent in 57% of cases (n = 4). About half of the patients (55%, n = 10) presented with a varied degree of left ventricular enlargement (LVE), four showing biventricular involvement. Eleven patients (61%) underwent implantable cardioverter defibrillator (ICD) implantation, with a mean age of 46.81 years (IQR 36.00-64.00). Cardiac magnetic resonance imaging (CMRI) identified in all 18 patients a delayed enhancement (DE) area consistent with left ventricular (LV) myocardial fibrosis, with a larger localization and extent in patients presenting with recurrent episodes of myocardial injury. These clinical and genetic data confirm that DSP-related cardiomyopathy may represent a distinct clinical entity characterized by a high arrhythmic burden, variable degrees of LVE, Late Gadolinium Enhancement (LGE) with subepicardial distribution and episodes of myocarditis-like picture.

Clinical application of CMR in cardiomyopathies: evolving concepts and techniques : A position paper of myocardial and pericardial diseases and cardiac magnetic resonance working groups of Italian society of cardiology

Cardiac magnetic resonance (CMR) has become an essential tool for the evaluation of patients affected or at risk of developing cardiomyopathies (CMPs). In fact, CMR not only provides precise data on cardiac volumes, wall thickness, mass and systolic function but it also a non-invasive characterization of myocardial tissue, thus helping the early diagnosis and the precise phenotyping of the different CMPs, which is essential for early and individualized treatment of patients. Furthermore, several CMR characteristics, such as the presence of extensive LGE or abnormal mapping values, are emerging as prognostic markers, therefore helping to define patients' risk. Lastly new experimental CMR techniques are under investigation and might contribute to widen our knowledge in the field of CMPs. In this perspective, CMR appears an essential tool to be systematically applied in the diagnostic and prognostic work-up of CMPs in clinical practice. This review provides a deep overview of clinical applicability of standard and emerging CMR techniques in the management of CMPs.

The scar: the wind in the perfect storm-insights into the mysterious living tissue originating ventricular arrhythmias

BACKGROUND

Arrhythmic death is very common among patients with structural heart disease, and it is estimated that in European countries, 1 per 1000 inhabitants yearly dies for sudden cardiac death (SCD), mainly as a result of ventricular arrhythmias (VA). The scar is the result of cardiac remodelling process that occurs in several cardiomyopathies, both ischemic and non-ischemic, and is considered the perfect substrate for re-entrant and non-re-entrant arrhythmias.

METHODS

Our aim was to review published evidence on the histological and electrophysiological properties of myocardial scar and to review the central role of cardiac magnetic resonance (CMR) in assessing ventricular arrhythmias substrate and its potential implication in risk stratification of SCD.

RESULTS

Scarring process affects both structural and electrical myocardial properties and paves the background for enhanced arrhythmogenicity. Non-uniform anisotropic conduction, gap junctions remodelling, source to sink mismatch and refractoriness dispersion are some of the underlining mechanisms contributing to arrhythmic potential of the scar. All these mechanisms lead to the initiation and maintenance of VA. CMR has a crucial role in the evaluation of patients suffering from VA, as it is considered the gold standard imaging test for scar characterization. Mounting evidences support the use of CMR not only for the definition of gross scar features, as size, localization and transmurality, but also for the identification of possible conducting channels suitable of discrete ablation. Moreover, several studies call out the CMR-based scar characterization as a stratification tool useful in selecting patients at risk of SCD and amenable to implantable cardioverter-defibrillator (ICD) implantation.

CONCLUSIONS

Scar represents the substrate of ventricular arrhythmias. CMR, defining scar presence and its features, may be a useful tool for guiding ablation procedures and for identifying patients at risk of SCD amenable to ICD therapy.

Association of Late-Gadolinium Enhancement in Cardiac Magnetic Resonance with Mortality, Ventricular Arrhythmias, and Heart Failure in Patients with Non-Ischemic Cardiomyopathy: A Systematic Review and Meta-Analysis

Background

Late gadolinium enhancement (LGE) on cardiac magnetic resonance is a predictor of adverse events in patients with nonischemic cardiomyopathy (NICM).

Objective

This meta-analysis evaluated the correlation between LGE and mortality, ventricular arrhythmias (VAs) and sudden cardiac death (SCD), and heart failure (HF) outcomes.

Methods

A literature search was conducted for studies reporting the association between LGE in NICM and the study endpoints. The primary endpoint was mortality. Secondary endpoints included VA and SCD, HF hospitalization, improvement in left ventricular ejection fraction (LVEF) to >35%, and heart transplantation referral. The search was not restricted to time or publication status. The minimum follow-up duration was 1 year.

Results

A total of 46 studies and 10,548 NICM patients (4610 with LGE, 5938 without LGE) were included; mean follow-up was 3 years (range 13-71 months). LGE was associated with increased mortality (odds ratio [OR] 2.9; 95% confidence interval [CI] 2.3-3.8; P < .01) and VA and SCD (OR 4.6; 95% CI 3.5-6.0; P < .01). LGE was associated with an increased risk of HF hospitalization (OR 3.4; 95% CI 2.3-5.0; P < .01), referral for transplantation (OR 5.1; 95% CI 2.5-10.4; P < .01), and decreased incidence of LVEF improvement to >35% (OR 0.2; 95% CI 0.03-0.85; P = .03).

Conclusion

LGE in NICM patients is associated with increased mortality, VA and SCD, and HF hospitalization and heart transplantation referral during long-term follow up. Given these competing risks of mortality and HF progression, prospective randomized controlled trials are required to determine if LGE is useful for guiding prophylactic implantable cardioverter-defibrillator placement in NICM patients.

Longitudinal assessment of structural phenotype in Brugada syndrome using cardiac magnetic resonance imaging

Background

Despite historically being considered a channelopathy, subtle structural changes have been reported in Brugada syndrome (BrS) on histopathology and cardiac magnetic resonance (CMR) imaging. It is not known if these structural changes progress over time.

Objective

The study sought to assess if structural changes in BrS evolve over time with serial CMR assessment and to investigate the utility of parametric mapping techniques to identify diffuse fibrosis in BrS.

Methods

Patients with a diagnosis of BrS based on international guidelines and normal CMR at least 3 years prior to the study period were invited to undergo repeat CMR. CMR images were analyzed de novo and compared at baseline and follow-up.

Results

Eighteen patients with BrS (72% men; mean age at follow-up 47.4 ± 8.9 years) underwent serial CMR with an average of 5.0 ± 1.7 years between scans. No patients had late gadolinium enhancement (LGE) on baseline CMR, but 4 (22%) developed LGE on follow-up, typically localized to the right ventricular (RV) side of the basal septum. RV end-systolic volume increased over time (P = .04) and was associated with a trend toward reduction in RV ejection fraction (P = .07). Four patients showed a reduction in RV ejection fraction >10%. There was no evidence of diffuse myocardial fibrosis observed on parametric mapping.

Conclusions

Structural changes may evolve over time with development of focal fibrosis, evidenced by LGE on CMR in a significant proportion of patients with BrS. These findings have implications for our understanding of the pathological substrate in BrS and the longitudinal evaluation of patients with BrS.

The Future of Cardiac Magnetic Resonance Clinical Trials

Over the past 2 decades, cardiac magnetic resonance (CMR) has become an essential component of cardiovascular clinical care and contributed to imaging-guided diagnosis and management of coronary artery disease, cardiomyopathy, congenital heart disease, cardio-oncology, valvular, and vascular disease, amongst others. The widespread availability, safety, and capability of CMR to provide corresponding anatomical, physiological, and functional data in 1 imaging session can improve the design and conduct of clinical trials through both a reduction of sample size and provision of important mechanistic data that may augment clinical trial findings. Moreover, prospective imaging-guided strategies using CMR can enhance safety, efficacy, and cost-effectiveness of cardiovascular pathways in clinical practice around the world. As the future of large-scale clinical trial design evolves to integrate personalized medicine, cost-effectiveness, and mechanistic insights of novel therapies, the integration of CMR will continue to play a critical role. In this document, the attributes, limitations, and challenges of CMR's integration into the future design and conduct of clinical trials will also be covered, and recommendations for trialists will be explored. Several prominent examples of clinical trials that test the efficacy of CMR-imaging guided pathways will also be discussed.

State of the art: multimodality imaging in dilated cardiomyopathy

Dilated cardiomyopathy represents a common phenotype expressed in individuals with a family of overlapping myocardial diseases due to acquired and/or genetic susceptibility. Disease trajectory, response to therapy and outcomes vary widely; therefore, further refinement of the diagnosis can help guide therapy and inform prognosis. Multimodality imaging plays a key role in this process, as well as excluding alternative causes which may mimic a primary myocardial disease. The following article discusses the role of different imaging modalities as well as what the future may look like in the context of recent research innovations.

Association of Whole-Heart Myocardial Mechanics by Transthoracic Echocardiography with Presence of Late Gadolinium Enhancement by CMR in Non-Ischemic Dilated Cardiomyopathy

Background: In patients with non-ischemic dilated cardiomyopathy (NIDCM), myocardial fibrosis (MF) is related to adverse cardiovascular outcomes. The purpose of this study was to evaluate the potential relationship between the myocardial mechanics of different chambers of the heart and the presence of MF and to determine the accuracy of the whole-heart myocardial strain parameters to predict MF in patients with NIDCM. Methods: We studied 101 patients (64% male; 50 ± 11 years) with a first-time diagnosis of NIDCM who were referred for a clinical cardiovascular magnetic resonance (CMR) and speckle tracking 2D echocardiography examination. We analyzed MF by late gadolinium enhancement (LGE), and the whole-heart myocardial mechanics were assessed by speckle tracking. The presence of MF was related to worse strain parameters in both ventricles and atria. The strongest correlations were found between MF and left ventricle (LV) global longitudinal strain (GLS) (r = −0.586, p < 0.001), global circumferential strain (GCS) (r = −0.609, p < 0.001), LV ejection fraction (LVEF) (r = 0.662, p < 0.001), and left atrial strain during the reservoir phase (LASr) (r = 0.588, p < 0.001). However, the binary logistic regression analysis revealed that only LV GLS, GCS, and LASr were independently associated with the presence of MF (area under the curves of 0.84, 0.85, and 0.64, respectively). None of the echocardiographic parameters correlated with fibrosis localization. Conclusions: In NIDCM patients, MF is correlated with reduced mechanical parameters in both ventricles and atria. LV GLS, LASr, and LV GCS are the most accurate 2D echocardiography predictive factors for the presence of MF.

Cardiovascular Imaging in China: Yesterday, Today, and Tomorrow

The high prevalence and mortality of cardiovascular diseases in China's large population has increased the use of cardiovascular imaging for the assessment of conditions in recent years. In this study, we review the past 20 years of cardiovascular imaging in China, the increasingly important role played by cardiovascular computed tomography in coronary artery disease and pulmonary embolism assessment, magnetic resonance imaging's use for cardiomyopathy assessment, the development and application of artificial intelligence in cardiovascular imaging, and the future of Chinese cardiovascular imaging.

The role of late gadolinium enhancement in predicting arrhythmic events in cardiac sarcoidosis patients - a mini-review

Sarcoidosis is a multisystem inflammatory disorder with an unknown origin. Symptomatic cardiac involvement is rare and occurs in about 5% of patients with sarcoidosis. Fatal ventricular arrhythmias are the most severe clinical presentation of the disease. Cardiac magnetic resonance (CMR) is a useful non-invasive tool for the risk stratification of ventricular arrhythmias and sudden cardiac death (SCD) in patients with cardiac sarcoidosis (CS). More specifically, late gadolinium enhancement (LGE), a CMR tool for scar detection, has been found to be significantly associated with arrhythmic events in CS patients. This review aims to present the existing evidence regarding the association of LGE with adverse events and especially with fatal ventricular arrhythmias.

Myocardial Viability Testing in the Management of Ischemic Heart Failure

Although major advances have occurred lately in medical therapy, ischemic heart failure remains an important cause of death and disability. Viable myocardium represents a cause of reversible ischemic left ventricular dysfunction. Coronary revascularization may improve left ventricular function and prognosis in patients with viable myocardium. Although patients with impaired left ventricular function and multi-vessel coronary artery disease benefit the most from revascularization, they are at high risk of complications related to revascularization procedure. An important element in selecting the patients for myocardial revascularization is the presence of the viable myocardium. Multiple imaging modalities can assess myocardial viability and predict functional improvement after revascularization, with dobutamine stress echocardiography, nuclear imaging tests and magnetic resonance imaging being the most frequently used. However, the role of myocardial viability testing in the management of patients with ischemic heart failure is still controversial due to the failure of randomized controlled trials of revascularization to reveal clear benefits of viability testing. This review summarizes the current knowledge regarding the concept of viable myocardium, depicts the role and tools for viability testing, discusses the research involving this topic and the controversies related to the utility of myocardial viability testing and provides a patient-centered approach for clinical practice.

Impact of late gadolinium enhancement extent, location, and pattern on ventricular tachycardia and major adverse cardiac events in patients with ischemic vs. non-ischemic cardiomyopathy

Background

Left ventricular late gadolinium enhancement (LGE) by cardiac magnetic resonance (CMR) has been associated with increased risk for life-threatening ventricular tachyarrhythmias. The differences in association between LGE characteristics and prognosis in patients with ischemic (ICM) vs. non-ischemic (NICM) cardiomyopathy is incompletely understood.

Methods

A total of 168 consecutive patients who underwent CMR imaging with either ICM or NICM were included in our study. LGE extent, location and pattern were examined for association to the primary endpoint of ventricular tachycardia (VT) and secondary endpoint of major adverse cardiac events (MACE).

Results

Of 68 (41%) patients with ICM and 97 (59%) patients with NICM, median LGE mass was 15% (IQR 9–28) for the ICM group and 10% (IQR 6–15) for the NICM group. On multivariate analysis for both groups, LGE characteristics were prognostic while LVEF was not. In patients with ICM, septal and apical segment LGE, and involvement of multiple walls predicted both endpoints on multivariate analysis. LGE extent (≥median) and inferior wall LGE independently predicted the primary endpoint. In patients with NICM, anterior, inferior and apical segment LGE, and involvement of multiple walls predicted both endpoints on multivariate analysis. LGE extent (≥median, number of LGE segments, LGE stratified per 5% increase) and midwall LGE were independent predictors of the primary endpoint.

Conclusions

Although LGE was an independent predictor of prognosis in both groups, LGE extent, location, and pattern characteristics were more powerful correlates to worse outcomes in patients with NICM than ICM.

Prognostic Value of Late Gadolinium Enhancement in Left Ventricular Noncompaction: A Multicenter Study

Current diagnostic criteria for left ventricular noncompaction (LVNC) may be poorly related to adverse prognosis. Late gadolinium enhancement (LGE) is a predictor of major adverse cardiovascular events (MACE), but risk stratification of LGE in patients with LVNC remains unclear. We retrospectively analyzed the clinical and cardiovascular magnetic resonance (CMR) data of 75 patients from three institutes and examined the correlation between different LGE types and MACE based on the extent, pattern (including a specific ring-like pattern), and locations of LGE in LVNC. A total of 51 patients (68%) presented LGE. A specific ring-like pattern was observed in 9 (12%). MACE occurred in 29 (38.7%) at 4.3 years of follow-up (interquartile range: 2.1−5.7 years). The adjusted hazard ratio (HR) for patients with ring-like LGE were 6.10 (95% CI, 1.39−26.75, p < 0.05). Free-wall or mid-wall LGE was associated with an increased risk of MACE after adjustment (HR 2.85, 95% CI, 1.31−6.21; HR 4.35, 95% CI, 1.23−15.37, respectively, p < 0.05). The risk of MACE in LVNC significantly increased when the LGE extent was greater than 7.5% and ring-like, multiple segments, and free-wall LGE were associated with MACE. These results suggest the value of LGE risk stratification in patients with LVNC.

The addition of genetic testing and cardiovascular magnetic resonance to routine clinical data for stratification of etiology in dilated cardiomyopathy

Background

Guidelines recommend genetic testing and cardiovascular magnetic resonance (CMR) for the investigation of dilated cardiomyopathy (DCM). However, the incremental value is unclear. We assessed the impact of these investigations in determining etiology.

Methods

Sixty consecutive patients referred with DCM and recruited to our hospital biobank were selected. Six independent experts determined the etiology of each phenotype in a step-wise manner based on (1) routine clinical data, (2) clinical and genetic data and (3) clinical, genetic and CMR data. They indicated their confidence (1-3) in the classification and any changes to management at each step.

Results

Six physicians adjudicated 60 cases. The addition of genetics and CMR resulted in 57 (15.8%) and 26 (7.2%) changes in the classification of etiology, including an increased number of genetic diagnoses and a reduction in idiopathic diagnoses. Diagnostic confidence improved at each step (p < 0.0005). The number of diagnoses made with low confidence reduced from 105 (29.2%) with routine clinical data to 71 (19.7%) following the addition of genetics and 37 (10.3%) with the addition of CMR. The addition of genetics and CMR led to 101 (28.1%) and 112 (31.1%) proposed changes to management, respectively. Interobserver variability showed moderate agreement with clinical data (κ = 0.44) which improved following the addition of genetics (κ = 0.65) and CMR (κ = 0.68).

Conclusion

We demonstrate that genetics and CMR, frequently changed the classification of etiology in DCM, improved confidence and interobserver variability in determining the diagnosis and had an impact on proposed management.

The role of multimodality imaging in the selection for implantable cardioverter-defibrillators in heart failure: A narrative review

Advanced pharmacologic and interventional therapies have improved survival in heart failure. Implantable cardioverter-defibrillators (ICD) have been shown to reduce mortality in patients with heart failure, but the benefit appears to be uneven in this population. We reviewed the evidence showing the benefit of ICD therapy in heart failure patients, the main issues arising from these studies, and the possible answers for a better risk stratification. In addition, we showed that multimodality imaging could improve patient selection for the implantation of ICDs, in both primary and secondary prevention, beyond the selection using only the left ventricular ejection fraction, by concentrating on arrhythmic substrate.

From mid-range to mildly reduced ejection fraction heart failure: A call to treat

The historical classification of heart failure (HF) has considered two distinct subgroups, HF with reduced ejection fraction (HFrEF), generally classified as EF below 40%, and HF with preserved ejection fraction (HFpEF) variably classified as EF above 40%, 45% or 50%. One of the principal reasons behind this distinction was related to presence of effective therapy in HFrEF, but not in HFpEF. Recently the expanding knowledge in the specific subgroup of patient with a LVEF between 41% and 49% and the potential benefit of new therapies and of those used in patients with LVEF below 40%, has led to rename this group as HF with mildly reduced EF (HFmrEF). In this review we discuss the reasons behind this modification, we summarize the main characteristics of HFmrEF the similarities and differences with the two other EF categories, and finally we provide a comprehensive overview of the current available evidence supporting the treatment of patients with HFmrEF.

Advanced imaging for risk stratification for ventricular arrhythmias and sudden cardiac death

Sudden cardiac death (SCD) is a leading cause of mortality, comprising approximately half of all deaths from cardiovascular disease. In the US, the majority of SCD (85%) occurs in patients with ischemic cardiomyopathy (ICM) and a subset in patients with non-ischemic cardiomyopathy (NICM), who tend to be younger and whose risk of mortality is less clearly delineated than in ischemic cardiomyopathies. The conventional means of SCD risk stratification has been the determination of the ejection fraction (EF), typically via echocardiography, which is currently a means of determining candidacy for primary prevention in the form of implantable cardiac defibrillators (ICDs). Advanced cardiac imaging methods such as cardiac magnetic resonance imaging (CMR), single-photon emission computerized tomography (SPECT) and positron emission tomography (PET), and computed tomography (CT) have emerged as promising and non-invasive means of risk stratification for sudden death through their characterization of the underlying myocardial substrate that predisposes to SCD. Late gadolinium enhancement (LGE) on CMR detects myocardial scar, which can inform ICD decision-making. Overall scar burden, region-specific scar burden, and scar heterogeneity have all been studied in risk stratification. PET and SPECT are nuclear methods that determine myocardial viability and innervation, as well as inflammation. CT can be used for assessment of myocardial fat and its association with reentrant circuits. Emerging methodologies include the development of "virtual hearts" using complex electrophysiologic modeling derived from CMR to attempt to predict arrhythmic susceptibility. Recent developments have paired novel machine learning (ML) algorithms with established imaging techniques to improve predictive performance. The use of advanced imaging to augment risk stratification for sudden death is increasingly well-established and may soon have an expanded role in clinical decision-making. ML could help shift this paradigm further by advancing variable discovery and data analysis.

ECG as a risk stratification tool in patients with wearable cardioverter-defibrillator

BACKGROUND

The wearable cardioverter defibrillator (WCD) is increasingly used in patients at elevated risk for ventricular arrhythmias but not fulfilling the indications for an implantable cardioverter defibrillator (ICD). Currently, there is an insufficient risk prediction of fatal arrhythmias in patients at risk. In this study, we assessed the prognostic role of baseline electrocardiogram (ECG) in WCD patients.

METHODS

WCD patients from diverse clinical institutions in Germany (n = 227) were retrospectively enrolled and investigated for the incidences of death or ventricular arrhythmias during WCD wearing. In addition, the widely accepted ECG predictors of adverse outcome were analyzed in patients with arrhythmic events.

RESULTS

Life-threatening arrhythmias occurred in 22 (9.7 %) patients, mostly in subjects with ischemic heart disease (15 of 22). There was no difference in baseline left ventricular ejection fraction (LVEF) in subjects with and without arrhythmic events (31.3 ± 7.9 % vs. 32.6 ± 8.3 %; p = 0,24). Patients with arrhythmia exhibited significantly longer QRS duration (109.5 ± 23.1 ms vs. 100.6 ± 22.3 ms, p = 0,04), Tpeak-Tend (Tp-e) (103.1 ± 15.6 ms vs. 93.2 ± 19.2 ms, p = 0,01) and QTc (475.0 ± 60.0 ms vs. 429.6 ± 59.4 ms, p < 0,001) intervals. In contrast, no significant differences were found for incidences of fragmented QRS (27.3 % vs. 24 %, p = 0.79) and inverted/biphasic T-waves (16.6 % vs. 22.7 %, p = 0,55). In multivariate regression analysis both Tp-e (HR 1.03; 95 % CI 1.001-1.057; p = 0.02) and QTc (HR 1.02; 95 % CI 1.006-1.026; p < 0.001) were identified as independent predictors of ventricular arrhythmias. After WCD use, the prophylactic ICD was indicated in 76 patients (33 %) with uneventful clinical course but persistent LVEF ≤35 %. The ECG analysis in these subjects did not reveal any relevant changes in arrhythmogenesis markers.

CONCLUSIONS

ECG repolarization markers Tp-e and QTc are associated with malignant arrhythmias in WCD patients and may be used - in addition to other established risk markers - to identify appropriate patients for ICD implantation.

Isotropic 3D compressed sensing (CS) based sequence is comparable to 2D-LGE in left ventricular scar quantification in different disease entities

The goal of this study was to evaluate a three-dimensional compressed sensing (3D-CS) LGE prototype sequence for the detection and quantification of myocardial fibrosis in patients with chronic myocardial infarction (CMI) and myocarditis (MYC) compared with a 2D-LGE standard. Patients with left-ventricular LGE due to CMI (n = 33) or MYC (n = 20) were prospectively recruited. 2D-LGE and 3D-CS images were acquired in random order at 1.5 Tesla. 3D-CS short axis (SAX) images were reconstructed corresponding to 2D SAX images. LGE was quantitatively assessed on patient and segment level using semi-automated threshold methods. Image quality (4-point scoring system), Contrast-ratio (CR) and acquisition times were compared. There was no significant difference between 2D and 3D sequences regarding global LGE (%) (CMI [2D-LGE: 11.4 ± 7.5; 3D-LGE: 11.5 ± 8.5; p = 0.99]; MYC [2D-LGE: 27.0 ± 15.7; 3D-LGE: 26.2 ± 13.1; p = 0.70]) and segmental LGE-extent (p = 0.63). 3D-CS identified papillary infarction in 5 cases which was not present in 2D images. 2D-LGE acquisition time was shorter (2D: median: 06:59 min [IQR: 05:51-08:18]; 3D: 14:48 min [12:45-16:57]). 3D-CS obtained better quality scores (2D: 2.06 ± 0.56 vs. 3D: 2.29 ± 0.61). CR did not differ (p = 0.63) between basal and apical regions in 3D-CS images but decreased significantly in 2D apical images (CR basal: 2D: 0.77 ± 0.11, 3D: 0.59 ± 0.10; CR apical: 2D: 0.64 ± 0.17, 3D: 0.53 ± 0.11). 3D-LGE shows high congruency with standard LGE and allows better identification of small lesions. However, the current 3D-CS LGE sequence did not provide PSIR reconstruction and acquisition time was longer.

Machine Learning Patient-Specific Prediction of Heart Failure Hospitalization Using Cardiac MRI-Based Phenotype and Electronic Health Information

Background

Heart failure (HF) hospitalization is a dominant contributor of morbidity and healthcare expenditures in patients with systolic HF. Cardiovascular magnetic resonance (CMR) imaging is increasingly employed for the evaluation of HF given capacity to provide highly reproducible phenotypic markers of disease. The combined value of CMR phenotypic markers and patient health information to deliver predictions of future HF events has not been explored. We sought to develop and validate a novel risk model for the patient-specific prediction of time to HF hospitalization using routinely reported CMR variables, patient-reported health status, and electronic health information.

Methods

Standardized data capture was performed for 1,775 consecutive patients with chronic systolic HF referred for CMR imaging. Patient demographics, symptoms, Health-related Quality of Life, pharmacy, and routinely reported CMR features were provided to both machine learning (ML) and competing risk Fine-Gray-based models (FGM) for the prediction of time to HF hospitalization.

Results

The mean age was 59 years with a mean LVEF of 36 ± 11%. The population was evenly distributed between ischemic (52%) and idiopathic non-ischemic cardiomyopathy (48%). Over a median follow-up of 2.79 years (IQR: 1.59–4.04) 333 patients (19%) experienced HF related hospitalization. Both ML and competing risk FGM based models achieved robust performance for the prediction of time to HF hospitalization. Respective 90-day, 1 and 2-year AUC values were 0.87, 0.83, and 0.80 for the ML model, and 0.89, 0.84, and 0.80 for the competing risk FGM-based model in a holdout validation cohort. Patients classified as high-risk by the ML model experienced a 34-fold higher occurrence of HF hospitalization at 90 days vs. the low-risk group.

Conclusion

In this study we demonstrated capacity for routinely reported CMR phenotypic markers and patient health information to be combined for the delivery of patient-specific predictions of time to HF hospitalization. This work supports an evolving migration toward multi-domain data collection for the delivery of personalized risk prediction at time of diagnostic imaging.

Clinical Manifestations, Monitoring, and Prognosis: A Review of Cardiotoxicity After Antitumor Strategy

The development of various antitumor drugs has significantly improved the survival of patients with cancer. Many first-line chemotherapy drugs are cytotoxic and the cardiotoxicity is one of the most significant effects that could leads to poor prognosis and decreased survival rate. Cancer treatment include traditional anthracycline drugs, as well as some new targeted drugs such as trastuzumab and ICIs. These drugs may directly or indirectly cause cardiovascular injury through different mechanisms, and lead to increasing the risk of cardiovascular disease or accelerating the development of cardiovascular disease. Cardiotoxicity is clinically manifested by arrhythmia, decreased cardiac function, or even sudden death. The cardiotoxicity caused by traditional chemotherapy drugs such as anthracyclines are significantly known. The cardiotoxicity of some new antitumor drugs such like immune checkpoint inhibitors (ICIs) is also relatively clear and requiring further observation and verification. This review is focused on major three drugs with relatively high incidence of cardiotoxicity and poor prognosis and intended to provide an update on the clinical complications and outcomes of these drugs, and we innovatively summarize the monitoring status of survivors using these drugs and discuss the biomarkers and non-invasive imaging features to identify early cardiotoxicity. Finally, we summarize the prevention that decreasing antitumor drugs-induced cardiotoxicity.

Combination of late gadolinium enhancement and genotype improves prediction of prognosis in non-ischemic dilated cardiomyopathy

Aims

Genotype and left ventricular scar on cardiac magnetic resonance (CMR) are increasingly recognized as risk markers for adverse outcomes in non‐ischaemic dilated cardiomyopathy (DCM). We investigated the combined influence of genotype and late gadolinium enhancement (LGE) in assessing prognosis in a large cohort of patients with DCM.

Methods and results

Outcomes of 600 patients with DCM (53.3 ± 14.1 years, 66% male) who underwent clinical CMR and genetic testing were retrospectively analysed. The primary endpoints were end‐stage heart failure (ESHF) and malignant ventricular arrhythmias (MVA). During a median follow‐up of 2.7 years (interquartile range 1.3–4.9), 24 (4.00%) and 48 (8.00%) patients had ESHF and MVA, respectively. In total, 242 (40.3%) patients had pathogenic/likely pathogenic variants (positive genotype) and 151 (25.2%) had LGE. In survival analysis, positive LGE was associated with MVA and ESHF (both, p < 0.001) while positive genotype was associated with ESHF (p = 0.034) but not with MVA (p = 0.102). Classification of patients according to genotype (G+/G−) and LGE presence (L+/L−) revealed progressively increasing events across L−/G−, L−/G+, L+/G− and L+/G+ groups and resulted in optimized MVA and ESHF prediction (p < 0.001 and p = 0.001, respectively). Hazard ratios for MVA and ESHF in patients with either L+ or G+ compared with those with L−/G− were 4.71 (95% confidence interval: 2.11–10.50, p < 0.001) and 7.92 (95% confidence interval: 1.86–33.78, p < 0.001), respectively.

Conclusion

Classification of patients with DCM according to genotype and LGE improves MVA and ESHF prediction. Scar assessment with CMR and genotyping should be considered to select patients for primary prevention implantable cardioverter‐defibrillator placement.

Prevalence and prognostic significance of ischemic late gadolinium enhancement pattern in non-ischemic dilated cardiomyopathy

BACKGROUND

Typical late gadolinium enhancement (LGE) patterns in dilated cardiomyopathy (DCM) include intramyocardial and subepicardial distribution. However, the ischemic pattern of LGE (subendocardial and transmural) has also been reported in DCM without coronary artery disease (CAD), but its correlates and prognostic significance are still not known. On these bases, this study sought to describe the prevalence and prognostic significance of the ischemic LGE pattern in DCM.

METHODS

A total of 611 DCM patients with available cardiac magnetic resonance were retrospectively analyzed. A composite of all-cause-death, major ventricular arrhythmias (MVAs), heart transplantation (HTx) or ventricular assist device (VAD) implantation was the primary outcome of the study. Secondary outcomes were a composite of sudden cardiac death or MVAs and a composite of death for refractory heart failure, HTx or VAD implantation.

RESULTS

Ischemic LGE was found in 7% of DCM patients without significant CAD or history of myocardial infarction, most commonly inferior/inferolateral/anterolateral. Compared to patients with non-ischemic LGE, those with ischemic LGE had higher prevalence of hypertension and atrial fibrillation or flutter. Ischemic LGE was associated with worse long-term outcomes compared to non-ischemic LGE (36% vs 23% risk of primary outcome events at 5 years respectively, P = .006), and remained an independent predictor of primary outcome after adjustment for clinically and statistically significant variables (adjusted hazard ratio 2.059 [1.055-4.015], P = .034 with respect to non-ischemic LGE).

CONCLUSIONS

The ischemic pattern of LGE is not uncommon among DCM patients without CAD and is independently associated with worse long-term outcomes.

Arrhythmic risk stratification in ischemic, non-ischemic and hypertrophic cardiomyopathy: A two-step multifactorial, electrophysiology study inclusive approach

Annual arrhythmic sudden cardiac death ranges from 0.6% to 4% in ischemic cardiomyopathy (ICM), 1% to 2% in non-ischemic cardiomyopathy (NICM), and 1% in hypertrophic cardiomyopathy (HCM). Towards a more effective arrhythmic risk stratification (ARS) we hereby present a two-step ARS with the usage of seven non-invasive risk factors: Late potentials presence (≥ 2/3 positive criteria), premature ventricular contractions (≥ 30/h), non-sustained ventricular tachycardia (≥ 1episode/24 h), abnormal heart rate turbulence (onset ≥ 0% and slope ≤ 2.5 ms) and reduced deceleration capacity (≤ 4.5 ms), abnormal T wave alternans (≥ 65μV), decreased heart rate variability (SDNN < 70ms), and prolonged QTc interval (> 440 ms in males and > 450 ms in females) which reflect the arrhythmogenic mechanisms for the selection of the intermediate arrhythmic risk patients in the first step. In the second step, these intermediate-risk patients undergo a programmed ventricular stimulation (PVS) for the detection of inducible, truly high-risk ICM and NICM patients, who will benefit from an implantable cardioverter defibrillator. For HCM patients, we also suggest the incorporation of the PVS either for the low HCM Risk-score patients or for the patients with one traditional risk factor in order to improve the inadequate sensitivity of the former and the low specificity of the latter.

Recent Non-Invasive Parameters to Identify Subjects at High Risk of Sudden Cardiac Death

Cardiovascular diseases remain among the leading causes of death worldwide and sudden cardiac death (SCD) accounts for ~25% of these deaths. Despite its epidemiologic relevance, there are very few diagnostic strategies available useful to prevent SCD mainly focused on patients already affected by specific cardiovascular diseases. Unfortunately, most of these parameters exhibit poor positive predictive accuracy. Moreover, there is also a need to identify parameters to stratify the risk of SCD among otherwise healthy subjects. This review aims to provide an update on the most relevant non-invasive diagnostic features to identify patients at higher risk of developing malignant ventricular arrhythmias and SCD.

Cardiac MR: From Theory to Practice

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.