Incremental Values of T1 Mapping in the Prediction of Sudden Cardiac Death Risk in Hypertrophic Cardiomyopathy: A Comparison With Two Guidelines

The Prognostic Value of Left Ventricular Entropy From T1 Mapping in Patients With Hypertrophic Cardiomyopathy

Background

The prognostic value of left ventricular (LV) entropy in hypertrophic cardiomyopathy (HCM) is unclear.

Objectives

This study aimed to assess the prognostic value of LV entropy from T1 mapping in HCM.

Methods

A total of 748 participants with HCM, who underwent cardiovascular magnetic resonance (CMR), were consecutively enrolled. LV entropy was quantified by native T1 mapping. A competing risk analysis and a Cox proportional hazards regression analysis were performed to identify potential associations of LV entropy with sudden cardiac death (SCD) and cardiovascular death (CVD), respectively.

Results

A total of 40 patients with HCM experienced SCD, and 65 experienced CVD during a median follow-up of 43 months. Participants with increased LV entropy (≥4.06) were more likely to experience SCD and CVD (all P < 0.05) in the entire study cohort or the subgroup with low late gadolinium enhancement (LGE) extent (<15%). After adjustment for the European Society of Cardiology predictors and the presence of high LGE extent (≥15%), LV mean entropy was an independent predictor for SCD (HR: 1.03; all P < 0.05) by the multivariable competing risk analysis and CVD (HR: 1.06; 95% CI: 1.03-1.09; P < 0.001) by multivariable Cox regression analysis.

Conclusions

LV mean entropy derived from native T1 mapping, reflecting myocardial tissue heterogeneity, was an independent predictor of SCD and CVD in participants with HCM. (Cardiac Magnetic Resonance Imaging Clinical Application Registration Study; ChiCTR1900024094).

Multiparametric Mapping via Cardiovascular Magnetic Resonance in the Risk Stratification of Ventricular Arrhythmias and Sudden Cardiac Death

Risk stratification for malignant ventricular arrhythmias and sudden cardiac death is a daunting task for physicians in daily practice. Multiparametric mapping sequences obtained via cardiovascular magnetic resonance imaging can improve the risk stratification for malignant ventricular arrhythmias by unveiling the presence of pathophysiological pro-arrhythmogenic processes. However, their employment in clinical practice is still restricted. The present review explores the current evidence supporting the association between mapping abnormalities and the risk of ventricular arrhythmias in several cardiovascular diseases. The key message is that further clinical studies are needed to test the additional value of mapping techniques beyond conventional cardiovascular magnetic resonance imaging for selecting patients eligible for an implantable cardioverter defibrillator.

Post-hoc standardisation of parametric T1 maps in cardiovascular magnetic resonance imaging: a proof-of-concept

BACKGROUND

In cardiovascular magnetic resonance imaging parametric T1 mapping lacks universally valid reference values. This limits its extensive use in the clinical routine. The aim of this work was the introduction of our self-developed Magnetic Resonance Imaging Software for Standardization (MARISSA) as a post-hoc standardisation approach.

METHODS

Our standardisation approach minimises the bias of confounding parameters (CPs) on the base of regression models. 214 healthy subjects with 814 parametric T1 maps were used for training those models on the CPs: age, gender, scanner and sequence. The training dataset included both sex, eleven different scanners and eight different sequences. The regression model type and four other adjustable standardisation parameters were optimised among 240 tested settings to achieve the lowest coefficient of variation, as measure for the inter-subject variability, in the mean T1 value across the healthy test datasets (HTE, N = 40, 156 T1 maps). The HTE were then compared to 135 patients with left ventricular hypertrophy including hypertrophic cardiomyopathy (HCM, N = 112, 121 T1 maps) and amyloidosis (AMY, N = 24, 24 T1 maps) after applying the best performing standardisation pipeline (BPSP) to evaluate the diagnostic accuracy.

FINDINGS

The BPSP reduced the COV of the HTE from 12.47% to 5.81%. Sensitivity and specificity reached 95.83% / 91.67% between HTE and AMY, 71.90% / 72.44% between HTE and HCM, and 87.50% / 98.35% between HCM and AMY.

INTERPRETATION

Regarding the BPSP, MARISSA enabled the comparability of T1 maps independently of CPs while keeping the discrimination of healthy and patient groups as found in literature.

FUNDING

This study was supported by the BMBF / DZHK.

Current perspectives of sudden cardiac death management in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant disorder characterized by left ventricular hypertrophy. Sudden cardiac death (SCD) is a rare but the most catastrophic complication in patients with HCM. Implantable cardioverter-defibrillators (ICDs) are widely recognized as effective preventive measures for SCD. Individualized risk stratification and early intervention in HCM can significantly improve patient prognosis. In this study, we review the latest findings regarding pathogenesis, risk stratification, and prevention of SCD in HCM patients, highlighting the clinic practice of cardiovascular magnetic resonance imaging for SCD management.

Contemporary review on pediatric hypertrophic cardiomyopathy: insights into detection and management

Hypertrophic cardiomyopathy is the most common genetic cardiac disorder and is defined by the presence of left ventricular (LV) hypertrophy in the absence of a condition capable of producing such a magnitude of hypertrophy. Over the past decade, guidelines on the screening, diagnostic, and management protocols of pediatric primary (i.e., sarcomeric) HCM have undergone significant revisions. Important revisions include changes to the appropriate screening age, the role of cardiac MRI (CMR) in HCM diagnosis, and the introduction of individualized pediatric SCD risk assessment models like HCM Risk-kids and PRIMaCY. This review explores open uncertainties in pediatric HCM that merit further attention, such as the divergent American and European recommendations on CMR use in HCM screening and diagnosis, the need for incorporating key genetic and imaging parameters into HCM-Risk Kids and PRIMaCY, the best method of quantifying myocardial fibrosis and its prognostic utility in SCD prediction for pediatric HCM, devising appropriate genotype- and phenotype-based exercise recommendations, and use of heart failure medications that can reverse cardiac remodeling in pediatric HCM.

Motion-compensated T1 mapping in cardiovascular magnetic resonance imaging: a technical review

T 1 mapping is becoming a staple magnetic resonance imaging method for diagnosing myocardial diseases such as ischemic cardiomyopathy, hypertrophic cardiomyopathy, myocarditis, and more. Clinically, most T 1 mapping sequences acquire a single slice at a single cardiac phase across a 10 to 15-heartbeat breath-hold, with one to three slices acquired in total. This leaves opportunities for improving patient comfort and information density by acquiring data across multiple cardiac phases in free-running acquisitions and across multiple respiratory phases in free-breathing acquisitions. Scanning in the presence of cardiac and respiratory motion requires more complex motion characterization and compensation. Most clinical mapping sequences use 2D single-slice acquisitions; however newer techniques allow for motion-compensated reconstructions in three dimensions and beyond. To further address confounding factors and improve measurement accuracy, T 1 maps can be acquired jointly with other quantitative parameters such as T 2 , T 2 ∗ , fat fraction, and more. These multiparametric acquisitions allow for constrained reconstruction approaches that isolate contributions to T 1 from other motion and relaxation mechanisms. In this review, we examine the state of the literature in motion-corrected and motion-resolved T 1 mapping, with potential future directions for further technical development and clinical translation.

The Value of Myocardial Fibrosis Parameters Derived from Cardiac Magnetic Resonance Imaging in Risk Stratification for Patients with Hypertrophic Cardiomyopathy

RATIONALE AND OBJECTIVES

The aim of the study was to determine whether myocardial fibrosis parameters of cardiac magnetic resonance imaging (MRI) has added value in the risk stratification of hypertrophic cardiomyopathy (HCM) patients.

MATERIALS AND METHODS

In this retrospective study, 108 patients with HCM (mean age ± standard deviation, 55.5 ± 13.4 years) were included from January 2019 to April 2022, and were followed up for 2 years to record sudden cardiac death (SCD) adverse events. All HCM patients underwent cardiac MRI and were divided into a training cohort (n = 81; mean age, 56.1 ± 13.0 years) and a validation cohort (n = 27; mean age, 57.8 ± 13.9 years). According to the presence of SCD risk factors defined by the 2020 AHA/ACC guidelines, HCM patients were classified into low-risk and high-risk groups. Cardiac MRI features, including late gadolinium enhancement (LGE), T1 mapping, and extracellular volume fraction (ECV), were assessed and compared between the two groups. Logistic regression analysis was used to select the optimal predictors of SCD from cardiac MRI features and HCM Risk-SCD score to construct prediction models. Receiver operating curve (ROC) analysis was used to assess the predictive performance of the constructed prediction model. Cox regression analysis was also used to determine the optimal predictors of SCD adverse events.

RESULTS

Multivariate logistic analysis showed that the global ECV was the single myocardial fibrosis parameter predictive of the risk of SCD (p < 0.001). The areas under the ROC curves (AUC) of global ECV were higher than those of LGE, global native T1, global postcontrast T1, and HCM Risk-SCD (AUC = 0.85 vs. 0.74, 0.77, 0.63, 0.78). An integrative risk stratification model combining global ECV (odds ratio, 1.36 [95% CI: 1.16-1.60]; p < 0.001) and HCM Risk-SCD score (odds ratio, 1.63 [95% CI: 1.08-2.47]; p < 0.001) achieved an AUC of 0.89 (95% CI: 0.81-0.96) in the training cohort, which was significantly higher than that of HCM Risk-SCD score alone (p = 0.03). The AUC of the integrative model was 0.93 (95% CI: 0.84-1.00) in the validation cohort. Multivariate Cox regression analysis also showed that the global ECV was an independent predictor of SCD adverse events (hazard ratio, 1.27 [95% CI: 1.10-1.47]).

CONCLUSION

The ECV derived from cardiac MRI is comparable to the HCM Risk-SCD scale in predicting the SCD risk stratification in patients with HCM.

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.

Solving the Riddle of Sudden Cardiac Death in Hypertrophic Cardiomyopathy: The Added Role of Cardiac Magnetic Resonance

Cardiac magnetic resonance (CMR) has been recently implemented in clinical practice to refine the daunting task of establishing the risk of sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM). We present an exemplificative case highlighting the practical clinical utility of this imaging modality in a 24-year-old man newly diagnosed with an apical HCM. CMR was essential in unmasking a high risk of SCD, which appeared low-intermediate after traditional risk assessment. A discussion examines the essential role of CMR in guiding the patient's therapy and underlines the added value of CMR, including novel and potential CMR parameters, compared to traditional imaging assessment for SCD risk stratification.

Incident Clinical and Mortality Associations of Myocardial Native T1 in the UK Biobank

BACKGROUND

Cardiac magnetic resonance native T1-mapping provides noninvasive, quantitative, and contrast-free myocardial characterization. However, its predictive value in population cohorts has not been studied.

OBJECTIVES

The associations of native T1 with incident events were evaluated in 42,308 UK Biobank participants over 3.17 ± 1.53 years of prospective follow-up.

METHODS

Native T1-mapping was performed in 1 midventricular short-axis slice using the Shortened Modified Look-Locker Inversion recovery technique (WIP780B) in 1.5-T scanners (Siemens Healthcare). Global myocardial T1 was calculated using an automated tool. Associations of T1 with: 1) prevalent risk factors (eg, diabetes, hypertension, and high cholesterol); 2) prevalent and incident diseases (eg, any cardiovascular disease [CVD], any brain disease, valvular heart disease, heart failure, nonischemic cardiomyopathies, cardiac arrhythmias, atrial fibrillation [AF], myocardial infarction, ischemic heart disease [IHD], and stroke); and 3) mortality (eg, all-cause, CVD, and IHD) were examined. Results are reported as odds ratios (ORs) or HRs per SD increment of T1 value with 95% CIs and corrected P values, from logistic and Cox proportional hazards regression models.

RESULTS

Higher myocardial T1 was associated with greater odds of a range of prevalent conditions (eg, any CVD, brain disease, heart failure, nonischemic cardiomyopathies, AF, stroke, and diabetes). The strongest relationships were with heart failure (OR: 1.41 [95% CI: 1.26-1.57]; P = 1.60 × 10-9) and nonischemic cardiomyopathies (OR: 1.40 [95% CI: 1.16-1.66]; P = 2.42 × 10-4). Native T1 was positively associated with incident AF (HR: 1.25 [95% CI: 1.10-1.43]; P = 9.19 × 10-4), incident heart failure (HR: 1.47 [95% CI: 1.31-1.65]; P = 4.79 × 10-11), all-cause mortality (HR: 1.24 [95% CI: 1.12-1.36]; P = 1.51 × 10-5), CVD mortality (HR: 1.40 [95% CI: 1.14-1.73]; P = 0.0014), and IHD mortality (HR: 1.36 [95% CI: 1.03-1.80]; P = 0.0310).

CONCLUSIONS

This large population study demonstrates the utility of myocardial native T1-mapping for disease discrimination and outcome prediction.

Identification of fibrosis in hypertrophic cardiomyopathy: a radiomic study on cardiac magnetic resonance cine imaging

OBJECTIVES

Hypertrophic cardiomyopathy (HCM) often requires repeated enhanced cardiac magnetic resonance (CMR) imaging to detect fibrosis. We aimed to develop a practical model based on cine imaging to help identify patients with high risk of fibrosis and screen out patients without fibrosis to avoid unnecessary injection of contrast.

METHODS

A total of 273 patients with HCM were divided into training and test sets at a ratio of 7:3. Logistic regression analysis was used to find predictive image features to construct CMR model. Radiomic features were derived from the maximal wall thickness (MWT) slice and entire left ventricular (LV) myocardium. Extreme gradient boosting was used to build radiomic models. Integrated models were established by fusing image features and radiomic models. The model performance was validated in the test set and assessed by ROC and calibration curve and decision curve analysis (DCA).

RESULTS

We established five prediction models, including CMR, R1 (based on the MWT slice), R2 (based on the entire LV myocardium), and two integrated models (I_CMR+R1 and I_CMR+R2). In the test set, I_CMR+R2 model had an excellent AUC value (0.898), diagnostic accuracy (89.02%), sensitivity (92.54%), and F1 score (93.23%) in identifying patients with positive late gadolinium enhancement. The calibration plots and DCA indicated that I_CMR+R2 model was well-calibrated and presented a better net benefit than other models.

CONCLUSIONS

A predictive model that fused image and radiomic features from the entire LV myocardium had good diagnostic performance, robustness, and clinical utility.

KEY POINTS

• Hypertrophic cardiomyopathy is prone to fibrosis, requiring patients to undergo repeated enhanced cardiac magnetic resonance imaging to detect fibrosis over their lifetime follow-up. • A predictive model based on the entire left ventricular myocardium outperformed a model based on a slice of the maximal wall thickness. • A predictive model that fused image and radiomic features from the entire left ventricular myocardium had excellent diagnostic performance, robustness, and clinical utility.

Catheter Ablation for Ventricular Arrhythmias in Hypertrophic Cardiomyopathy

Implantable cardioverter-defibrillators are the mainstay of therapy for prevention of sudden cardiac death in high-risk patients with hypertrophic cardiomyopathy (HCM). Catheter ablation is a useful option for patients with recurrent, drug refractory monomorphic ventricular tachycardia (VT), and device therapy. Compared with other nonischemic substrates, there are limited data on the role and outcomes of catheter ablation in HCM. The challenges of VT ablation in HCM patients include deep intramural and epicardial substrates, suboptimal power delivery, and higher recurrence due to progression of disease. Patient selection, using cardiac MRI scar localization, and optimizing ablation techniques can improve outcomes in these patients.

Imaging for risk stratification of sudden cardiac death

Sudden cardiac death (SCD) can be effectively prevented with the use of implantable cardioverter-defibrillator (ICD). Current guidelines advocate an ICD for primary prevention in the presence of an left ventricular ejection fraction (LVEF) ≤ 35%. The majority of individuals that experience SCD, however, have an LVEF > 35%. Multimodality cardiac imaging has the ability to visualize the three factors responsible for arrhythmia-mediated SCD, namely substrate, trigger and modulator. Advances in cardiac imaging techniques have allowed improved SCD risk stratification, especially in the group of patients with an LVEF > 35%. However, clinical integration of cardiac imaging for SCD risk stratification will require more comparative data between modalities and parameters, as well as evidence of an impact on outcomes. The current review represents an update on the use of multimodality imaging techniques for SCD risk stratification.

Myocardial Extracellular Volume Fraction Measured by Cardiac Magnetic Resonance Imaging Negatively Correlates With Cardiomyocyte Breadth in a Healthy Porcine Model

Background

The extracellular volume fraction (ECV) derived from cardiac magnetic resonance imaging (MRI) is extensively used to evaluate myocardial fibrosis. However, due to the limited histological verification in healthy individuals, it remains unclear whether the size of cardiomyocytes may play a potential role in the physiological changes of ECV. The aim of this study was to examine the association between cardiomyocyte size and myocardial ECV by using a healthy porcine model.

Methods

Sixteen domestic healthy pigs were anesthetized and underwent cardiac MRI with mechanical controlled breathing. Intravenous contrast medium was introduced at a dose of 0.2–0.25 mmol/kg. The interventricular septum ECV was calculated using an established MRI procedure, which was based on the pre- and post-contrast T1 values of the heart and individual blood hematocrit. The cardiomyocyte breadth (CmyB) in cross section was measured by hematoxylin and eosin staining to reflect the cardiomyocyte size.

Results

Data were successfully acquired from 14 pigs. The CmyB was obtained from the myocardial tissues corresponding to the region of interest on cardiac MRI. The mean ± SD of the ECV was 0.253 ± 0.043, and the mean ± SD of the CmyB was 10.02 ± 0.84 μm. The ECV exhibited a negative correlation with the CmyB (r = −0.729, p = 0.003).

Conclusion

The myocardial ECV detected by cardiac MRI is negatively correlated with the CmyB in healthy pigs, demonstrating that the size of cardiomyocytes is potentially associated with the ECV under physiological conditions.

Multimodality Cardiac Imaging in Cardiomyopathies: From Diagnosis to Prognosis

Cardiomyopathies are a group of structural and/or functional myocardial disorders which encompasses hypertrophic, dilated, arrhythmogenic, restrictive, and other cardiomyopathies. Multimodality cardiac imaging techniques are the cornerstone of cardiomyopathy diagnosis; transthoracic echocardiography should be the first-line imaging modality due to its availability, and diagnosis should be confirmed by cardiovascular magnetic resonance, which will provide more accurate morphologic and functional information, as well as extensive tissue characterization. Multimodality cardiac imaging techniques are also essential in assessing the prognosis of patients with cardiomyopathies; left ventricular ejection fraction and late gadolinium enhancement are two of the main variables used for risk stratification, and they are incorporated into clinical practice guidelines. Finally, periodic testing with cardiac imaging techniques should also be performed due to the evolving and progressive natural history of most cardiomyopathies.