Clinical Cardiac Magnetic Resonance Research Articles

Prediction of cancer therapy related cardiac dysfunction by using a machine learning approach with cardiac magnetic resonance images

Abstract Background There is inconsistent data on the value of baseline and early cardiac function assessment on identifying patients at risk of cancer therapy related cardiac dysfunction (CTRCD). Whether machine learning (ML) approaches applied to cardiac MRI (CMR) images may help risk stratify patients is unclear. Purpose In women with HER2+ breast cancer receiving sequential anthracyclines and trastuzumab we sought to (i) assess if a ML approach applied to pre-cancer therapy and early post anthracycline CMR short axis (SAX) cines can help identify patients at risk for future CTRCD and (ii) whether this approach is superior to using clinical and manual quantitative CMR data. Methods Women with HER2+ breast cancer from the EMBRACE-MRI study underwent 5 CMR studies (pre-cancer therapy, post anthracyclines, 3, 6 and 12 months during trastuzumab). CTRCD was defined using the CREC criteria by end of treatment. Three models were created: 1) clinical data (demographics, cardiovascular risk factors and medications); 2) clinical and manual quantitative CMR data (right and left ventricular volumes and LVEF); and 3) ML model based on SAX cine CMR images only. We focused on the pre-cancer therapy CMR and 1st visit post-anthracycline CMR. All images underwent standardised formatting. A 3D convolutional neural networks model architecture was used. The model consisted of multiple convolutional layers followed by max pooling and global average pooling layers. The output of the convolutional layers were then fed into a dense layer of 128 nodes incorporating an L2 activity regularizer and a subsequent dropout layer. To train and tune the model, the process was iterated 50 times. In each iteration, the patient participant dataset was shuffled, and a random 80% of patients were selected for training and tuning. The tuned model was then applied to the remaining 20% of patients in each iteration, and this entire cycle of shuffling, training, and testing was repeated 50 times with replacement. Area Under the Curve (AUC), accuracy, sensitivity, and specificity were calculated on the test set and averaged across folds to determine each model’s performance. Results 135 women were included (mean age 51.1±9.2 years) mean doxorubicin equivalent was dose 204.9±12.5mg/m2. Cardiovascular risk factors were prevalent: 33 (24%) had a smoking history; 21 (15%) had hypertension. 37 (27%) developed CTRCD. The ML model using baseline CMR cine data only had a higher AUC (0.84 95% CI [0.83-0.86]) for the detection of CTRCD compared to clinical data (0.62 95% CI [0.59-0.65]) and clinical and CMR data (0.62 95% CI [0.60-0.65]). This further improved with the addition of post-anthracycline CMR data (Table 1). Conclusion A ML model examining early cardiac MRI data with short axis cine CMR images performed better than those using clinical or manual quantitative CMR data for the prediction of CTRCD. Further studies including external validation are needed.Table 1 Mean and 95% CIs

Percutaneous revascularization in late-presenting STEMI with absence of viability: effects on left ventricular remodeling and scar

Abstract Introduction In patients with ST-elevation myocardial infarction (STEMI), percutaneous coronary intervention (PCI) should be conducted within 12 hours of symptom onset. The potential benefits attributable to late reperfusion in STEMI fall under the "open artery hypothesis" where the stunned peri-infarction zone after revascularization would restore blood supply and contractility. Purpose To estimate the differences on the LV ejection fraction (LVEF), indexed LV end-systolic volume (iLVESV) and scar in patients with STEMI without viabilitity randomized to optimal medical therapy (OMT) alone or OMT and a late percutaneous coronary intervention (PCI) performed between 24 hours and 30 days after the event. Methods Patients with non-reperfused STEMI were evaluated from September 2021 to June 2022 at a tertiary cardiology hospital. The patients underwent Cardiac Magnetic Resonance (CMR) to assess myocardial viability and were classified as non-viable if they had only 1 wall segment with less than fifty percent thickness of the affected wall with late gadolinium enhancement. The patients were randomized to PCI or OMT alone. CMR was repeated at 6 months to evaluate LVEF, iLVESV and fibrosis. This summary presents a planned partial analysis of the 6-month results (N=51). Descriptive statistics analysis included central and dispersion estimators, or absolute and relative frequencies. To explore the differences between groups and time, Mann-Whitney and Wilcoxon tests were run, and results were given as point-estimates and confidence intervals at 95% (95% CI). A significance level of 5% was adopted for inferential analysis. Results 51 patients (60±11 years, 71% male) were included in the analysis. Of this total, 24 were randomized to PCI + OMT, and 27 to isolated OMT. The groups showed balanced distribution regarding clinical characteristics and initial CMR parameters (LVEF, iLVESV, and fibrosis). The difference in LVEF at the end of 6 months between the OMT and PCI groups was 2.07%, favoring the OMT group; however, this difference was not significant (p= 0.677, 95% CI: -5 to 10). Between the groups, the difference at the end of 6 months in iLVESV was -6.82 ml/m², also without statistical significance (p= 0.858, 95% CI: -19 to 11). There was a significant reduction in the amount of fibrosis in both PCI group with -14.68g (p= 0.011) and in the OMT group with -12.57g (p= 0.009). Detailed results are presented in Table 1. Conclusion Despite a significant reduction in fibrosis in both groups, there was no superiority observed in late PCI compared to isolated OMT in reducing reverse remodeling and fibrosis in patients with non-viable STEMI when compared to isolated OMT.Remodeling changes.

AI derived myocardial left ventricular volumes outperforms clinician segmentation for prediction of all-cause mortality

Abstract Background Measuring heart structure and function drives much cardiac decision making and therapy. Precise quantification is therefore of high importance, but manual (clinician) segmentation introduces measurement variability. Purpose Automated segmentation of cardiac MRI (CMR) left ventricular (LV) volumes provides improved precision but how this translates into clinical outcomes has yet to be defined. In order to test predictive accuracy in a wide range of adverse LV morphologies, we applied AI LV segmentation to patients with coronary disease or cardiomyopathy. Methods Scans were analysed from a retrospective clinical CMR database and mortality data was obtained from a national database. Clinician measurement of indexed LV end-diastolic volume (LVEDVi), LV mass (LVMi), myocardial contraction fraction (MCF: ratio of stroke volume to myocardial volume; a measure of myocardial efficiency) and EF were recorded from clinical reports (all senior clinicians with >5 years level 3 experience) and compared to AI measurement using a segmentation algorithm. This has previously been shown to exceed human precision and required no manual correction (1,2). Random survival forests were built to identify overall predictive value of AI vs clinician derived LV volumes. These are machine-learning algorithms for predicting time-to-event outcomes and can capture complex relationships between predictors and outcome. Random survival forests were built from AI and clinician models with EF, EDVi, LVMi and MCF as predictors for all-cause mortality. A train:test (80:20) split, stratified for outcome was employed. Concordance (C)-indices (measuring predictive accuracy) and permutation importances (measuring significance of each predictor within the model) (Table) with 1000 bootstrapped 95% confidence intervals and p-values were derived. Results 8,299 patients were analysed. Patients were 60(51-70) years old and 37% female. 49% had coronary disease, 25% had DCM and 19% had HCM. At a median follow-up of 5.3 years (IQR 4.2-6.6 years) there were 1,384 deaths (17%). AI derived LV-parameter models had higher predictive accuracy than clinician derived models (C-Indices: 0.66±0.002 vs 0.65±0.005, p<0.001). A subgroup analysis of patients undergoing ischaemia testing for coronary disease was performed (n=3,560) and markers of ischaemia (positive vs negative) and infarction (non-viable vs viable) were included in the models. AI had a higher predictive accuracy compared to clinicians when including these additional predictors (C-Indices: 0.68±0.03 vs 0.63±0.01, p<0.001). Conclusion AI derived LV volumes outperforms clinicians in prediction of all-cause mortality reflecting improved precision. Improvements in predictive accuracy are likely to be clinically important when applied to populations and high-risk groups. Manual clinician segmentation should be superseded by clinician-supervised AI.

Prognostic value of CMR-derived extracellular volume in AL amyloidosis: a multicenter study

Background This study aimed to assess the prognostic value of cardiac magnetic resonance (CMR) variables and compare them with biological and echocardiographic markers in patients with AL cardiac amyloidosis (CA). Methods We conducted a prospective study across three tertiary centres, where patients underwent clinical examination, blood tests, echocardiography, and CMR. The primary endpoint was all-cause mortality. Results A total of 176 patients with AL CA were included, with a median age of 68 years (IQR 58-75). According to the 2004 Mayo Clinic staging, 121 patients (69%) were in stage 3. During a median follow-up of 22 months (IQR 8–48), 45 patients died, and 55 were hospitalized for heart failure. Patients who died had higher NT-proBNP and troponin levels, and lower LVEF, cardiac output, and longitudinal strain. Among CMR variables, extracellular volume (ECV) was most strongly associated with all-cause mortality. In multivariate Cox models, including Mayo Clinic staging, ECV ≥ 0.45 was independently associated with mortality (HR 2.36, CI 95% 1.47–5.60) and also with heart failure hospitalizations (HR 4.10, 95%CI 2.15–8.8). Conclusion ECV is a powerful predictor of outcomes in AL CA, providing additional prognostic value on top of Mayo Clinic staging.

Role of advanced CMR features in identifying a positive genotype of hypertrophic cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease that affects approximately one in 500 people. Cardiac magnetic resonance (CMR) imaging has emerged as a powerful tool for the non-invasive assessment of HCM. CMR can accurately quantify the extent and distribution of hypertrophy, assess the presence and severity of myocardial fibrosis, and detect associated abnormalities. We will study basic and advanced features of CMR in 2 groups of HCM patients with negative and positive genotype, respectively. Materials and methodsThe study population consisted in consecutive HCM patients referred to Centro Cardiologico Monzino who performed both CMR and genetic testing. Clinical CMR images were acquired at 1.5 T Discovery MR450 scanner (GE Healthcare, Milwaukee, Wisconsin)) using standardized protocols T1 mapping, T2 mapping and late gadolinium enhancement (LGE). Population was divided in 2 groups: group 1 with HCM patients with a negative genotype and group 2 with a positive genotype. ResultsThe analytic population consisted of 110 patients: 75 in group 1 and 35 patients in group 2.At CMR evaluation, patients with a positive genotype had higher LV mass (136 vs. 116 g, p = 0.02), LV thickness (17.5 vs. 16.9 mm), right ventricle ejection fraction (63 % vs. 58 %, p = 0.002).Regarding the LGE patients with positive genotype have a higher absolute (33.8 vs 16.7 g, p = 0.0003) and relative LGE mass (31.6 % vs 14.6 %, p = 0.0007). On a segmental analysis all the septum (segments 2, 8, 9, and 14) had a significantly increased native T1 compared to others segments. ECV in the mid antero and infero-septum (segments 8 and 9) have lower values in positive genotype HCM. Interestingly the mean T2 was lower in positive genotype HCM as compared to negative genotype HCM (50,1 ms vs 52,4). ConclusionsOur paper identifies the mid septum (segments 8 and 9) as a key to diagnose a positive genotype HCM.

Test-retest repeatability of myocardial radiomic features from quantitative cardiac magnetic resonance T1 and T2 mapping

Radiomics of cardiac magnetic resonance (MR) imaging has proved to be potentially useful in the study of various myocardial diseases. Therefore, assessing the repeatability degree in radiomic features measurement is of fundamental importance.The aim of this study was to assess test-retest repeatability of myocardial radiomic features extracted from quantitative T1 and T2 maps.A representative group of 24 subjects (mean age 54 ± 18 years) referred for clinical cardiac MR imaging were enrolled in the study. For each subject, T1 and T2 mapping through MOLLI and T2-prepared TrueFISP acquisition sequences, respectively, were performed at 1.5 T. Then, 98 radiomic features of different classes (shape, first-order, second-order) were extracted from a region of interest encompassing the whole left ventricle myocardium in a short axis slice. The repeatability was assessed performing different and complementary analyses: intraclass correlation coefficient (ICC) and limits of agreement (LOA) (i.e., the interval within which 95% of the percentage differences between two repeated measures are expected to lie).Radiomic features were characterized by a relatively wide range of repeatability degree in terms of both ICC and LOA. Overall, 44.9% and 38.8% of radiomic features showed ICC values > 0.75 for T1 and T2 maps, respectively, while 25.5% and 23.4% of radiomic features showed LOA between ±10%. A subset of radiomic features for T1 (Mean, Median, 10Percentile, 90Percentile, RootMeanSquared, Imc2, RunLengthNonUniformityNormalized, RunPercentage and ShortRunEmphasis) and T2 (MaximumDiameter, RunLengthNonUniformityNormalized, RunPercentage, ShortRunEmphasis) maps presented both ICC > 0.75 and LOA between ±5%.Overall, radiomic features extracted from T1 maps showed better repeatability performance than those extracted from T2 maps, with shape features characterized by better repeatability than first-order and textural features. Moreover, only a limited subset of 9 and 4 radiomic features for T1 and T2 maps, respectively, showed high repeatability degree in terms of both ICC and LOA. These results confirm the importance of assessing test-retest repeatability degree in radiomic feature estimation and might be useful for a more effective/reliable use of myocardial T1 and T2 mapping radiomics in clinical or research studies.

Cardiac MRI Oversampling in Heart Digital Twins Improves Preprocedure Ventricular Tachycardia Identification in Postinfarction Patients

BackgroundVentricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients after myocardial infarction. Radiofrequency catheter ablation (RFA) is a modestly effective treatment of VT, but it has limitations and risks. Cardiac magnetic resonance (CMR)–based heart digital twins have emerged as a useful tool for identifying VT circuits for RFA treatment planning. However, the CMR resolution used to reconstruct these digital twins may impact VT circuit predictions, leading to incorrect RFA treatment planning. ObjectivesThis study sought to predict RFA targets in the arrhythmogenic substrate using heart digital twins reconstructed from both clinical and high-resolution 2-dimensional CMR datasets and compare the predictions. MethodsHigh-resolution (1.35 × 1.35 × 3 mm), or oversampled resolution (Ov-Res), short-axis late gadolinium–enhanced CMR was acquired by combining 2 subsequent clinical resolution (Clin-Res) (1.35 × 1.35 × 6 mm) short-axis late gadolinium–enhanced CMR scans from 6 post–myocardial infarction patients undergoing VT ablation and used to reconstruct a total of 3 digital twins (1 Ov-Res, 2 Clin-Res) for each patient. Rapid pacing was used to assess VT circuits and identify the optimal ablation targets in each digital twin. VT circuits predicted by the digital twins were compared with intraprocedural electroanatomic mapping data and used to identify emergent VT. ResultsThe Ov-Res digital twins reduced partial volume effects and better predicted unique VT circuits compared with the Clin-Res digital twins (66.6% vs 54.5%; P < 0.01). Only the Ov-Res digital twin successfully identified emergent VT after a failed initial ablation. ConclusionsDigital twin infarct geometry and VT circuit predictions depend on the magnetic resonance resolution. Ov-Res digital twins better predict VT circuits and emergent VT, which may improve RFA outcomes.

Diphteric Myocarditis: A Case Report on Ecg and Cardiac Imaging Findings with the Levels of Cardiac Enzymes in a 17-Year-Old

Background: Diphtheria, caused by Corynebacterium diphtheriae, remains a life-threatening infectious disease in regions with low vaccination uptake. Myocarditis, a severe cardiac complication of diphtheria, is a leading cause of mortality. Despite the success of vaccines in reducing diphtheria cases, sporadic cases continue to occur, leading to significant health complications. Objective: This case report aims to present the clinical course, electrocardiogram (ECG) and cardiac imaging findings, and serial levels of serum troponin in a 17-year-old patient with diphtheritic myocarditis, and to discuss the management and outcomes. Methods: This study was conducted at Lady Reading Hospital, Peshawar, Pakistan. Ethical approval was obtained from the hospital's ethical review board, and informed consent was acquired from the patient and guardians. A comprehensive diagnostic workup was performed, including clinical examination, laboratory tests, ECG, transthoracic echocardiography (TTE), and cardiac magnetic resonance imaging (MRI). The patient’s vital signs, blood pressure, pulse rate, and jugular venous pressure were recorded. Laboratory tests included leukocyte count, erythrocyte sedimentation rate (ESR), and serial serum troponin measurements. ECG findings were documented, and TTE was used to assess left ventricular ejection fraction (LVEF). Cardiac MRI was performed to identify myocardial edema and delayed enhancement. Treatment included intravenous diuretics, ACE inhibitors, SGLT2 inhibitors, benzylpenicillin, and corticosteroids. Data were analyzed using SPSS version 25.0. Results: The patient presented with a blood pressure of 110/70 mmHg and a pulse rate of 88 bpm. Initial laboratory tests showed a normal leukocyte count, ESR of 45 mm/hr, and troponin levels of 25 ng/ml, which decreased to 21.85 ng/ml and then to 8 ng/ml. ECG revealed ST segment depressions in the precordial leads. TTE showed an initial LVEF of 50%, declining to 35% and then to 28% within a week. Post-treatment, LVEF improved to 44% and subsequently to 55% at four weeks. Cardiac MRI indicated myocardial edema in the apical anterior and apical septal walls, with intramyocardial and subepicardial delayed enhancement. Conclusion: Diphtheritic myocarditis can lead to rapid and severe deterioration of cardiac function. Early diagnosis and aggressive treatment, including the use of advanced imaging techniques and comprehensive medical therapy, can result in significant improvement in cardiac function and patient outcomes. Public health initiatives to improve vaccination coverage are essential to prevent such life-threatening complications.

A machine learning-derived risk score to predict left ventricular diastolic dysfunction from clinical cardiovascular magnetic resonance imaging.

The evaluation of left ventricular diastolic dysfunction (LVDD) by clinical cardiac magnetic resonance (CMR) remains a challenge. We aimed to train and evaluate a machine-learning (ML) algorithm for the assessment of LVDD by clinical CMR variables and to investigate its prognostic value for predicting hospitalized heart failure and all-cause mortality. LVDD was characterized by echocardiography following the ASE guidelines. Eight demographic and nineteen common clinical CMR variables including delayed enhancement were used to train Random Forest models with a Bayesian optimizer. The model was evaluated using bootstrap and five-fold cross-validation. Area under the ROC curve (AUC) was utilized to evaluate the model performance. An ML risk score was used to stratify the risk of heart failure hospitalization and all-cause mortality. A total of 606 consecutive patients underwent CMR and echocardiography within 7 days for cardiovascular disease evaluation. LVDD was present in 303 subjects by echocardiography. The performance of the ML algorithm was good using the CMR variables alone with an AUC of 0.868 (95% CI: 0.811-0.917), which was improved by combining with demographic data yielding an AUC 0.895 (95% CI: 0.845-0.939). The algorithm performed well in an independent validation cohort with AUC 0.810 (0.731-0.874). Subjects with higher ML scores (>0.4121) were associated with increased adjusted hazard ratio for a composite outcome than subjects with lower ML scores (1.72, 95% confidence interval 1.09-2.71). An ML algorithm using variables derived from clinical CMR is effective in identifying patients with LVDD and providing prognostication for adverse clinical outcomes.

Deformation-encoding Deep Learning Transformer for High-Frame-Rate Cardiac Cine MRI.

Purpose To develop a deep learning model for increasing cardiac cine frame rate while maintaining spatial resolution and scan time. Materials and Methods A transformer-based model was trained and tested on a retrospective sample of cine images from 5840 patients (mean age, 55 years ± 19 [SD]; 3527 male patients) referred for clinical cardiac MRI from 2003 to 2021 at nine centers; images were acquired using 1.5- and 3-T scanners from three vendors. Data from three centers were used for training and testing (4:1 ratio). The remaining data were used for external testing. Cines with downsampled frame rates were restored using linear, bicubic, and model-based interpolation. The root mean square error between interpolated and original cine images was modeled using ordinary least squares regression. In a prospective study of 49 participants referred for clinical cardiac MRI (mean age, 56 years ± 13; 25 male participants) and 12 healthy participants (mean age, 51 years ± 16; eight male participants), the model was applied to cines acquired at 25 frames per second (fps), thereby doubling the frame rate, and these interpolated cines were compared with actual 50-fps cines. The preference of two readers based on perceived temporal smoothness and image quality was evaluated using a noninferiority margin of 10%. Results The model generated artifact-free interpolated images. Ordinary least squares regression analysis accounting for vendor and field strength showed lower error (P < .001) with model-based interpolation compared with linear and bicubic interpolation in internal and external test sets. The highest proportion of reader choices was "no preference" (84 of 122) between actual and interpolated 50-fps cines. The 90% CI for the difference between reader proportions favoring collected (15 of 122) and interpolated (23 of 122) high-frame-rate cines was -0.01 to 0.14, indicating noninferiority. Conclusion A transformer-based deep learning model increased cardiac cine frame rates while preserving both spatial resolution and scan time, resulting in images with quality comparable to that of images obtained at actual high frame rates. Keywords: Functional MRI, Heart, Cardiac, Deep Learning, High Frame Rate Supplemental material is available for this article. © RSNA, 2024.

Arrhythmogenic right ventricular cardiomyopathy: Unveiling clinical presentations, CMR insights and prognosis in a single-center retrospective study

Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is a hereditary condition with a prevalence ranging from 1 in 2000 to 1 in 5000 individuals. ARVC is a significant contributor to sudden cardiac death, particularly in young individuals and athletes, and remains challenging to diagnose definitively. We conducted a single-center retrospective study to evaluate the presentations, electrocardiogram findings, and imaging characteristics of ARVC patients evaluated at our center between 2021 and 2023. Notably, our study is the second investigation of ARVC conducted in Pakistan. We report divergent symptom prevalence as compared to the current literature and have incorporated the Task Force Criteria. Despite limited access to cardiac magnetic resonance (CMR) facilities worldwide, our findings underscore the critical role ofCMR in ARVC diagnosis. Our cohort had a mortality rate of 17 % highlighting the importance of early detection and the need for improved diagnostic facilities for ARVC in the region.

AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning.

In cardiac cine imaging, acquiring high-quality data is challenging and time-consuming due to the artifacts generated by the heart's continuous movement. Volumetric, fully isotropic data acquisition with high temporal resolution is, to date, intractable due to MR physics constraints. To assess whole-heart movement under minimal acquisition time, we propose a deep learning model that reconstructs the volumetric shape of multiple cardiac chambers from a limited number of input slices while simultaneously optimizing the slice acquisition orientation for this task. We mimic the current clinical protocols for cardiac imaging and compare the shape reconstruction quality of standard clinical views and optimized views. In our experiments, we show that the jointly trained model achieves accurate high-resolution multi-chamber shape reconstruction with errors of <13 mm HD95 and Dice scores of >80%, indicating its effectiveness in both simulated cardiac cine MRI and clinical cardiac MRI with a wide range of pathological shape variations.

Characteristics and changes of cardiac injury with age in children of Duchenne muscular dystrophy: a prospective cohort study

Objective: To explore the characteristics and changes of cardiac injury with age in Duchenne muscular dystrophy (DMD) and its clinical significance. Methods: A prospective cohort study was conducted. The 215 patients diagnosed with DMD in West China Second Hospital from January 2019 to November 2022 and aged from 6 to 18 years were enrolled. Their clinical data, myocardial injury markers, routine electrocardiogram, cardiac magnetic resonance (CMR) and echocardiography were collected. The patients were divided into five age groups: 6-<8, 8-<10, 10-<12, 12-<14 and 14-18 years of age, and matched with healthy boys respectively. Independent sample t test or Mann-Whitney U test was used to compare the clinical data and CMR indexes between DMD patients and controls in all age subgroups, and to compare the value of left ventricular ejection fraction (LVEF) measured by echocardiography and CMR in each subgroup of DMD patitents. Pearson correlation analysis or Spearman correlation analysis was used to explore the relation between the CMR indexes and age in DMD patients. Results: A total of 215 patients with DMD (all male) and 122 healthy boys were included in the study. There were 75 DMD patients and 23 controls in 6-<8 years of age group, 77 DMD and 28 controls in 8-<10 years of age group, 39 DMD and 23 controls in 10-<12 years of age group, 10 DMD and 31 controls in the 12-<14 years of age group, and 14 DMD and 17 controls in 14-18 years of age group. In the DMD patients, the older the age, the lower the levels of creatine kinase (CK) and creatine kinase isoenzyme (CK-MB). In the 6-<8 years of age group, the CK level was 10 760 (7 800, 15 757) U/L, while in the group of 14-18 years of age, it was 2 369 (1 480, 6 944) U/L. As for CK-MB, it was (189±17) μg/L in the 6-<8 years of age group and (62±16) μg/L in the 14-18 years of age group. Cardiac troponin I remained unchanged in <12 years of age groups, but significantly increased in 12-<14 years of age group, reaching the highest value of 0.112 (0.006, 0.085) μg/L. In the DMD patients, the older the age, the higher the proportion of abnormal electrocardiogram (ECG). In the 6-<8 years of age group, the proportion is 29.3% (22/75), while in the 14-18 years of age group, it was 10/14. Correlation analysis showed that the left ventricular end-diastolic volume index was positively related with age (r=0.18, P=0.015), and the left ventricular stroke volume index and cardiac output index were negatively related with age (r=-0.34 and -0.31, respectively, both P<0.001). In the DMD patients, the older the age, the lower LVEF, with the LVEF decreasing to (49.3±3.1)% in the 14-18 years of age group. The LVEF of DMD cases was significantly lower than that of controls in the age subgroups of 8-<10, 10-<12, 12-<14 and 14-18 years of age groups ((57.9±5.2) % vs. (63.6±0.8)%, 60.7% (55.9%, 61.9%) vs. 63.7% (60.2%, 66.0%), 57.1% (51.8%, 63.4%) vs. 62.1 % (59.5%, 64.5)%, (49.3±3.1) % vs. (61.6±1.3)%, respectively; all P<0.01). In the DMD patients, the older the age, the higher the proportion of positive late gadolinium enhancement (LGE). In the 6-<8 years of age group, it was 22% (11/51), in the 12-<14 years of age group, it was 13/14, and in the 14-18 years of age group, all DMD showed positive LGE. The value of LVEF of DMD cases measured by echocardiography was significantly higher than that measured by CMR in 6-<8 years of age group and 8-<10 years of age group (63.2% (60.1%, 66.4%) vs. 59.1 % (55.4%, 62.9%), and (62.8±5.2) % vs. (57.9±5.2)%, all P<0.001). Conclusion: DMD patients develop cardiac injury in the early stage of the disease, and the incidence of cardiac damage gradually increases with both age and the progression of disease.

Endomyocardial biopsy in clinical practice: the diagnostic yield and insights from a 5-year single-center experience

ObjectivesEndomyocardial biopsy (EMB) is a diagnostic tool for evaluating various cardiac conditions, such as myocarditis and myocardial infiltrative diseases. It is also the gold standard screening technique for detecting allograft rejection after heart transplantation. Despite advances in noninvasive imaging modalities for myocardial tissue characterization, EMB is still necessary for making a definitive diagnosis and determining treatment for certain conditions. Herein, we report our recent experience using EMB and its diagnostic yield. Methods and ResultsWe retrospectively reviewed EMBs performed at our institution from March 2018 through March 2023. Clinical data, including patient characteristics, indication and diagnostic yield of EMB, and procedure-related complications, were collected. Histopathological findings of the biopsies were recorded and classified based on the degree to which they matched the clinical diagnosis and cardiac magnetic resonance imaging (CMR) findings. A total of 212 EMBs obtained in 178 consecutive patients were retrospectively analyzed, with 42 biopsies performed for allograft rejection surveillance (10 patients) and the remaining performed for presumptive diagnosis of acute myocarditis or unexplained cardiomyopathy. Among the non-heart transplant cases, 54.7% of EMBs provided a clear diagnosis. The most common diagnosis was myocarditis (69%), followed by cardiac amyloidosis (CA) (26%). EMB was also helpful in detecting several rare cardiac conditions, such as eosinophilic granulomatosis with polyangiitis (EGPA), Fabry disease, and cardiac sarcoidosis. In a cohort of 101 patients who underwent both CMR and EMB, the results were concordant in 66% of cases. However, in 24.7% of patients, EMB was able to identify pathological conditions where CMR results were inconclusive, highlighting its complementary role in determining an accurate diagnosis. No complications were reported in any of the 212 EMBs performed. ConclusionsWith advances in cardiac imaging modalities, EMB is not routinely indicated for the diagnosis of cardiomyopathy. However, EMB is still an important tool for diagnosing specific cardiac diseases and could be crucial for confirming the diagnosis. EMB is generally safe if performed at experienced centers.

Prognostic value of right atrial strains in arrhythmogenic right ventricular cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by progressive fibrofatty infiltration of atrial and ventricular myocardium resulting in adverse cardiac events. Atrial function has been increasingly recognized as prognostically important for cardiovascular disease. As the right atrial (RA) strain is a sensitive parameter to describe RA function, we aimed to analyze the prognostic value of the RA strain in ARVC. RA strain parameters were derived from cardiac magnetic resonance (CMR) images of 105 participants with definite ARVC. The endpoint was defined as a combination of sudden cardiac death, survival cardiac arrest, and appropriate implantable cardioverter-defibrillator intervention. Cox regression and Kaplan-Meier survival analyses were performed to evaluate the association between RA strain parameters and endpoint. Concordance index (C index), net reclassification index (NRI), and integrated discrimination improvement (IDI) were calculated to assess the incremental value of RA strain in predicting the endpoint. After a median follow-up of 5years, 36 (34.3%) reaching the endpoint displayed significantly reduced RA strain parameters. At Kaplan-Meier analysis, impaired RA reservoir (RARS) and booster strains (RABS) were associated with an increased risk of the endpoint. After adjusting for conventional risk factors, RARS (hazard ratio [HR], 0.956; p = 0.005) and RABS (HR, 0.906; p = 0.002) resulted as independent predictors for endpoint at Cox regression analyses. In addition, RARS and RABS improved prognostic value to clinical risk factors and CMR morphological and functional predictors (all p < 0.05). RARS and RABS were independent predictors for adverse cardiac events, which could provide incremental prognostic value for conventional predictors in ARVC. We evaluated the prognostic value of right atrial strain in ARVC patients and suggested cardiologists consider RA strain as a predictive parameter when evaluating the long-term outcome of ARVC patients in order to formulate better clinical therapy. • Patients with ARVC had significantly reduced RA strain and strain rates compared with healthy participants. • Participants with lower RA reservoir and booster stains were associated with a significantly higher risk of adverse cardiac events. • RA booster and reservoir strain provide incremental value to conventional parameters.

Prognostic value of native T1 and extracellular volume in patients with immunoglubin light-chain amyloidosis

BackgroundCardiac involvement in patients with immunoglubin light-chain amyloidosis (AL) is a major determinant of treatment choice and prognosis, and early identification of high-risk patients can initiate intensive treatment strategies to achieve better survival. This study aimed to investigate the prognostic value of native T1 and ECV in patients with AL-cardiac amyloidosis (CA).MethodsA total of 38 patients (mean age 59 ± 11 years) with AL diagnosed histopathologically from July 2017 to October 2021 were collected consecutively. All patients were performed 3.0-T cardiac magnetic resonance (CMR) including cine, T1 mapping, and late gadolinium enhancement (LGE). Pre- and post-contrast T1 mapping images were transferred to a dedicated research software package (CVI42 v5.11.3) to create parametric T1 and ECV values. In addition, clinical and laboratory data of all patients were collected, and patients or their family members were regularly followed up by telephone every 3 months. The starting point of follow-up was the time of definitive pathological diagnosis, and the main endpoint was all-cause death. Kaplan-Meier analysis and Cox proportional risk model were used to evaluate the association between native T1 and ECV and death in patients with CA.ResultsAfter a median follow-up of 27 (16, 37) months, 12 patients with CA died. Kaplan-Meier analysis showed that elevated native T1 and ECV were closely associated with poor prognosis in patients with CA. The survival rate of patients with ECV > 44% and native T1 > 1389ms were significantly lower than that of patients with ECV ≤ 44% and native T1 ≤ 1389ms (Log-rank P < 0.001), and was not associated with the presence of LGE. After adjusting for clinical risk factors and CMR measurements in a stepwise multivariate Cox regression model, ECV [risk ratio (HR):1.37, 95%CI: 1.09–1.73, P = 0.008] and native T1 (HR:1.01, 95%CI: 1.00-1.02, P = 0.037) remained independent predictors of all-cause mortality in patients with CA.ConclusionsBoth native T1 and ECV were independently prognostic for mortality in patients with CA, and can be used as important indicators for clinical prognosis assessment of AL.

Radiomics from Cardiovascular MR Cine Images for Identifying Patients with Hypertrophic Cardiomyopathy at High Risk for Heart Failure.

Purpose To develop a model integrating radiomics features from cardiac MR cine images with clinical and standard cardiac MRI predictors to identify patients with hypertrophic cardiomyopathy (HCM) at high risk for heart failure (HF). Materials and Methods In this retrospective study, 516 patients with HCM (median age, 51 years [IQR: 40-62]; 367 [71.1%] men) who underwent cardiac MRI from January 2015 to June 2021 were divided into training and validation sets (7:3 ratio). Radiomics features were extracted from cardiac cine images, and radiomics scores were calculated based on reproducible features using the least absolute shrinkage and selection operator Cox regression. Radiomics scores and clinical and standard cardiac MRI predictors that were significantly associated with HF events in univariable Cox regression analysis were incorporated into a multivariable analysis to construct a combined prediction model. Model performance was validated using time-dependent area under the receiver operating characteristic curve (AUC), and the optimal cutoff value of the combined model was determined for patient risk stratification. Results The radiomics score was the strongest predictor for HF events in both univariable (hazard ratio, 10.37; P < .001) and multivariable (hazard ratio, 10.25; P < .001) analyses. The combined model yielded the highest 1- and 3-year AUCs of 0.81 and 0.80, respectively, in the training set and 0.82 and 0.77 in the validation set. Patients stratified as high risk had more than sixfold increased risk of HF events compared with patients at low risk. Conclusion The combined model with radiomics features and clinical and standard cardiac MRI parameters accurately identified patients with HCM at high risk for HF. Keywords: Cardiomyopathies, Outcomes Analysis, Cardiovascular MRI, Hypertrophic Cardiomyopathy, Radiomics, Heart Failure Supplemental material is available for this article. © RSNA, 2024.

Optimizing Clinical Cardiac MRI Workflow through Single Breath-Hold Compressed Sensing Cine: An Evaluation of Feasibility and Efficiency

Background: Although compressed sensing (CS) accelerated cine holds immense potential to replace conventional cardiovascular magnetic resonance (CMR) cine, how to use CS-based cine appropriately during clinical CMR examinations still needs exploring. Methods: A total of 104 patients (46.5 ± 17.1 years) participated in this prospective study. For each participant, a balanced steady state free precession (bSSFP) cine was acquired as a reference, followed by two CS accelerated cine sequences with identical parameters before and after contrast injection. Lastly, a CS accelerated cine sequence with an increased flip angle was obtained. We subsequently compared scanning time, image quality, and biventricular function parameters between these sequences. Results: All CS cine sequences demonstrated significantly shorter acquisition times compared to bSSFPref cine (p &lt; 0.001). The bSSFPref cine showed higher left ventricular ejection fraction (LVEF) than all CS cine sequences (all p &lt; 0.001), but no significant differences in LVEF were observed among the three CS cine sequences. Additionally, CS cine sequences displayed superior global image quality (p &lt; 0.05) and fewer artifacts than bSSFPref cine (p &lt; 0.005). Unenhanced CS cine and enhanced CS cine with increased flip angle showed higher global image quality than other cine sequences (p &lt; 0.005). Conclusion: Single breath-hold CS cine delivers precise biventricular function parameters and offers a range of benefits including shorter scan time, better global image quality, and diminished motion artifacts. This innovative approach holds great promise in replacing conventional bSSFP cine and optimizing the CMR examination workflow.

A novel pathogenic variant in the carnitine transporter gene, SLC22A5, in association with metabolic carnitine deficiency and cardiomyopathy features

BackgroundPrimary carnitine deficiency (PCD) denotes low carnitine levels with an autosomal recessive pattern of inheritance. Cardiomyopathy is the most common cardiac symptom in patients with PCD, and early diagnosis can prevent complications. Next-generation sequencing can identify genetic variants attributable to PCD efficiently.ObjectiveWe aimed to detect the genetic cause of the early manifestations of hypertrophic cardiomyopathy and metabolic abnormalities in an Iranian family.MethodsWe herein describe an 8-year-old boy with symptoms of weakness and lethargy diagnosed with PCD through clinical evaluations, lab tests, echocardiography, and cardiac magnetic resonance imaging. The candidate variant was confirmed through whole-exome sequencing, polymerase chain reaction, and direct Sanger sequencing. The binding efficacy of normal and mutant protein-ligand complexes were evaluated via structural modeling and docking studies.ResultsClinical evaluations, echocardiography, and cardiac magnetic resonance imaging findings revealed hypertrophic cardiomyopathy as a clinical presentation of PCD. Whole-exome sequencing identified a new homozygous variant, SLC22A5 (NM_003060.4), c.821G > A: p.Trp274Ter, associated with carnitine transport. Docking analysis highlighted the impact of the variant on carnitine transport, further indicating its potential role in PCD development.ConclusionsThe c.821G > A: p.Trp274Ter variant in SLC22A5 potentially acted as a pathogenic factor by reducing the binding affinity of organic carnitine transporter type 2 proteins for carnitine. So, the c.821G > A variant may be associated with carnitine deficiency, metabolic abnormalities, and cardiomyopathic characteristics.

Case Report: Optical Pumped Magnetometer Magnetocardiography as a Potential Method of Therapy Monitoring in Fulminant Myocarditis

Background: Fulminant myocarditis (FM) is associated with high mortality and an unfavorable long-term prognosis. However, noninvasive, rapid diagnostic and monitoring methods for FM are lacking. Case summary: This report details the case of a patient diagnosed with FM through a comprehensive assessment involving typical clinical symptoms, laboratory analyses, echocardiographic evidence, and cardiac magnetic resonance (CMR) findings. Before the patient underwent CMR, optical pumped magnetometer magnetocardiography (OPM-MCG) revealed abnormalities characteristic of substantial myocardial injury. After invasive coronary angiography, the patient’s coronary arteries were determined not to exhibit significant stenosis. Additionally, a myocardial bridge was observed in the middle segment of the anterior descending branch of the left coronary artery. Over a 7-month follow-up, the patient’s symptoms showed marked improvement, and the OPM-MCG eventually normalized, aligning with the findings indicated by the CMR. Conclusion: OPM-MCG is a valuable tool for therapy monitoring in FMs, offering a safe, non-invasive, and highly effective test for ancillary diagnostics and long-term prognostic follow-up. Additionally, MCG may potentially assist in clinical decision-making regarding the need for further interventions in patients with myocardial bridge.