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Deep phenotyping the right ventricle (RV) is essential for understanding the mechanisms of adaptive and maladaptive RV responses to pulmonary hypertension (PH). In this study, feature selection coupled with machine learning classification/ranking of specific cardiac magnetic resonance imaging (MRI) features from cine-MRI, flow-sensitized, and extracellular-volume techniques were used to assess RV remodelling in monocrotaline (MCT) and Sugen hypoxia (SuHx) PH rats. Early physiological changes associated with RV adaptation were detected along with prediction of RV maladaptive outcomes. Key adaptation features included haemodynamic alterations of pulmonary blood flow ejection and wave reflection, mild RV dilatation, progressive RV hypertrophy with subtle extracellular volume growth of RV wall. A dominant component of maladaptation was the extracellular matrix increase at RV insertion points and septum, observations compatible with histopathologic and RNA-sequencing results. The upregulation of mammalian target of rapamycin (mTOR) paralleled by AMP-activated protein kinase (AMPK) deactivation was seen at 4-week MCT and 8-week SuHx, along with reduced sarcoplasmic/endoplasmic reticulum Ca2+ATPase (SERCA2) expression, strongly associated with the RV systolic malfunction seen at this stage in vivo. The here established MRI features can serve as potential imaging biomarkers to evaluate PH treatment efficacy in preclinical studies and build up translational markers for the PH clinic. [ABSTRACT FROM AUTHOR]

We sought to assess cardiac magnetic resonance derived left ventricular hemodynamic forces (HDF) in athletes compared to patients with hypertension. Sixty athletes and 48 hypertensive patients were studied. HDF were measured during the entire cardiac cycle, the systolic phase, suction, early LV filling, and atrial thrust. Statistical comparisons were made between athletes and hypertensive patients, and between endurance and strength athletes. The slope of the systolic ejection was higher in athletes compared to hypertensive patients (541.5 vs. 435 1/sec; p = 0.033). Athletes showed higher HDF during the first phase of systole (4.53 vs. 3.86; p = 0.047) and the systolic impulse (11.26 vs. 8.76; p = 0.045). Compared to hypertensive patients, the AUC of the elastic rebound in athletes was lower (-0.31 vs. -0.44; p = 0.011). Moreover, hypertensive patients had an abnormal suction as revealed by a divergent direction (apex-to-base) of the HDF. The atrial thrust was higher in hypertensive patients than in athletes (-0.31 vs. -0.05; p < 0.001). Compared to endurance athletes, strength athletes had a shorter duration of the systolic impulse (250 vs. 280 ms; p = 0.019) and higher AUC during the early LV filling (1.65 vs. 0.97; p = 0.016). We conclude that HDF allows distinction between the hemodynamic patterns of athletes and patients with hypertension. [ABSTRACT FROM AUTHOR]

Diffusion-weighted magnetic resonance imaging (DW-MRI) performed before target temperature management, within 6 h of return of spontaneous circulation (ROSC), is defined as ultra-early DW-MRI. In previous studies, high-signal intensity (HSI) on ultra-early DW-MRI can predict poor neurological outcomes (Cerebral Performance Category 3–5 at 6-months post-ROSC). We aimed to assess the optimal-timing for ultra-early DW-MRI to avoid false-negative outcomes post out-of-hospital cardiac arrest, considering cardiopulmonary resuscitation (CPR) factors. The primary outcomes were HSI in the cerebral cortex or deep gray matter on ultra-early DW-MRI. The impact of CPR factors and ROSC to DW-MRI scan-interval on HSI-presence was assessed. Of 206 included patients, 108 exhibited HSI-presence, exclusively associated with poor neurological outcomes. In multivariate regression analysis, ROSC to DW-MRI scan-interval (adjusted odds ratio [aOR], 1.509; 95% confidence interval (CI): 1.113–2.046; P = 0.008), low-flow time (aOR, 1.176; 95%CI: 1.121–1.233; P < 0.001), and non-shockable rhythm (aOR, 9.974; 95%CI: 3.363–29.578; P < 0.001) were independently associated with HSI-presence. ROSC to DW-MRI scan-interval cutoff of ≥ 2.2 h was particularly significant in low-flow time ≤ 21 min or shockable rhythm group. In conclusion, short low-flow time and shockable rhythm require a longer ROSC to DW-MRI scan-interval. Prolonged low-flow time and non-shockable rhythm reduce the need to consider scan-interval. [ABSTRACT FROM AUTHOR]

Left ventricular ejection fraction (LVEF) is the most ubiquitous parameter in cardiac imaging examinations, we aimed to investigate the associations between subtle changes of LVEF and risk of common cardiovascular diseases. This is a prospective cohort study based on UK Biobank. LVEF was obtained from cardiac magnetic resonance. Incident cardiovascular disease was the outcome, including heart failure, atrial fibrillation, ischemic heart disease, and myocardial infarction. Cox proportional hazard model was the main method. A U-shaped relationship was observed between quantified LVEF and cardiovascular events risk with the nadir at the LVEF of 55–64%. As compared to moderate LVEF (55–64%), both low (40–54%) and high LVEF (≥ 5%) were related to higher risk of cardiovascular diseases after adjusting for confounders (HRlow = 1.15, 95%CI = 1.02–1.30; HRhigh = 1.34, 95%CI = 1.05–1.72). Specifically, low LVEF was associated with increased risk of heart failure while high LVEF predominantly predicted elevated risk of ischemic heart diseases, both low and high LVEF were related to a borderline higher incidence of atrial fibrillation. Besides, associations with specific cardiovascular diseases varied by age, sex or comorbidities. There was a U-shaped relationship between LVEF and cardiovascular events risk with the nadir at the LVEF of 55–64%, while these associations were disease-specific and varied by age, sex or comorbidities. [ABSTRACT FROM AUTHOR]

A hypertensive crisis is associated with an increased risk of cardiovascular events. Although altered cardiac structure, function, and myocardial architecture on cardiovascular magnetic resonance (CMR) have been associated with increased adverse events in hypertensive patients, the studies did not include patients with hypertensive crisis. Our study aimed to determine myocardial tissue characteristics in patients with hypertensive crisis using CMR imaging. Participants underwent comprehensive CMR imaging at 1.5T. The imaging protocol included cine-, T2-weighted-, contrasted- and multi-parametric mapping images. Blood and imaging biomarkers were compared in hypertensive emergency and hypertensive urgency. Predictors of myocardial edema was assessed using linear regression. The predictive value of T1- and T2 mapping for identifying hypertensive emergency (from urgency) was assessed with receiver operator characteristics curves. Eighty-two patients (48.5 ± 13.4 years, 57% men) were included. Hypertensive emergency constituted 78%. Native T1 was higher in patients with LVH compared to those without (1056 ± 33 vs. 1013 ± 40, P < 0.001), and tended to be higher in hypertensive emergency than urgency (1051 ± 37 vs. 1033 ± 40, P = 0.077). T2-w signal intensity (SI) ratio and T2 mapping values were higher in hypertensive emergency (1.5 ± 0.2 vs. 1.4 ± 0.1, P = 0.044 and 48 ± 2 vs. 47 ± 2, P = 0.004), and in patients with than without LVH (1.5 ± 0.2 vs. 1.4 ± 0.1, P = 0.045 and P = 0.030). A trend for higher extracellular volume was noted in hypertensive emergency compared to urgency (25 ± 4 vs. 22 ± 3, P = 0.050). Native T1 correlated with T2 mapping (rs = 0.429, P < 0.001), indexed LV mass (rs = 0.493, P < 0.001), cardiac troponin (rs = 0.316, P < 0.001) and NT-proBNP (rs = 0.537, P < 0.001), while T2 correlated with cardiac troponin (rs = 0.390, P < 0.001), and NT-proBNP (rs = 0.348, P < 0.001). Non-ischemic LGE pattern occurred in 59% and was 21% more prevalent in the hypertensive emergency group (P = 0.005). Our findings demonstrate that hypertensive crisis is associated with distinct myocardial tissue alterations, including increased myocardial edema and fibrosis, as detected on CMR. Patients with hypertensive emergency had a higher degree of myocardial oedema than hypertensive urgency. Further research is necessary to explore the prognostic value of these findings. [ABSTRACT FROM AUTHOR]

Abstract To develop a deep learning-based model capable of segmenting the left ventricular (LV) myocardium on native T1 maps from cardiac MRI in both long-axis and short-axis orientations. Models were trained on native myocardial T1 maps from 50 healthy volunteers and 75 patients using manual segmentation as the reference standard. Based on a U-Net architecture, we systematically optimized the model design using two different training metrics (Sørensen-Dice coefficient = DSC and Intersection-over-Union = IOU), two different activation functions (ReLU and LeakyReLU) and various numbers of training epochs. Training with DSC metric and a ReLU activation function over 35 epochs achieved the highest overall performance (mean error in T1 10.6 ± 17.9 ms, mean DSC 0.88 ± 0.07). Limits of agreement between model results and ground truth were from -35.5 to + 36.1 ms. This was superior to the agreement between two human raters (-34.7 to + 59.1 ms). Segmentation was as accurate for long-axis views (mean error T1: 6.77 ± 8.3 ms, mean DSC: 0.89 ± 0.03) as for short-axis images (mean error ΔT1: 11.6 ± 19.7 ms, mean DSC: 0.88 ± 0.08). Fully automated segmentation and quantitative analysis of native myocardial T1 maps is possible in both long-axis and short-axis orientations with very high accuracy.

Abstract The pathophysiology underlying impaired LV function in PAH remains unclear, with some studies implicating intrinsic myocardial dysfunction and others pointing to LV underfilling. Evaluation of pulmonary vein area (PVA) and flow may offer novel, mechanistic insight by distinguishing elevated LV filling pressure common in myocardial dysfunction from LV underfilling. This study aimed to elucidate LV filling physiology in PAH by assessing PVA and flow using cardiac magnetic resonance (CMR) and compare pulmonary vein flow in PAH with HFrEF as a model representing elevated filling pressures, in addition to healthy controls. Patients with PAH or heart failure with reduced ejection fraction (HFrEF) referred for CMR were retrospectively reviewed, and healthy controls were included as reference. Pulmonary vein S, D and A-wave were compared between groups. Associations between pulmonary vein area (PVA) by CMR and echocardiographic indices of LV filling pressure were evaluated. Nineteen patients with PAH, 25 with HFrEF and 24 controls were included. Both PAH and HFrEF had lower ejection fraction and S-wave velocity than controls. PAH displayed smaller LV end-diastolic volumes than controls, while HFrEF demonstrated larger PVA and higher A-wave reversal. PVA was associated with mitral E/e′ ratio (r2 = 0.10; p = 0.03), e′ velocity (r2 = 0.23; p = 0.001) and left atrial volume (r2 = 0.07; p = 0.005). Among PAH, PVA was not associated with LV-GLS. A PVA cut-off of 2.3cm2 displayed 87% sensitivity and 72% specificity to differentiate HFrEF and PAH (AUC = 0.82). PAH displayed lower pulmonary vein S-wave velocity, smaller LV volume and reduced function compared with controls. Reduced LV function in PAH may be owing to underfilling rather than intrinsic myocardial disease. PVA demonstrates promise as a novel, non-invasive imaging marker to assess LV filling status.

Abstract While Q-waves in inferior leads, particularly lead III, can be regarded as a minor abnormality, it can also indicate the presence of myocardial scar. This study assessed the diagnostic value of pathologic inferior Q-waves (lead II, III, aVF) for detecting ischemic scars using a high-resolution 3.0 T cardiac magnetic resonance (CMR). We retrospectively analyzed 1692 patients with suspected or known coronary artery disease who underwent stress CMR perfusion or viability assessment. Pathologic Q-waves were defined as duration of ≥ 30 ms and depth of ≥ 1 mm or QS-complex. Eleven models were created to evaluate the presence of Q-waves in different combinations of inferior leads. Of the 1692 patients, 436 (25.8%) had pathologic Q-waves. Models with Q-waves in leads II + aVF (model 7) and II + III + aVF (model 9) showed high specificity (100% and 99.6%), positive predictive value (PPV) (80.0% and 86.7%), and negative predictive value (NPV) (82.6% and 84.3%) but low sensitivity (1.3% and 13.1%). Other models also maintained high specificity and NPV but poor sensitivity and PPV. Notably, 21% of patients with an isolated pathologic Q-wave in lead III (model 4) exhibited scars. These findings highlight the need for careful clinical assessment when pathologic Q-waves are present.

Aortic valve replacement (AVR) leads to reverse cardiac remodeling in patients with aortic stenosis (AS). The aim of this secondary pooled analysis was to assess the degree and determinants of changes in myocardial perfusion post AVR, and its link with exercise capacity, in patients with severe AS. A total of 68 patients underwent same-day echocardiography and cardiac magnetic resonance imaging with adenosine stress pre and 6–12 months post-AVR. Of these, 50 had matched perfusion data available (age 67 ± 8 years, 86% male, aortic valve peak velocity 4.38 ± 0.63 m/s, aortic valve area index 0.45 ± 0.13cm2/m2). A subgroup of 34 patients underwent a symptom-limited cardiopulmonary exercise test (CPET) to assess maximal exercise capacity (peak VO2). Baseline and post-AVR parameters were compared and linear regression was used to determine associations between baseline variables and change in myocardial perfusion and exercise capacity. Following AVR, stress myocardial blood flow (MBF) increased from 1.56 ± 0.52 mL/min/g to 1.80 ± 0.62 mL/min/g (p < 0.001), with a corresponding 15% increase in myocardial perfusion reserve (MPR) (2.04 ± 0.57 to 2.34 ± 0.68; p = 0.004). Increasing severity of AS, presence of late gadolinium enhancement, lower baseline stress MBF and MPR were associated with a greater improvement in MPR post-AVR. On multivariable analysis low baseline MPR was independently associated with increased MPR post-AVR. There was no significant change in peak VO2 post-AVR, but a significant increase in exercise duration. Change in MPR was associated with change in peak VO2 post AVR (r = 0.346, p = 0.045). Those with the most impaired stress MBF and MPR at baseline demonstrate the greatest improvements in these parameters following AVR and the magnitude of change in MPR correlated with improvement in peak VO2, the gold standard measure of aerobic exercise capacity. [ABSTRACT FROM AUTHOR]

To develop a deep learning-based model capable of segmenting the left ventricular (LV) myocardium on native T1 maps from cardiac MRI in both long-axis and short-axis orientations. Models were trained on native myocardial T1 maps from 50 healthy volunteers and 75 patients using manual segmentation as the reference standard. Based on a U-Net architecture, we systematically optimized the model design using two different training metrics (Sørensen-Dice coefficient = DSC and Intersection-over-Union = IOU), two different activation functions (ReLU and LeakyReLU) and various numbers of training epochs. Training with DSC metric and a ReLU activation function over 35 epochs achieved the highest overall performance (mean error in T1 10.6 ± 17.9 ms, mean DSC 0.88 ± 0.07). Limits of agreement between model results and ground truth were from -35.5 to + 36.1 ms. This was superior to the agreement between two human raters (-34.7 to + 59.1 ms). Segmentation was as accurate for long-axis views (mean error T1: 6.77 ± 8.3 ms, mean DSC: 0.89 ± 0.03) as for short-axis images (mean error ΔT1: 11.6 ± 19.7 ms, mean DSC: 0.88 ± 0.08). Fully automated segmentation and quantitative analysis of native myocardial T1 maps is possible in both long-axis and short-axis orientations with very high accuracy. [ABSTRACT FROM AUTHOR]

The pathophysiology underlying impaired LV function in PAH remains unclear, with some studies implicating intrinsic myocardial dysfunction and others pointing to LV underfilling. Evaluation of pulmonary vein area (PVA) and flow may offer novel, mechanistic insight by distinguishing elevated LV filling pressure common in myocardial dysfunction from LV underfilling. This study aimed to elucidate LV filling physiology in PAH by assessing PVA and flow using cardiac magnetic resonance (CMR) and compare pulmonary vein flow in PAH with HFrEF as a model representing elevated filling pressures, in addition to healthy controls. Patients with PAH or heart failure with reduced ejection fraction (HFrEF) referred for CMR were retrospectively reviewed, and healthy controls were included as reference. Pulmonary vein S, D and A-wave were compared between groups. Associations between pulmonary vein area (PVA) by CMR and echocardiographic indices of LV filling pressure were evaluated. Nineteen patients with PAH, 25 with HFrEF and 24 controls were included. Both PAH and HFrEF had lower ejection fraction and S-wave velocity than controls. PAH displayed smaller LV end-diastolic volumes than controls, while HFrEF demonstrated larger PVA and higher A-wave reversal. PVA was associated with mitral E/e′ ratio (r2 = 0.10; p = 0.03), e′ velocity (r2 = 0.23; p = 0.001) and left atrial volume (r2 = 0.07; p = 0.005). Among PAH, PVA was not associated with LV-GLS. A PVA cut-off of 2.3cm2 displayed 87% sensitivity and 72% specificity to differentiate HFrEF and PAH (AUC = 0.82). PAH displayed lower pulmonary vein S-wave velocity, smaller LV volume and reduced function compared with controls. Reduced LV function in PAH may be owing to underfilling rather than intrinsic myocardial disease. PVA demonstrates promise as a novel, non-invasive imaging marker to assess LV filling status. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess the effectiveness of conventional and two additional functional markers derived from standard cardiac magnetic resonance (CMR) images in detecting the occurrence of late gadolinium enhancement (LGE) in patients with secondary cardiac amyloidosis (CA) related to multiple myeloma (MM). This study retrospectively included 32 patients with preserved ejection fraction (EF) who had MM-CA diagnosed consecutively. Conventional left ventricular (LV) function markers and two additional functional markers, namely myocardial contraction fraction (MCF) and LV long-axis strain (LAS), were obtained using commercial cardiac post-processing software. Logistic regression analyses and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive performances. (1) There were no notable distinctions in clinical features between the LGE+ and LGE− groups, with the exception of a reduced systolic blood pressure in the former (105.60 ± 18.85 mmHg vs. 124.50 ± 20.95 mmHg, P = 0.022). (2) Patients with MM-CA presented with intractable heart failure with preserved ejection fraction (HFpEF). The LVEF in the LGE+ group exhibited a greater reduction (54.27%, IQR 51.59–58.39%) in comparison to the LGE− group (P < 0.05). And MM-CA patients with LGE+ had significantly higher LVMI (90.15 ± 23.69 g/m2), lower MCF (47.39%, IQR 34.28–54.90%), and the LV LAS were more severely damaged (− 9.94 ± 3.42%) than patients with LGE− (all P values < 0.05). (3) The study found that MCF exhibited a significant independent association with LGE, as indicated by an odds ratio of 0.89 (P < 0.05). The cut-off value for MCF was determined to be 64.25% with a 95% confidence interval ranging from 0.758 to 0.983. The sensitivity and specificity of this association were calculated to be 95% and 83%, respectively. MCF is a simple reproducible predict marker of LGE in MM-CA patients. It is a potentially CMR-based method that promise to reduce scan times and costs, and boost the accessibility of CMR. [ABSTRACT FROM AUTHOR]

While Q-waves in inferior leads, particularly lead III, can be regarded as a minor abnormality, it can also indicate the presence of myocardial scar. This study assessed the diagnostic value of pathologic inferior Q-waves (lead II, III, aVF) for detecting ischemic scars using a high-resolution 3.0 T cardiac magnetic resonance (CMR). We retrospectively analyzed 1692 patients with suspected or known coronary artery disease who underwent stress CMR perfusion or viability assessment. Pathologic Q-waves were defined as duration of ≥ 30 ms and depth of ≥ 1 mm or QS-complex. Eleven models were created to evaluate the presence of Q-waves in different combinations of inferior leads. Of the 1692 patients, 436 (25.8%) had pathologic Q-waves. Models with Q-waves in leads II + aVF (model 7) and II + III + aVF (model 9) showed high specificity (100% and 99.6%), positive predictive value (PPV) (80.0% and 86.7%), and negative predictive value (NPV) (82.6% and 84.3%) but low sensitivity (1.3% and 13.1%). Other models also maintained high specificity and NPV but poor sensitivity and PPV. Notably, 21% of patients with an isolated pathologic Q-wave in lead III (model 4) exhibited scars. These findings highlight the need for careful clinical assessment when pathologic Q-waves are present. [ABSTRACT FROM AUTHOR]

Abstract The evidence about the associations of leukocyte telomere length (LTL) and intermediary cardiovascular phenotypes with adverse cardiovascular outcomes is inconclusive. This study assessed these relationships with cardiovascular imaging, electrocardiography, and the risks of sudden cardiac death (SCD), coronary events, and heart failure (HF) admission. We conducted a cross-sectional analysis of UK Biobank participants enrolled between 2006 and 2010. LTL was measured using quantitative polymerase chain reactions. Electronic health records were used to determine the incidence of SCD, coronary events, and HF admission. Cardiovascular measurements were made using cardiovascular magnetic resonance imaging and machine learning. The associations of LTL with SCD, coronary events, and HF admission and cardiac magnetic resonance imaging, electrocardiogram parameters of 33,043 and 19,554 participants were evaluated by multivariate regression. The median (interquartile range) follow-up period was 11.9 (11.2–12.6) years. Data was analyzed from January to May 2023. Among the 403,382 white participants without coronary artery disease or HF, 181,637 (45.0%) were male with a mean age of 57.1 years old. LTL was independently negatively associated with a risk of SCD (LTL third quartile vs first quartile: hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.72–0.92), coronary events (LTL third quartile vs first quartile: HR: 0.88, 95% CI: 0.84–0.92), and HF admission (LTL fourth quartile vs first quartile: HR: 0.84, 95% CI: 0.74–0.95). LTL was also independently positively associated with cardiac remodeling, specifically left ventricular mass index, left-ventricular-end systolic and diastolic volumes, mean left ventricular myocardial wall thickness, left ventricular stroke volume, and with electrocardiogram changes along the negative degree of T-axis. Cross-sectional study results showed that LTL was positively associated with heart size and cardiac function in middle age, but electrocardiography results did not show these associations, which could explain the negative association between LTL and risk of SCD, coronary events, and HF admission in UK Biobank participants.

Abstract Clinical application of cardiac magnetic resonance (CMR) is expanding but CMR assessment of LV diastolic function is still being validated. The purpose of this study was to validate assessments of left ventricular (LV) diastolic dysfunction (DD) using CMR by comparing with transthoracic echocardiography (TTE) performed on the same day. Patients with suspected or diagnosed cardiomyopathy (n = 63) and healthy volunteers (n = 24) were prospectively recruited and included in the study. CMR diastolic parameters were measured on cine images and velocity-encoded phase contrast cine images and compared with corresponding parameters measured on TTE. A contextual correlation feature tracking method was developed to calculate the mitral annular velocity curve. LV DD was classified by CMR and TTE following 2016 guidelines. Overall DD classification was 78.1% concordant between CMR and TTE (p

The efficacy of an implantable cardioverter-defibrillator (ICD) in patients with a non-ischaemic cardiomyopathy for primary prevention of sudden cardiac death is increasingly debated. We developed a multimodal deep learning model for arrhythmic risk prediction that integrated late gadolinium enhanced (LGE) cardiac magnetic resonance imaging (MRI), electrocardiography (ECG) and clinical data. Short-axis LGE-MRI scans and 12-lead ECGs were retrospectively collected from a cohort of 289 patients prior to ICD implantation, across two tertiary hospitals. A residual variational autoencoder was developed to extract physiological features from LGE-MRI and ECG, and used as inputs for a machine learning model (DEEP RISK) to predict malignant ventricular arrhythmia onset. In the validation cohort, the multimodal DEEP RISK model predicted malignant ventricular arrhythmias with an area under the receiver operating characteristic curve (AUROC) of 0.84 (95% confidence interval (CI) 0.71–0.96), a sensitivity of 0.98 (95% CI 0.75–1.00) and a specificity of 0.73 (95% CI 0.58–0.97). The models trained on individual modalities exhibited lower AUROC values compared to DEEP RISK [MRI branch: 0.80 (95% CI 0.65–0.94), ECG branch: 0.54 (95% CI 0.26–0.82), Clinical branch: 0.64 (95% CI 0.39–0.87)]. These results suggest that a multimodal model achieves high prognostic accuracy in predicting ventricular arrhythmias in a cohort of patients with non-ischaemic systolic heart failure, using data collected prior to ICD implantation. [ABSTRACT FROM AUTHOR]

The evidence about the associations of leukocyte telomere length (LTL) and intermediary cardiovascular phenotypes with adverse cardiovascular outcomes is inconclusive. This study assessed these relationships with cardiovascular imaging, electrocardiography, and the risks of sudden cardiac death (SCD), coronary events, and heart failure (HF) admission. We conducted a cross-sectional analysis of UK Biobank participants enrolled between 2006 and 2010. LTL was measured using quantitative polymerase chain reactions. Electronic health records were used to determine the incidence of SCD, coronary events, and HF admission. Cardiovascular measurements were made using cardiovascular magnetic resonance imaging and machine learning. The associations of LTL with SCD, coronary events, and HF admission and cardiac magnetic resonance imaging, electrocardiogram parameters of 33,043 and 19,554 participants were evaluated by multivariate regression. The median (interquartile range) follow-up period was 11.9 (11.2–12.6) years. Data was analyzed from January to May 2023. Among the 403,382 white participants without coronary artery disease or HF, 181,637 (45.0%) were male with a mean age of 57.1 years old. LTL was independently negatively associated with a risk of SCD (LTL third quartile vs first quartile: hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.72–0.92), coronary events (LTL third quartile vs first quartile: HR: 0.88, 95% CI: 0.84–0.92), and HF admission (LTL fourth quartile vs first quartile: HR: 0.84, 95% CI: 0.74–0.95). LTL was also independently positively associated with cardiac remodeling, specifically left ventricular mass index, left-ventricular-end systolic and diastolic volumes, mean left ventricular myocardial wall thickness, left ventricular stroke volume, and with electrocardiogram changes along the negative degree of T-axis. Cross-sectional study results showed that LTL was positively associated with heart size and cardiac function in middle age, but electrocardiography results did not show these associations, which could explain the negative association between LTL and risk of SCD, coronary events, and HF admission in UK Biobank participants. [ABSTRACT FROM AUTHOR]

Nonischaemic myocardial fibrosis is associated with cardiac dysfunction, malignant arrhythmias and sudden cardiac death. In the absence of a specific aetiology, its finding as late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging is often attributed to preceding viral myocarditis. Athletes presenting with ventricular arrhythmias often have nonischaemic LGE. Previous studies have demonstrated an adverse effect of exercise on the course of acute viral myocarditis. In this study, we have investigated, for the first time, the impact of endurance training on longer-term outcomes such as myocardial fibrosis and arrhythmogenicity in a murine coxsackievirus B3 (CVB)-induced myocarditis model. Male C57BL/6J mice (n = 72) were randomly assigned to 8 weeks of forced treadmill running (EEX) or no exercise (SED). Myocarditis was induced 2 weeks later by a single intraperitoneal injection with CVB, versus vehicle in the controls (PBS). In a separate study, mice (n = 30) were subjected to pretraining for 13 weeks (preEEX), without continuation of exercise during myocarditis. Overall, continuation of exercise resulted in a milder clinical course of viral disease, with less weight loss and better preserved running capacity. CVB-EEX and preEEX-CVB mice tended to have a lower mortality rate. At sacrifice (i.e. 6 weeks after inoculation), the majority of virus was cleared from the heart. Histological assessment demonstrated prominent myocardial inflammatory infiltration and cardiomyocyte loss in both CVB groups. Inflammatory lesions in the CVB-EEX group contained higher numbers of pro-inflammatory cells (iNOS-reactive macrophages and CD8+ T lymphocytes) compared to these in CVB-SED. Treadmill running during myocarditis increased interstitial fibrosis [82.4% (CVB-EEX) vs. 56.3% (CVB-SED); P = 0.049]. Additionally, perivascular and/or interstitial fibrosis with extensive distribution was more likely to occur with exercise [64.7% and 64.7% (CVB-EEX) vs. 50% and 31.3% (CVB-SED); P = 0.048]. There was a numerical, but not significant, increase in the number of scars per cross-section (1.9 vs. 1.2; P = 0.195), with similar scar distribution and histological appearance in CVB-EEX and CVB-SED. In vivo electrophysiology studies did not induce sustained monomorphic ventricular tachycardia, only nonsustained (usually polymorphic) runs. Their cumulative beat count and duration paralleled the increased fibrosis between CVB-EEX and CVB-SED, but the difference was not significant (P = 0.084 for each). Interestingly, in mice that were subjected to pretraining only without continuation of exercise during myocarditis, no differences between pretrained and sedentary mice were observed at sacrifice (i.e. 6 weeks after inoculation and training cessation) with regard to myocardial inflammation, fibrosis, and ventricular arrhythmogenicity. In conclusion, endurance exercise during viral myocarditis modulates the inflammatory process with more pro-inflammatory cells and enhances perivascular and interstitial fibrosis development. The impact on ventricular arrhythmogenesis requires further exploration. [ABSTRACT FROM AUTHOR]

Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this step. These are, however, designed for segmentation of human images obtained at clinical field strengths. They reach their limits when applied to preclinical data and ultrahigh field strength (such as CMR of pigs at 7 T). In our study, eleven animals (seven with myocardial infarction) underwent four CMR scans each. Short-axis cine stacks were acquired and used for functional cardiac analysis. End-systolic and end-diastolic images were labelled manually by two observers and inter- and intra-observer variability were assessed. Aiming to make the functional analysis faster and more reproducible, an established deep learning (DL) model for myocardial segmentation in humans was re-trained using our preclinical 7 T data (n = 772 images and labels). We then tested the model on n = 288 images. Excellent agreement in parameters of cardiac function was found between manual and DL segmentation: For ejection fraction (EF) we achieved a Pearson's r of 0.95, an Intraclass correlation coefficient (ICC) of 0.97, and a Coefficient of variability (CoV) of 6.6%. Dice scores were 0.88 for the left ventricle and 0.84 for the myocardium. [ABSTRACT FROM AUTHOR]

Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner's reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy. [ABSTRACT FROM AUTHOR]

This study clinically implemented a ready-to-use quantitative perfusion (QP) cardiovascular magnetic resonance (QP CMR) workflow, encompassing a simplified dual-bolus gadolinium-based contrast agent (GBCA) administration scheme and fully automated QP image post-processing. Twenty-five patients with suspected obstructive coronary artery disease (CAD) underwent both adenosine stress perfusion CMR and an invasive coronary angiography or coronary computed tomography angiography. The dual-bolus protocol consisted of a pre-bolus (0.0075 mmol/kg GBCA at 0.5 mmol/ml concentration + 20 ml saline) and a main bolus (0.075 mmol/kg GBCA at 0.5 mmol/ml concentration + 20 ml saline) at an infusion rate of 3 ml/s. The arterial input function curves showed excellent quality. Stress MBF ≤ 1.84 ml/g/min accurately detected obstructive CAD (area under the curve 0.79; 95% Confidence Interval: 0.66 to 0.89). Combined visual assessment of color pixel QP maps and conventional perfusion images yielded a diagnostic accuracy of 84%, sensitivity of 70% and specificity of 93%. The proposed easy-to-use dual-bolus QP CMR workflow provides good image quality and holds promise for high accuracy in diagnosis of obstructive CAD. Implementation of this approach has the potential to serve as an alternative to current methods thus increasing the accessibility to offer high-quality QP CMR imaging by a wide range of CMR laboratories. [ABSTRACT FROM AUTHOR]

Fully CMR-guided electrophysiological interventions (EP-CMR) have recently been introduced but data on the optimal CMR imaging protocol are scarce. This study determined the clinical utility of 3D non-selective whole heart steady-state free precession imaging using compressed SENSE (nsWHcs) for automatic segmentation of cardiac cavities as the basis for targeted catheter navigation during EP-CMR cavo-tricuspid isthmus ablation. Fourty-two consecutive patients with isthmus-dependent right atrial flutter underwent EP-CMR radiofrequency ablations. nsWHcs succeeded in all patients (nominal scan duration, 98 ± 10 s); automatic segmentation/generation of surface meshes of right-sided cavities exhibited short computation times (16 ± 3 s) with correct delineation of right atrium, right ventricle, tricuspid annulus and coronary sinus ostium in 100%, 100%, 100% and 95%, respectively. Point-by-point ablation adhered to the predefined isthmus line in 62% of patients (26/42); activation mapping confirmed complete bidirectional isthmus block (conduction time difference, 136 ± 28 ms). nsWHcs ensured automatic and reliable 3D segmentation of targeted endoluminal cavities, multiplanar reformatting and image fusion (e.g. activation time measurements) and represented the basis for precise real-time active catheter navigation during EP-CMR ablations of isthmus-dependent right atrial flutter. Hence, nsWHcs can be considered a key component in order to advance EP-CMR towards the ultimate goal of targeted substrate-based ablation procedures. [ABSTRACT FROM AUTHOR]

This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (P < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771—0.777) vs. 0.683 (0.681—0.685) cross-validated AUC, P < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment. [ABSTRACT FROM AUTHOR]

The potential association between endurance exercise and myocardial fibrosis is controversial. Data on exercise exposure and diffuse myocardial fibrosis in endurance athletes are scarce and conflicting. We aimed to investigate the association between exercise exposure and markers of diffuse myocardial fibrosis by cardiovascular magnetic resonance imaging (CMR) in endurance athletes. We examined 27 healthy adult male competitive endurance athletes aged 41 ± 9 years and 16 healthy controls in a cross sectional study using 3 Tesla CMR including late gadolinium enhancement and T1 mapping. Athletes reported detailed exercise history from 12 years of age. Left ventricular total mass, cellular mass and extracellular mass were higher in athletes than controls (86 vs. 58 g/m2, 67 vs. 44 g/m2 and 19 vs. 13 g/m2, all p < 0.01). Extracellular volume (ECV) was lower (21.5% vs. 23.8%, p = 0.03) and native T1 time was shorter (1214 ms vs. 1268 ms, p < 0.01) in the athletes. Increasing exercise dose was independently associated with shorter native T1 time (regression coefficient − 24.1, p < 0.05), but expressed no association with ECV. Our results indicate that diffuse myocardial fibrosis has a low prevalence in healthy male endurance athletes and do not indicate an adverse dose–response relationship between exercise and diffuse myocardial fibrosis in healthy athletes. [ABSTRACT FROM AUTHOR]

In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) technique for evaluating the microstructure of myocardial tissue in living hearts, providing insights into cardiac function and enabling the development of innovative therapeutic strategies. However, the integration of cDTI into routine clinical practice poses challenging due to the technical obstacles involved in the acquisition, such as low signal-to-noise ratio and prolonged scanning times. In this study, we investigated and implemented three different types of deep learning-based MRI reconstruction models for cDTI reconstruction. We evaluated the performance of these models based on the reconstruction quality assessment, the diffusion tensor parameter assessment as well as the computational cost assessment. Our results indicate that the models discussed in this study can be applied for clinical use at an acceleration factor (AF) of × 2 and × 4 , with the D5C5 model showing superior fidelity for reconstruction and the SwinMR model providing higher perceptual scores. There is no statistical difference from the reference for all diffusion tensor parameters at AF × 2 or most DT parameters at AF × 4 , and the quality of most diffusion tensor parameter maps is visually acceptable. SwinMR is recommended as the optimal approach for reconstruction at AF × 2 and AF × 4 . However, we believe that the models discussed in this study are not yet ready for clinical use at a higher AF. At AF × 8 , the performance of all models discussed remains limited, with only half of the diffusion tensor parameters being recovered to a level with no statistical difference from the reference. Some diffusion tensor parameter maps even provide wrong and misleading information. [ABSTRACT FROM AUTHOR]

Cardiac diffusion weighted-magnetic resonance imaging (DWI) has slowly developed due to its technical difficulties. However, this limitation could be overcome by advanced techniques, including a stimulated echo technique and a gradient moment nulling technique. This study aimed to develop and validate a high-order DWI sequence, using echo-planar imaging (EPI) and second-order motion-compensated (M012) diffusion gradient applied to cardiac imaging in small-sized animals with fast heart and respiratory rates, and to investigate the feasibility of cardiac DWI, diagnosing acute myocardial injury in isoproterenol-induced myocardial injury rat models. The M012 diffusion gradient sequence was designed for diffusion tensor imaging of the rat myocardium and validated in the polyvinylpyrrolidone phantom. Following sequence optimization, 23 rats with isoproterenol-induced acute myocardial injury and five healthy control rats underwent cardiac MRI, including cine imaging, T1 mapping, and DWI. Diffusion gradient was applied using a 9.4-T MRI scanner (Bruker, BioSpec 94/20, gradient amplitude = 440 mT/m, maximum slew rate = 3440 T/m/s) with double gating (electrocardiogram and respiratory gating). Troponin I was used as a serum biomarker for myocardial injury. Histopathologic examination of the heart was subsequently performed. The developed DWI sequence using EPI and M012 provided the interpretable images of rat hearts. The apparent diffusion coefficient (ADC) values were significantly higher in rats with acute myocardial injury than in the control group (1.847 ± 0.326 * 10–3 mm2/s vs. 1.578 ± 0.144 * 10–3 mm2/s, P < 0.001). Troponin I levels were increased in the blood samples of rats with acute myocardial injury (P < 0.001). Histopathologic examinations detected myocardial damage and subendocardial fibrosis in rats with acute myocardial injury. The newly developed DWI technique has the ability to detect myocardial injury in small animal models, representing high ADC values on the myocardium with isoproterenol-induced injury. [ABSTRACT FROM AUTHOR]

In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress. Data from healthy volunteers (n = 15) for cine and real-time free-breathing CMR at rest and under exercise stress were analyzed retrospectively. Exercise stress was performed using an ergometer in the supine position. Segmentations of two deep learning methods, a commercially available technique (comDL) and an openly available network (nnU-Net), were compared to a reference model created via the manual correction of segmentations obtained with comDL. Segmentations of left ventricular endocardium (LV), left ventricular myocardium (MYO), and right ventricle (RV) are compared for both end-systolic and end-diastolic phases and analyzed with Dice's coefficient. The volumetric analysis includes the cardiac function parameters LV end-diastolic volume (EDV), LV end-systolic volume (ESV), and LV ejection fraction (EF), evaluated with respect to both absolute and relative differences. For cine CMR, nnU-Net and comDL achieve Dice's coefficients above 0.95 for LV and 0.9 for MYO, and RV. For real-time CMR, the accuracy of nnU-Net exceeds that of comDL overall. For real-time CMR at rest, nnU-Net achieves Dice's coefficients of 0.94 for LV, 0.89 for MYO, and 0.90 for RV and the mean absolute differences between nnU-Net and the reference are 2.9 mL for EDV, 3.5 mL for ESV, and 2.6% for EF. For real-time CMR under exercise stress, nnU-Net achieves Dice's coefficients of 0.92 for LV, 0.85 for MYO, and 0.83 for RV and the mean absolute differences between nnU-Net and reference are 11.4 mL for EDV, 2.9 mL for ESV, and 3.6% for EF. Deep learning methods designed or trained for cine CMR segmentation can perform well on real-time CMR. For real-time free-breathing CMR at rest, the performance of deep learning methods is comparable to inter-observer variability in cine CMR and is usable for fully automatic segmentation. For real-time CMR under exercise stress, the performance of nnU-Net could promise a higher degree of automation in the future. [ABSTRACT FROM AUTHOR]

Bone marrow mononuclear cells (BMMCs) have been evaluated for their ability to improve cardiac repair and benefit patients with severe ischemic heart disease and heart failure. In our single-center trial in 2006–2011 we demonstrated the safety and efficacy of BMMCs injected intramyocardially in conjunction with coronary artery bypass surgery. The effect persisted in the follow-up study 5 years later. In this study, we investigated the efficacy of BMMC therapy beyond 10 years. A total of 18 patients (46%) died during over 10-years follow-up and 21 were contacted for participation. Late gadolinium enhancement cardiac magnetic resonance imaging (CMRI) and clinical evaluation were performed on 14 patients, seven from each group. CMRIs from the study baseline, 1-year and 5-years follow-ups were re-analyzed to enable comparison. The CMRI demonstrated a 2.1-fold larger reduction in the mass of late gadolinium enhancement values between the preoperative and the over 10-years follow-up, suggesting less scar or fibrosis after BMMC treatment (− 15.1%; 95% CI − 23 to − 6.7% vs. − 7.3%; 95% CI − 16 to 4.5%, p = 0.039), compared to placebo. No differences in mortality or morbidity were observed. Intramyocardially injected BMMCs may exert long-term benefits in patients with ischemic heart failure. This deserves further evaluation in patients who have received BMMCs in international clinical studies over two decades. [ABSTRACT FROM AUTHOR]

Myocardial infarction with nonobstructive coronary arteries (MINOCA) has several possible underlying causes, including coronary microvascular dysfunction (CMD). Early cardiovascular magnetic resonance imaging (CMR) is recommended, however cannot provide a diagnosis in 25% of cases. Quantitative stress CMR perfusion mapping can identify CMD, however it is unknown if CMD is present during long-term follow-up of MINOCA patients. Therefore, this study aimed to evaluate presence of CMD during long-term follow-up in MINOCA patients with an initial normal CMR scan. MINOCA patients from the second Stockholm myocardial infarction with normal coronaries study (SMINC-2), with a normal CMR scan at median 3 days after hospitalization were investigated with comprehensive CMR including stress perfusion mapping a median of 5 years after the index event, together with age- and sex-matched volunteers without symptomatic ischemic heart disease. Cardiovascular risk factors, medication and symptoms of myocardial ischemia measured by the Seattle Angina Questionnaire 7 (SAQ-7), were registered. In total, 15 patients with MINOCA and an initial normal CMR scan (59 ± 7 years old, 60% female), and 15 age- and sex-matched volunteers, underwent CMR. Patients with MINOCA and an initial normal CMR scan had lower global stress perfusion compared to volunteers (2.83 ± 1.8 vs 3.53 ± 0.7 ml/min/g, p = 0.02). There were no differences in other CMR parameters, hemodynamic parameters, or cardiovascular risk factors, except for more frequent use of statins in the MINOCA patient group compared to volunteers. In conclusion, global stress perfusion is lower in MINOCA patients during follow-up, compared to age- and sex-matched volunteers, suggesting that CMD may be a possible pathophysiological mechanism in MINOCA. Clinical Trial Registration: Clinicaltrials.gov identifier NCT02318498. Registered 2014-12-17. [ABSTRACT FROM AUTHOR]

A method of determining the optimal kernel size for filtering noise in vortex dominated flow-fields, as found in the cardiac chambers is presented in this paper. Using synthetic flow fields generated using harmonic functions and perturbed using Gaussian noises of different amplitudes and spreads, the effect of kernel size on noise removal using the Median filter is tested systematically. It is shown that there exists an optimal kernel size at which the Median filter works best. The size of the optimal kernel is shown to be related to the vortex size. When applied to MRI generated cardiac flow-fields, the approach is seen to reveal underlying vortex patterns thereby aiding as an effective tool in the diagnosis and prognosis of cardiac diseases based on vortices as clinical biomarkers. The behavior of the restored cardiac flow fields which are filtered with the optimal kernel size and also with some values preceding and succeeding it are similar to that observed in studies with synthetic flow fields. This confirms that the optimal size of the kernel is related to the cardiac vortex size as is observed in the case of synthetic flow fields. [ABSTRACT FROM AUTHOR]

This study sought to evaluate the prognostic implications of the presence of preprocedural unrecognized myocardial infarction (UMI) and periprocedural myocardial injury (PMI) evaluated by delayed gadolinium enhancement cardiac magnetic resonance (DE-CMR) in patients with chronic coronary syndrome (CCS) undergoing elective percutaneous coronary intervention (PCI). We enrolled 250 CCS patients scheduled for elective PCI. UMI was defined as the presence of late gadolinium enhancement (LGE) detected by pre-PCI CMR in the region without medical history of revascularization and/or MI. Periprocedural new occurrence or increased volume of LGE in the target territory detected by post-PCI CMR (PPL) were used to assess PMI. In the final analysis of 235 patients, UMI and PPL were detected in 43 patients (18.3%) and 45 patients (19.1%), respectively. During follow-up for a median of 2.2 years, major adverse cardiac events (MACE) occurred in 31 (13.2%) patients. On multivariable analysis, UMI and PPL remained as significant predictors of MACE after adjusting confounding factors (HR 4.62, 95% CI 2.24–9.54, P < 0.001, HR 2.33, 95% CI 1.11–4.91, P = 0.026). In patients with CCS who underwent elective PCI, UMI and PPL were independent predictors of worse outcomes. UMI and PPL on DE-CMR might provide additional potential insight for the risk stratification of patients undergoing elective PCI. [ABSTRACT FROM AUTHOR]

Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement biases specific to each protocol. We show how dynamic time warping and partial least squares regression can be applied to effectively map between left ventricular geometries derived from different imaging modalities and analysis protocols to account for such differences. To demonstrate this method, paired real-time 3D echocardiography (3DE) and cardiac magnetic resonance (CMR) sequences from 138 subjects were used to construct a mapping function between the two modalities to correct for biases in left ventricular clinical cardiac indices, as well as regional shape. Leave-one-out cross-validation revealed a significant reduction in mean bias, narrower limits of agreement, and higher intraclass correlation coefficients for all functional indices between CMR and 3DE geometries after spatiotemporal mapping. Meanwhile, average root mean squared errors between surface coordinates of 3DE and CMR geometries across the cardiac cycle decreased from 7 ± 1 to 4 ± 1 mm for the total study population. Our generalised method for mapping between time-varying cardiac geometries obtained using different acquisition and analysis protocols enables the pooling of data between modalities and the potential for smaller studies to leverage large population databases for quantitative comparisons. [ABSTRACT FROM AUTHOR]

Label noise hampers supervised training of neural networks. However, data without label noise is often infeasible to attain, especially for medical tasks. Attaining high-quality medical labels would require a pool of experts and their consensus reading, which would be extremely costly. Several methods have been proposed to mitigate the adverse effects of label noise during training. State-of-the-art methods use multiple networks that exploit different decision boundaries to identify label noise. Among the best performing methods is co-teaching. However, co-teaching comes with the requirement of knowing label noise a priori. Hence, we propose a co-teaching method that does not require any prior knowledge about the level of label noise. We introduce stochasticity to select or reject training instances. We have extensively evaluated the method on synthetic experiments with extreme label noise levels and applied it to real-world medical problems of ECG classification and cardiac MRI segmentation. Results show that the approach is robust to its hyperparameter choice and applies to various classification tasks with unknown levels of label noise. [ABSTRACT FROM AUTHOR]

An increasing and aging patient population poses a growing burden on healthcare professionals. Automation of medical imaging diagnostics holds promise for enhancing patient care and reducing manpower required to accommodate an increasing patient-population. Deep learning, a subset of machine learning, has the potential to facilitate automated diagnostics, but commonly requires large-scaled labeled datasets. In medical domains, data is often abundant but labeling is a laborious and costly task. Active learning provides a method to optimize the selection of unlabeled samples that are most suitable for improvement of the model and incorporate them into the model training process. This approach proves beneficial when only a small number of labeled samples are available. Various selection methods currently exist, but most of them employ fixed querying schedules. There is limited research on how the timing of a query can impact performance in relation to the number of queried samples. This paper proposes a novel approach called dynamic querying, which aims to optimize the timing of queries to enhance model development while utilizing as few labeled images as possible. The performance of the proposed model is compared to a model trained utilizing a fully-supervised training method, and its effectiveness is assessed based on dataset size requirements and loss rates. Dynamic querying demonstrates a considerably faster learning curve in relation to the number of labeled samples used, achieving an accuracy of 70% using only 24 samples, compared to 82% for a fully-supervised model trained on the complete training dataset of 1017 images. [ABSTRACT FROM AUTHOR]

Left ventricular (LV) myocardial mass is important in the evaluation of cardiac remodeling and requires accurate assessment when performed on linear measurements in two-dimensional echocardiography (Echo). We aimed to compare the accuracy of the Devereaux formula (DEV) and the Teichholz formula (TEICH) in calculating LV myocardial mass in Echo using cardiac magnetic resonance (CMR) as the reference method. Based on preceding mathematical calculations, we identified primarily LV size rather than wall thickness as the main source of bias between DEV and TEICH in a retrospective derivation cohort (n = 1276). Although LV mass from DEV and TEICH were correlated with CMR, TEICH did not show a proportional bias as did DEV (− 2 g/m2 vs. + 22 g/m2). This could be validated in an independent prospective cohort (n = 226) with symptomatic non-ischemic heart failure. DEV systematically overestimated LV mass in all tiers of LV remodeling as compared to TEICH. In conclusion, the TEICH method accounts for the changes in LV geometry with increasing LV mass and thus better reflects the different pattern of LV remodeling than the DEV method. This has important clinical implications, as TEICH may be more appropriate for use in clinical practice, rather than DEV, currently recommended. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

OPG/RANK/RANKL axis was reportedly involved in initiating various diseases, especially bone and cardiovascular diseases. This study aimed to assess the relationship between some OPG, RANK, and RANKL polymorphisms and alleles and iron-overload-induced cardiomyopathy in children with transfusion-dependent thalassemia (TDT). This study included 80 TDT children and 80 age and sex-matched controls. Real-time PCR was done for rs207318 polymorphism for the OPG gene and rs1805034, rs1245811, and rs75404003 polymorphisms for the RANK gene, and rs9594782 and rs2277438 polymorphisms for the RANKL gene. Cardiac T2* MRI and ejection fraction (EF) were done to assess the myocardial iron status and cardiac function. In this study, there were no significant differences in frequencies of the studied polymorphisms between cases and controls (p > 0.05 in all). In TDT children, OPG rs2073618 (G > C) had a significant relation to myocardial iron overload (p = 0.02). Its C allele had significantly more frequent normal EF than its G allele (p = 0.04). RANK rs75404403 (C > DEL) had a significant relation to cardiac dysfunction (p = 0.02). Moreover, the C allele of that gene had significantly more frequent affected EF than its DEL allele (p = 0.02). The A allele of RANKL rs2277438 (G > A) had significantly less frequent severe cardiac iron overload than the G allele (p = 0.04). In conclusion, the OPG/ RANK/RANKL genes may act as genetic markers for iron-induced cardiomyopathy in TDT children. Some of the studied genes' polymorphisms and alleles were significantly related to myocardial iron overload and cardiac dysfunction in TDT children. [ABSTRACT FROM AUTHOR]

Pectus excavatum (PE) is a congenital malformation with a funnel-shaped depression of the sternum that can lead to cardiac symptoms. However, there are patients with thoracic constriction (defined as elevated Haller-Index > 3.25 determined by cardiac magnetic resonance imaging (CMR)) without visible evidence of PE, leading to similar complaints. Between January 2004 till June 2020, patients who underwent CMR for further evaluation of the heart, due to cardiac symptoms were enrolled and compared to controls. Biventricular global strain analysis was assessed using feature tracking (CMR-FT). ECG and/or Holter recordings were performed to detect rhythm events. Cardiac symptoms were evaluated in detail using a questionnaire. Finally, 88 patients (male 35, female 53) with elevated Haller-Index (3.9 ± 0.8) were included and compared to CMR data from 25 individuals with confirmed PE and 25 healthy controls (HC). Mean age at time of CMR was 35 ± 16 years. The most common symptoms at presentation were palpitations (41%), followed by dyspnea (24%) and atypical chest pain (14%). Three patients (3%) had atrial fibrillation or atrial flutter. Concomitant phenomena were pericardial effusion in 39% and mitral valve prolapse (MVP) in 27% of the study cohort. While there were no differences in left ventricular function or volumes, right ventricular function (RVEF) was significantly lower in patients with internal PE compared to HC (RVEF (%) 50 ± 5 vs 59 ± 4, p < 0.01). Strain analysis revealed only discrete changes in RV strain, implying a purely mechanical problem in the absence of structural changes. RV dimensions were negatively correlated with the size of thoracic indices (r = 0.41), reflecting the extent of thoracic constriction. MVP was more prevalent in patients with greater thoracic indices (r = 0.24). The described cohort, referred to as internal PE because of the absence of external changes, showed similar CMR morphologic findings as patients with real PE (especially altered dimensions of the right heart and a lower RVEF). In addition, there was a high incidence of rhythm disturbances, such as extrasystoles or arrhythmias. In one-third of the study cohort additional abnormalities such as pericardial effusion or MVP were present, with MVP being found more frequently in patients with larger thoracic indices, suggesting a possible common pathogenesis. Trial registration: ISRCTN registry, ISRCTN15355937, retrospectively registered 03.06.2022, https://www.isrctn.com/ISRCTN15355937?q=15355937&filters=&sort=&offset=1&totalResults=1&page=1&pageSize=10. [ABSTRACT FROM AUTHOR]

Myocardial deformation analysis by cardiac MRI (CMR) yielding global circumferential and longitudinal strain (GCS and GLS) is an increasingly utilized method to accurately quantify systolic function and predict clinical events in patients with Fontan circulation. The purpose of this study was to use principal component analysis (PCA) to investigate myocardial temporal deformation patterns derived from strain–time curves to learn about latent strain features beyond peak values. We conducted the study with specific attention to dominant single left or right ventricle (SLV and SRV) morphologies. Methods and Results: Patients remote from Fontan operation who underwent follow-up CMR were analyzed for standard volumetric and function hemodynamics including myocardial deformation parameters including GCS and GLS. We applied PCA to investigate in an unbiased fashion the strain–time curve morphology and to calculate patient specific shape scores. All variables were subjected to single variable Cox regression analysis to detect composite clinical outcome including death, heart transplant, protein losing enteropathy and plastic bronchitis. A total of 122 patients, (SLV = 67, SRV = 55) with a mean age of 12.7 years underwent comprehensive CMR analysis. The PCA revealed 3 primary modes of strain-curve variation regardless of single ventricle morphology and type of strain investigated. Principle components (PCs) described changes in (1) strain–time curve amplitude, (2) time-to-peak strain, and (3) post-systolic slope of the strain–time curve. Considering only SLV patients, GCS was only CMR variable predictive of clinical events (HR 1.46, p = 0.020). In the SRV group, significant CMR predictors of clinical events were derived indexed end-diastolic (HR 1.02, p = 0.023) and end-systolic (HR 1.03, p = 0.022) volumes, GCS (HR 1.91, p = 0.003) and its related first component score (HR 1.20, p = 0.005), GLS (HR 1.32, p = 0.029) and its third component score (HR 1.58, p = 0.017). CMR derived global strain measures are sensitive markers of clinical outcomes in patients with Fontan circulation, particularly in patients with the SRV morphology. Myocardial strain–time curve morphology specific to SLV and SRV patients inspired by unbiased PCA technique can further aid with predicting clinical outcomes. [ABSTRACT FROM AUTHOR]

Whether sex differences exist in the cardiac remodeling related to aortic regurgitation (AR) is unclear. Cardiac magnetic resonance (CMR) is the current non-invasive reference standard for cardiac remodeling assessment and can evaluate tissue characteristics. This prospective cohort included patients with AR undergoing CMR between 2011 and 2020. We excluded patients with confounding causes of remodeling. We quantified left ventricular (LV) volume, mass, AR severity, replacement fibrosis by late Gadolinium enhancement (LGE), and extracellular expansion by extracellular volume fraction (ECV). We studied 280 patients (109 women), median age 59.5 (47.2, 68.6) years (P for age = 0.25 between sexes). Women had smaller absolute LV volume and mass than men across the spectrum of regurgitation volume (RVol) (P ≤ 0.01). In patients with ≥ moderate AR and with adjustment for body surface area, indexed LV end-diastolic volume and mass were not significantly different between sexes (all P > 0.5) but men had larger indexed LV end systolic volume and lower LV ejection fraction (P ≥ 0.01). Women were more likely to have NYHA class II or greater symptoms than men but underwent surgery at a similar rate. Prevalence and extent of LGE was not significantly different between sexes or across RVol. Increasing RVol was independently associated with increasing ECV in women, but not in men (adjusted P for interaction = 0.03). In conclusion, women had lower LV volumes and mass than men across AR severity but their ECV increased with higher regurgitant volume, while ECV did not change in men. Indexing to body surface area did not fully correct for the cardiac remodeling differences between men and women. Women were more likely to have symptoms but underwent surgery at a similar rate to men. Further research is needed to determine if differences in ECV would translate to differences in the course of AR and outcomes. [ABSTRACT FROM AUTHOR]

Robust dynamic cardiac magnetic resonance imaging (MRI) has been a long-standing endeavor—as real-time imaging can provide information on the temporal signatures of disease we currently cannot assess—with the past decade seeing remarkable advances in acceleration using compressed sensing (CS) and artificial intelligence (AI). However, substantial limitations to real-time imaging remain and reconstruction quality is not always guaranteed. To improve reconstruction fidelity in dynamic cardiac MRI, we propose a novel predictive signal model that uses a priori statistics to adaptively predict temporal cardiac dynamics. By using a small training set obtained from the same patient, the new signal model can achieve robust dynamic cardiac MRI in the presence of irregular cardiac rhythm. Evaluation on simulated irregular cardiac dynamics and prospectively undersampled clinical cardiac MRI data demonstrate improved reconstruction quality for two reconstruction frameworks: Kalman filter and CS. The predictive model also works with different undersampling patterns (cartesian, radial, spiral) and can serve as a versatile foundation for robust dynamic cardiac MRI. [ABSTRACT FROM AUTHOR]

Succinate is enhanced during initial reperfusion in blood from the coronary sinus in ST-segment elevation myocardial infarction (STEMI) patients and in pigs submitted to transient coronary occlusion. Succinate levels might have a prognostic value, as they may correlate with edema volume or myocardial infarct size. However, blood from the coronary sinus is not routinely obtained in the CathLab. As succinate might be also increased in peripheral blood, we aimed to investigate whether peripheral plasma concentrations of succinate and other metabolites obtained during coronary revascularization correlate with edema volume or infarct size in STEMI patients. Plasma samples were obtained from peripheral blood within the first 10 min of revascularization in 102 STEMI patients included in the COMBAT-MI trial (initial TIMI 1) and from 9 additional patients with restituted coronary blood flow (TIMI 2). Metabolite concentrations were analyzed by 1H-NMR. Succinate concentration averaged 0.069 ± 0.0073 mmol/L in patients with TIMI flow ≤ 1 and was significantly increased in those with TIMI 2 at admission (0.141 ± 0.058 mmol/L, p < 0.05). However, regression analysis did not detect any significant correlation between most metabolite concentrations and infarct size, extent of edema or other cardiac magnetic resonance (CMR) variables. In conclusion, spontaneous reperfusion in TIMI 2 patients associates with enhanced succinate levels in peripheral blood, suggesting that succinate release increases overtime following reperfusion. However, early plasma levels of succinate and other metabolites obtained from peripheral blood does not correlate with the degree of irreversible injury or area at risk in STEMI patients, and cannot be considered as predictors of CMR variables. Trial registration: Registered at www.clinicaltrials.gov (NCT02404376) on 31/03/2015. EudraCT number: 2015-001000-58. [ABSTRACT FROM AUTHOR]

In patients with transfusion-dependent thalassemia (TDT), pulmonary function impairment has been reported but data are conflicting. Moreover, it remains unclear whether pulmonary dysfunction is associated with iron overload. This study aimed to evaluate the pulmonary function in patients with TDT and to investigate the associations between pulmonary dysfunction and iron overload. It was a retrospective observational study. 101 patients with TDT were recruited for lung function tests. The most recent ferritin levels (pmol/L) and the magnetic resonance imaging (MRI) measurements of the myocardial and liver iron status, as measured by heart and liver T2* relaxation time (millisecond, ms) respectively, were retrieved from the computerized medical records. Only data within 12 months from the lung function measurement were included in the analysis. The serum ferritin, and the cardiac and liver T2* relaxation time were the surrogate indexes of body iron content. The threshold of abnormality in lung function was defined as under 80% of the predicted value. 101 subjects were recruited with a mean age of 25.1 years (standard deviation (SD) 7.9 years). Thirty-eight (38%) and five (5%) demonstrated restrictive and obstructive lung function deficits, respectively. A weak correlation of FVC %Predicted and TLC %Predicted with MRI myocardial T2* relaxation time (rho = 0.32, p = 0.03 and rho = 0.33, p = 0.03 respectively) was observed. By logistic regression, MRI cardiac T2* relaxation time was negatively associated with restrictive lung function deficit (B − 0.06; SE 0.03; Odds ratio 0.94; 95% confidence interval (CI) 0.89–0.99; p = 0.023) after adjusting for age, sex and body mass index. Restrictive pulmonary function deficit was commonly observed in patients with TDT, and the severity potentially correlates with myocardial iron content. Monitoring of lung function in this group of patients, particularly for those with iron overload, is important. [ABSTRACT FROM AUTHOR]

Manganese-enhanced magnetic resonance imaging can provide a surrogate measure of myocardial calcium handling. Its repeatability and reproducibility are currently unknown. Sixty-eight participants: 20 healthy volunteers, 20 with acute myocardial infarction, 18 with hypertrophic and 10 with non-ischemic dilated cardiomyopathy underwent manganese-enhanced magnetic resonance imaging. Ten healthy volunteers were re-scanned at 3 months. Native T1 values and myocardial manganese uptake were assessed for intra and inter-observer repeatability. Scan-rescan reproducibility was assessed in ten healthy volunteers. Intra-observer and inter-observer correlation was excellent in healthy volunteers for mean native T1 mapping [Lin's correlation coefficient (LCC) 0.97 and 0.97 respectively] and myocardial manganese uptake (LCC: 0.99 and 0.96 respectively). Scan-rescan correlation for native T1 and myocardial manganese uptake was also excellent. Similarly, intra-observer correlations for native T1 and myocardial manganese uptake in patients with acute myocardial infarction (LCC: 0.97 and 0.97 respectively), hypertrophic (LCC: 0.98 and 0.97 respectively) and dilated cardiomyopathy (LCC: 0.99 and 0.95 respectively) were excellent. Limits of agreement were broader in patients with dilated cardiomyopathy. Manganese-enhanced magnetic resonance imaging has high repeatability and reproducibility in healthy myocardium and high repeatability in diseased myocardium. However, further study is needed to establish robustness in pathologies with diffuse myocardial fibrosis. [ABSTRACT FROM AUTHOR]

Cardiac magnetic resonance (CMR) examinations require standardization to achieve reproducible results. Therefore, quality control as known as in other industries such as in-vitro diagnostics, could be of essential value. One such method is the statistical detection of long-time drifts of clinically relevant measurements. Starting in 2010, reports from all CMR examinations of a high-volume center were stored in a hospital information system. Quantitative parameters of the left ventricle were analyzed over time with moving averages of different window sizes. Influencing factors on the acquisition and on the downstream analysis were captured. 26,902 patient examinations were exported from the clinical information system. The moving median was compared to predefined tolerance ranges, which revealed an overall of 50 potential quality relevant changes ("alerts") in SV, EDV and LVM. Potential causes such as change of staff, scanner relocation and software changes were found not to be causal of the alerts. No other influencing factors were identified retrospectively. Statistical quality assurance systems based on moving average control charts may provide an important step towards reliability of quantitative CMR. A prospective evaluation is needed for the effective root cause analysis of quality relevant alerts. [ABSTRACT FROM AUTHOR]

Premature cardiovascular mortality is increased in long-term allogeneic stem cell transplant (allo-SCT) survivors, but little information exists regarding subclinical cardiovascular dysfunction in this population. We compared peak oxygen uptake ( V ˙ O2peak), a prognostic cardiovascular marker, and its determinants between long-term allo-SCT survivors and non-cancer controls. Fourteen allo-SCT survivors (mean ± SD, 44 ± 15 years, 50% male, median time since allo-SCT: 6.5 years [range 2–20]) and 14 age- and sex-matched controls (46 ± 13 years, 50% male) underwent cardiopulmonary exercise testing to quantify V ˙ O2peak. Resting echocardiography (left-ventricular ejection fraction and strain), exercise cardiac MRI (peak cardiac and stroke volume index [CIpeak, SVIpeak]), biochemistry (hemoglobin, troponin-I, B-natriuretic peptide), dual-energy x-ray absorptiometry (lean [LM] and fat [FM] mass, percent body fat [%BF]) and Fick-principal calculation (arteriovenous oxygen difference) were also performed. Survivors exhibited impaired V ˙ O2peak as compared with controls (25.9 ± 5.1 vs. 33.7 ± 6.5 ml kg−1 min−1, p = 0.002), which coincided with reduced CIpeak (6.6 ± 0.8 vs. 8.6 ± 1.9 L min−1 m−2; p = 0.001) secondary to reduced SVIpeak (48 ± 4 vs. 61 ± 8 ml m−2; p < 0.001) rather than chronotropic impairment, and higher %BF (difference, 7.9%, p = 0.007) due to greater FM (5.8 kg; p = 0.069) and lower LM (4.3 kg, p = 0.25). All other measures were similar between groups. Despite comparable resting cardiac function and biomarker profiles, survivors exhibited reduced V ˙ O2peak and exercise cardiac function and increased %BF relative to controls. These results highlight potential therapeutic avenues and the utility of exercise-based cardiovascular assessment in unmasking cardiovascular dysfunction in allo-SCT survivors. [ABSTRACT FROM AUTHOR]

This study presents a particle filter based framework to track cardiac surface from a time sequence of single magnetic resonance imaging (MRI) slices with the future goal of utilizing the presented framework for interventional cardiovascular magnetic resonance procedures, which rely on the accurate and online tracking of the cardiac surface from MRI data. The framework exploits a low-order parametric deformable model of the cardiac surface. A stochastic dynamic system represents the cardiac surface motion. Deformable models are employed to introduce shape prior to control the degree of the deformations. Adaptive filters are used to model complex cardiac motion in the dynamic model of the system. Particle filters are utilized to recursively estimate the current state of the system over time. The proposed method is applied to recover biventricular deformations and validated with a numerical phantom and multiple real cardiac MRI datasets. The algorithm is evaluated with multiple experiments using fixed and varying image slice planes at each time step. For the real cardiac MRI datasets, the average root-mean-square tracking errors of 2.61 mm and 3.42 mm are reported respectively for the fixed and varying image slice planes. This work serves as a proof-of-concept study for modeling and tracking the cardiac surface deformations via a low-order probabilistic model with the future goal of utilizing this method for the targeted interventional cardiac procedures under MR image guidance. For the real cardiac MRI datasets, the presented method was able to track the points-of-interests located on different sections of the cardiac surface within a precision of 3 pixels. The analyses show that the use of deformable cardiac surface tracking algorithm can pave the way for performing precise targeted intracardiac ablation procedures under MRI guidance. The main contributions of this work are twofold. First, it presents a framework for the tracking of whole cardiac surface from a time sequence of single image slices. Second, it employs adaptive filters to incorporate motion information in the tracking of nonrigid cardiac surface motion for temporal coherence. [ABSTRACT FROM AUTHOR]

Right ventricular (RV) volumes are commonly obtained through time-consuming manual delineations of cardiac magnetic resonance (CMR) images. Deep learning-based methods can generate RV delineations, but few studies have assessed their ability to accelerate clinical practice. Therefore, we aimed to develop a clinical pipeline for deep learning-based RV delineations and validate its ability to reduce the manual delineation time. Quality-controlled delineations in short-axis CMR scans from 1114 subjects were used for development. Time reduction was assessed by two observers using 50 additional clinical scans. Automated delineations were subjectively rated as (A) sufficient for clinical use, or as needing (B) minor or (C) major corrections. Times were measured for manual corrections of delineations rated as B or C, and for fully manual delineations on all 50 scans. Fifty-eight % of automated delineations were rated as A, 42% as B, and none as C. The average time was 6 min for a fully manual delineation, 2 s for an automated delineation, and 2 min for a minor correction, yielding a time reduction of 87%. The deep learning-based pipeline could substantially reduce the time needed to manually obtain clinically applicable delineations, indicating ability to yield right ventricular assessments faster than fully manual analysis in clinical practice. However, these results may not generalize to clinics using other RV delineation guidelines. [ABSTRACT FROM AUTHOR]

Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is associated with many pathological features, such as a reduction in global longitudinal strain (GLS), myofiber disarray and hypertrophy. The effects of these features on left ventricle (LV) function are, however, not clear in two phenotypes of HCM, namely, obstructive and non-obstructive. To address this issue, we developed patient-specific computational models of the LV using clinical measurements from 2 female HCM patients and a control subject. Left ventricular mechanics was described using an active stress formulation and myofiber disarray was described using a structural tensor in the constitutive models. Unloaded LV configuration for each subject was first determined from their respective end-diastole LV geometries segmented from the cardiac magnetic resonance images, and an empirical single-beat estimation of the end-diastolic pressure volume relationship. The LV was then connected to a closed-loop circulatory model and calibrated using the clinically measured LV pressure and volume waveforms, peak GLS and blood pressure. Without consideration of myofiber disarray, peak myofiber tension was found to be lowest in the obstructive HCM subject (60 kPa), followed by the non-obstructive subject (242 kPa) and the control subject (375 kPa). With increasing myofiber disarray, we found that peak tension has to increase in the HCM models to match the clinical measurements. In the obstructive HCM patient, however, peak tension was still depressed (cf. normal subject) at the largest degree of myofiber disarray found in the clinic. The computational modeling workflow proposed here can be used in future studies with more HCM patient data. [ABSTRACT FROM AUTHOR]