Cardiac Magnetic Resonance Imaging Data Research Articles

Deep learning of left atrial structure and function provides link to atrial fibrillation risk

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Role of cardiac magnetic resonance imaging in assessing the risk of various myocardial remodeling types in left ventricular noncompaction: genetic analysis data

Aim. To analyze contrast-enhanced cardiac magnetic resonance imaging (MRI) in patients with phenotypic manifestations of left ventricular non-compaction (LVNC) and related genetic mutations, as well as to determine the relationship between mutations and types of left ventricular (LV) remodeling and with a number of other morphological and functional cardiac parameters.Material and methods. From the registry of patients with LVNC and their relatives, patients with morphological signs of LVNC and 4 related mutations (MYH7, MYBPC3, TTN, and desmin genes (DES, DSG2, DSP and DSC2)). All patients underwent contrast-enhanced cardiac MRI, based on which the type of LV remodeling was determined.Results. The study included 44 patients who, according to genetic analysis, had mutations in sarcomeric genes responsible for LVNC development. In each patient, the type of LV remodeling was determined based on cardiac MRI results. We found that if patients with LVNC have mutations in the MYBPC3 and TTN genes, the chance of LV dilatation remodeling is significantly higher. On the contrary, in the presence of a DES gene mutation, the probability of this LV remodeling is lower, and milder morphological manifestations of LVNC are noted.Conclusion. The combination of cardiac MRI data and genetic analysis improves the morphological and functional stratification of patients with LVNC.

Patient-specific tissue engineered vascular graft for aortic arch reconstruction

Objective(s)The complexity of aortic arch reconstruction due to diverse 3-dimensional geometrical abnormalities is a major challenge. This study introduces 3-dimensional printed tissue-engineered vascular grafts, which can fit patient-specific dimensions, optimize hemodynamics, exhibit antithrombotic and anti-infective properties, and accommodate growth. MethodsWe procured cardiac magnetic resonance imaging with 4-dimensional flow for native porcine anatomy (n = 10), from which we designed tissue-engineered vascular grafts for the distal aortic arch, 4 weeks before surgery. An optimal shape of the curved vascular graft was designed using computer-aided design informed by computational fluid dynamics analysis. Grafts were manufactured and implanted into the distal aortic arch of porcine models, and postoperative cardiac magnetic resonance imaging data were collected. Pre- and postimplant hemodynamic data and histology were analyzed. ResultsPostoperative magnetic resonance imaging of all pigs with 1:1 ratio of polycaprolactone and poly-L-lactide-co-ε-caprolactone demonstrated no specific dilatation or stenosis of the graft, revealing a positive growth trend in the graft area from the day after surgery to 3 months later, with maintaining a similar shape. The peak wall shear stress of the polycaprolactone/poly-L-lactide-co-ε-caprolactone graft portion did not change significantly between the day after surgery and 3 months later. Immunohistochemistry showed endothelization and smooth muscle layer formation without calcification of the polycaprolactone/poly-L-lactide-co-ε-caprolactone graft. ConclusionsOur patient-specific polycaprolactone/poly-L-lactide-co-ε-caprolactone tissue-engineered vascular grafts demonstrated optimal anatomical fit maintaining ideal hemodynamics and neotissue formation in a porcine model. This study provides a proof of concept of patient-specific tissue-engineered vascular grafts for aortic arch reconstruction.

Prolonged mHealth-Based Arrhythmia Monitoring in Patients With Hypertrophic Cardiomyopathy (HCM-PATCH): Protocol for a Single-Center Cohort Study.

Patients with hypertrophic cardiomyopathy (HCM) are at increased risk of sudden cardiac death (SCD) due to ventricular arrhythmias and other arrhythmias. Screening for arrhythmias is mandatory to assess the individual SCD risk, but long-term electrocardiography (ECG) is rarely performed in routine clinical practice. Intensified monitoring may increase the detection rate of ventricular arrhythmias and identify more patients with an increased SCD risk who are potential candidates for the primary prophylactic implantation of an implantable cardioverter-defibrillator. To date, reliable data on the clinical benefit of prolonged arrhythmia monitoring in patients with HCM are rare. This prospective study aims to measure the prevalence of ventricular arrhythmias in patients with HCM observed by mobile health (mHealth)-based continuous rhythm monitoring over 14 days compared to standard practice (a 24- and 48-h long-term ECG). The frequency of ventricular arrhythmias in this 14-day period is compared with the frequency in the first 24 or 48 hours for the same patient (intraindividual comparison). Following the sample size calculation, 34 patients with a low or intermediate risk for SCD, assessed by the HCM Risk-SCD calculator, will need to be recruited in this single-center cohort study between June 2023 and February 2024. All patients will receive an ECG patch that records their heart activity over 14 days. In addition, cardiac magnetic resonance imaging and genetic testing data will be integrated into risk stratification. All patients will be asked to complete questionnaires about their symptoms; previous therapy; family history; and, at the end of the study, their experience with the ECG patch-based monitoring. The Hypertrophic Cardiomyopathy: Clinical Impact of a Prolonged mHealth-Based Arrhythmia Monitoring by Single-Channel ECG (HCM-PATCH) study investigates the prevalence of nonsustained ventricular tachycardia (ie, ≥3 consecutive ventricular beats at a rate of 120 beats per minute, lasting for <30 seconds) in low- to intermediate-risk patients with HCM (according to the HCM Risk-SCD calculator) with additional mHealth-based prolonged rhythm monitoring. The study was funded by third-party funding from the Department of Cardiology and Intensive Care Medicine, University Hospital Ostwestfalen-Lippe of Bielefeld University in June 2023 and approved by the institutional review board in May 2023. Data collection began in June 2023, and we plan to end the study in February 2024. Of the 34 patients, 26 have been recruited. Data analysis has not yet taken place. Publication of the results is planned for the fall of 2024. Prolonged mHealth-based rhythm monitoring could lead to differences in the prevalence of arrhythmias compared to 24- and 48-hour long-term ECGs. This may lead to improved identification of patients at high risk and trigger therapeutic interventions that may provide better protection from SCD or atrial fibrillation-related complications such as embolic stroke. Deutsches Register Klinischer Studien DRKS00032144; https://tinyurl.com/498bkrx8. DERR1-10.2196/52035.

Multiparametric assessment of right ventricular function in heart transplant recipients by echocardiography and relations with pulmonary hemodynamics

AbstractObjectiveRight ventricular (RV) dilatation and dysfunction are usually present in heart transplant (HTx) patients and worsened with residual pulmonary hypertension (PH). We aimed to determine the ability of different echocardiographic modalities to evaluate RV function in comparison with cardiac magnetic resonance (CMR) and their relations with pulmonary hemodynamics in HTx patients.MethodsA total of 62 data sets [echocardiographic, hemodynamic, and CMR] were acquired from 35 HTx patients. Comprehensive echocardiography, including two‐dimensional (2D) transthoracic echocardiography, speckle tracking echocardiography, and three‐dimensional (3D) echocardiography, was performed. Mean pulmonary artery pressure (mPAP) was obtained invasively from right heart catheterization. The correlations between all echocardiographic parameters and CMR imaging data and the differences between patients with and without residual PH were evaluated.ResultsDiastolic and systolic RV volumes and RV ejection fraction (RVEF) by 3D echocardiography correlated strongly with CMR‐derived volumes and RVEF (r = .91, r = .79, r = .64; p &lt; .0001 for each, respectively). Among other parameters, RV fractional area change (r = .439; p &lt; .001) and RV free wall longitudinal strain (RVFW‐LS) (r = −.34; p &lt; .05) correlated moderately with CMR‐RVEF, whereas tricuspid annulus S’ velocity (r = .29; p &lt; .05) and tricuspid annular systolic plane excursion (r = .27; p &lt; .05) correlated weakly with CMR‐RVEF. Additionally, 3D‐RVEF and RVFW‐LS were significantly decreased in studies with mPAP ≥ 20 mm Hg in comparison to those with mPAP &lt; 20 mm Hg (47.7 ± 3.7 vs. 50.9 ± 5.3, p = .04 and −15.5 ± 3.1 vs. −17.5 ± 3, p = .03, respectively).ConclusionThe best method for the evaluation of RV function in HTx recipients is 3D echocardiography. Besides, the subclinical impact of residual PH on RV function can be best determined by RVFW‐LS and 3D‐RVEF in these patients.

Microvascular function and inflammatory activation in Takotsubo cardiomyopathy.

The aim of this study was to determine microvascular function in the acute phase of Takotsubo syndrome (TTS) and to identify inflammatory mediators that could reflect TTS-induced pathology. The study included 20 females [median age 65years; interquarile range (IQR)=58-70years] with TTS according to the Mayo diagnostic criteria. During heart catheterization, we determined the index of microvascular resistance (IMR) and drew blood samples almost simultaneously from the aorta and coronary sinus. Cardiac magnetic resonance imaging (MRI) was done in the acute phase. We present descriptive coronary physiology and cardiac MRI data and compare inflammatory biomarkers between samples from the aorta, coronary sinus, and venous samples after 3months using the Wilcoxon signed-rank test. For comparison, we also analysed the actual biomarkers in venous blood from 15 healthy female controls. A supplementary analysis explored Spearman's rank correlation between the inflammatory biomarkers, IMR, MRI data, and cardiac biomarkers. The median IMR was 16.5mmHg·s (IQR=10.5-28.2mmHg·s), which was only slightly higher than that in the reference populations. Seven (35%) of the study subjects had IMR>25mmHg·s, suggesting a microvascular dysfunction. IMR was not affected by time from symptom onset. According to MRI, the apical region of the left ventricle was affected in 65% of the subjects. The median ejection fraction was 41% (IQR=31-48%). Biomarker analyses revealed elevation of markers for extracellular matrix remodelling and fibrosis, inflammation, immune activation, and upstream inflammation as compared with healthy controls. Only the levels of interleukin (IL)-1 receptor antagonist and soluble T-cell immunoglobulin mucin domain-3 (sTIM-3) were higher in the coronary sinus than in the aorta. No variable was significantly correlated with IMR. The IL-6 level in the aorta was inversely correlated with the left ventricular ejection fraction. Growth differentiation factor-15, osteoprotegerin, and von Willebrand factor levels in both aorta and coronary sinus were positively correlated with N-terminal-pro-brain-natriuretic peptide, while the correlations of IL-6 and sTIM-3 with N-terminal-pro-brain-natriuretic peptide were restricted to the aorta and coronary sinus, respectively. While most of the markers were within normal limits after 3months, matrix metalloproteinase-9 increased during follow-up to reach levels higher than those in the healthy controls. The median IMR was only slightly elevated in this study, but about one-third of the patients had values indicating microvascular dysfunction. The present study supports the involvement of several inflammatory pathways in TTS, including monocyte/macrophage activation, with sTIM-3 as a potential novel marker.

The arrhythmogenic cardiomyopathy phenotype associated with PKP2 c.1211dup variant.

The arrhythmogenic cardiomyopathy (ACM) phenotype, with life-threatening ventricular arrhythmias and heart failure, varies according to genetic aetiology. We aimed to characterise the phenotype associated with the variant c.1211dup (p.Val406Serfs*4) in the plakophilin‑2 gene (PKP2) and compare it with previously reported Dutch PKP2 founder variants. Clinical data were collected retrospectively from medical records of 106 PKP2 c.1211dup heterozygous carriers. Using data from the Netherlands ACM Registry, c.1211dup was compared with 3 other truncating PKP2 variants (c.235C > T (p.Arg79*), c.397C > T (p.Gln133*) and c.2489+1G > A (p.?)). Of the 106 carriers, 47 (44%) were diagnosed with ACM, at amean age of 41years. By the end of follow-up, 29 (27%) had experienced sustained ventricular arrhythmias and 12 (11%) had developed heart failure, with male carriers showing significantly higher risks than females on these endpoints (p < 0.05). Based on available cardiac magnetic resonance imaging and echocardiographic data, 46% of the carriers showed either right ventricular dilatation and/or dysfunction, whereas asubstantial minority (37%) had some form of left ventricular involvement. Both geographical distribution of carriers and haplotype analysis suggested PKP2 c.1211dup to be afounder variant originating from the South-Western coast of the Netherlands. Finally, aCox proportional hazards model suggested significant differences in ventricular arrhythmia-free survival between 4 PKP2 founder variants, including c.1211dup. The PKP2 c.1211dup variant is aDutch founder variant associated with atypical right-dominant ACM phenotype, but also left ventricular involvement, and apossibly more severe phenotype than other Dutch PKP2 founder variants.

Circulating biomarker- and magnetic resonance-based nomogram predicting long-term outcomes in dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) has a high mortality rate and is the most common indication for heart transplantation. Our study sought to develop a multiparametric nomogram to assess individualized all-cause mortality or heart transplantation (ACM/HTx) risk in DCM patients. The present study is a retrospective cohort study. The demographic, clinical, blood test, and cardiac magnetic resonance imaging (CMRI) data of DCM patients in the tertiary center (Fuwai Hospital) were collected. The primary endpoint was ACM/HTx. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied for variable selection. Multivariable Cox regression was used to develop a nomogram. The concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. A total of 218 patients were included in the present study. They were randomly divided into a training cohort and a validation cohort. The nomogram was established based on eight variables, including mid-wall late gadolinium enhancement, systolic blood pressure, diastolic blood pressure, left ventricular ejection fraction, left ventricular end-diastolic diameter, left ventricular end-diastolic volume index, free triiodothyronine, and N-terminal pro-B type natriuretic peptide. The AUCs regarding 1-year, 3-year, and 5-year ACM/HTx events were 0.859, 0.831, and 0.840 in the training cohort and 0.770, 0.789, and 0.819 in the validation cohort, respectively. The calibration curve and DCA showed good accuracy and clinical utility of the nomogram. We established and validated a circulating biomarker- and CMRI-based nomogram that could provide a personalized prediction of ACM/HTx for DCM patients, which might help risk stratification and decision-making in clinical practice.

A predictive signal model for dynamic cardiac magnetic resonance imaging

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.

#4703 IMPACT OF THE EARLY STAGES OF CKD WITH AND WITHOUT PROTEINURIA ON CARDIOVASCULAR OUTCOMES IN THE UK BIOBANK COHORT

Abstract Background and Aims Chronic kidney disease (CKD) is an established predictor of cardiovascular disease. However, the relationship between cardiovascular disease and the early stages of CKD defined as stage 1 (eGFR &amp;gt; 90 mL/min per 1.73 m2 + albuminuria) and stage 2 (eGFR 60–89 mL/min per 1.73 m2) with and without proteinuria, is lacking. In this study, we explored the incidence of major adverse cardiovascular events (MACE), heart failure (HF) and all-cause mortality of participants with early stages of CKD in the UK Biobank population. Method 456,015 participants from the UK Biobank were categorised into CKD stages. We calculated eGFR using the CKD-EPI 2021 equation and proteinuria was ascertained by the urinary protein creatinine ratio (defined as &amp;gt; 30mg/ mmol). We demonstrated the survival probability of adverse outcomes using unadjusted Kaplan-Meier curves and performed an adjusted Cox proportional hazard analysis to include MACE, HF, MACE and HF and all-cause mortality across CKD stages. Results Among the participants (mean age ± standard deviation, 56.5 ± 8.1 years) 282,121 (61.9%) had normal kidney function, 33,582 (7.4%) stage 1 CKD, 121,358 (26.6%) stage 2 CKD without proteinuria, 10,788 (2.4%) stage 2 CKD with proteinuria, 4,654 (1.0%) CKD stage 3A (eGFR 59-45mL/min per 1.73 m2) without proteinuria, 1034 (0.2%) stage 3A with proteinuria and 1,478 (0.3%) with more advanced CKD defined as stages 3B and above. Using Cox regression setting normal kidney function as the reference group, with the exception of stage 2 CKD without proteinuria; there was a progressive increase in the hazard ratio (HR) in all other stages of CKD with respect to MACE, HF, MACE and HF (Figure 1). Significantly, stage 2 CKD without proteinuria was associated with a lower incidence of adverse events than stage 1 CKD and had a comparable prognosis to normal renal function. There was a statistically significant association between stage 2 with proteinuria and MACE (HR 1.33, CI: 1.26 – 1.41), which was comparable to stage 3A without proteinuria (HR 1.32, CI: 1.22 – 1.42). Preliminary analysis of the ongoing cardiac magnetic resonance imaging (cMRI) data from this cohort shows similar progressive changes, apart from stage 2 CKD without proteinuria. Conclusion The presence of proteinuria in patients with mild CKD is a significant risk factor for MACE, HF, cMRI changes and all-cause mortality independent of age, sex, ethnicity, height, BMI, hypertension, diabetes, smoking status, and hyperlipidaemia. We recommend that in order to better risk stratify patients for prognostication and early treatment, stage 2 CKD should be considered as a significant cardiovascular risk only in the presence of proteinuria.

Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications.

In this investigation, an image-based method has been developed to estimate the volume of the left ventricular cavity using cardiac magnetic resonance (CMR) imaging data. Deep learning and Gaussian processes have been applied to bring the estimations closer to the cavity volumes manually extracted. CMR data from 339 patients and healthy volunteers have been used to train a stepwise regression model that can estimate the volume of the left ventricular cavity at the beginning and end of diastole. We have decreased the root mean square error (RMSE) of cavity volume estimation approximately from 13 to 8ml compared to the common practice in the literature. Considering the RMSE of manual measurements is approximately 4ml on the same dataset, 8ml of error is notable for a fully automated estimation method, which needs no supervision or user-hours once it has been trained. Additionally, to demonstrate a clinically relevant application of automatically estimated volumes, we inferred the passive material properties of the myocardium given the volume estimates using a well-validated cardiac model. These material properties can be further used for patient treatment planning and diagnosis.

Effect of pulmonary regurgitation on cardiac functions based on a human bi-ventricle model

Background and objective: Assessing the severity of pulmonary regurgitation (PR) and identifying optimal clinically relevant indicators for its treatment is crucial, yet standards for quantifying PR remain unclear in clinical practice. Computational modelling of the heart is in the process of providing valuable insights and information for cardiovascular physiology research. However, the advancements of finite element computational models have not been widely applied to simulate cardiac outputs in patients with PR. Furthermore, a computational model that incorporates both the left ventricle (LV) and right ventricle (RV) can be valuable in assessing the relationship between left and right ventricular morphometry and septal motion in PR patients. To enhance our understanding of the effect of PR on cardiac functions and mechanical behaviour, we developed a human bi-ventricle model to simulate five cases with varying degrees of PR severity. Methods: This bi-ventricle model was built using a patient-specific geometry and a widely used myofibre architecture. The myocardial material properties were described by a hyperelastic passive constitutive law and a modified time-varying elastance active tension model. To simulate realistic cardiac functions and the dysfunction of the pulmonary valve in PR disease cases, open-loop lumped parameter models representing systemic and pulmonary circulatory systems were designed. Results: In the baseline case, pressures in the aorta and main pulmonary artery and ejection fractions of both the LV and RV were within normal physiological ranges reported in the literature. The end-diastolic volume (EDV) of the RV under varying degrees of PR was comparable to the reported cardiac magnetic resonance imaging data. Moreover, RV dilation and interventricular septum motion from the baseline to the PR cases were clearly observed through the long-axis and short-axis views of the bi-ventricle geometry. The RV EDV in the severe PR case increased by 50.3% compared to the baseline case, while the LV EDV decreased by 18.1%. The motion of the interventricular septum was consistent with the literature. Furthermore, ejection fractions of both the LV and RV decreased as PR became severe, with LV ejection fraction decreasing from 60.5% at baseline to 56.3% in the severe case and RV ejection fraction decreasing from 51.8% to 46.8%. Additionally, the average myofibre stress of the RV wall at end-diastole significantly increased due to PR, from 2.7±12.1 kPa at baseline to 10.9±26.5 kPa in the severe case. The average myofibre stress of the LV wall at end-diastole increased from 3.7±18.1 kPa to 4.3±20.3 kPa. Conclusions: This study established a foundation for the computational modelling of PR. The simulated results showed that severe PR leads to reduced cardiac outputs in both the LV and RV, clearly observable septum motion, and a significant increase in the average myofibre stress in the RV wall. These findings demonstrate the potential of the model for further exploration of PR.

PO-01-050 STRUCTURAL CARDIAC CHANGES DETECTED BY MRI AFTER STEREOTACTIC BODY RADIOTHERAPY FOR TARGETS IN CLOSE PROXIMITY TO THE HEART

Stereotactic body radiation therapy (SBRT) has become a standard of care for inoperable early-stage non-small cell lung cancer and in case of pulmonary oligometastases. Recent studies indicate that incidental irradiation of the heart may be associated with an increased risk of non-cancer-related deaths. This study aims to assess and examine structural cardiac changes following peri- and myocardial SBRT using a systematic cardiac follow-up protocol including cardiac magnetic resonance (CMR) imaging. For 1485 patients treated with local-ablative SBRT from January 2014 to February 2022 at our institution, the distance between the planning target volume (PTV) and the heart was measured. Forty-eight out of 134 patients treated in close proximity (<2cm) to the heart were alive at follow-up. Of those, 20 were randomly invited to undergo a structured cardiac follow-up protocol including CMR. Ten patients consented to participate and underwent a structural follow-up protocol. Registration of CMR image data and the SBRT treatment plan was performed to examine a possible correlation between the dose delivered to the myocardium and structural cardiac changes assessed by CMR. Among the 10 participating patients, the most common primary tumors were non-small cell lung cancer (n=3) and small-cell lung cancer (n=2) (Table 1). Five patients presented with pre-SBRT cardiovascular comorbidities. Seven patients received SBRT for pulmonary or vertebral metastases and three patients for primary lung cancer with a median dose of 42.5 Gy (30.0-48.0 Gy) in 3-10 fractions. The mean heart dose (Dmean) and maximum heart dose (Dmax) were 4.9 Gy (0.7-8.4 Gy) and 36.2 Gy (8.3 – 64.1 Gy), respectively. On CMR, five patients showed myocardial alterations, such as late gadolinium enhancement and edema after a median follow-up time of 5.6 years (0.1-6.3 years) as shown in Figure 1. In patients with structural changes of the myocardium the median distance between the treated lesion and myocardium with 0.0 (0.0-1.08) cm vs. 1.4 (0.41-2.0) cm was significantly lower (p=0.015). Additionally, patients with structural changes on CMR showed significantly higher Dmax (135.4 Gy vs. 25.4 Gy, p=0.009), Dmean (4.4 Gy vs. 3.4 Gy, p=0.05). In this pilot study, patients treated with SBRT for pulmonary targets with PTV overlapping the heart showed structural changes of the myocardium in CMR. The presence of structural changes correlates with higher heart doses.

Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes

Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size and function. Examining variation in cardiac shape can add to our ability to understand cardiovascular risk and pathophysiology. We measured the left ventricle (LV) sphericity index (short axis length/long axis length) using deep learning-enabled image segmentation of cardiac magnetic resonance imaging data from the UK Biobank. Subjects with abnormal LV size or systolic function were excluded. The relationship between LV sphericity and cardiomyopathy was assessed using Cox analyses, genome-wide association studies, and two-sample Mendelian randomization. In a cohort of 38,897 subjects, we show that a one standard deviation increase in sphericity index is associated with a 47% increased incidence of cardiomyopathy (hazard ratio [HR]: 1.47, 95% confidence interval [CI]: 1.10-1.98, p= 0.01) and a 20% increased incidence of atrial fibrillation (HR: 1.20, 95% CI: 1.11-1.28, p<0.001), independent of clinical factors and traditional magnetic resonance imaging (MRI) measurements. We identify four loci associated with sphericity at genome-wide significance, and Mendelian randomization supports non-ischemic cardiomyopathy as causal for LV sphericity. Variation in LV sphericity in otherwise normal hearts predicts risk for cardiomyopathy and related outcomes and is caused by non-ischemic cardiomyopathy. This study was supported by grants K99-HL157421 (D.O.) and KL2TR003143 (S.L.C.) from the National Institutes of Health.

RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images

BackgroundAutomated segmentation techniques for cardiac magnetic resonance imaging (MRI) are beneficial for evaluating cardiac functional parameters in clinical diagnosis. However, due to the characteristics of unclear image boundaries and anisotropic resolution anisotropy produced by cardiac magnetic resonance imaging technology, most of the existing methods still have the problems of intra-class uncertainty and inter-class uncertainty. However, due to the irregularity of the anatomical shape of the heart and the inhomogeneity of tissue density, the boundaries of its anatomical structures become uncertain and discontinuous. Therefore, fast and accurate segmentation of cardiac tissue remains a challenging problem in medical image processing. MethodologyWe collected cardiac MRI data from 195 patients as training set and 35patients from different medical centers as external validation set. Our research proposed a U-net network architecture with residual connections and a self-attentive mechanism (Residual Self-Attention U-net, RSU-Net). The network relies on the classic U-net network, adopts the U-shaped symmetric architecture of the encoding and decoding mode, improves the convolution module in the network, introduces skip connections, and improves the network's capacity for feature extraction. Then for solving locality defects of ordinary convolutional networks. To achieve a global receptive field, a self-attention mechanism is introduced at the bottom of the model. The loss function employs a combination of Cross Entropy Loss and Dice Loss to jointly guide network training, resulting in more stable network training. ResultsIn our study, we employ the Hausdorff distance (HD) and the Dice similarity coefficient (DSC) as metrics for assessing segmentation outcomes. Comparsion was made with the segmentation frameworks of other papers, and the comparison results prove that our RSU-Net network performs better and can make accurate segmentation of the heart. New ideas for scientific research. ConclusionOur proposed RSU-Net network combines the advantages of residual connections and self-attention. This paper uses the residual links to facilitate the training of the network. In this paper, a self-attention mechanism is introduced, and a bottom self-attention block (BSA Block) is used to aggregate global information. Self-attention aggregates global information, and has achieved good segmentation results on the cardiac segmentation dataset. It facilitates the diagnosis of cardiovascular patients in the future.

Population-Level Prevalence of Rare Variants Associated With Atrial Fibrillation and its Impact on Patient Outcomes

BackgroundWhole exome sequencing may identify rare pathogenic/likely pathogenic variants (LPVs) that are linked to atrial fibrillation (AF). The impact of LPVs associated with AF on a population level on outcomes is unclear. ObjectivesThis study sought to examine the association of LPVs with AF and their impact on clinical outcomes using the UK Biobank, a national repository of participants with available whole exome sequencing data. MethodsA total of 200,631 individuals in the UK Biobank were studied. Incident and prevalent AF, comorbidities, and outcomes were identified using self-reported assessments and hospital stay operative, and death registry records. LPVs were determined using arrhythmia and cardiomyopathy gene panels with LOFTEE and ClinVar to predict variants of functional significance. ResultsCompared with control subjects, there was a modestly increased prevalence of LPVs among 9,585 patients with AF (2.0% vs 1.7%, respectively; P = 0.01). Among those with prevalent AF at <45 years of age, 4.2% were LPV carriers. LPVs in TTN and PKP2 were associated with AF with adjusted odds ratios of 2.69 (95% CI: 1.57-4.61) and 2.69 (95% CI: 1.54-4.68), respectively. There was no significant difference in combined ischemic stroke, heart failure hospitalization, and mortality among patients who have AF with and without LPVs (25.1% vs 23.8%; P = 0.49). Among participants with AF and available cardiac magnetic resonance imaging data, LPV carriers had lower left ventricular ejection fractions than non-LPV carriers (42% vs 52%; P = 0.027). ConclusionsPatients with AF had a modestly increased prevalence of LPVs. Among reference arrhythmia and cardiomyopathy genes, the contribution of rare variants to AF risk at a population level is modest and its impact on outcomes appears to be limited, despite an association of LPVs with reduced left ventricular ejection fraction among patients with AF.

Cardiovascular Disease Among Persons Living With HIV: New Insights Into Pathogenesis and Clinical Manifestations in a Global Context

Widespread use of contemporary antiretroviral therapy globally has transformed HIV disease into a chronic illness associated with excess risk for disorders of the heart and circulatory system. Current clinical care and research has focused on improving HIV-related cardiovascular disease outcomes, survival, and quality of life. In high-income countries, emphasis on prevention of atherosclerotic coronary artery disease over the past decade, including aggressive management of traditional risk factors and earlier initiation of antiretroviral therapy, has reduced risk for myocardial infarction among persons living with human immunodeficiency virus-1 infection. Still, across the globe, persons living with human immunodeficiency virus-1 infection on effective antiretroviral therapy treatment remain at increased risk for ischemic outcomes such as myocardial infarction and stroke relative to the persons without HIV. Unique features of HIV-related cardiovascular disease, in part, include the pathogenesis of coronary disease characterized by remodeling ectasia and unusual plaque morphology, the relative high proportion of type 2 myocardial infarction events, abnormalities of the aorta such as aneurysms and diffuse aortic inflammation, and HIV cerebrovasculopathy as a contributor to stroke risk. Literature over the past decade has also reflected a shift in the profile and prevalence of HIV-associated heart failure, with a reduced but persistent risk of heart failure with reduced ejection fraction and a growing risk of heart failure with preserved ejection fraction. Cardiac magnetic resonance imaging and autopsy data have emphasized the central importance of intramyocardial fibrosis for the pathogenesis of both heart failure with preserved ejection fraction and the increase in risk of sudden cardiac death. Still, more research is needed to better characterize the underlying mechanisms and clinical phenotype of HIV-associated myocardial disease in the current era. Across the different cardiovascular disease manifestations, a common pathogenic feature is that HIV-associated inflammation working through different mechanisms may amplify underlying pathology because of traditional risk and other host factors. The prevalence and phenotype of individual cardiovascular disease manifestations is ultimately influenced by the degree of injury from HIV disease combined with the profile of underlying cardiometabolic factors, both of which may differ substantially by region globally.

Relationship between the degree of myocardial damage according to contrast-enhanced cardiac magnetic resonance imaging and laboratory data in patients with acute myocardial infarction

Aim. To evaluate the information value of a complex of clinical and biochemical parameters of myocardial damage in predicting the development of transmural myocardial damage according to magnetic resonance imaging (MRI) in patients with acute myocardial infarction (AMI).Material and methods. The study included patients admitted to the emergency cardiology department with acute coronary syndrome. All patients underwent invasive coronary angiography, laboratory tests, and dynamic determination of cardiac biomarkers. In the interval of 6,1±4 days from admission to the hospital, patients underwent contrast-enhanced cardiac MRI. According to the pattern of delayed contrast enhancement, patients were divided into two groups: with a transmural and subendocardial pattern.Results. The mean age of patients was 62,5±10,5 years, while 27 (71,1%) had ST-segment elevation AMI. Among the risk factors for coronary artery disease, dyslipidemia (89,5%), hypertension (68,4%), and smoking (57,9%) were the most common. Creatine phosphokinase-MB (CPK-MB), serum high-sensitivity cardiac troponin I (cTnI) and C-reactive protein (CRP) values after 24 h were significantly higher in patients with transmural hyperenhancement. Moderate positive relationship was found between the global size of left ventricular (LV) damage according to MRI data and the levels of CPK-MB after 24 h and 4 days, as well as with CRP after 24 h, 4 and 7 days, and cTnI level after 24 h and 4 days. In the group of patients with transmural pattern, the global size of LV damage was significantly higher. Patients of this group were characterized by higher prevalence of microvascular obstruction. In a univariate regression analysis, there were following significant predictors of transmural myocardial damage: CPK-MB after 4 days (p=0,023) and ST segment elevation (p=0,029). Multivariate regression analysis showed that the only independent predictor of transmural myocardial damage was an increase in CPKMB after 4 days (p=0,023).Conclusion. An independent predictor of LV transmural damage in AMI was an elevated level of CPK-MB after 4 days. However, this laboratory marker had unsatisfactory information completeness and predictive quality. In this regard, cardiac MRI in patients with AMI, compared with the standard clinical assessment, can be considered preferable for assessing the depth of myocardial damage, risk stratification, and prognosis.

Variational Manifold Learning From Incomplete Data: Application to Multislice Dynamic MRI.

Current deep learning-based manifold learning algorithms such as the variational autoencoder (VAE) require fully sampled data to learn the probability density of real-world datasets. However, fully sampled data is often unavailable in a variety of problems, including the recovery of dynamic and high-resolution magnetic resonance imaging (MRI). We introduce a novel variational approach to learn a manifold from undersampled data. The VAE uses a decoder fed by latent vectors, drawn from a conditional density estimated from the fully sampled images using an encoder. Since fully sampled images are not available in our setting, we approximate the conditional density of the latent vectors by a parametric model whose parameters are estimated from the undersampled measurements using back-propagation. We use the framework for the joint alignment and recovery of multi-slice free breathing and ungated cardiac MRI data from highly undersampled measurements. Experimental results demonstrate the utility of the proposed scheme in dynamic imaging alignment and reconstructions.

Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta

Neonatal coarctation of the aorta (CoA) is a common congenital heart defect. Its antenatal diagnosis remains challenging, and its pathophysiology is poorly understood. We present a novel statistical shape modeling (SSM) pipeline to study the role and predictive value of arch shape in CoA in utero. Cardiac magnetic resonance imaging (CMR) data of 112 fetuses with suspected CoA was acquired and motion-corrected to three-dimensional volumes. Centerlines from fetal arches were extracted and used to build a statistical shape model capturing relevant anatomical variations. A linear discriminant analysis was used to find the optimal axis between CoA and false positive cases. The CoA shape risk score classified cases with an area under the curve of 0.907. We demonstrate the feasibility of applying a SSM pipeline to three-dimensional fetal CMR data while providing novel insights into the anatomical determinants of CoA and the relevance of in utero arch anatomy for antenatal diagnosis of CoA.Graphical abstract