A simulation-based phantom model for generating synthetic mitral valve image data-application to MRI acquisition planning.

PURPOSE: Numerical phantom methods are widely used in the development of medical imaging methods. They enable quantitative evaluation and direct comparison with controlled and known ground truth information. Cardiac magnetic resonance has the potential for a comprehensive evaluation of the mitral valve (MV). The goal of this work is the development of a numerical simulation framework that supports the investigation of MRI imaging strategies for the mitral valve. METHODS: We present a pipeline for synthetic image generation based on the combination of individual anatomical 3D models with a position-based dynamics simulation of the mitral valve closure. The corresponding images are generated using modality-specific intensity models and spatiotemporal sampling concepts. We test the applicability in the context of MRI imaging strategies for the assessment of the mitral valve. Synthetic images are generated with different strategies regarding image orientation (SAX and rLAX) and spatial sampling density. RESULTS: The suitability of the imaging strategy is evaluated by comparing MV segmentations against ground truth annotations. The generated synthetic images were compared to ones acquired with similar parameters, and the result is promising. The quantitative analysis of annotation results suggests that the rLAX sampling strategy is preferable for MV assessment, reaching accuracy values that are comparable to or even outperform literature values. CONCLUSION: The proposed approach provides a valuable tool for the evaluation and optimization of cardiac valve image acquisition. Its application to the use case identifies the radial image sampling strategy as the most suitable for MV assessment through MRI.

Noninvasive evaluation of pulmonary artery stiffness in heart failure patients via cardiovascular magnetic resonance.

Heart failure (HF) presents manifestations in both cardiac and vascular abnormalities. Pulmonary hypertension (PH) is prevalent in up 50% of HF patients. While pulmonary arterial hypertension (PAH) is closely associated with pulmonary artery (PA) stiffness, the association of HF caused, post-capillary PH and PA stiffness is unknown. We aimed to assess and compare PA stiffness and blood flow hemodynamics noninvasively across HF entities and control subjects without HF using CMR. We analyzed data of a prospectively conducted study with 74 adults, including 55 patients with HF across the spectrum (20 HF with preserved ejection fraction [HFpEF], 18 HF with mildly-reduced ejection fraction [HFmrEF] and 17 HF with reduced ejection fraction [HFrEF]) as well as 19 control subjects without HF. PA stiffness was defined as reduced vascular compliance, indicated primarily by the relative area change (RAC), altered flow hemodynamics were detected by increased flow velocities, mainly by pulse wave velocity (PWV). Correlations between the variables were explored using correlation and linear regression analysis. PA stiffness was significantly increased in HF patients compared to controls (RAC 30.92 ± 8.47 vs. 50.08 ± 9.08%, p < 0.001). PA blood flow parameters were significantly altered in HF patients (PWV 3.03 ± 0.53 vs. 2.11 ± 0.48, p < 0.001). These results were consistent in all three HF groups (HFrEF, HFmrEF and HFpEF) compared to the control group. Furthermore, PA stiffness was associated with higher NT-proBNP levels and a reduced functional status. PA stiffness can be assessed non-invasively by CMR. PA stiffness is increased in HFrEF, HFmrEF and HFpEF patients when compared to control subjects.Trial registration The study was registered at the German Clinical Trials Register (DRKS, registration number: DRKS00015615).

VEGF-B hypertrophy predisposes to transition from diastolic to systolic heart failure in hypertensive rats.

AIMS: Cardiac energy metabolism is centrally involved in heart failure (HF), although the direction of the metabolic alterations is complex and likely dependent on the particular stage of HF progression. Vascular endothelial growth factor B (VEGF-B) has been shown to modulate metabolic processes and to induce physiological cardiac hypertrophy; thus, it could be cardioprotective in the failing myocardium. This study investigates the role of VEGF-B in cardiac proteomic and metabolic adaptation in HF during aldosterone and high-salt hypertensive challenges. METHODS AND RESULTS: Male rats overexpressing the cardiac-specific VEGF-B transgene (VEGF-B TG) were treated for 3 or 6 weeks with deoxycorticosterone-acetate combined with a high-salt (HS) diet (DOCA + HS) to induce hypertension and cardiac damage. Extensive longitudinal echocardiographic studies of HF progression were conducted, starting at baseline. Sham-treated rats served as controls. To evaluate the metabolic alterations associated with HF, cardiac proteomics by mass spectrometry was performed. Hypertrophic non-treated VEGF-B TG hearts demonstrated high oxygen and adenosine triphosphate (ATP) demand with early onset of diastolic dysfunction. Administration of DOCA + HS to VEGF-B TG rats for 6 weeks amplified the progression from cardiac hypertrophy to HF, with a drastic drop in heart ATP concentration. Dobutamine stress echocardiographic analyses uncovered a significantly impaired systolic reserve. Mechanistically, the hallmark of the failing TG heart was an abnormal energy metabolism with decreased mitochondrial ATP, preceding the attenuated cardiac performance and leading to systolic HF. CONCLUSIONS: This study shows that the VEGF-B TG accelerates metabolic maladaptation which precedes structural cardiomyopathy in experimental hypertension and ultimately leads to systolic HF.

Comparison of hemodynamics in biological surgical aortic valve replacement and transcatheter aortic valve implantation: An in-silico study.

OBJECTIVES: In aortic valve replacement (AVR), the treatment strategy as well as the model and size of the implanted prosthesis have a major impact on the postoperative hemodynamics and thus on the clinical outcome. Preinterventional prediction of the hemodynamics could support the treatment decision. Therefore, we performed paired virtual treatment with transcatheter AVR (TAVI) and biological surgical AVR (SAVR) and compared hemodynamic outcomes using numerical simulations. METHODS: 10 patients with severe aortic stenosis (AS) undergoing TAVI were virtually treated with both biological SAVR and TAVI to compare post-interventional hemodynamics using numerical simulations of peak-systolic flow. Virtual treatment procedure was done using an in-house developed tool based on position-based dynamics methodology, which was applied to the patient's anatomy including LVOT, aortic root and aorta. Geometries were automatically segmented from dynamic CT-scans and patient-specific flow rates were calculated by volumetric analysis of the left ventricle. Hemodynamics were assessed using the STAR CCM+ software by solving the RANS equations. RESULTS: Virtual treatment with TAVI resulted in realistic hemodynamics comparable to echocardiographic measurements (median difference in transvalvular pressure gradient [TPG]: -0.33 mm Hg). Virtual TAVI and SAVR showed similar hemodynamic functions with a mean TPG with standard deviation of 8.45 ± 4.60 mm Hg in TAVI and 6.66 ± 3.79 mm Hg in SAVR (p = 0.03) while max. Wall shear stress being 12.6 ± 4.59 vs. 10.2 ± 4.42 Pa (p = 0.001). CONCLUSIONS: Using the presented method for virtual treatment of AS, we were able to reliably predict post-interventional hemodynamics. TAVI and SAVR show similar hemodynamics in a pairwise comparison.

Brief Research Report: Quantitative Analysis of Potential Coronary Microvascular Disease in Suspected Long-COVID Syndrome.

Background: Case series have reported persistent cardiopulmonary symptoms, often termed long-COVID or post-COVID syndrome, in more than half of patients recovering from Coronavirus Disease 19 (COVID-19). Recently, alterations in microvascular perfusion have been proposed as a possible pathomechanism in long-COVID syndrome. We examined whether microvascular perfusion, measured by quantitative stress perfusion cardiac magnetic resonance (CMR), is impaired in patients with persistent cardiac symptoms post-COVID-19. Methods: Our population consisted of 33 patients post-COVID-19 examined in Berlin and London, 11 (33%) of which complained of persistent chest pain and 13 (39%) of dyspnea. The scan protocol included standard cardiac imaging and dual-sequence quantitative stress perfusion. Standard parameters were compared to 17 healthy controls from our institution. Quantitative perfusion was compared to published values of healthy controls. Results: The stress myocardial blood flow (MBF) was significantly lower [31.8 ± 5.1 vs. 37.8 ± 6.0 (µl/g/beat), P < 0.001] and the T2 relaxation time was significantly higher (46.2 ± 3.6 vs. 42.7 ± 2.8 ms, P = 0.002) post-COVID-19 compared to healthy controls. Stress MBF and T1 and T2 relaxation times were not correlated to the COVID-19 severity (Spearman r = -0.302, -0.070, and -0.297, respectively) or the presence of symptoms. The stress MBF showed a U-shaped relation to time from PCR to CMR, no correlation to T1 relaxation time, and a negative correlation to T2 relaxation time (Pearson r = -0.446, P = 0.029). Conclusion: While we found a significantly reduced microvascular perfusion post-COVID-19 compared to healthy controls, this reduction was not related to symptoms or COVID-19 severity.

Impact of Right Ventricular Pressure Load After Repair of Tetralogy of Fallot.

Background Right ventricular outflow tract (RVOT) stenosis after repair of tetralogy of Fallot has been linked with favorable right ventricular remodeling but adverse outcomes. The aim of our study was to assess the hemodynamic impact and prognostic relevance of right ventricular pressure load in this population. Methods and Results A total of 296 patients with repaired tetralogy of Fallot (mean age, 17.8±7.9 years) were included in a prospective cardiovascular magnetic resonance multicenter study. Myocardial strain was quantified by feature tracking technique at study entry. Follow-up, including the need for pulmonary valve replacement, was assessed. The combined end point consisted of ventricular tachycardia and cardiac death. A higher echocardiographic RVOT peak gradient was significantly associated with smaller right ventricular volumes and less pulmonary regurgitation, but lower biventricular longitudinal strain. During a follow-up of 10.1 (0.1-12.9) years, the primary end point was reached in 19 of 296 patients (cardiac death, n=6; sustained ventricular tachycardia, n=2; and nonsustained ventricular tachycardia, n=11). A higher RVOT gradient was associated with the combined outcome (hazard ratio [HR], 1.03; 95% CI, 1.00-1.06; P=0.026), and a cutoff gradient of ≥25 mm Hg was predictive for cardiovascular events (HR, 3.69; 95% CI, 1.47-9.27; P=0.005). In patients with pulmonary regurgitation ≥25%, a mild residual RVOT gradient (15-30 mm Hg) was not associated with a lower risk for pulmonary valve replacement. Conclusions Higher RVOT gradients were associated with less pulmonary regurgitation and smaller right ventricular dimensions but were related to reduced biventricular strain and emerged as univariate predictors of adverse events. Mild residual pressure gradients did not protect from pulmonary valve replacement. These results may have implications for the indication for RVOT reintervention in this population.

CMR findings after COVID-19 and after COVID-19-vaccination-same but different?

Cardiac involvement has been described in varying proportions of patients recovered from COVID-19 and proposed as a potential cause of prolonged symptoms, often described as post-COVID or long COVID syndrome. Recently, cardiac complications have been reported from COVID-19 vaccines as well. We aimed to compare CMR-findings in patients with clinical cardiac symptoms after COVID-19 and after vaccination. From May 2020 to May 2021, we included 104 patients with suspected cardiac involvement after COVID-19 who received a clinically indicated cardiac magnetic resonance (CMR) examination at a high-volume center. The mean time from first positive PCR to CMR was 112 ± 76 days. During their COVID-19 disease, 21% of patients required hospitalization, 17% supplemental oxygen and 7% mechanical ventilation. In 34 (32.7%) of patients, CMR provided a clinically relevant diagnosis: Isolated pericarditis in 10 (9.6%), %), acute myocarditis (both LLC) in 7 (6.7%), possible myocarditis (one LLC) in 5 (4.8%), ischemia in 4 (3.8%), recent infarction in 2 (1.9%), old infarction in 4 (3.8%), dilated cardiomyopathy in 3 (2.9%), hypertrophic cardiomyopathy in 2 (1.9%), aortic stenosis, pleural tumor and mitral valve prolapse each in 1 (1.0%). Between May 2021 and August 2021, we examined an additional 27 patients with suspected cardiac disease after COVID-19 vaccination. Of these, CMR provided at least one diagnosis in 22 (81.5%): Isolated pericarditis in 4 (14.8%), acute myocarditis in 9 (33.3%), possible myocarditis (acute or subsided) in 6 (22.2%), ischemia in 3 (37.5% out of 8 patients with stress test), isolated pericardial effusion (> 10 mm) and non-compaction-cardiomyopathy each in 1 (3.7%). The number of myocarditis diagnoses after COVID-19 was highly dependent on the stringency of the myocarditis criteria applied. When including only cases of matching edema and LGE and excluding findings in the right ventricular insertion site, the number of cases dropped from 7 to 2 while the number of cases after COVID-19 vaccination remained unchanged at 9. While myocarditis is an overall rare side effect after COVID-19 vaccination, it is currently the leading cause of myocarditis in our institution due to the large number of vaccinations applied over the last months. Contrary to myocarditis after vaccination, LGE and edema in myocarditis after COVID-19 often did not match or were confined to the RV-insertion site. Whether these cases truly represent myocarditis or a different pathological entity is to be determined in further studies.

COVID-19 vs. Classical Myocarditis Associated Myocardial Injury Evaluated by Cardiac Magnetic Resonance and Endomyocardial Biopsy.

Background: Despite the ongoing global pandemic, the impact of COVID-19 on cardiac structure and function is still not completely understood. Myocarditis is a rare but potentially serious complication of other viral infections with variable recovery, and is, in some cases, associated with long-term cardiac remodeling and functional impairment. Aim: To assess myocardial injury in patients who recently recovered from an acute SARS-CoV-2 infection with advanced cardiac magnetic resonance imaging (CMR) and endomyocardial biopsy (EMB). Methods: In total, 32 patients with persistent cardiac symptoms after a COVID-19 infection, 22 patients with acute classic myocarditis not related to COVID-19, and 16 healthy volunteers were included in this study and underwent a comprehensive baseline CMR scan. Of these, 10 patients post COVID-19 and 13 with non-COVID-19 myocarditis underwent a follow-up scan. In 10 of the post-COVID-19 and 15 of the non-COVID-19 patients with myocarditis endomyocardial biopsy (EMB) with histological, immunohistological, and molecular analysis was performed. Results: In total, 10 (31%) patients with COVID-19 showed evidence of myocardial injury, eight (25%) presented with myocardial oedema, eight (25%) exhibited global or regional systolic left ventricular (LV) dysfunction, and nine (28%) exhibited impaired right ventricular (RV) function. However, only three (9%) of COVID-19 patients fulfilled updated CMR-Lake Louise criteria (LLC) for acute myocarditis. Regarding EMB, none of the COVID-19 patients but 87% of the non-COVID-19 patients with myocarditis presented histological findings in keeping with acute or chronic inflammation. COVID-19 patients with severe disease on the WHO scale presented with reduced biventricular longitudinal function, increased RV mass, and longer native T1 times compared with those with only mild or moderate disease. Conclusions: In our cohort, CMR and EMB findings revealed that SARS-CoV-2 infection was associated with relatively mild but variable cardiac involvement. More symptomatic COVID-19 patients and those with higher clinical care demands were more likely to exhibit chronic inflammation and impaired cardiac function compared to patients with milder forms of the disease.

Assessment of hemodynamic responses to exercise in aortic coarctation using MRI-ergometry in combination with computational fluid dynamics.

In patients with aortic coarctation it would be desirable to assess pressure gradients as well as information about blood flow profiles at rest and during exercise. We aimed to assess the hemodynamic responses to physical exercise by combining MRI-ergometry with computational fluid dynamics (CFD). MRI was performed on 20 patients with aortic coarctation (13 men, 7 women, mean age 21.5 ± 13.7 years) at rest and during ergometry. Peak systolic pressure gradients, wall shear stress (WSS), secondary flow degree (SFD) and normalized flow displacement (NFD) were calculated using CFD. Stroke volume was determined based on MRI. On average, the pressure gradient was 18.0 ± 16.6 mmHg at rest and increased to 28.5 ± 22.6 mmHg (p < 0.001) during exercise. A significant increase in cardiac index was observed (p < 0.001), which was mainly driven by an increase in heart rate (p < 0.001). WSS significantly increased during exercise (p = 0.006), whereas SFD and NFD remained unchanged. The combination of MRI-ergometry with CFD allows assessing pressure gradients as well as flow profiles during physical exercise. This concept has the potential to serve as an alternative to cardiac catheterization with pharmacological stress testing and provides hemodynamic information valuable for studying the pathophysiology of aortic coarctation.

Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance.

Acute kidney injury (AKI) is a major complication after cardiothoracic surgery. Early prediction of AKI could prompt preventive measures, but is challenging in the clinical routine. One important reason is that the amount of postoperative data is too massive and too high-dimensional to be effectively processed by the human operator. We therefore sought to develop a deep-learning-based algorithm that is able to predict postoperative AKI prior to the onset of symptoms and complications. Based on 96 routinely collected parameters we built a recurrent neural network (RNN) for real-time prediction of AKI after cardiothoracic surgery. From the data of 15,564 admissions we constructed a balanced training set (2224 admissions) for the development of the RNN. The model was then evaluated on an independent test set (350 admissions) and yielded an area under curve (AUC) (95% confidence interval) of 0.893 (0.862-0.924). We compared the performance of our model against that of experienced clinicians. The RNN significantly outperformed clinicians (AUC = 0.901 vs. 0.745, p < 0.001) and was overall well calibrated. This was not the case for the physicians, who systematically underestimated the risk (p < 0.001). In conclusion, the RNN was superior to physicians in the prediction of AKI after cardiothoracic surgery. It could potentially be integrated into hospitals' electronic health records for real-time patient monitoring and may help to detect early AKI and hence modify the treatment in perioperative care.

Variability of Myocardial Strain During Isometric Exercise in Subjects With and Without Heart Failure.

Background: Fast strain-encoded cardiac magnetic resonance imaging (cMRI, fast-SENC) is a novel technology potentially improving characterization of heart failure (HF) patients by quantifying cardiac strain. We sought to describe the impact of isometric handgrip exercise (HG) on cardiac strain assessed by fast-SENC in HF patients and controls. Methods: Patients with stable HF and controls were examined using cMRI at rest and during HG. Left ventricular (LV) global longitudinal strain (GLS) and global circumferential (GCS) were derived from image analysis software using fast-SENC. Strain change < -0.5 and > +0.5 was classified as increase and decrease, respectively. Results: The study population comprised 72 subjects, including HF with reduced, mid-range and preserved ejection fraction and controls (HFrEF n = 18 HFmrEF n = 18, HFpEF n = 17, controls: n = 19). In controls, LV GLS remained stable in 36.8%, increased in 36.8% and decreased in 26.3% of subjects during HG. In HF subgroups, similar patterns of LV GLS response were observed (HFpEF: stable 41.2%, increase 35.3%, decrease: 23.5%; HFmrEF: stable 50.0%, increase 16.7%, decrease: 33.3%; HFrEF: stable 33.3%, increase 22.2%, decrease: 44.4%, p = 0.668). Mean change between LV GLS at rest and during HG ranged close to zero with broad standard deviation in all subgroups and was not significantly different between subgroups (+1.2 ± 5.4%, -0.6 ± 8.3%, -1.7 ± 10.7%, and -3.1 ± 19.4%, p = 0.746 in controls, HFpEF, HFmrEF and HFrEF, respectively). However, the absolute value of LV GLS change-irrespective of increase or decrease-was significantly different between subgroups with 4.4 ± 3.2% in controls, 5.9 ± 5.7% in HFpEF, 6.8 ± 8.3% in HFmrEF and 14.1 ± 13.3% in HFrEF (p = 0.005). The absolute value of LV GLS change significantly correlated with resting LVEF, NTproBNP and Minnesota Living with Heart Failure questionnaire scores. Conclusion: The response to isometric exercise in LV GLS is heterogeneous in all HF subgroups and in controls. The absolute value of LV GLS change during HG exercise is elevated in HF patients and associated with measures of HF severity. The diagnostic utility of fast-SENC strain assessment in conjunction with HG appears to be limited. Trial Registration: URL: https://www.drks.de; Unique Identifier: DRKS00015615.

Hemodynamic Modeling of Biological Aortic Valve Replacement Using Preoperative Data Only.

Objectives: Prediction of aortic hemodynamics after aortic valve replacement (AVR) could help optimize treatment planning and improve outcomes. This study aims to demonstrate an approach to predict postoperative maximum velocity, maximum pressure gradient, secondary flow degree (SFD), and normalized flow displacement (NFD) in patients receiving biological AVR. Methods: Virtual AVR was performed for 10 patients, who received actual AVR with a biological prosthesis. The virtual AVRs used only preoperative anatomical and 4D flow MRI data. Subsequently, computational fluid dynamics (CFD) simulations were performed and the abovementioned hemodynamic parameters compared between postoperative 4D flow MRI data and CFD results. Results: For maximum velocities and pressure gradients, postoperative 4D flow MRI data and CFD results were strongly correlated (R 2 = 0.75 and R 2 = 0.81) with low root mean square error (0.21 m/s and 3.8 mmHg). SFD and NFD were moderately and weakly correlated at R 2 = 0.44 and R 2 = 0.20, respectively. Flow visualization through streamlines indicates good qualitative agreement between 4D flow MRI data and CFD results in most cases. Conclusion: The approach presented here seems suitable to estimate postoperative maximum velocity and pressure gradient in patients receiving biological AVR, using only preoperative MRI data. The workflow can be performed in a reasonable time frame and offers a method to estimate postoperative valve prosthesis performance and to identify patients at risk of patient-prosthesis mismatch preoperatively. Novel parameters, such as SFD and NFD, appear to be more sensitive, and estimation seems harder. Further workflow optimization and validation of results seems warranted.

Virtual downsizing for decision support in mitral valve repair.

PURPOSE: Various options are available for the treatment of mitral valve insufficiency, including reconstructive approaches such as annulus correction through ring implants. The correct choice of general therapy and implant is relevant for an optimal outcome. Additional to guidelines, decision support systems (DSS) can provide decision aid by means of virtual intervention planning and predictive simulations. Our approach on virtual downsizing is one of the virtual intervention tools that are part of the DSS workflow. It allows for emulating a ring implantation based on patient-specific lumen geometry and vendor-specific implants. METHODS: Our approach is fully automatic and relies on a lumen mask and an annulus contour as inputs. Both are acquired from previous DSS workflow steps. A virtual surface- and contour-based model of a vendor-specific ring design (26-40 mm) is generated. For each case, the ring geometry is positioned with respect to the original, patient-specific annulus and additional anatomical landmarks. The lumen mesh is parameterized to allow for a vertex-based deformation with respect to the user-defined annulus. Derived from post-interventional observations, specific deformation schemes are applied to atrium and ventricle and the lumen mesh is altered with respect to the ring location. RESULTS: For quantitative evaluation, the surface distance between the deformed lumen mesh and segmented post-operative echo lumen close to the annulus was computed for 11 datasets. The results indicate a good agreement. An arbitrary subset of six datasets was used for a qualitative evaluation of the complete lumen. Two domain experts compared the deformed lumen mesh with post-interventional echo images. All deformations were deemed plausible. CONCLUSION: Our approach on virtual downsizing allows for an automatic creation of plausible lumen deformations. As it takes only a few seconds to generate results, it can be added to a virtual intervention toolset without unnecessarily increasing the pipeline complexity.

Uncertainty Quantification for Non-invasive Assessment of Pressure Drop Across a Coarctation of the Aorta Using CFD.

PURPOSE: Numerical assessment of the pressure drop across an aortic coarctation using CFD is a promising approach to replace invasive catheter-based measurements. The aim of this study was to investigate and quantify the uncertainty of numerical calculation of the pressure drop introduced during two essential steps of medical image processing: segmentation of the patient-specific geometry and measurement of patient-specific flow rates from 4D-flow-MRI. METHODS: Based on the baseline segmentation, geometries with different stenosis diameters were generated for a sample of ten patients. The pressure drop generated by these geometries was calculated for different volume flow rates using computational fluid dynamics. Based on these simulations, a second order polynomial fit was calculated. Based on these polynomial fits an uncertainty of pressure drop calculation was quantified. RESULTS: The calculated pressure drop values varied strongly between the patients. In four patients, pressure drops above and below the clinical threshold of 20 mmHg were found. The median standard deviation of the pressure drop was 2.3 mmHg. The sensitivity of the pressure drop toward changes in the volume flow rate or the stenosis geometry varied between patients. CONCLUSION: The uncertainty of numerical pressure drop calculation introduced by uncertainties during image segmentation and measurement of volume flow rates was comparable to the uncertainty of pressure drop measurements using invasive catheterization. However, in some patients this uncertainty would have led to different treatment decision. Therefore, patient-specific uncertainty assessment might help to better understand the reliability of a numerically calculated biomarker as the pressure drop across an aortic coarctation.

Renal sympathetic denervation restores aortic distensibility in patients with resistant hypertension: data from a multi-center trial.

Renal sympathetic denervation (RDN) is under investigation as a treatment option in patients with resistant hypertension (RH). Determinants of arterial compliance may, however, help to predict the BP response to therapy. Aortic distensibility (AD) is a well-established parameter of aortic stiffness and can reliably be obtained by CMR. This analysis sought to investigate the effects of RDN on AD and to assess the predictive value of pre-treatment AD for BP changes. We analyzed data of 65 patients with RH included in a multicenter trial. RDN was performed in all participants. A standardized CMR protocol was utilized at baseline and at 6-month follow-up. AD was determined as the change in cross-sectional aortic area per unit change in BP. Office BP decreased significantly from 173/92 ± 24/16 mmHg at baseline to 151/85 ± 24/17 mmHg (p < 0.001) 6 months after RDN. Maximum aortic areas increased from 604.7 ± 157.7 to 621.1 ± 157.3 mm2 (p = 0.011). AD improved significantly by 33% from 1.52 ± 0.82 to 2.02 ± 0.93 × 10-3 mmHg-1 (p < 0.001). Increase of AD at follow-up was significantly more pronounced in younger patients (p = 0.005) and responders to RDN (p = 0.002). Patients with high-baseline AD were significantly younger (61.4 ± 10.1 vs. 67.1 ± 8.4 years, p = 0.022). However, there was no significant correlation of baseline AD to response to RDN. AD is improved after RDN across all age groups. Importantly, these improvements appear to be unrelated to observed BP changes, suggesting that RDN may have direct effects on the central vasculature.

Non-invasive assessment of patient-specific aortic haemodynamics from four-dimensional flow MRI data.

We introduce a parameter estimation framework for automatically and robustly personalizing aortic haemodynamic computations from four-dimensional magnetic resonance imaging data. The framework is based on a reduced-order multiscale fluid-structure interaction blood flow model, and on two calibration procedures. First, Windkessel parameters of the outlet boundary conditions are personalized by solving a system of nonlinear equations. Second, the regional mechanical wall properties of the aorta are personalized by employing a nonlinear least-squares minimization method. The two calibration procedures are run sequentially and iteratively until both procedures have converged. The parameter estimation framework was successfully evaluated on 15 datasets from patients with aortic valve disease. On average, only 1.27 ± 0.96 and 7.07 ± 1.44 iterations were required to personalize the outlet boundary conditions and the regional mechanical wall properties, respectively. Overall, the computational model was in close agreement with the clinical measurements used as objectives (pressures, flow rates, cross-sectional areas), with a maximum error of less than 1%. Given its level of automation, robustness and the short execution time (6.2 ± 1.2 min on a standard hardware configuration), the framework is potentially well suited for a clinical setting.

Myocardial deformation parameters predict outcome in patients with repaired tetralogy of Fallot.

BACKGROUND: Parameters of myocardial deformation have been suggested to be superior to conventional measures of ventricular function and to predict outcome in repaired tetralogy of Fallot (ToF). We aimed to test the hypothesis that parameters of myocardial deformation on cardiac MRI (CMR) relate to symptoms and provide prognostic information in patients with repaired ToF. METHODS AND RESULTS: We included 372 patients with ToF (median age 16 years; 55% male), recruited within a nationwide, prospective study. Longitudinal (LS), circumferential (CS) and radial global strain (RS) were analysed by CMR-based feature tracking (FT). A combined endpoint of death, successful resuscitation or documented ventricular tachycardia was employed. Parameters of global strain were associated with New York Heart Association (NYHA) class and symptomatic deterioration. During a median follow-up of 7.4 years, 20 events occurred. Left ventricular (LV) CS and right ventricular (RV) LS emerged as predictors of outcome, independent of QRS duration, LV/RV ejection fraction and volumes, NYHA class and peak oxygen uptake. In combination, these parameters also identified a subgroup of patients at significantly increased risk of adverse of outcomes (HR 3.3, p=0.002). Furthermore, LV LS, RS, CS and RV LS were related to the risk of death and nearly missed death (p<0.05 for all). CONCLUSIONS: FT-CMR provides myocardial deformation parameters, easily derived from standard CMR studies. They relate to symptoms and clinical deterioration in patients with ToF. More importantly, they predict adverse outcome independent of established risk markers, and should be considered as a useful adjunct to established outcome predictors, especially in younger patients with ToF. CLINICAL TRIAL REGISTRATION NUMBER: http://www.clinicaltrials.gov: NCT00266188; Results.

Effects of incremental beta-blocker dosing on myocardial mechanics of the human left ventricle: MRI 3D-tagging insight into pharmacodynamics supports theory of inner antagonism.

Beta-blockers contribute to treatment of heart failure. Their mechanism of action, however, is incompletely understood. Gradients in beta-blocker sensitivity of helically aligned cardiomyocytes compared with counteracting transversely intruding cardiomyocytes seem crucial. We hypothesize that selective blockade of transversely intruding cardiomyocytes by low-dose beta-blockade unloads ventricular performance. Cardiac magnetic resonance imaging (MRI) 3D tagging delivers parameters of myocardial performance. We studied 13 healthy volunteers by MRI 3D tagging during escalated intravenous administration of esmolol. The circumferential, longitudinal, and radial myocardial shortening was determined for each dose. The curves were analyzed for peak value, time-to-peak, upslope, and area-under-the-curve. At low doses, from 5 to 25 µg·kg(-1)·min(-1), peak contraction increased while time-to-peak decreased yielding a steeper upslope. Combining the values revealed a left shift of the curves at low doses compared with baseline without esmolol. At doses of 50 to 150 µg·kg(-1)·min(-1), a right shift with flattening occurred. In healthy volunteers we found more pronounced myocardial shortening at low compared with clinical dosage of beta-blockers. In patients with ventricular hypertrophy and higher prevalence of transversely intruding cardiomyocytes selective low-dose beta-blockade could be even more effective. MRI 3D tagging could help to determine optimal individual beta-blocker dosing avoiding undesirable side effects.

An open-source software tool for the generation of relaxation time maps in magnetic resonance imaging.

BACKGROUND: In magnetic resonance (MR) imaging, T1, T2 and T2* relaxation times represent characteristic tissue properties that can be quantified with the help of specific imaging strategies. While there are basic software tools for specific pulse sequences, until now there is no universal software program available to automate pixel-wise mapping of relaxation times from various types of images or MR systems. Such a software program would allow researchers to test and compare new imaging strategies and thus would significantly facilitate research in the area of quantitative tissue characterization. RESULTS: After defining requirements for a universal MR mapping tool, a software program named MRmap was created using a high-level graphics language. Additional features include a manual registration tool for source images with motion artifacts and a tabular DICOM viewer to examine pulse sequence parameters. MRmap was successfully tested on three different computer platforms with image data from three different MR system manufacturers and five different sorts of pulse sequences: multi-image inversion recovery T1; Look-Locker/TOMROP T1; modified Look-Locker (MOLLI) T1; single-echo T2/T2*; and multi-echo T2/T2*. Computing times varied between 2 and 113 seconds. Estimates of relaxation times compared favorably to those obtained from non-automated curve fitting. Completed maps were exported in DICOM format and could be read in standard software packages used for analysis of clinical and research MR data. CONCLUSIONS: MRmap is a flexible cross-platform research tool that enables accurate mapping of relaxation times from various pulse sequences. The software allows researchers to optimize quantitative MR strategies in a manufacturer-independent fashion. The program and its source code were made available as open-source software on the internet.