22 research outputs found

    Free breathing contrast-enhanced time-resolved magnetic resonance angiography in pediatric and adult congenital heart disease

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    Contrast enhanced magnetic resonance angiography (MRA) is generally performed during a long breath-hold (BH), limiting its utility in infants and small children. This study proposes a free-breathing (FB) time resolved MRA (TRA) technique for use in pediatric and adult congenital heart disease (CHD)

    Real time flow with fast GPU reconstruction for continuous assessment of cardiac output

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    A novel approach for continuous cardiac output quantification during an exercise was developed and implemented on a heterogeneous image reconstruction system. Combination of spiral real-time PCMR sequence with parallel imaging allowed on high-temporal acquisition. Application of a GPU for image processing resulted in almost instantaneous reconstruction. An external computer equipped with the GPU was networked using CORBA technology. This let on seamless processing from a clinician point of view. The implementation was tested and validated against our multi -core CP

    Magnetic Resonance-Augmented Cardiopulmonary Exercise Testing Comprehensively Assessing Exercise Intolerance in Children with Cardiovascular Disease

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    BACKGROUND: Conventional cardiopulmonary exercise testing can objectively measure exercise intolerance but cannot provide comprehensive evaluation of physiology. This requires additional assessment of cardiac output and arteriovenous oxygen content difference. We developed magnetic resonance (MR)–augmented cardiopulmonary exercise testing to achieve this goal and assessed children with right heart disease. METHODS AND RESULTS: Healthy controls (n=10) and children with pulmonary arterial hypertension (PAH; n=10) and repaired tetralogy of Fallot (n=10) underwent MR-augmented cardiopulmonary exercise testing. All exercises were performed on an MR-compatible ergometer, and oxygen uptake was continuously acquired using a modified metabolic cart. Simultaneous cardiac output was measured using a real-time MR flow sequence and combined with oxygen uptake to calculate arteriovenous oxygen content difference. Peak oxygen uptake was significantly lower in the PAH group (12.6±1.31 mL/kg per minute; P=0.01) and trended toward lower in the tetralogy of Fallot group (13.5±1.29 mL/kg per minute; P=0.06) compared with controls (16.7±1.37 mL/kg per minute). Although tetralogy of Fallot patients had the largest increase in cardiac output, they had lower resting (3±1.2 L/min per m2) and peak (5.3±1.2 L/min per m2) values compared with controls (resting 4.3±1.2 L/min per m2 and peak 6.6±1.2 L/min per m2) and PAH patients (resting 4.5±1.1 L/min per m2 and peak 5.9±1.1 L/min per m2). Both the PAH and tetralogy of Fallot patients had blunted exercise–induced increases in arteriovenous oxygen content difference. However, only the PAH patients had significantly reduced peak values (6.9±1.3 mlO2/100 mL) compared with controls (8.4±1.4 mlO2/100 mL; P=0.005). CONCLUSIONS: MR-augmented cardiopulmonary exercise testing is feasible in both healthy children and children with cardiac disease. Using this novel technique, we have demonstrated abnormal exercise patterns in oxygen uptake, cardiac output, and arteriovenous oxygen content difference

    Real time magnetic resonance assessment of septal curvature accurately tracks acute hemodynamic changes in pediatric pulmonary hypertension

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    International audienceBACKGROUND:This study assesses the relationship between septal curvature and mean pulmonary artery pressure and indexed pulmonary vascular resistance in children with pulmonary hypertension. We hypothesized that septal curvature could be used to estimate right ventricular afterload and track acute changes in pulmonary hemodynamics.METHODS AND RESULTS:Fifty patients with a median age of 6.7 years (range, 0.45-16.5 years) underwent combined cardiac catheterization and cardiovascular magnetic resonance. The majority had idiopathic pulmonary arterial hypertension (n=30); the remaining patients had pulmonary hypertension associated with repaired congenital heart disease (n=17) or lung disease (n=3). Mean pulmonary artery pressure and pulmonary vascular resistance were acquired at baseline and during vasodilation. Septal curvature was measured using real-time cardiovascular magnetic resonance. There was a strong correlation between mean pulmonary artery pressure and SCmin at baseline and during vasodilator testing (r=-0.81 and -0.85, respectively; P<0.01). A strong linear relationship also existed between pulmonary vascular resistance and minimum septal curvature indexed to cardiac output both at baseline and during vasodilator testing (r=-0.88 and -0.87, respectively; P<0.01). Change in septal curvature metrics moderately correlated with absolute change in mean pulmonary artery pressure and pulmonary vascular resistance, respectively (r=0.58 and -0.74; P<0.01). Septal curvature metrics were able to identify vasoresponders with a sensitivity of 83% (95% confidence interval, 0.36-0.99) and a specificity of 91% (95% confidence interval, 0.77-0.97), using the Sitbon criteria. Idiopathic pulmonary arterial hypertension subgroup analysis revealed 3 responders with ΔSCmin values of 0.523, 0.551, and 0.568. If the middle value of 0.551 is taken as a cutoff, the approximate sensitivity would be 67% and the specificity would be 93%.CONCLUSIONS:Septal curvature metrics are able to estimate right ventricular afterload and track acute changes in pulmonary hemodynamics during vasodilator testing. This suggests that septal curvature could be used for continuing assessment of load in pulmonary hypertension

    2D sodium MRI of the human calf using half-sinc excitation pulses and compressed sensing

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    PURPOSE: Sodium MRI can be used to quantify tissue sodium concentration (TSC) in vivo; however, UTE sequences are required to capture the rapidly decaying signal. 2D MRI enables high in-plane resolution but typically has long TEs. Half-sinc excitation may enable UTE; however, twice as many readouts are necessary. Scan time can be minimized by reducing the number of signal averages (NSAs), but at a cost to SNR. We propose using compressed sensing (CS) to accelerate 2D half-sinc acquisitions while maintaining SNR and TSC. METHODS: Ex vivo and in vivo TSC were compared between 2D spiral sequences with full-sinc (TE = 0.73 ms, scan time ≈ 5 min) and half-sinc excitation (TE = 0.23 ms, scan time ≈ 10 min), with 150 NSAs. Ex vivo, these were compared to a reference 3D sequence (TE = 0.22 ms, scan time ≈ 24 min). To investigate shortening 2D scan times, half-sinc data was retrospectively reconstructed with fewer NSAs, comparing a nonuniform fast Fourier transform to CS. Resultant TSC and image quality were compared to reference 150 NSAs nonuniform fast Fourier transform images. RESULTS: TSC was significantly higher from half-sinc than from full-sinc acquisitions, ex vivo and in vivo. Ex vivo, half-sinc data more closely matched the reference 3D sequence, indicating improved accuracy. In silico modeling confirmed this was due to shorter TEs minimizing bias caused by relaxation differences between phantoms and tissue. CS was successfully applied to in vivo, half-sinc data, maintaining TSC and image quality (estimated SNR, edge sharpness, and qualitative metrics) with ≥50 NSAs. CONCLUSION: 2D sodium MRI with half-sinc excitation and CS was validated, enabling TSC quantification with 2.25 × 2.25 mm2 resolution and scan times of ≤5 mins

    Cleaning up our acts: Psychological interventions to reduce engine idling and improve air quality

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    A large-scale field experiment tested psychological interventions to reduce engine idling at long-wait stops. Messages based on theories of normative influence, outcome efficacy, and self-regulation were displayed approaching railway crossing on street poles. Observers coded whether drivers (N = 6049) turned off their engine while waiting at the railway crossings (only 27.2% did so at baseline). Automatic air quality monitors recorded levels of pollutants during barrier down times. To different degrees, the social norm and outcome efficacy messages successfully increased the proportion of drivers who turned off their engines (by 42% and 25%, respectively) and significantly reduced concentrations of atmospheric particulate matter (PM2.5) 2 m above ground level. Thus, the environment was improved through behavior change. Moreover, of both practical and theoretical significance, there was an ‘accelerator effect’, in line with theories of normative influence whereby the social norm message was increasingly effective as the volume of traffic increased

    Financing intersectoral action for health: a systematic review of co-financing models.

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    BACKGROUND: Addressing the social and other non-biological determinants of health largely depends on policies and programmes implemented outside the health sector. While there is growing evidence on the effectiveness of interventions that tackle these upstream determinants, the health sector does not typically prioritise them. From a health perspective, they may not be cost-effective because their non-health outcomes tend to be ignored. Non-health sectors may, in turn, undervalue interventions with important co-benefits for population health, given their focus on their own sectoral objectives. The societal value of win-win interventions with impacts on multiple development goals may, therefore, be under-valued and under-resourced, as a result of siloed resource allocation mechanisms. Pooling budgets across sectors could ensure the total multi-sectoral value of these interventions is captured, and sectors' shared goals are achieved more efficiently. Under such a co-financing approach, the cost of interventions with multi-sectoral outcomes would be shared by benefiting sectors, stimulating mutually beneficial cross-sectoral investments. Leveraging funding in other sectors could off-set flat-lining global development assistance for health and optimise public spending. Although there have been experiments with such cross-sectoral co-financing in several settings, there has been limited analysis to examine these models, their performance and their institutional feasibility. AIM: This study aimed to identify and characterise cross-sectoral co-financing models, their operational modalities, effectiveness, and institutional enablers and barriers. METHODS: We conducted a systematic review of peer-reviewed and grey literature, following PRISMA guidelines. Studies were included if data was provided on interventions funded across two or more sectors, or multiple budgets. Extracted data were categorised and qualitatively coded. RESULTS: Of 2751 publications screened, 81 cases of co-financing were identified. Most were from high-income countries (93%), but six innovative models were found in Uganda, Brazil, El Salvador, Mozambique, Zambia, and Kenya that also included non-public and international payers. The highest number of cases involved the health (93%), social care (64%) and education (22%) sectors. Co-financing models were most often implemented with the intention of integrating services across sectors for defined target populations, although models were also found aimed at health promotion activities outside the health sector and cross-sectoral financial rewards. Interventions were either implemented and governed by a single sector or delivered in an integrated manner with cross-sectoral accountability. Resource constraints and political relevance emerged as key enablers of co-financing, while lack of clarity around the roles of different sectoral players and the objectives of the pooling were found to be barriers to success. Although rigorous impact or economic evaluations were scarce, positive process measures were frequently reported with some evidence suggesting co-financing contributed to improved outcomes. CONCLUSION: Co-financing remains in an exploratory phase, with diverse models having been implemented across sectors and settings. By incentivising intersectoral action on structural inequities and barriers to health interventions, such a novel financing mechanism could contribute to more effective engagement of non-health sectors; to efficiency gains in the financing of universal health coverage; and to simultaneously achieving health and other well-being related sustainable development goals
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