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

AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance

Aims One of the major challenges in the quantification of myocardial blood flow (MBF) from stress perfusion cardiac magnetic resonance (CMR) is the estimation of the arterial input function (AIF). This is due to the non-linear relationship between the concentration of gadolinium and the MR signal, which leads to signal saturation. In this work, we show that a deep learning model can be trained to predict the unsaturated AIF from standard images, using the reference dual-sequence acquisition AIFs (DS-AIFs) for training. Methods and results A 1D U-Net was trained, to take the saturated AIF from the standard images as input and predict the unsaturated AIF, using the data from 201 patients from centre 1 and a test set comprised of both an independent cohort of consecutive patients from centre 1 and an external cohort of patients from centre 2 (n = 44). Fully-automated MBF was compared between the DS-AIF and AI-AIF methods using the Mann–Whitney U test and Bland–Altman analysis. There was no statistical difference between the MBF quantified with the DS-AIF [2.77 mL/min/g (1.08)] and predicted with the AI-AIF (2.79 mL/min/g (1.08), P = 0.33. Bland–Altman analysis shows minimal bias between the DS-AIF and AI-AIF methods for quantitative MBF (bias of −0.11 mL/min/g). Additionally, the MBF diagnosis classification of the AI-AIF matched the DS-AIF in 669/704 (95%) of myocardial segments. Conclusion Quantification of stress perfusion CMR is feasible with a single-sequence acquisition and a single contrast injection using an AI-based correction of the AIF

Collisionality and safety factor scalings of H-mode energy transport in the MAST spherical tokamak

A factor of 4 dimensionless collisionality scan of H-mode plasmas in MAST shows that the thermal energy confinement time scales as [formula]. Local heat transport is dominated by electrons and is consistent with the global scaling. The neutron rate is in good agreement with the ¿* dependence of tE,th. The gyrokinetic code GYRO indicates that micro-tearing turbulence might explain such a trend. A factor of 1.4 dimensionless safety factor scan shows that the energy confinement time scales as [formula] . These two scalings are consistent with the dependence of energy confinement time on plasma current and magnetic field. Weaker qeng and stronger ¿* dependences compared with the IPB98y2 scaling could be favourable for an ST-CTF device, in that it would allow operation at lower plasma current

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation : The MMs Challenge

The emergence of deep learning has considerably advanced the state-of-the-art in cardiac magnetic resonance (CMR) segmentation. Many techniques have been proposed over the last few years, bringing the accuracy of automated segmentation close to human performance. However, these models have been all too often trained and validated using cardiac imaging samples from single clinical centres or homogeneous imaging protocols. This has prevented the development and validation of models that are generalizable across different clinical centres, imaging conditions or scanner vendors. To promote further research and scientific benchmarking in the field of generalizable deep learning for cardiac segmentation, this paper presents the results of the Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation (MMs) Challenge, which was recently organized as part of the MICCAI 2020 Conference. A total of 14 teams submitted different solutions to the problem, combining various baseline models, data augmentation strategies, and domain adaptation techniques. The obtained results indicate the importance of intensity-driven data augmentation, as well as the need for further research to improve generalizability towards unseen scanner vendors or new imaging protocols. Furthermore, we present a new resource of 375 heterogeneous CMR datasets acquired by using four different scanner vendors in six hospitals and three different countries (Spain, Canada and Germany), which we provide as open-access for the community to enable future research in the field

Overview of mast results

Significant progress has been made on the Mega Ampere Spherical Tokamak (MAST) towards a fundamental understanding of transport, stability and edge physics and addressing technological issues for future large devices. Collaborative studies of the L-H transition with NSTX and ASDEX Upgrade confirm that operation in a connected double-null configuration significantly reduces the threshold power, Pthr. The MAST data provide support for a theory for the transition based on finite β drift wave turbulence suppression by self-generated zonal flows. Analysis of low and high field side density gradients in the H-mode pedestal provides support for an analytical model of the density pedestal width dependent on the neutral penetration depth. Adding MAST data to international confinement databases has enhanced confidence in scalings for ITER by significantly expanding the range of β and ε explored and indicates a slightly stronger ε dependence than in current scalings. Studies of core transport have been conducted for well-diagnosed L-mode, H-mode and internal transport barrier (ITB) discharges using TRANSP, and microstability and turbulence studies have been carried out using GS2. Linear micro-stability analysis indicates that ITG modes are typically unstable on all flux surfaces with growth rates that are comparable to the equilibrium E × B flow shearing rate. Mixing length estimates of transport coefficients from ITG (neglecting flow shear) give diffusion coefficients that are broadly comparable with observed thermal diffusivities. Non-linear, collisionless ETG calculations have been performed and suggest radially extended electrostatic streamers up to 100ρe across in radius. Transport from ITG could easily be suppressed in regions where the E × B shear flow rate, ωSE, exceeds the ITG growth rate, possibly contributing to ITBs. Toroidal rotation, driven by neutral beam torque, is the dominant contribution to ωSE via the vBθ term in the radial electric field. Early edge localized mode activity on MAST is associated with the formation of narrow filamentary structures following field lines in the edge. These filaments rotate toroidally with the edge plasma and, away from the X-points, accelerate radially outwards from the edge up to 20 cm. Studies of disruptions on MAST demonstrate a complex evolution of core energy loss and resultant divertor power loads, including phases where the target heat flux width is broadened by a factor of 8. Observations of energetic particle modes driven by super-Alfvénic beam ions provide support for a model for the non-linear evolution of toroidal Alfvén eigenmodes (AEs) forming Bernstein-Green-Krushal waves. The AE activity reduces to low levels with increasing β. Plasma start-up without a central solenoid and in a manner compatible with future large spherical tokamak (ST) devices has been demonstrated using breakdown at a quadrupole magnetic null. Closed flux surface plasmas with peak plasma currents up to 370 kA have been generated and sustained for 0.3 s. New error field correction coils have extended the operational space for low density plasmas and enabled scaling studies of error field induced locked mode formation in the ST

Overview of physics results from MAST

Major developments on the Mega Amp Spherical Tokamak (MAST) have enabled important advances in support of ITER and the physics basis of a spherical tokamak (ST) based component test facility (CTF), as well as providing new insight into underlying tokamak physics. For example, L-H transition studies benefit from high spatial and temporal resolution measurements of pedestal profile evolution (temperature, density and radial electric field) and in support of pedestal stability studies the edge current density profile has been inferred from motional Stark effect measurements. The influence of the q-profile and E x B flow shear on transport has been studied in MAST and equilibrium flow shear has been included in gyro-kinetic codes, improving comparisons with the experimental data. H-modes exhibit a weaker q and stronger collisionality dependence of heat diffusivity than implied by IPB98(gamma, 2) scaling, which may have important implications for the design of an ST-based CTF. ELM mitigation, an important issue for ITER, has been demonstrated by applying resonant magnetic perturbations (RMPs) using both internal and external coils, but full stabilization of type-I ELMs has not been observed. Modelling shows the importance of including the plasma response to the RMP fields. MAST plasmas with q > 1 and weak central magnetic shear regularly exhibit a long-lived saturated ideal internal mode. Measured plasma braking in the presence of this mode compares well with neo-classical toroidal viscosity theory. In support of basic physics understanding, high resolution Thomson scattering measurements are providing new insight into sawtooth crash dynamics and neo-classical tearing mode critical island widths. Retarding field analyser measurements show elevated ion temperatures in the scrape-off layer of L-mode plasmas and, in the presence of type-I ELMs, ions with energy greater than 500 eV are detected 20 cm outside the separatrix. Disruption mitigation by massive gas injection has reduced divertor heat loads by up to 70%

Overview of physics results from MAST

Major developments on the Mega Amp Spherical Tokamak (MAST) have enabled important advances in support of ITER and the physics basis of a spherical tokamak (ST) based component test facility (CTF), as well as providing new insight into underlying tokamak physics. For example, L-H transition studies benefit from high spatial and temporal resolution measurements of pedestal profile evolution (temperature, density and radial electric field) and in support of pedestal stability studies the edge current density profile has been inferred from motional Stark effect measurements. The influence of the q-profile and E x B flow shear on transport has been studied in MAST and equilibrium flow shear has been included in gyro-kinetic codes, improving comparisons with the experimental data. H-modes exhibit a weaker q and stronger collisionality dependence of heat diffusivity than implied by IPB98(gamma, 2) scaling, which may have important implications for the design of an ST-based CTF. ELM mitigation, an important issue for ITER, has been demonstrated by applying resonant magnetic perturbations (RMPs) using both internal and external coils, but full stabilization of type-I ELMs has not been observed. Modelling shows the importance of including the plasma response to the RMP fields. MAST plasmas with q &amp;gt; 1 and weak central magnetic shear regularly exhibit a long-lived saturated ideal internal mode. Measured plasma braking in the presence of this mode compares well with neo-classical toroidal viscosity theory. In support of basic physics understanding, high resolution Thomson scattering measurements are providing new insight into sawtooth crash dynamics and neo-classical tearing mode critical island widths. Retarding field analyser measurements show elevated ion temperatures in the scrape-off layer of L-mode plasmas and, in the presence of type-I ELMs, ions with energy greater than 500 eV are detected 20 cm outside the separatrix. Disruption mitigation by massive gas injection has reduced divertor heat loads by up to 70%