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Objectives Measures of right heart size and function are prognostic in systemic sclerosis-associated pulmonary hypertension (SSc-PH), but the importance of myocardial tissue characterisation remains unclear. We aimed to investigate the predictive potential and interaction of cardiovascular magnetic resonance (CMR) myocardial tissue characterisation and right heart size and function in SSc-PH. Methods A retrospective, single-centre, observational study of 148 SSc-PH patients confirmed by right heart catheterization who underwent clinically indicated CMR including native myocardial T1 and T2 mapping from 2016 to 2023 was performed. Results Sixty-six (45%) patients died during follow-up (median 3.5 years, range 0.1–7.3). Patients who died were older (65 vs 60 years, P  = 0.035) with more dilated (P  < 0.001), hypertrophied (P  = 0.013) and impaired (P  < 0.001) right ventricles, more dilated right atria (P  = 0.043) and higher native myocardial T1 (P  < 0.001). After adjustment for age, indexed right ventricular end-systolic volume (RVESVi, P  = 0.0023) and native T1 (P  = 0.0024) were independent predictors of all-cause mortality. Both RVESVi and native T1 remained independently predictive after adjusting for age and PH subtype (RVESVi P  < 0.001, T1 P  = 0.0056). Optimal prognostic thresholds for RVESVi and native T1 were ≤38 mL/m2 and ≤1119 ms, respectively (P  < 0.001). Patients with RVESVi ≤ 38 mL/m2 and native T1 ≤ 1119 ms had significantly better outcomes than all other combinations (P  < 0.001). Furthermore, patients with RVESVi > 38mL/m2 and native T1 ≤ 1119 ms had significantly better survival than patients with RVESVi > 38mL/m2 and native T1 > 1119ms (P  = 0.017). Conclusion We identified prognostically relevant CMR metrics and thresholds for patients with SSc-PH. Assessing myocardial tissue characterisation alongside right ventricular function confers added value in SSc-PH and may represent an additional treatment target. [ABSTRACT FROM AUTHOR]

Optical ultrasound (OpUS) imaging is an ultrasound modality that utilizes fiber-optic ultrasound sources and detectors to perform pulse-echo ultrasound imaging. These probes can be constructed entirely from glass optical fibers and plastic components, and as such, these devices have been predicted to be compatible with computed tomography (CT) and magnetic resonance imaging (MRI), modalities that use intense electromagnetic fields for imaging. However, to date, this compatibility has not been demonstrated. In this work, a free-hand OpUS imaging system was developed specifically to investigate the compatibility of OpUS systems with CT and MRI imaging systems. The OpUS imaging platform discussed in this work was used to perform real-time OpUS imaging under (separately) concurrent CT and MRI. CT and MRI imaging of the OpUS probe was used to determine if the probe itself would induce artifacts in the CT and MRI imaging, and ultrasound resolution targets and background measurements were used to assess any impact of CT and MRI on the OpUS signal fidelity. These measurements demonstrate that there was negligible interaction between the OpUS system and both the CT and MRI systems, and to further demonstrate this capability, concurrent OpUS-CT and OpUS-MRI imaging was conducted of a tissue-mimicking phantom and a dynamic motion phantom. This work presents a comprehensive demonstration of an OpUS imaging system operating alongside CT and MRI, which opens up new applications of ultrasound imaging in electromagnetically challenging settings. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) can be used for non-invasive evaluation of hemodynamics. However, its routine use is limited by labor-intensive manual segmentation, CFD mesh creation, and time-consuming simulation. This study aims to train a deep learning model to both generate patient-specific volume-meshes of the pulmonary artery from 3D cardiac MRI data and directly estimate CFD flow fields. This proof-of-concept study used 135 3D cardiac MRIs from both a public and private dataset. The pulmonary arteries in the MRIs were manually segmented and converted into volume-meshes. CFD simulations were performed on ground truth meshes and interpolated onto point-point correspondent meshes to create the ground truth dataset. The dataset was split 110/10/15 for training, validation, and testing. Image2Flow, a hybrid image and graph convolutional neural network, was trained to transform a pulmonary artery template to patient-specific anatomy and CFD values, taking a specific inlet velocity as an additional input. Image2Flow was evaluated in terms of segmentation, and the accuracy of predicted CFD was assessed using node-wise comparisons. In addition, the ability of Image2Flow to respond to increasing inlet velocities was also evaluated. Image2Flow achieved excellent segmentation accuracy with a median Dice score of 0.91 (IQR: 0.86–0.92). The median node-wise normalized absolute error for pressure and velocity magnitude was 11.75% (IQR: 9.60–15.30%) and 9.90% (IQR: 8.47–11.90), respectively. Image2Flow also showed an expected response to increased inlet velocities with increasing pressure and velocity values. This proof-of-concept study has shown that it is possible to simultaneously perform patient-specific volume-mesh based segmentation and pressure and flow field estimation using Image2Flow. Image2Flow completes segmentation and CFD in ~330ms, which is ~5000 times faster than manual methods, making it more feasible in a clinical environment. Author summary: Computational fluid dynamics is an engineering tool that can be used in a clinical setting to non-invasively model blood flow through blood vessels, such as the pulmonary artery. This information can be used to inform treatment planning for patients, especially those with cardiovascular conditions. However, its routine use is limited by a labor-intensive process, requiring substantial expertise and computational resources. Recently, machine learning has offered solutions to automate parts of this process, but no single model has addressed the entire workflow. Therefore, we created Image2Flow, a machine learning model capable of generating a patient-specific representation of a pulmonary artery while predicting blood flow through the vessel. Image2Flow can generate highly accurate pulmonary artery representations and reasonably accurate blood flow predictions. Notably, it performs this whole process in 330ms, which is ~5000x faster than the manual methods. With its speed and accuracy, Image2Flow holds substantial promise for facilitating computational fluid dynamics in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Anti-human leukocyte antigen (HLA)-antibody production represents a major barrier to heart transplantation, limiting recipient compatibility with potential donors and increasing the risk of complications with poor waiting-list outcomes. Currently there is no consensus to when desensitization should take place, and through what mechanism, meaning that sensitized patients must wait for a compatible donor for many months, if not years. We aimed to determine if intraoperative immunoadsorption could provide a potential desensitization methodology. Methods: Anti-HLA antibody-containing whole blood was added to a Cardiopulmonary bypass (CPB) circuit set up to mimic a 20 kg patient undergoing heart transplantation. Plasma was separated and diverted to a standalone, secondary immunoadsorption system, with antibody-depleted plasma returned to the CPB circuit. Samples for anti-HLA antibody definition were taken at baseline, when combined with the CPB prime (on bypass), and then every 20 min for the duration of treatment (total 180 min). Results: A reduction in individual allele median fluorescence intensity (MFI) to below clinically relevant levels (<1000 MFI), and in the majority of cases below the lower positive detection limit (<500 MFI), even in alleles with a baseline MFI >4000 was demonstrated. Reduction occurred in all cases within 120 min, demonstrating efficacy in a time period usual for heart transplantation. Flowcytometric crossmatching of suitable pseudo-donor lymphocytes demonstrated a change from T cell and B cell positive channel shifts to negative, demonstrating a reduction in binding capacity. Conclusions: Intraoperative immunoadsorption in an ex vivo setting demonstrates clinically relevant reductions in anti-HLA antibodies within the normal timeframe for heart transplantation. This method represents a potential desensitization technique that could enable sensitized children to accept a donor organ earlier, even in the presence of donor-specific anti-HLA antibodies. [ABSTRACT FROM AUTHOR]

Purpose: Interactive cardiac MRI is used for fast scan planning and MR‐guided interventions. However, the requirement for real‐time acquisition and near‐real‐time visualization constrains the achievable spatio‐temporal resolution. This study aims to improve interactive imaging resolution through optimization of undersampled spiral sampling and leveraging of deep learning for low‐latency reconstruction (deep artifact suppression). Methods: A variable density spiral trajectory was parametrized and optimized via HyperBand to provide the best candidate trajectory for rapid deep artifact suppression. Training data consisted of 692 breath‐held CINEs. The developed interactive sequence was tested in simulations and prospectively in 13 subjects (10 for image evaluation, 2 during catheterization, 1 during exercise). In the prospective study, the optimized framework—HyperSLICE— was compared with conventional Cartesian real‐time and breath‐hold CINE imaging in terms quantitative and qualitative image metrics. Statistical differences were tested using Friedman chi‐squared tests with post hoc Nemenyi test (p < 0.05). Results: In simulations the normalized RMS error, peak SNR, structural similarity, and Laplacian energy were all statistically significantly higher using optimized spiral compared to radial and uniform spiral sampling, particularly after scan plan changes (structural similarity: 0.71 vs. 0.45 and 0.43). Prospectively, HyperSLICE enabled a higher spatial and temporal resolution than conventional Cartesian real‐time imaging. The pipeline was demonstrated in patients during catheter pull back, showing sufficiently fast reconstruction for interactive imaging. Conclusion: HyperSLICE enables high spatial and temporal resolution interactive imaging. Optimizing the spiral sampling enabled better overall image quality and superior handling of image transitions compared with radial and uniform spiral trajectories. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background and Aims Interventional studies in pulmonary arterial hypertension completed to date have shown to be effective in symptomatic patients with significantly elevated mean pulmonary artery pressure (mPAP) (≥25 mmHg) and pulmonary vascular resistance (PVR) > 3 Wood Unit (WU). However, in health the mPAP does not exceed 20 mmHg and PVR is 2 WU or lower, at rest. The ESC/ERS guidelines have recently been updated to reflect this. There is limited published data on the nature of these newly defined populations (mPAP 21–24 mmHg and PVR >2–≤3 WU) and the role of comorbidity in determining their natural history. With the change in guidelines, there is a need to understand this population and the impact of the ESC/ERS guidelines in greater detail. Methods A retrospective nationwide evaluation of the role of pulmonary haemodynamics and comorbidity in predicting survival among patients referred to the UK pulmonary hypertension (PH) centres between 2009 and 2017. In total, 2929 patients were included in the study. Patients were stratified by mPAP (<21 mmHg, 21–24 mmHg, and ≥25 mmHg) and PVR (≤2 WU, > 2–≤3 WU, and >3 WU), with 968 (33.0%) in the mPAP <21 mmHg group, 689 (23.5%) in the mPAP 21–24 mmHg group, and 1272 (43.4%) in the mPAP ≥25 mmHg group. Results Survival was negatively correlated with mPAP and PVR in the population as a whole. Survival in patients with mildly elevated mPAP (21–24 mmHg) or PVR (>2–≤3WU) was lower than among those with normal pressures (mPAP <21 mmHg) and normal PVR (PVR ≤ 2WU) independent of comorbid lung and heart disease [hazard ratio (HR) 1.36, 95% confidence interval (CI) 1.14–1.61, P =.0004 for mPAP vs. HR 1.28, 95% CI 1.10–1.49, P =.0012 for PVR]. Among patients with mildly elevated mPAP, a mildly elevated PVR remained an independent predictor of survival when adjusted for comorbid lung and heart disease (HR 1.33, 95% CI 1.01–1.75, P =.042 vs. HR 1.4, 95% CI 1.06–1.86, P =.019). 68.2% of patients with a mPAP 21–24 mmHg had evidence of underlying heart or lung disease. Patients with mildly abnormal haemodynamics were not more symptomatic than patients with normal haemodynamics. Excluding patients with heart and lung disease, connective tissue disease was associated with a poorer survival among those with PH. In this subpopulation evaluating those with a mPAP of 21–24 mmHg, survival curves only diverged after 5 years. Conclusions This study supports the change in diagnostic category of the ESC/ERS guidelines in a PH population. The newly included patients have an increased mortality independent of significant lung or heart disease. The majority of patients in this new category have underlying heart or lung disease rather than an isolated pulmonary vasculopathy. Mortality is higher if comorbidity is present. Rigorous phenotyping will be pivotal to determine which patients are at risk of progressive vasculopathic disease and in whom surveillance and recruitment to studies may be of benefit. This study provides an insight into the population defined by the new guidelines. [ABSTRACT FROM AUTHOR]