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The pathophysiology underlying impaired LV function in PAH remains unclear, with some studies implicating intrinsic myocardial dysfunction and others pointing to LV underfilling. Evaluation of pulmonary vein area (PVA) and flow may offer novel, mechanistic insight by distinguishing elevated LV filling pressure common in myocardial dysfunction from LV underfilling. This study aimed to elucidate LV filling physiology in PAH by assessing PVA and flow using cardiac magnetic resonance (CMR) and compare pulmonary vein flow in PAH with HFrEF as a model representing elevated filling pressures, in addition to healthy controls. Patients with PAH or heart failure with reduced ejection fraction (HFrEF) referred for CMR were retrospectively reviewed, and healthy controls were included as reference. Pulmonary vein S, D and A-wave were compared between groups. Associations between pulmonary vein area (PVA) by CMR and echocardiographic indices of LV filling pressure were evaluated. Nineteen patients with PAH, 25 with HFrEF and 24 controls were included. Both PAH and HFrEF had lower ejection fraction and S-wave velocity than controls. PAH displayed smaller LV end-diastolic volumes than controls, while HFrEF demonstrated larger PVA and higher A-wave reversal. PVA was associated with mitral E/e' ratio (r 2  = 0.10; p = 0.03), e' velocity (r 2  = 0.23; p = 0.001) and left atrial volume (r 2  = 0.07; p = 0.005). Among PAH, PVA was not associated with LV-GLS. A PVA cut-off of 2.3cm 2 displayed 87% sensitivity and 72% specificity to differentiate HFrEF and PAH (AUC = 0.82). PAH displayed lower pulmonary vein S-wave velocity, smaller LV volume and reduced function compared with controls. Reduced LV function in PAH may be owing to underfilling rather than intrinsic myocardial disease. PVA demonstrates promise as a novel, non-invasive imaging marker to assess LV filling status., (© 2024. The Author(s).)

Right ventricular (RV) volumes are commonly obtained through time-consuming manual delineations of cardiac magnetic resonance (CMR) images. Deep learning-based methods can generate RV delineations, but few studies have assessed their ability to accelerate clinical practice. Therefore, we aimed to develop a clinical pipeline for deep learning-based RV delineations and validate its ability to reduce the manual delineation time. Quality-controlled delineations in short-axis CMR scans from 1114 subjects were used for development. Time reduction was assessed by two observers using 50 additional clinical scans. Automated delineations were subjectively rated as (A) sufficient for clinical use, or as needing (B) minor or (C) major corrections. Times were measured for manual corrections of delineations rated as B or C, and for fully manual delineations on all 50 scans. Fifty-eight % of automated delineations were rated as A, 42% as B, and none as C. The average time was 6 min for a fully manual delineation, 2 s for an automated delineation, and 2 min for a minor correction, yielding a time reduction of 87%. The deep learning-based pipeline could substantially reduce the time needed to manually obtain clinically applicable delineations, indicating ability to yield right ventricular assessments faster than fully manual analysis in clinical practice. However, these results may not generalize to clinics using other RV delineation guidelines., (© 2023. The Author(s).)

Precapillary pulmonary hypertension (PH precap ) is a condition with elevated pulmonary vascular pressure and resistance. Patients have a poor prognosis and understanding the underlying pathophysiological mechanisms is crucial to guide and improve treatment. Ventricular hemodynamic forces (HDF) are a potential early marker of cardiac dysfunction, which may improve evaluation of treatment effect. Therefore, we aimed to investigate if HDF differ in patients with PH precap compared to healthy controls. Patients with PH precap (n = 20) and age- and sex-matched healthy controls (n = 12) underwent cardiac magnetic resonance imaging including 4D flow. Biventricular HDF were computed in three spatial directions throughout the cardiac cycle using the Navier-Stokes equations. Biventricular HDF (N) indexed to stroke volume (l) were larger in patients than controls in all three directions. Data is presented as median N/l for patients vs controls. In the RV, systolic HDF diaphragm-outflow tract were 2.1 vs 1.4 (p = 0.003), and septum-free wall 0.64 vs 0.42 (p = 0.007). Diastolic RV HDF apex-base were 1.4 vs 0.87 (p < 0.0001), diaphragm-outflow tract 0.80 vs 0.47 (p = 0.005), and septum-free wall 0.60 vs 0.38 (p = 0.003). In the LV, systolic HDF apex-base were 2.1 vs 1.5 (p = 0.005), and lateral wall-septum 1.5 vs 1.2 (p = 0.02). Diastolic LV HDF apex-base were 1.6 vs 1.2 (p = 0.008), and inferior-anterior 0.46 vs 0.24 (p = 0.02). Hemodynamic force analysis conveys information of pathological cardiac pumping mechanisms complementary to more established volumetric and functional parameters in precapillary pulmonary hypertension. The right ventricle compensates for the increased afterload in part by augmenting transverse forces, and left ventricular hemodynamic abnormalities are mainly a result of underfilling rather than intrinsic ventricular dysfunction., (© 2022. The Author(s).)

Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that semi-automatically sorts real-time CMR images according to breathing to facilitate quantification of LV function in free breathing exercise. A semi-automatic algorithm utilizing manifold learning (Laplacian Eigenmaps) was developed for respiratory sorting. Feasibility was tested in eight healthy volunteers and eight patients who underwent ECG-gated and real-time CMR at rest. Additionally, volunteers performed exercise CMR at 60% of maximum heart rate. The algorithm was validated for exercise by comparing LV mass during exercise to rest. Respiratory sorting to end expiration and end inspiration (processing time 20 to 40 min) succeeded in all research participants. Bias ± SD for LV mass was 0 ± 5 g when comparing real-time CMR at rest, and 0 ± 7 g when comparing real-time CMR during exercise to ECG-gated at rest. This study presents a semi-automatic algorithm to retrospectively perform respiratory sorting in free breathing real-time CMR. This can facilitate implementation of exercise CMR with non-ECG-gated free breathing real-time imaging, without any additional physiological input., (© 2022. The Author(s).)

Breath-hold divers (BHD) enduring apnea for more than 4 min are characterized by resistance to release of reactive oxygen species, reduced sensitivity to hypoxia, and low mitochondrial oxygen consumption in their skeletal muscles similar to northern elephant seals. The muscles and myocardium of harbor seals also exhibit metabolic adaptations including increased cardiac lactate-dehydrogenase-activity, exceeding their hypoxic limit. We hypothesized that the myocardium of BHD possesses similar adaptive mechanisms. During maximum apnea 15 O-H 2 O-PET/CT (n = 6) revealed no myocardial perfusion deficits but increased myocardial blood flow (MBF). Cardiac MRI determined blood oxygen level dependence oxygenation (n = 8) after 4 min of apnea was unaltered compared to rest, whereas cine-MRI demonstrated increased left ventricular wall thickness (LVWT). Arterial blood gases were collected after warm-up and maximum apnea in a pool. At the end of the maximum pool apnea (5 min), arterial saturation decreased to 52%, and lactate decreased 20%. Our findings contrast with previous MR studies of BHD, that reported elevated cardiac troponins and decreased myocardial perfusion after 4 min of apnea. In conclusion, we demonstrated for the first time with 15 O-H 2 O-PET/CT and MRI in elite BHD during maximum apnea, that MBF and LVWT increases while lactate decreases, indicating anaerobic/fat-based cardiac-metabolism similar to diving mammals.