Impact of 4D-Flow CMR Parameters on Functional Evaluation of Fontan Circulation.

We sought to evaluate the potential clinical role of 4D-flow cardiac magnetic resonance (CMR)-derived energetics and flow parameters in a cohort of patients' post-Fontan palliation. In patients with Fontan circulation who underwent 4D-Flow CMR, streamlines distribution was evaluated, as well a 4D-flow CMR-derived energetics parameters as kinetic energy (KE) and energy loss (EL) normalized by volume. EL/KE index as a marker of flow efficiency was also calculated. Cardiopulmonary exercise test (CPET) was also performed in a subgroup of patients. The population study included 55 patients (mean age 22 ± 11 years). The analysis of the streamlines revealed a preferential distribution of the right superior vena cava flow for the right pulmonary artery (62.5 ± 35.4%) and a mild preferential flow for the left pulmonary artery (52.3 ± 40.6%) of the inferior vena cave-pulmonary arteries (IVC-PA) conduit. Patients with heart failure (HF) presented lower IVC/PA-conduit flow (0.75 ± 0.5 vs 1.3 ± 0.5 l/min/m2, p = 0.004) and a higher mean flow-jet angle of the IVC-PA conduit (39.2 ± 22.8 vs 15.2 ± 8.9, p < 0.001) than the remaining patients. EL/KE index correlates inversely with VO2/kg/min: R: - 0.45, p = 0.01 peak, minute ventilation (VE) R: - 0.466, p < 0.01, maximal voluntary ventilation: R:0.44, p = 0.001 and positively with the physiological dead space to the tidal volume ratio (VD/VT) peak: R: 0.58, p < 0.01. From our data, lower blood flow in IVC/PA conduit and eccentric flow was associated with HF whereas higher EL/KE index was associated with reduced functional capacity and impaired lung function. Larger studies are needed to confirm our results and to further improve the prognostic role of the 4D-Flow CMR in this challenging population.

Coupling synthetic and real-world data for a deep learning-based segmentation process of 4D flow MRI.

BACKGROUND AND OBJECTIVE: Phase contrast magnetic resonance imaging (4D flow MRI) is an imaging technique able to provide blood velocity in vivo and morphological information. This capability has been used to study mainly the hemodynamics of large vessels, such as the thoracic aorta. However, the segmentation of 4D flow MRI data is a complex and time-consuming task. In recent years, neural networks have shown great accuracy in segmentation tasks if large datasets are provided. Unfortunately, in the context of 4D flow MRI, the availability of these data is limited due to its recent adoption in clinical settings. In this study, we propose a pipeline for generating synthetic thoracic aorta phase contrast magnetic resonance angiography (PCMRA) to expand the limited dataset of patient-specific PCMRA images, ultimately improving the accuracy of the neural network segmentation even with a small real dataset. METHODS: The pipeline involves several steps. First, a statistical shape model is used to synthesize new artificial geometries to improve data numerosity and variability. Secondly, computational fluid dynamics simulations are employed to simulate the velocity fields and, finally, after a downsampling and a signal-to-noise and velocity limit adjustment in both frequency and spatial domains, volumes are obtained using the PCMRA formula. These synthesized volumes are used in combination with real-world data to train a 3D U-Net neural network. Different settings of real and synthetic data are tested. RESULTS: Incorporating synthetic data into the training set significantly improved the segmentation performance compared to using only real data. The experiments with synthetic data achieved a DICE score (DS) value of 0.83 and a better target reconstruction with respect to the case with only real data (DS = 0.65). CONCLUSION: The proposed pipeline demonstrated the ability to increase the dataset in terms of numerosity and variability and to improve the segmentation accuracy for the thoracic aorta using PCMRA.

Fabrication of deformable patient-specific AAA models by material casting techniques.

Background: Abdominal Aortic Aneurysm (AAA) is a balloon-like dilatation that can be life-threatening if not treated. Fabricating patient-specific AAA models can be beneficial for in-vitro investigations of hemodynamics, as well as for pre-surgical planning and training, testing the effectiveness of different interventions, or developing new surgical procedures. The current direct additive manufacturing techniques cannot simultaneously ensure the flexibility and transparency of models required by some applications. Therefore, casting techniques are presented to overcome these limitations and make the manufactured models suitable for in-vitro hemodynamic investigations, such as particle image velocimetry (PIV) measurements or medical imaging. Methods: Two complex patient-specific AAA geometries were considered, and the related 3D models were fabricated through material casting. In particular, two casting approaches, i.e. lost molds and lost core casting, were investigated and tested to manufacture the deformable AAA models. The manufactured models were acquired by magnetic resonance, computed tomography (CT), ultrasound imaging, and PIV. In particular, CT scans were segmented to generate a volumetric reconstruction for each manufactured model that was compared to a reference model to assess the accuracy of the manufacturing process. Results: Both lost molds and lost core casting techniques were successful in the manufacturing of the models. The lost molds casting allowed a high-level surface finish in the final 3D model. In this first case, the average signed distance between the manufactured model and the reference was (-0.2±0.2) mm. However, this approach was more expensive and time-consuming. On the other hand, the lost core casting was more affordable and allowed the reuse of the external molds to fabricate multiple copies of the same AAA model. In this second case, the average signed distance between the manufactured model and the reference was (0.1±0.6) mm. However, the final model's surface finish quality was poorer compared to the model obtained by lost molds casting as the sealing of the outer molds was not as firm as the other casting technique. Conclusions: Both lost molds and lost core casting techniques can be used for manufacturing patient-specific deformable AAA models suitable for hemodynamic investigations, including medical imaging and PIV.

Big gamma-glutamyltransferase is associated with epicardial fat volume and cardiovascular outcome in the general population.

AIMS: Gamma-glutamyltransferase (GGT) has been recognized as a cardiovascular risk factor, and its highest molecular weight fraction [big GGT (b-GGT)] is found in vulnerable atherosclerotic plaques. We explored the relationship between b-GGT, computed tomography findings, and long-term outcomes in the general population. METHODS AND RESULTS: Between May 2010 and October 2011, subjects aged 45-75 years living in a Tuscan city and without known cardiac disease were screened. The primary endpoint was a composite of cardiovascular death or acute coronary syndrome requiring urgent coronary revascularization. Gamma-glutamyltransferase fractions were available in 898 subjects [median age 65 years (25th-75th percentile 55-70), 46% men]. Median plasma GGT was 20 IU (15-29), and b-GGT was 2.28 (1.28-4.17). Coronary artery calcium (CAC) score values were 0 (0-60), and the volume of pro-atherogenic epicardial fat was 155 mL (114-204). In a model including age, sex, low-density lipoprotein (LDL) cholesterol, current or previous smoking status, hypertension, diabetes, obesity, b-GGT independently predicted epicardial fat volume (EFV) (r = 0.162, P < 0.001), but not CAC (P = 0.198). Over a 10.3-year follow-up (9.6-10.8), 27 subjects (3%) experienced the primary endpoint. We evaluated couples of variables including b-GGT and a cardiovascular risk factor, CAC or EFV. Big GGT yielded independent prognostic significance from age, LDL cholesterol, current or previous smoking status, hypertension, diabetes, obesity, but not CAC or EFV. Conversely, GGT predicted the primary endpoint even independently from CAC and EFV. CONCLUSION: Big GGT seemed at least as predictive as the commonly available GGT assay; therefore, the need for b-GGT rather than GGT measurement should be carefully examined.

Giant solitary fibrous tumor of the epicardium causing reversible heart failure.

A 68-year-old woman with a 2-year history of dyspnea and fatigue was admitted to our hospital with a massive pericardial effusion. Computed tomography and cardiovascular magnetic resonance imaging revealed a huge (17 cm maximum diameter) intrapericardial mass. After successful tumor resection, a giant solitary fibrous tumour of the epicardium was diagnosed by histology. Histologic features of malignancy were absent, and the patient is alive and well 1 year after the operation, undergoing close follow-up at regular intervals. Recurrences have been exceptionally reported in benign solitary fibrous tumors, and experience with this exceptionally rare and enigmatic cardiac tumor is lacking.