Abnormal wave reflections and left ventricular hypertrophy late after coarctation of the aorta repair

Patients with repaired coarctation of the aorta are thought to have increased afterload due to abnormalities in vessel structure and function. We have developed a novel cardiovascular magnetic resonance protocol that allows assessment of central hemodynamics, including central aortic systolic blood pressure, resistance, total arterial compliance, pulse wave velocity, and wave reflections. The main study aims were to (1) characterize group differences in central aortic systolic blood pressure and peripheral systolic blood pressure, (2) comprehensively evaluate afterload (including wave reflections) in the 2 groups, and (3) identify possible biomarkers among covariates associated with elevated left ventricular mass (LVM). Fifty adult patients with repaired coarctation and 25 age- and sex-matched controls were recruited. Ascending aorta area and flow waveforms were obtained using a high temporal-resolution spiral phase-contrast cardiovascular magnetic resonance flow sequence. These data were used to derive central hemodynamics and to perform wave intensity analysis noninvasively. Covariates associated with LVM were assessed using multivariable linear regression analysis. There were no significant group differences (P≥0.1) in brachial systolic, mean, or diastolic BP. However central aortic systolic blood pressure was significantly higher in patients compared with controls (113 versus 107 mm Hg, P=0.002). Patients had reduced total arterial compliance, increased pulse wave velocity, and larger backward compression waves compared with controls. LVM index was significantly higher in patients than controls (72 versus 59 g/m(2), P<0.0005). The magnitude of the backward compression waves was independently associated with variation in LVM (P=0.01). Using a novel, noninvasive hemodynamic assessment, we have shown abnormal conduit vessel function after coarctation of the aorta repair, including abnormal wave reflections that are associated with elevated LVM

IN VITRO MULTI-SCALE PATIENT-SPECIFIC MODELING OF HEMODYNAMICS IN STAGE 1 NORWOOD PALLIATION FOR THE TREATMENT OF SINGLE VENTRICLE HEART DISEASE

Hypoplastic left heart syndrome (HLHS) is a congenital heart defect in which the left ventricle is severely underdeveloped. The Norwood procedure is the first stage procedure to make an unrestrictive systemic blood flow and at the same time balance it with the pulmonary flow. This is done by constructing a neo-aorta using the pulmonary artery root and the autologous aorta, and then installing a shunt to the pulmonary artery. Variations of the Norwood surgery include the modified Blalock-Taussig (mBT) shunt, which diverts blood from the innominate artery to the pulmonary artery (PA), and the Right Ventricle Shunt (RVS), which diverts blood from the right ventricle to the PA. Recurrent neo-aortic coarctation (NAO) is a frequent complication of the Norwood procedure. It causes changes in circulation flow rate balances and hypertension in the aortic arch. Conventionally, the value of a coarctation index (CoI) is used in choosing interventions to treat NAO. Aortic arch morphology of Norwood patients is suspected to be a factor of hemodynamic response to NAO. This study aims to develop and validate an in vitro model of the Norwood circulation and to use it to better understand the hemodynamic impact of progressive coarctation severity in the Norwood patients with mBT and RVS shunts. Five patient-specific cases were selected, each case having a different aortic morphology. A multi-scale mock circulatory system (MCS) was developed to simulate patient-specific Norwood circulation. The MCS couples a lumped parameter network (LPN) model of the circulation with the 3D test section of the aorta and superior arteries. The system includes branches for the pulmonary, upper body, lower body and single ventricle. The MCS was set to patient specific conditions based on the clinical measurements. Flow rate and pressure measurements were made around the circulation model. The native arch anatomy of each patient was morphed to simulate coarctation by controlling the amount of narrowing of the aortic isthmus, while keeping the original patient-specific aortic geometry intact. Separate NAO models were created to provide for a range of CoI. Aortic pressure measurements were made to study pressure drop and recovery effects. In a further study, the MCS was modified to simulate the Norwood circulation with RVS. The NAO models were used to study coarctation effects. The MCS was validated against clinical measurements. The experimental measurements demonstrated that the time-based flow rate and pressure developed within the circulation recapitulated clinical measurements (0.72 \u3c R2 \u3c 0.95). The results showed good fidelity in replicating the mean values of the Norwood circulation at the patient-specific level (p \u3e 0.10). The system demonstrated the coarctation effects in the Norwood circulation with mBT. For all patient cases, the single ventricle power (SVP), mean pressure difference, and Qp/Qs increased noticeably when CoI \u3c 0.5 (p\u3c0.05). An increased SVP correlated with abnormal aortic arch morphology (dilated or tubular). Measurements from two of four cases studied showed that substituting the mBT with the RVS can relieve pulmonary overcirculation and improve the pulmonary to systemic flow balance (Qp/Qs). Using the RVS reduced SVP requirements by 74.5 mW on average. A tubular arch morphology was associated with a higher SVP with the RVS than those patients with a dilated arch. The study has shown that the hypothesis, “NAO may not need immediate surgical intervention at an early stage for some patients†was accepted. Aortic arch morphology does affect the hemodynamic response to NAO. Any morphological abnormality causes extra SVP. The RVS can relieve overcirculation and is associated with lower SVP level and SVP changes in some of the patients

Shape-driven deep neural networks for fast acquisition of aortic 3D pressure and velocity flow fields

Computational fluid dynamics (CFD) can be used to simulate vascular haemodynamics and analyse potential treatment options. CFD has shown to be beneficial in improving patient outcomes. However, the implementation of CFD for routine clinical use is yet to be realised. Barriers for CFD include high computational resources, specialist experience needed for designing simulation set-ups, and long processing times. The aim of this study was to explore the use of machine learning (ML) to replicate conventional aortic CFD with automatic and fast regression models. Data used to train/test the model consisted of 3,000 CFD simulations performed on synthetically generated 3D aortic shapes. These subjects were generated from a statistical shape model (SSM) built on real patient-specific aortas (N = 67). Inference performed on 200 test shapes resulted in average errors of 6.01% ±3.12 SD and 3.99% ±0.93 SD for pressure and velocity, respectively. Our ML-based models performed CFD in ∼0.075 seconds (4,000x faster than the solver). This proof-of-concept study shows that results from conventional vascular CFD can be reproduced using ML at a much faster rate, in an automatic process, and with reasonable accuracy