Hemodynamic Assessment in Bicuspid Aortic Valve Disease and Aortic Dilation: New Insights From Voxel-By-Voxel Analysis of Reverse Flow, Stasis, and Energetics

Objectives: Clinical management decisions surrounding ascending aorta (AAo) dilation in bicuspid aortic valve (BAV) disease benefit from personalized predictive tools. 4D-flow MRI may provide patient-specific markers reflective of BAV-associated aortopathy. This study aims to explore novel 4D-flow MRI parametric voxel-by-voxel forward flow, reverse flow, kinetic energy and stasis in BAV disease. We hypothesize that novel parametric voxel-by-voxel markers will be associated with aortic dilation and referral for surgery and can enhance our understanding of BAV hemodynamics beyond standard metrics.

Methods: A total of 96 subjects (73 BAV patients, 23 healthy controls) underwent MRI scan. Healthy controls had no known cardiovascular disease. Patients were clinically referred for AAo dilation assessment. Indexed diameters were obtained by dividing the aortic diameter by the patient’s body surface area. Patients were followed for the occurrence of aortic surgery. 4D-flow analysis was performed by a single observer in five regions: left ventricular outflow tract (LVOT), AAo, arch, proximal descending aorta (PDAo), and distal descending aorta (DDAo). In each region peak velocity, kinetic energy (KE), forward flow (FF), reverse flow (RF), and stasis were measured on a voxel-by-voxel basis. T-tests (or non-parametric equivalent) compared flow parameters between cohorts. Univariate and multivariate analyses explored associations between diameter and parametric voxel-by-voxel parameters.

Results: Compared to controls, BAV patients showed reduced stasis (p < 0.01) and increased RF and FF (p < 0.01) throughout the aorta, and KE remained similar. In the AAo, indexed diameter correlated with age (R = 0.326, p = 0.01), FF (R = −0.648, p < 0.001), RF (R = −0.441, p < 0.001), and stasis (R = −0.288, p < 0.05). In multivariate analysis, FF showed a significant inverse association with AAo indexed diameter, independent of age. During a median 179 ± 180 days of follow-up, 23 patients (32%) required aortic surgery. Compared to patients not requiring surgery, they showed increased KE and peak velocity in the proximal aorta (p < 0.01), accompanied by increased RF and reduced stasis throughout the entire aorta (p < 0.01).

Conclusion: Novel voxel-by-voxel reverse flow and stasis were altered in BAV patients and are associated with aortic dilation and surgical treatment.

Bicuspid aortic valve disease is associated with abnormal wall shear stress, viscous energy loss, and pressure drop within the ascending thoracic aorta: A cross-sectional study

Bicuspid aortic valve (BAV) disease has significant gaps in its clinical management practices. To highlight the potential utility of advanced hemodynamic biomarkers in strengthening BAV assessment, we used 4-dimentional flow magnetic resonance imaging to investigate altered hemodynamics in the ascending aorta (AAo).A total of 32 healthy controls and 53 age-matched BAV patients underwent cardiac magnetic resonance imaging at 3T, with cine imaging and 4D-flow. Analysis planes were placed along 3D-segmented aortas at the left ventricular outflow tract (LVOT), sinuses of Valsalva, mid-ascending aorta (MAA), and proximal to the first aortic branch. Locations were analyzed for aortic diameter (normalized to body surface area), pressure drop (PD), viscous energy loss (EL), and wall shear stress (WSS) sub-vectors (axial wall shear stress, circumferential wall shear stress [WSSC], magnitude wall shear stress). Student's t tests, or non-parametric equivalents, compared parameters between cohorts. Univariable and multivariable analyses explored the associations of AAo diameter with hemodynamics within the BAV cohort.Compared to control cohort, BAV patients showed significantly greater PD (MAA: 9.5 ± 8.0 vs 2.8 ± 2.4 mm Hg; P < .01), EL (from LVOT-AA1: 7.39 ± 4.57 mW vs 2.90 ± 1.07 mW; P < .01), and WSSC (MAA: 0.3 ± 0.1 vs 0.2 ± 0.06 Pa; P ≤ .01) throughout the AAo. Correlational analyses revealed an inverse association between AAo diameter and both magnitude wall shear stress and axial wall shear stress.BAV patients exhibited increased PD, EL, and WSSC in the AAo, and an inverse association between AAo diameter and WSS sub-vectors. This demonstrated the impact of PD, EL, and WSS in BAV disease and the importance of altered hemodynamics in aortic remodelling.

Bicuspid aortic valve disease associates with abnormal wall shear stress, viscous energy loss, and pressure drop within the ascending thoracic aorta

Introduction

We use 4D Flow MRI to (1) investigate the effects of bicuspid aortic valve (BAV) disease on downstream pressure drop (PD), wall shear stress (WSS), and viscous energy loss (EL) in the ascending aorta (AAo) and (2) explore the associations between AAo diameter and PD, WSS, and EL.

Hypothesis

BAV patients show increased PD, WSS, and EL in the AAo compared to age-matched controls

Methods

32 healthy controls (41±15 y, 10 female) and 53 BAV patients (44±16 y, 19 female) underwent cardiac MRI at 3T, inclusive of cine imaging and 4D flow. Cross sections were placed along segmented aortas at the: left ventricular outflow tract (LVOT), sinuses of Valsalva (SOV), mid-ascending aorta (MAA), and proximal to first aortic branch (AA1). Locations were analyzed for (i) net flow, (ii) aortic diameter (normalized to BSA), (iii) systolic PD (referenced to LVOT), (iv) systolic EL (measured within LVOT-AA1 volume and normalized by LVOT net flow; mW/mL), and (v) systolic WSS. Sub-vectors of WSS, axial (WSSax) and circumferential (WSScirc), were also analyzed.

Results

In comparison to controls, BAV patients showed greater PD (e.g. MAA: 9.5±8.0 vs. 2.8±2.4mmHg; p&lt;0.01), EL (0.09±0.05 vs. 0.04±0.01 mW/mL; p≤0.01), and WSScirc (e.g. MAA: 0.3±0.1 vs. 0.2±0.06 Pa; p≤0.01) throughout the AAo (Table 1 and Fig. 1). BAV patients exhibited significantly lower WSS and WSSax only at the SOV. In univariate analyses, AAo diameter was inversely correlated with WSS (R=−0.32, p&lt;0.01) and WSSax (R=−0.51, p≤0.01). In multivariate analyses, AAo diameter was associated with WSS (β=−0.36, p&lt;0.01) and WSSax (β=−0.26, p&lt;0.01).

Conclusions

BAV patients demonstrate significantly increased PD, EL, and WSScirc in the AAo, and an inverse association between AAo diameter and WSS measures.

Funding Acknowledgement

Type of funding source: Public Institution(s). Main funding source(s): Alberta Health Services

Left Ventricular Flow Analysis in Atrial Fibrillation

Atrial fibrillation (AF) is a global common disease which 33.5 million individuals suffer from. Conventional cardiac magnetic resonance and 4D flow magnetic resonance imaging have been used to study AF patients. We propose a left ventricular flow component analysis from 4D flow for AF detection. This method was applied to healthy controls and AF patients before catheter ablation. Retained inflow, delayed ejection, and residual volume had a significant difference between controls and the AF group as well as a conventional LV stroke volume parameter, and among them, residual volume was the strongest parameter to detect AF.

Analysis of spliceosome dynamics by maximum likelihood fitting of dwell time distributions

Colocalization single-molecule methods can provide a wealth of information concerning the ordering and dynamics of biomolecule assembly. These have been used extensively to study the pathways of spliceosome assembly in vitro. Key to these experiments is the measurement of binding times-either the dwell times of a multi-molecular interaction or times in between binding events. By analyzing hundreds of these times, many new insights into the kinetic pathways governing spliceosome assembly have been obtained. Collections of binding times are often plotted as histograms and can be fit to kinetic models using a variety of methods. Here, we describe the use of maximum likelihood methods to fit dwell time distributions without binning. In addition, we discuss several aspects of analyzing these distributions with histograms and pitfalls that can be encountered if improperly binned histograms are used. We have automated several aspects of maximum likelihood fitting of dwell time distributions in the AGATHA software package.