Pressure drop mapping using 4D flow MRI in patients with bicuspid aortic valve disease: A novel marker of valvular obstruction

Pressure drop mapping using 4D flow MRI in patients with bicuspid aortic valve disease: A novel marker of valvular obstruction

Journal Pre-proof Pressure drop mapping using 4D flow MRI in patients with bicuspid aortic valve disease: A novel marker of valvular obstruction Ali ...

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Journal Pre-proof Pressure drop mapping using 4D flow MRI in patients with bicuspid aortic valve disease: A novel marker of valvular obstruction

Ali Fatehi Hassanabad, Fiona Burns, Michael S. Bristow, Carmen Lydell, Andrew G. Howarth, Bobak Heydari, Xuexin Gao, Paul W.M. Fedak, James A. White, Julio Garcia PII:

S0730-725X(19)30506-5

DOI:

https://doi.org/10.1016/j.mri.2019.11.011

Reference:

MRI 9342

To appear in:

Magnetic Resonance Imaging

Received date:

17 August 2019

Revised date:

2 November 2019

Accepted date:

9 November 2019

Please cite this article as: A.F. Hassanabad, F. Burns, M.S. Bristow, et al., Pressure drop mapping using 4D flow MRI in patients with bicuspid aortic valve disease: A novel marker of valvular obstruction, Magnetic Resonance Imaging(2019), https://doi.org/ 10.1016/j.mri.2019.11.011

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© 2019 Published by Elsevier.

Journal Pre-proof Pressure Drop Mapping Using 4D Flow MRI in Patients with Bicuspid Aortic Valve Disease: A Novel Marker of Valvular Obstruction Ali Fatehi Hassanabad, MD MSc1*; Fiona Burns, BS1, 2*; Michael S Bristow, MD, MSc 1, 2,3; Carmen Lydell, MD1, 3; Andrew G Howarth, MD, PhD1, 2; Bobak Heydari, MD, MPH1, 2; Xuexin Gao, PhD4; Paul W.M. Fedak, MD, PhD1; James A. White, MD1, 2; Julio Garcia, PhD1, 2, 3, 5 AFH ([email protected]); FB ([email protected]); MSB ([email protected]); CL ([email protected]); AGH ([email protected]); BH ([email protected]); XG ([email protected]); PWF ([email protected]); JW ([email protected]) ; JG ([email protected]). Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada. 2 Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, Calgary, AB, Canada. 3 Department of Radiology, University of Calgary, Calgary, AB, Canada. 4 Circle Cardiovascular Imaging, Advanced Technologies, Calgary, AB, Canada. 5 Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada.

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Julio Garcia, PhD

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Address for correspondence:

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*Authors contributed equally

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Libin Cardiovascular Institute of Alberta – Stephenson Cardiac Imaging Centre Department of Cardiac Sciences and Radiology

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University of Calgary – Cumming School of Medicine

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Suite 0700 Foothills Medical Centre – 1403 29th St NW Calgary, AB, Canada, T2N 2T9 Tel. (403) 944-2847

E-mail: [email protected] Short title: Pressure Drop Bicuspid Aortic Valve

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Journal Pre-proof ABSTRACT Background: The influence of complex bicuspid aortic valve (BAV) flow patterns on net intraluminal aortic pressure, both among patients with and without significant aortic stenosis, is unknown. Pressure drop (PD), as estimated by 4D Flow MRI, can quantify pre- vs post-valvular pressure at multiple levels simultaneously. Methods: In this prospective clinical study, 32 patients with BAV with varying degrees of aortic

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stenosis and regurgitation and 11 healthy subjects were enrolled. 4D flow MRI was processed

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and analyzed at 9 pre-defined thoracic aortic levels. PD was calculated at each plane relative to a reference located within the left ventricular outflow tract. Conventional 2D phase-contrast

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imaging was used as reference of hemodynamic obstruction. PD was compared between healthy

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subjects versus BAV patients using Kruskal-Wallis H test and Mann-Whitney U. Correlation

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studies were conducted using Spearman’s rank-order correlation. Results: Both BAV patients and healthy subjects showed progressive elevation in PD from the

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aortic root to the distal descending thoracic aorta. However, BAV patients showed higher PD

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than healthy subjects (p≤0.01) at all analysis planes. Patients with moderate-severe aortic

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stenosis (n=5) by 2D phase-contrast (peak PG >40mmHg) showed higher PD than those without in the descending aortic segments (p≤0.005). A correlation (r=0.88, p<0.05) was observed between PD at the distal descending thoracic aorta and peak trans-valvular velocity measured by 2D phase-contrast MRI. Conclusion: We demonstrated that PD with 4D flow MRI is clinically feasible in BAV patients and provides an additional physiologic description of valve-related hemodynamic obstruction.

Key words: Bicuspid aortic valve; blood flow; 4-D flow magnetic resonance imaging; pressure drop 2

Journal Pre-proof 1. INTRODUCTION Bicuspid aortic valve (BAV), present in 1% to 2% of the general population, is responsible for more deaths and complications than all other congenital heart defects combined (1,2). Clinical consequences of the disease, which include valvular stenosis/dysfunction and aortic dilatation (1), are present in ~50% of individuals (3). Different studies have shown the role of various flow patterns on the development of aortopathy, but the impact of hemodynamic and genetic factors

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on aortic dilatation continues to be a subject of debate (3,4). Aortic stenosis (AS) in patients

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with BAV is typically evaluated by peak transvalvular velocity, pressure gradient (PG), and valve effective orifice area (EOA) using transthoracic Doppler-echocardiography (TTE).

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Although TTE is a safe and reliable imaging modality, evaluating valvular stenosis severity by

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TTE indices may conflict with the patient’s clinical status in some cases (5–8). Accurate grading

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of BAV AS severity is critical for patient management, so it is essential that recommendations are based on reliable parameters. For this reason, there has been interest in exploring multi-

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modality imaging to confirm the grading of aortic stenosis severity (9).

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4D flow MRI (three-dimensional phase-contrast imaging with three-directional velocity encoding) provides a complete description of blood flow in three spatial dimensions throughout the cardiac cycle, thus avoiding the tendency of TTE and 2D phase-contrast (2D PC) MRI to underestimate PG (10). Mapping of pressure drop (PD) along the aorta can be calculated from 4D flow MRI data, providing a novel and alternate hemodynamic marker of aortic stenosis severity which could help inform clinical decisions. PD maps are derived by solving the pressure Poisson equation while TTE and 2D PC PG are derived by the modified Bernoulli equation using velocity-time integration (11,12). PD maps offer the advantage of providing an estimate of both temporal and spatial variations of relative pressure within a vessel segment. 3

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The objectives of this pilot study were to: i) demonstrate the clinical feasibility of 4D Flow MRIbased quantification of PD maps in BAV patients, ii) test for differences in PD between BAV patients without significant AS and similar healthy control subjects with tricuspid valves, and iii) test for differences in PD between BAV patients with moderate-severe AS and those without. Our hypothesis was that a higher PD maps would be observed in BAV patients, even without

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significant AS, compared to healthy control subjects and that a higher PD would be present in

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BAV patients with moderate to severe AS as compared to those without.

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2. METHODS

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2.1 Patient Population

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Thirty-two patients with BAV (48 ± 15 years, 11 female) and 11 healthy control subjects with normal, tricuspid aortic valves (52 ± 9 years, 2 female) were prospectively enrolled. Study

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subjects were identified and enrolled through commercial registry management software (Acuity,

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Cohesic Inc, Calgary, Canada) at the time of clinical referral for cardiac MRI. Healthy control

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subjects were recruited from part of the same study protocol and were required to have no known cardiovascular disease, hypertension, diabetes, renal disease or any standard contra-indications for MRI (13). Healthy control screening was performed by a certified nurse from our institution. Study patients were required to have confirmed BAV by trans-thoracic echocardiography or prior MRI-based assessment or other contra-indications to contrast-based MRI. For this pilot study, no restrictions were placed on LV systolic function or concurrent valvular insufficiency. The study was approved by the IRB at our institution and all subjects provided written informed consent. All research activities were performed in accordance with the Declaration of Helsinki.

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Journal Pre-proof 2.2 MRI Data Acquisition All healthy volunteers and patients underwent a standardized MR imaging protocol using a 3T clinical scanner (Prisma (n=39) or Skyra (n=4), Siemens Healthineers, Erlangen, Germany) inclusive of standard multi-planar steady-state free-precession (SSFP) cine imaging in 4chamber, 3-chamber, 2-chamber, at valve planimetry to characterize valve type, short-axis of the left ventricle (LV) at end-expiration, 2D PC of the aortic valve, 3D magnetic resonance

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angiography (MRA) of the thoracic aorta, and 4D flow MRI. 2D PC assessments were performed

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at the level of the left ventricular outflow tract (LVOT), aortic valve, and sino-tubular junction. A trans-valvular jet in-plane velocity acquisition served as complementary velocity scout for 4D

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flow MRI velocity encoding (Venc) selection. Aortic 3D MRA was performed using

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administration of 0.2 mmol/kg gadolinium contrast (Gadovist®, Bayer Inc., Canada) and ECG-

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gated 3D fast low angle shot sequence (FLASH, FOV= 384×192-282×80-104, resolution = 1.171.30×1.17-1.30×1.4-1.8 mm3, flip angle = 24 º). 4D flow MRI was performed using a

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prospectively triggered sequence with respiratory navigator-based gating, as described

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previously (14). Acquisition parameters were as follows: spatial resolution 2.5–3.9 × 2.0–3.1 ×

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3.0–3.5 mm3, temporal resolution 44.0–48.0 ms, Venc = 150–450 cm/s), echo time = 2.85–3.24 ms, pulse repetition time = 5.50–6.00 ms, flip angle = 15º, FOV 240–400 × 320–400 mm2, matrix 130–160 × 110–160, bandwidth 490 pixel/MHz, time frames per cardiac cycle = 12–20. Total scan time for the 4D flow-sensitive measurement was 13 ± 4 min. The maximal Venc was chosen for each subject based on the non-aliasing encoding velocity identified from 2D PC MRI. In 10 subjects the 4D flow MRI acquisition was repeated same day for scan-rescan reproducibility.

2.3 MRI Data Processing and Analysis 5

Journal Pre-proof Cine MR images were processed and analyzed using commercial software (cvi42, Circle Cardiovascular Inc., Calgary, Canada) to determine LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), LV ejection fraction (LVEF), and LV mass. Where appropriate, volume and mass measurements were indexed to body surface area (BSA), calculated using the Mosteller formula. BAV valve type were identified by cine valve planimetry using the Sievers’s classification: BAV type 0 (no raphe) anteroposterior and lateral, BAV type 1 (one raphe) with

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RL fusion pattern (raphe between left coronary and right coronary sinuses) and RN fusion

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pattern (raphe between right coronary and non-coronary sinuses), and BAV type 2 / unicuspid (two raphes) with RL/RN fusion patterns (15). Standard aortic 3D MRA was used to measure

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aortic dimensions at the sinus of Valsalva, proximal ascending aorta and mid-ascending aorta as

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recommended by the guidelines (16). 2D PC-MRI were used to provide conventional measures

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of hemodynamic significance, including flow volume, regurgitant fraction, peak velocity (PV), peak PG and mean PG based on simplified Bernoulli’s equation. Aortic valve stenosis and

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regurgitation severity were ranged according to current guidelines (17). Clinical TTE reports,

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PD measurements.

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when available, within 3 months prior/after MRI scan were collected and used as reference for

4D flow MRI analysis was performed using a prototype module from cvi42 (v5.9.0) and the workflow is schematically summarized in Figure 1. Pre-processing corrections were applied to reduce noise, correct for eddy currents and perform phase unwrapping in the case of velocity aliasing. Segmentation of the entire aorta was achieved using a semi-automatic nearestneighbour algorithm. A volumetric centerline was constructed to facilitate the placement of analysis planes. 4D flow data was analyzed at 9 pre-defined aortic locations extending from the LVOT to the distal descending aorta (DDA), as indicated in Figure 1. Automatic contour 6

Journal Pre-proof detection was used to quantify flow for each time point at every plane. Contours were manually verified and corrected as needed. 4D flow data was visualized using velocity and pressure drop maps. Net flow, regurgitant fraction, PV, peak PG, and maximum PD were automatically calculated at each plane. It has been documented that beyond the valve EOA, the flow decelerates in a region of turbulent mixing, causing some of the energy to be irreversibly dissipated (18). PD quantifies the cumulative change in total pressure relative to the pre-valvular

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reference (LVOT) within the vessel. All 4D flow image analysis was performed blinded to

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observer PD variability was assessed in 10 subjects.

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patient identifiers, clinical information and results of 2D PC-MRI. Furthermore, inter- and intra-

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2.4 Statistical Analysis

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For assessing feasibility, a PD sample size calculation was performed based on σ=1 mmHg and a minimum expected difference of 1 mmHg (19). Continuous data was found in general to be non-

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parametrically distributed and is expressed with median and range values. A normality test was

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performed to assess data distribution. To analyze the effects of BAV Sievers type, AS,

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regurgitation, and aortic dilatation on PD in the BAV patient group, Kruskal-Wallis H test and Mann-Whitney U post hoc tests were performed unless otherwise indicated. Correlation studies were conducted using Spearman’s rank-order correlation. Bland-Altman analysis was performed to assess inter-observer, intra-observer, and scan-rescan PD reproducibility. Values of p< 0.05 were considered statistically significant. All statistical tests were 2-sided and performed in SPSS (IBM SPSS Statistics 24).

3. RESULTS 3.1 Baseline Characteristics 7

Journal Pre-proof A sample size estimation of 15 was obtained to differentiate PD severity. Patient demographics baseline is shown in Table 1. BAV subjects mean age was 47 ± 15 years (9 female) and presented comorbidities including: NYHA>II (27%), heart failure (3%), hypertension (15%), diabetes mellitus (9%), dyslipidemia (6%), obesity (18%), prior coronary intervention (3%) and cardiac arrythmias (6%). MRI baseline exam showed that controls and BAV patients had similar LV function. BAV subjects presented a mean LVEDVi and LVEF of 94±28 ml/m2 and 62±9 %,

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respectively. Aortic stenosis (AS) was classified based on 2D PC-MRI measurement of peak

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velocity above the valve, where mild AS = PV 200-300 cm/s and moderate/severe AS = PV >300 cm/s. Similarly, aortic regurgitation (AR) was classified based on 2D PC-MRI

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measurement of regurgitant fraction (RF) above the valve, where mild AR = RF 5-15%, mild-

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moderate AR = RF 15-30%, moderate AR = RF 30-35%, and moderate-severe AR = RF >35%.

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Aortic stenosis was thus characterized as mild in 7% and moderate/severe in 18%. Aortic regurgitation was observed as mild in 14%, mild-moderate in 29%, moderate in 7% and

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moderate-severe in 11%. Based on 2D PC-MRI performed above the aortic valve plane, 27

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patients had no flow acceleration with a peak systolic trans-valvular gradients ≤ 40 mmHg. Five

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patients showed moderate and severe AS, with a peak PG > 40 mmHg. Sievers classification identified the following distribution of valve morphology for the 32 study subjects: type 0 in 11%, type 1 RN in 25% and type 1 RL in 64%. Aortic dilation was characterized in the aortic root as mild in 7% and moderate in 11%, in the ascending aorta as mild in 11%, moderate in 18% and severe in 3%. A summary of MRI measurements is provided in Table 2.

3.2 Pressure Drop in Patients with BAV PD estimates from 4D flow showed progressive elevation along the length of the thoracic aorta, from the sinotubular junction (STJ) to the DDA. Increasing PD is evident in both BAV patients 8

Journal Pre-proof and healthy control subjects. Comparing all BAV patients to healthy controls, significant differences (p ≤ 0.01) were observed in PD for all analysis planes, as shown in Figure 2. At the mid ascending aorta (MAA), the median PD was 3 mmHg in healthy volunteers versus 6 mmHg in those with BAV (p = 0.001). In contrast, peak PG as measured by 4D flow only showed significant differences at the sinus of Valsalva (SOV), STJ, MAA, and Arch2 planes (p ≤ 0.05), with higher PV and peak PG values associated with BAV patients. Peak PG above the valve as

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measured by 2D PC-MRI demonstrated a significant difference (p<0.005) for BAV patients

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versus healthy controls, as shown in Figure 3. Among BAV patients without moderate or severe stenosis (n = 27), significant PD differences were observed versus healthy controls in all planes

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(p≤ 0.05). Among 5 study subjects with moderate-severe stenosis a significantly higher PD was

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seen versus all other BAV patients, only in the distal arch and descending aortic segments (p ≤

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0.005). PD differences between a healthy control, a BAV patient without aortic stenosis and a BAV patient with aortic stenosis are illustrated in Figure 4. Intra-observer variability showed a

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PD bias and agreement <1mmHg, inter-observer variability showed similar bias but increased

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range of agreement from the MAA to DDA (Table 3). Scan-rescan variability assessment

location, Table 3.

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showed a variable bias (from -6.7 mmHg to 0.3 mmHg) and agreement depending on the

3.3 Comparison to Conventional Measures of Flow Obstruction We performed correlation analyses of 4D-flow based PD measures to conventional measures of hemodynamic obstruction, measured by 2D PC-MRI (measured at peak systole at aortic cusp tips). Strong, positive correlations were observed between peak PD at the DDA and both peak velocity and mean pressure gradient as measured by 2D PC-MRI above the valve (rs = 0.761, p <

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Journal Pre-proof 0.01; rs = 0.768, p < 0.01, respectively). Similar analyses performed at more proximal locations, such as the MAA, failed to reach statistical significance.

3.4 Other 4D Flow-Derived Measurements Net flow measurements were not significantly different between BAV patients and healthy volunteers at any plane location. Regurgitant fraction was significantly higher among patients

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with BAV versus healthy controls (p ≤ 0.05) not only at the LVOT and SOV, but also at more

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distal locations inclusive of the MAA, Arch1, Arch3, PDA, and DDA planes. Distributions are shown in Figure 5. By published thresholds for severity of regurgitation by regurgitant fraction

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(17), 5 study subjects demonstrated moderate-severe regurgitation. Sensitivity analysis,

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performed following removal of these patients, did not change the presence of significant

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associations between PD and peak or mean trans-valvular gradients.

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Finally, energy loss was quantified in the ascending aorta, analyzed between planes placed at the

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LVOT and Arch1 positions. This demonstrated significant differences between energy loss

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observed in BAV patients versus healthy volunteers (p = 0.003), with a median energy loss of 3.2 mW (range 1.2-23.9 mW) in BAV subjects versus 1.7 mW (range 0.7-3.1 mW) in healthy volunteers. Table 4 summarize significant differences (p<0.05) of maximal PD, peak velocity, regurgitation fraction and energy loss at SOV. A strong, positive correlation (rs = 0.662, p < 0.01) was observed between absolute PV and energy loss in the ascending aorta.

4. DISCUSSION In this pilot study we demonstrate the feasibility of calculating PD using 4D Flow MRI in patients referred for the assessment of BAV disease. This study demonstrates that BAV patients 10

Journal Pre-proof without significant stenosis have significantly higher PD at all levels of the thoracic aorta compared to healthy volunteers, and that PD increases with the severity of valvular stenosis, as assessed by conventional 2D PC MRI. The distal descending thoracic aorta is especially suitable for PD measurement as it affords sufficient geographic distribution, hence minimizing potential data acquisition inaccuracies secondary to the loss of energy related to abnormal aortic flow.

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Contemporary clinical care pathways include cardiac catheterization to determine aortic valve

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PG, a gold standard to assess trans-valvular pressure drop. This, however, is an invasive method associated with risk of cerebral embolism (20). Transthoracic Doppler-echocardiography (TTE)

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is ubiquitously used to grade stenosis severity since it is non-invasive, low cost, and versatile.

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TTE provides an estimate of PG using the simplified Bernoulli equation, but has several

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theoretical and technical limitations including i) potential for underestimation of flow velocity due to misalignment of the Doppler beam with flow direction (21,22), ii) lack of information

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about spatial or temporal variations across the valve, and iii) important boundary conditions

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neglected by the simplified Bernoulli equation (23).

Further, the evaluation of the severity of valvular stenosis by different Dopplerechocardiographic indices (i.e. peak velocity, PG, and EOA) can be inconsistent, or may be incongruent with the patient’s clinical status (5–8). Correct grading of BAV stenosis severity is critical for patient management, so it is essential that recommendations are based on reliable parameters. Recent studies agree that optimal management of BAV patients with aortic dilatation will require the use of novel aortic risk markers for the development of consistent guidelines (24,25). For this reason, there has been interest in exploring innovative imaging modalities to help better identify patients who will benefit most from surgical intervention. 11

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Due to the risks of aortic dilatation, BAV patients require assessments of both the aortic valve and the aorta. Magnetic resonance imaging (MRI) allows for a comprehensive assessment of both, in addition to left ventricle (LV) function and tissue characterization. Furthermore, 4D flow MRI (three-dimensional cine phase-contrast CMR with three-directional velocity encoding) provides a complete description of blood flow in three spatial dimensions, thus limiting the

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tendency of TTE and 2D phase-contrast (2D PC) MRI to underestimate PG (10). In this way, 4D

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flow MRI is the most comprehensive method to measure velocity. 4D flow MRI also allows for pressure mapping along the aorta, a novel and alternate hemodynamic marker of disease severity

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which could help inform clinical decisions. As mentioned, using the time-resolved velocity field

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measured by 4D flow MRI, pressure drop (PD) maps can be derived by solving the pressure

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Poisson equation (11,12). Unlike other imaging modalities, these pressure maps offer the advantage of providing an estimate of both temporal and spatial variations of relative pressure

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within a vessel segment. Combining both parameters in producing such maps facilitates an

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accurate assessment of the blood flow jets seen with various types of valves.

4.1 Comparison of Results to Previous Studies 4D flow-derived measurements found in our cohort were generally in fair agreement with findings in other MRI studies. When studying patients with Sievers type 1-RL BAV, Barker et al. found that peak velocities were significantly elevated in BAV patients compared with age/size control cohorts (p<0.001) (26). This agrees with our findings that demonstrate PV and PG to have significant differences between BAV patients and healthy controls at all analysis planes throughout the thoracic aorta. With respect to our healthy control cohort, Van Ooij et al.

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Journal Pre-proof previously described peak systolic trans-valvular PG of 9±2 mmHg using 4D Flow MRI (27), compared to 5±2 mmHg in our study.

Several prior studies have assessed PD using 4D Flow MRI. These studies have provided the evidence for measuring PD in aortic coarct model (28), intracranial atherosclerotic disease (29), and bioprosthetic versus mechanical prosthetic aortic valve replacement (30). Our study is novel

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as it evaluates PD in specifically BAV versus healthy patients. Furthermore, the present study

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shows the feasibility and significance of applying PD measurements to creating aortic flow maps. This has clinical relevance as it can provide patient-specific information which could be

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used to devise guidelines for managing aortopathies in the future.

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With regards to PD measurements, it is difficult to compare absolute values due to the dependency on a specified reference point. In healthy volunteers, Ebbers et al. found the

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minimum pressure difference between the first and last supra-aortic branches (i.e. Arch1 and

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Arch3 in this study) to be -2 mmHg, while Nagao et al. observed -0.6 mmHg and Bock et al.

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measured -1 mmHg (23,31,32). These are on the same order of magnitude as our findings, which measured a PD of - 0.3 mmHg between these analysis planes. Between the ascending aorta and first branch, Nagao et al. and Bock et al. measured the minimum pressure difference to be -0.4 and -0.8 mmHg respectively (23,32); in this study we found a PD of - 0.3 mmHg between the MAA and Arch1 planes. Finally, between the ascending aorta and DDA Tyska et al. and Bock et al. measured a minimum pressure difference of -5 and -3 mmHg (23,33), which agrees with our measured minimum PD of - 2 mmHg between the MAA and DDA analysis planes. Note that our results reflect the average of 11 healthy volunteers, while the other studies

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Journal Pre-proof examined only one subject (with the exception of Bock et al. which considered 12 healthy patients). This limits the power of statistical comparison.

Lastly, our energy loss measurements for healthy volunteers (1.7 mW, range 07-3.1 mW) agree with the value of 1.2±0.6 found in a study by Barker et al. (34). Our findings for patients with BAV (3.2 mW, range 1.2-23.9 mW) are on the same order of magnitude as the results described

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in the Baker et al study as well (2.2±1.1 mW for BAV patients with aortic dilatation, 10.9±6.8

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mW for BAV patients with aortic stenosis).

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4.2 Study Limitations

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A major limitation for this study is the small sample size, particularly for patients with clinically

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moderate-severe BAV disease. Further exploration of the effect of type of BAV obstruction and aortic stenosis on PD will require a larger cohort of patients with different types of BAV disease.

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Future studies would also benefit from a full complement of corresponding echocardiographic

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and CMR studies. The analyst was blinded to comparative 2D measures during processing of 4D

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flow data. However, the analyst was not blinded to whether the subject was a healthy volunteer or patient with BAV at the time of cvi42 analysis. This may have introduced unintentional bias to this study and its results. Inter- and intra-observer variability was good in our study (bias <1 mmHg), but scan-rescan assessment suggested that PD variability and agreement can be affected by repeatability of 4D flow MRI acquisition. Further exploration in this context need to be considered.

Further, the discrete spatial and temporal resolution of 4D flow MRI results in a systematic underestimation of peak velocity (35), due to partial volumes effects and temporal filtering. This 14

Journal Pre-proof limits the accuracy of 4D flow-derived parameters and pressure gradients may be underestimated. Turbulence and complex flow can also result in signal dephasing, which may further compromise the accuracy of measurements estimated from 4D flow and 2D PC-MRI (36).

5. Conclusion

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In conclusion, the results of this study indicate that 4D flow-based PD is clinically feasible in

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patients with BAV, who exhibit significantly altered PD throughout the aorta compared to healthy volunteers with normal, tricuspid aortic valves. PD provides a physiologic description of

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valve-related hemodynamics through non-invasive pressure mapping. Further, measurements

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show a strong correlation between PD and conventional measures of valve-related flow

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obstruction as determined by 2D PC-MRI. This study acts primarily as proof-of-concept and

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in patients with BAV.

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justifies expanded investigation of PD and how this novel marker may improve risk stratification

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Journal Pre-proof Tables Table 1. Clinical baseline. Table 2. Magnetic resonance imaging baseline. Table 3 . Intra-observer, inter-observer, and scan-rescan pressure drop reproducibility. Table 4. Sinus of Valsalva measurements between healthy controls and patients with

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bicuspid aortic stenosis.

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Journal Pre-proof Figure Legends Figure 1: Flow chart representing the steps taken to process and analyze 4D flow data. Segmentation was achieved semi-automatically using a nearest-neighbour algorithm. Right image shows the location of 9 analysis planes: LVOT indicates left ventricular outflow tract, SOV indicates sinus of Valsalva, STJ indicates sinotubular junction, MAA indicates mid ascending aorta, PDA indicates proximal descending aorta, and DDA indicates distal descending

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aorta. Pressure drop maps are derived by solving the pressure Poisson equation.

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Figure 2: Boxplots illustrating the distribution of PD data sets for 8 analysis planes relative to

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the LVOT reference. TOP: healthy volunteers (white) and all BAV patients (grey); ▪ indicates

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that data was normally distributed (student t-test used). BOTTOM: healthy volunteers (white),

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BAV patients with AS (striped), and BAV patients without AS (grey). Controls N=11, BAV N=32, BAV, no or mild AS N=23, BAV mod or mod-sev AS N =5.

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Figure 3: Boxplot illustrating the distribution of peak PG data sets as measured by 2D PC-MRI

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volunteers (white).

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above the valve, showing significant differences between BAV patients (grey) and healthy

Figure 4: Pressure drop in a healthy control (left), a patient without BAV without aortic stenosis (center), and a patient with aortic stenosis. Figure 5: Boxplot illustrating distribution of the regurgitant fraction data sets for all 9 analysis planes. Healthy volunteers (white) and all BAV patients (grey); ▪ indicates that data was normally distributed (student t-test used).

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Journal Pre-proof Tables Table 1. Clinical baseline.

52 ± 9 (range 32-70) 2 (18) 1.70 ± 0.12 81 ± 8 1.95 ± 0.16 58 ± 10 113 ± 15 62 ± 3

47 ± 15 (range 18-74) 9 (32) 1.73 ± 0.13 84 ± 18 2.00 ± 0.24 62 ± 14 113 ± 13 63 ± 11

0.375 0.325 0.592 0.705 0.673 0.461 0.951 0.747

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p-value

9(27) 1(3) 5(15) 3(9) 2(6) 6(18) 0 0 1(3) 2(6)

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Comorbidities NYHA >II, n(%) Heart Failure, n(%) Hypertension, n(%) Diabetes Mellitus (%) Dyslipidemia (%) Obesity (%) Obstructive Apnea (%) Coronary Disease (%) Prior PCI or CABG (%) Arrythmias (%)

BAV (n=32)

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Demographics Age (years) Female n(%) Height (m) Weight (kg) Body surface area (m2) Heart rate (beats/min) Systolic BP (mmHg) Diastolic BP (mmHg)

Controls (n=11)

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Journal Pre-proof Table 2. Magnetic resonance imaging baseline. Controls (n=11)

BAV (n=32)

p-value

81 ± 10 30 ± 7 103 ± 14 5.8 ± 1.1 64 ± 7 55 ± 10

94 ± 28 37 ± 16 116 ± 33 6.8 ± 2.2 62 ± 9 65 ± 19

0.249 0.261 0.345 0.309 0.634 0.216

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Left ventricle Function LVEDVi (mL/m2) LVESVi (mL/m2) LVSV (mL) LVCO (L/min) LVEF (%) LVMi (g/m2)

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Aortic Dilatation Root Normal, n(%) Mild, n(%) Moderate, n(%) AsAo Normal, n(%) Mild, n(%) Moderate, n(%) Severe, n(%)

3 (11) 7 (25) 18 (64)

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BAV Sievers Classification Type 0, lateral, n(%) Type 1, RN, n(%) Type 1, RL, n(%)

21 (75) 2 (7) 5 (18) 11 (39) 4 (14) 8 (29) 2 (7) 3 (11)

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Aortic Valve Function No AS, n(%) Mild AS, n(%) Moderate/severe AS, n(%) No AR, n(%) Mild AR, n(%) Mild-moderate AR, n(%) Moderate AR, n(%) Moderate-severe AR, n(%)

23 (82) 2 (7) 3 (11) 18 (64) 3 (11) 5 (18) 1 (3)

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Journal Pre-proof Values are mean ± SD or n (%). AR = aortic regurgitation; AS = aortic stenosis; AsAo = ascending aorta; BAV = bicuspid aortic valve; RL = right-left coronary cusp fusion; RN = right

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coronary-noncoronary cusp fusion.

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Journal Pre-proof Table 3 . Intra-observer, inter-observer, and scan-rescan pressure drop reproducibility. Standard Deviation

0.1 0.1 0.2 0.1 0.1 0.2 -0.2 -0.03

0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4

Inter-Observer Sinus of Valsalva Sinotubular Junction Mid Ascending Aorta Arch 1 Arch 2 Arch 3 Proximal Descending Aorta Distal Descending Aorta

0.1 0.1 0.2 0.2 0.1 0.1 -0.2 -0.3

0.3 0.4 0.4 0.4 0.6 0.6 0.4 0.4

Scan-Rescan Sinus of Valsalva Sinotubular Junction Mid Ascending Aorta Arch 1 Arch 2 Arch 3 Proximal Descending Aorta Distal Descending Aorta

-2.8 -3.2 -4.7 -6.7 -5.5 -5.1 -1.5 0.3

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[ -0.5 to 0.7 ] [ -0.7 to 0.9 ] [ -0.6 to 1 ] [ -0.6 to 0.8 ] [ -0.6 to 0.9 ] [ -0.5 to 0.9 ] [ -1.0 to 0.6 ] [ -0.9 to 0.4 ]

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Intra-Observer Sinus of Valsalva Sinotubular Junction Mid Ascending Aorta Arch 1 Arch 2 Arch 3 Proximal Descending Aorta Distal Descending Aorta

Limits of Agreement

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Pressure Drop Plane (mmHg)

3.1 3.1 3.8 5.5 4.4 4.3 3.2 4.5

[ -0.5 to 0.7 ] [ -0.7 to 0.9 ] [ -0.6 to 1.1 ] [ -0.6 to 1.1 ] [ -1.1 to 1.3 ] [ -1.1 to 1.2 ] [ -1.0 to 0.6 ] [ -0.9 to 0.4 ]

[ -11.0 to 5.2 ] [ -12.3 to 2.8 ] [ -12.3 to 2.8 ] [ -17.7 to 4.2 ] [ -14.3 to 3.1 ] [ -13.5 to 3.3 ] [ -7.8 to 4.9 ] [ -8.6 to 9.2 ]

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Journal Pre-proof Table 4. Sinus of Valsalva measurements between healthy controls and patients with bicuspid aortic stenosis. BAV (n=32) ± SD 2.79 ± 1.79 157.68 ± 57.06 11.20 ± 9.27 10.81 ± 9.36 3.92 ± 2.87

p-value 0.006 0.038 0.069 0.019 0.020

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Maximal PD (mmHg) Peak Velocity (cm/s) Peak Gradient (mmHg) Regurgitant Fraction (%) Energy Loss (mW)

Control (n = 11) ± SD 1.12 ± 0.89 119.09 ± 22.46 5.86 ± 2.08 3.56 ± 4.18 1.73 ± 0.93

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Figure 1

Figure 2

Figure 3

Figure 4

Figure 5