Hemodynamic evaluation of the pulmonary arteries and aorta using 4D flow cardiac MRI in children and young adults with dextro-transposition of the great arteries after the arterial switch operation

Hemodynamic evaluation of the pulmonary arteries and aorta using 4D flow cardiac MRI in children and young adults with dextro-transposition of the great arteries after the arterial switch operation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hemodynamic evaluation of the pulmonary arteries and aorta using 4D flow cardiac MRI in children and young adults with dextro-transposition of the great arteries after the arterial switch operation Kylie Calderon, Aparna Sodhi, Ethan M.I. Johnson, Michael Markl, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5133875/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Dec, 2024 Read the published version in Pediatric Radiology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Pulmonary artery stenosis, neoaortic dilatation, and neoaortic valve insufficiency are among the most frequent complications of the arterial switch operation for repair of dextro-transposition of the great arteries (d-TGA). It remains difficult to predict which patients will require great arterial reintervention. Objective We aimed to characterize hemodynamics within the great arteries using 4D flow MRI in patients with d-TGA after the arterial switch operation. Materials and Methods Patients with d-TGA after the arterial switch operation and controls with normal cardiac anatomy who underwent 4D flow MRI between 2012 and 2024 were included. Velocity, stasis, kinetic energy, energy loss, wall shear stress, and pulse wave velocity were quantified in the aorta and pulmonary arteries. Results Patients with d-TGA after the arterial switch operation (15.7 years ± 2.4) demonstrated significantly higher maximum and mean velocity, maximum and mean kinetic energy, energy loss, and maximum and mean wall shear stress within the pulmonary arteries ( P < 0.0001 for all parameters) compared with age-matched controls (15.5 years ± 2.4). Aortic maximum ( P = 0.0011) and mean ( P = 0.0483) velocity, maximum ( P = 0.0008) and mean ( P = 0.0026) kinetic energy, energy loss ( P < 0.0001), maximum wall shear stress in five of six regions (range P < 0.0001 to P = 0.0022), and mean wall shear stress in three regions (range P = 0.0052 to P = 0.0310) were significantly higher in patients with d-TGA after the arterial switch operation patients compared with age-matched controls. Conclusion Patients with d-TGA after the arterial switch operation demonstrate hemodynamic abnormalities within the great arteries, which may provide insight into the mechanisms underlying postoperative consequences of the arterial switch operation and the need for reintervention. Transposition of the great arteries Arterial switch operation 4D flow MRI Wall shear stress Cardiac MRI Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Complications following the arterial switch operation for repair of dextro-transposition of the great arteries (d-TGA) include pulmonary artery stenosis, progressive neoaortic root dilatation, and neo-aortic valve insufficiency [ 1 – 3 ]. Although reintervention rates decreased after introduction of the LeCompte maneuver [ 4 ], pulmonary artery stenosis, either supravalvular or involving the right or left branch pulmonary arteries, remains the most common indication for reintervention [ 5 ]. Neoaortic root dilatation and valve insufficiency may require reintervention for aortic valve and/or neo-aortic root replacement, often late in follow-up [ 6 ]. Standard tools for postoperative evaluation and monitoring of patients after the arterial switch operation include Doppler echocardiography and cardiac MRI including 2D phase contrast imaging [ 7 ]. Although widely available and inexpensive, echocardiography is limited by acoustic windows, which can be challenging due to somatic growth [ 8 ] and the position of the pulmonary arteries posterior to the sternum after the LeCompte maneuver [ 9 ]. Echocardiography therefore has limited sensitivity for branch pulmonary artery stenosis [ 4 ]. Cardiac MRI allows for better branch pulmonary artery visualization following the arterial switch operation but relies on an operator-defined 2D imaging plane with unidirectional velocity encoding and does not provide full volumetric great artery coverage [ 7 , 10 ]. Three-dimensional cine (time-resolved) phase contrast cardiac MRI with three-directional velocity encoding (4D flow MRI) offers more comprehensive great artery evaluation and could thereby allow for improved great artery monitoring in d-TGA after arterial switch operation. Prior studies have used 4D flow MRI to assess hemodynamics in patients with d-TGA after the arterial switch operation [ 7 , 10 – 19 ], and found abnormalities in systolic flow displacement [ 12 ]; wall shear stress [ 11 – 13 ], a measure of the force exerted on a vessel wall due to blood flow [ 20 ]; oscillatory shear index [ 11 ]; viscous dissipation [ 11 ]; helical density [ 11 ]; and regurgitant fraction [ 11 ] in the aorta. However, prior studies have been limited by small cohorts of controls and/or patients with d-TGA after the arterial switch operation [ 10 , 11 , 13 ]. Furthermore, pulse wave velocity, an established marker of arterial stiffness [ 21 ], is one parameter not been previously quantified within the aorta using 4D flow MRI in patients with d-TGA after the arterial switch operation. Although many aortic flow parameters have been investigated, the hemodynamic pulmonary artery profile has yet to be thoroughly characterized. To our knowledge, kinetic energy, a measure of the energy of blood flow due to motion, used as an indicator of cardiovascular efficiency [ 22 ]; energy loss, another metric for cardiovascular efficiency, equal to kinetic energy lost as thermal energy due to viscosity-driven friction [ 23 ]; and wall shear stress, a measure of shear forces exerted on the vessel wall by blood flow that serves as an indicator of risk for vascular remodeling [ 21 ], have not previously been studied in the pulmonary arteries of patients with d-TGA after the arterial switch operation. These hemodynamic parameters could provide valuable insights into the mechanisms underlying pulmonary arterial stenosis. We hypothesized that d-TGA after the arterial switch operation patients demonstrate abnormal flow, such as increased velocity, kinetic energy, and energy loss within the aorta and pulmonary arteries, which results in vascular remodeling that leads to aortic pathologies and pulmonary artery stenosis. Abnormal hemodynamic parameters in patients with d-TGA after the arterial switch operation patients could solidify the utility of 4D flow MRI in long-term monitoring of this patient population. The aim of this study was thus to use 4D flow MRI to compare pulmonary arterial and aortic hemodynamics between patients with d-TGA after the arterial switch operation [ 23 ] [ 20 ] and patients with normal cardiac anatomy. Materials and Methods Study Cohort This retrospective cohort study included 44 children and young adults under 24 years old with d-TGA after the arterial switch operation (d-TGA group) and 25 children and young adults under 24 years old with normal cardiac anatomy (control group) who were age-matched to a subgroup of 25 d-TGA subjects. All d-TGA and control subjects were patients who underwent cardiac MRI at Lurie Children’s Hospital between June 2012 and January 2024. Cardiac MRI was clinically indicated for all d-TGA patients. For the d-TGA group, written consent or assent was obtained for 4D flow sequences prior to 2018, and 4D flow sequences were clinically indicated as part of the cardiac MRI examination after 2018. Controls included patients undergoing MRI for other indications who consented or assented to the addition of a 4D flow sequence for research purposes, as well as patients who underwent clinically indicated 4D flow MRI. All controls were found to have normal cardiac anatomy and function on MRI. All studies were retrospectively reviewed with a waiver of consent. This study is health insurance and accountability act compliant and was approved by the Institutional Review Board of Lurie Children’s Hospital. For the d-TGA group, exclusion criteria were other cardiac lesions at birth (26 patients), except for atrial septal defect and/or ventricular septal defect; and history of other surgical or catheter-based intervention affecting the great arteries prior to cardiac MRI (16 patients), except for balloon atrial septostomy. Other inclusion and exclusion criteria are summarized in Fig. 1 . For patients with more than one 4D flow scan, the most recent exam was used. Demographic information collected for each patient included sex and age, weight, height, and body surface area at the time of the exam. Patient charts were also reviewed for history of catheter-based or surgical reintervention affecting the great arteries and/or semilunar valves at any date after the exam. Cardiac MRI Acquisition All cardiac MRI examinations were performed on a 1.5T MRI scanner (Aera, Siemens Healthineers, Malvern PA). Each patient underwent cardiac MRI including multiplanar balanced steady state free precession cine imaging followed by 4D flow MRI. The 4D flow MRI parameters were tailored to each patient with the following ranges: FOV (mm 2 ) = 260–400 x 195–280, spatial resolution (mm 3 ) = 1.97–3.59 x 1.35–2.5 x 1.4–2.8, temporal resolution (ms) = 40-62.76, TE (ms) = 2.32-3.0009, flip angle (°) = 8–25, venc (cm/s) = 80–250. Studies were respiratory navigator gated and performed with free breathing. Electrocardiographic synchronization was via retrospective gating for 32 d-TGA patients and 13 controls, and prospective triggering for 12 d-TGA patients and 13 controls. For the d-TGA group, prior to the 4D flow sequence, a gadolinium-based contrast agent (Gadavist, Bayer, Whippany, USA; or Ablavar, Lantheus Medical, Billerica, USA) was administered per the clinical protocol to 13 patients and ferumoxytol (Ferahame, AMAG Pharmaceuticals, Waltham, USA) to 11 patients per the clinical indication. For the control group, a gadolinium-based contrast agent was administered to 23 patients prior to the 4D flow sequence. Twenty d-TGA patients and two controls were imaged without contrast. Cardiac MRI Anatomic Measurements Neoaortic root, main pulmonary artery, and proximal left and right pulmonary artery diameters for d-TGA patients were measured for clinical purposes at the time of the exam using double-oblique short axis vessel views generated on an independent workstation (Vitrea Software, Canon Medical Systems Corporation, Tustin, CA) from a fast low angle shot gradient echo MRI (FLASH) sequence. To account for age and body size differences in, Z-scores were determined for each vessel using Boston Children’s Hospital Z-score system [ 24 , 25 ]. The largest neoaortic root diameter and smallest main pulmonary artery, right pulmonary artery, and left pulmonary artery diameters for were used for Z-score determination. Z-scores less than − 2 and greater than + 2 were considered abnormal. 4D Flow MRI Analysis Pre- and post-processing 4D flow workflow is shown in Fig. 2 . An in-house MATLAB (version R2017b; Mathworks, Natick, USA) software tool was used for 4D flow data pre-processing, including correction for phase offset errors (Maxwell terms, eddy currents), noise masking, and velocity-antialiasing. As previously described [ 26 ], a mean sum square phase contrast magnetic resonance angiogram was calculated for each exam and was used for manual thoracic aorta and main and branch pulmonary artery 3D segmentation (Mimics, Materialize, Leuven, Belgium). Pulmonary artery segmentations included the main, left, and right pulmonary arteries, terminating at the proximal segmental branches. An automated quantification tool programmed in MATLAB was used to mask 4D flow data using the aorta and pulmonary artery segmentations to quantify nine hemodynamic parameters during systole summarized in Online Resource 1 , including mean and maximum velocity, mean and maximum kinetic energy, stasis, energy loss, and maximum and mean wall shear stress, and pulse wave velocity. Data were interpolated to isotropic 1mm 2 voxels for quantification of voxel-wise parameters. For each voxel, velocity magnitudes were measured at each time point and then averaged over all time points to determine the mean velocity. Flow stasis was calculated as the percentage of time frames for which velocity < 0.10 m/s. Kinetic energy and energy loss were calculated as previously described [ 23 , 27 ]. All voxel-wise parameters were averaged over the segmented volumes of the aorta and pulmonary arteries and are reported as means. For aortic regional analysis, a centerline was automatically calculated, and 2D analysis planes were manually placed to divide the aorta into three regions of interest, including the ascending aorta from the aortic valve to the brachiocephalic trunk, the aortic arch including proximal branch vessels, and descending aorta from the left subclavian artery through the distal thoracic aorta (Online Resource 2 ). 3D wall shear stress at each time point was quantified using an in-house developed tool based on a previously described technique [ 20 ]. Maximum wall shear stress was defined as the highest value within the region at any time point. Mean wall shear stress was determined by averaging wall shear stress over each region of the segmented aorta (Online Resource 2 ), and over the entire pulmonary artery segmentation. Voxel-wise maximum velocity was also measured within each aortic region and is reported as a mean average. As previously described [ 28 ], pulse wave velocity was quantified in the aorta using custom software programmed in MATLAB. Analysis planes were automatically placed perpendicular to the centerline of the aorta. Through-plane flow curves were calculated, from which pulse wave velocity was determined through cross-correlation analysis. Statistical Analysis Statistical analysis was performed in Graph Pad Prism (version 10.2.3; Graph Pad Software, Boston, MA). A Shapiro-Wilk test was used to determine normality. Normally distributed data are reported as means and SDs, and non-normal data are reported as medians and IQRs. For normally distributed data, an unpaired t-test with Welch’s correction was used for comparisons between controls and a subgroup of age-matched d-TGA patients, and between controls and the whole d-TGA cohort. For non-normal data, a Mann-Whitney test was used for between-group comparisons. Fisher’s exact test was used for comparison of sex, d-TGA type at birth, and location of maximum velocity in the pulmonary arteries between groups. Significance for all statistical analyses was defined as a P value less than 0.05. Results Study Cohort Forty-four d-TGA patients (mean age 15.3 years ± 4.9 [SD), age range 2.7 to 23.8 years; 9 [20.5%] female and 35 [79.5%] male patients) were included in this study. Twenty-five control patients (mean age 15.5 years ± 2.4 [SD], range 10.6 to 20.0 years; 14 [56.0%] female and 11 [44.0%] male patients) were age-matched to a subgroup of 25 d-TGA-ASO patients (mean age 15.7 years ± 2.4 [SD], age range 11.3 to 20.3 years; two [8.0%] female and 23 [92.0%] male patients) for paired comparisons. Quantification of pulse wave velocity, wall shear stress, and/or regional maximum velocity within the aorta failed for several patients (four d-TGA patients and three controls) due to errors in MATLAB that could not be resolved; when these patients were part of an age-matched pair, the entire pair was excluded from analysis (Online Resource 3 ). Baseline characteristics for the d-TGA groups compared with the control cohort are summarized in Table 1 . Average body surface area did not significantly differ between the d-TGA group and control group ( P = 0.19). The mean age difference between age-matched d-TGA and control pairs was 0.39 years ± 0.23 [SD]. Twelve (48%) of age-matched were also matched for sex (Online Resource 4 ). Of note, the arterial switch operation included the LeCompte maneuver for all patients within the d-TGA cohort. Four (9%) d-TGA patients underwent reintervention following 4D flow cardiac MRI, including two patients for pulmonary regurgitation and two patients for neo-aortic valve insufficiency with aortic root dilatation (Online Resource 5 ). Online Resource 6 displays averages and ranges for Z-scores of the aortic root, main pulmonary artery, right pulmonary artery, and left pulmonary artery diameters in d-TGA patients. The average Z-score for aortic root diameter was abnormally large at 3.61 ± 1.64 [SD]. The average Z-scores for main pulmonary artery (median − 2.02 [IQR, -2.44-(-1.15)]) and right pulmonary artery (median − 1.13 [IQR, -2.14-(-0.358)]) diameters were abnormally small. Table 1 Baseline characteristics of the control cohort compared with the whole cohort and age-matched sub-group of patients with dextro-transposition of the great arteries after the arterial switch operation Characteristic d-TGA-ASO Age-Matched Sub-Group (n = 25) d-TGA-ASO Whole Cohort (n = 44) Control Cohort (n = 25) Age (y) 15.7 ± 2.4 ( P = 0.8228) 15.3 ± 4.9 ( P = 0.8019) 15.5 ± 2.4 Sex: ( P = 0.006 ) ( P = 0.0037 ) Female 2 (8.0) 9 (20.5) 14 (56.0) Male 23 (92.0) 35 (79.5) 11 (44.0) Weight (kg) 65.8 ± 18.2 ( P = 0.3350) 65.8 ± 24.6 ( P = 0.9796) 61.0 ± 16.8 Height (cm) 168 ± 11.6 ( P = 0.1840) 161 ± 21.9 ( P = 0.7075) 163.0 ± 12.2 BSA (m 2 ) 1.74 ± 0.28 ( P = 0.1943) 1.63 ± 0.43 ( P = 0.8934) 1.64 ± 0.24 D-TGA type at birth: ---- D-TGA-IVS 18 (72.0) 29 (65.9) ---- D-TGA-VSD 4 (16.0) 8 (18.2) ---- D-TGA, type unknown 3 (12.0) 7 (15.9) ---- Baseline characteristics were compared between controls and an age-matched group of patients with d-TGA after the arterial switch operation (d-TGA-ASO), and between the control and whole d-TGA cohorts. For patient sex and d-TGA type at birth, the number of patients is provided for each characteristic with the percentage of the group in parentheses. P values of significance are shown in bold ( P < 0.05). BSA = body surface area (Mosteller formula), d-TGA-IVS = d-TGA with intact interventricular septum, d-TGA-VSD = d-TGA with ventricular septal defect, ASO = arterial switch operation, PA = main and branch pulmonary arteries Comparison of Pulmonary Arterial Hemodynamic Parameters Between d-TGA-ASO Patients and Controls Average values for all hemodynamic parameters quantified in the main and branch pulmonary arteries of d-TGA patients compared with controls are summarized in Table 2 . As shown in Fig. 3 , maximum and mean velocity, maximum and mean, and energy loss within the pulmonary arteries were significantly higher in the age-matched sub-group of d-TGA-ASO patients (N = 25) compared with controls (Fig. 3 b). The same pulmonary arterial flow parameters were significantly higher in the whole d-TGA cohort (N = 44) when compared to the control cohort (N = 25) (Fig. 3 c). The voxel with the highest maximum velocity was most commonly located in the right pulmonary artery for both d-TGA patients (34 patients, 77.3% of cohort) and controls (13 patients, 52.0% cohort) (Table 2 ). We found no evidence of differences in stasis in the pulmonary arteries between the d-TGA and control patients in either age-matched ( P = 0.4788) or whole-group ( P = 0.2143) comparisons. Table 2 4D flow hemodynamic parameters in the main and branch pulmonary arteries in patients with dextro-transposition of the great arteries after the arterial switch operation compared with controls Variable d-TGA-ASO Control P Value No. of patients Age-matched Whole cohort 25 44 25 25 ---- ---- V max Mean V max (m/s) Age-matched Whole cohort Location of V max MPA RPA LPA 1.68 [1.54–1.87] 1.63 [1.43–1.82] 5 (11.4) 34 (77.3) 5 (11.4) 0.873 [0.814–1.03] 0.873 [0.814–1.03] 9 (36.0) 13 (52.0) 3 (12.0) < 0.0001 < 0.0001 0.0497 Mean V mean (m/s) Age-matched Whole cohort 0.644 [0.5696–0.7058] 0.596 [0.5399–0.6964] 0.476 [0.423–0.569] 0.476 [0.423–0.569] < 0.0001 0.0001 Mean stasis (%) Age-matched Whole cohort 31.4 ± 10.1 32.7 ± 9.96 29.6 ± 9.78 29.6 ± 9.78 0.5206 0.2143 Mean KE max (µJ) Age-matched Whole cohort 5.24 [3.94–7.22] 4.53 [3.40–6.90] 1.75 [1.10–2.89] 1.75 [1.10–2.89] < 0.0001 < 0.0001 Mean KE mean (µJ) Age-matched Whole cohort 3.84 [3.20–5.79] 3.59 [2.62–5.65] 1.39 [8.89–2.38] 1.39 [8.89–2.38] < 0.0001 < 0.0001 Mean EL (µJ) Age-matched Whole cohort 0.374 [0.231–0.477] 0.290 [2.03–4.58]] 0.0527 [0.0294–0.0802] 0.0527 [0.0294–0.0802] < 0.0001 < 0.0001 Max WSS (N/m2) Age-matched Whole cohort 2.59 [2.24–3.19] 2.55 [2.09-3.00] 1.29 [1.04–1.45] 1.29 [1.04–1.45] < 0.0001 < 0.0001 Mean WSS (N/m 2 ) Age-matched Whole cohort 0.693 ± 0.130 0.675 ± 0.138 0.514 ± 0.0963 0.514 ± 0.0963 < 0.0001 < 0.0001 Hemodynamic parameters in the pulmonary arteries were compared between controls and an age-matched group of patients with d-TGA after arterial switch operation (d-TGA-ASO), and between the control and whole d-TGA-ASO cohort. For the location of Vmax, the number of patients is provided for each region with the percentage of the group in parentheses. V max = maximum velocity, MPA = main pulmonary artery, RPA = right pulmonary artery, LPA = left pulmonary artery, V mean = mean velocity, KE max = maximum kinetic energy, KE mean = mean kinetic energy, EL = energy loss, PWV = pulse wave velocity, WSS = wall shear stress. As shown in Fig. 4 b, maximum and mean wall shear stress were significantly higher in the age-matched sub-group of d-TGA patients compared to controls. Whole-group comparisons revealed similar findings, with significantly higher maximum and mean wall shear stress in the d-TGA cohort compared with controls (Fig. 4 c). Comparison of Aortic Hemodynamic Parameters Between d-TGA-ASO Patients and Controls Table 3 contains average values for all aortic flow parameters quantified for d-TGA patients compared with controls. Age-matched d-TGA patients (N = 25) had significantly higher maximum velocity in both the whole aorta and within all three regions of interest (ascending aorta, arch, and descending aorta) compared with controls. Mean velocity, maximum and mean kinetic energy, and energy loss were also significantly higher in the aorta of d-TGA patients compared with controls (Fig. 5 b). These parameters were also significantly higher in the whole d-TGA cohort (N = 44) when compared to the control cohort (N = 25), with the exception of mean velocity ( P = 0.1892). Stasis did not significantly differ between d-TGA patients and controls in either age-matched ( P = 0.2865) or whole-group ( P = 0.5086) comparisons. Table 3 Aortic velocity, stasis, kinetic energy, energy loss, and pulse wave velocity in patients with dextro-transposition of the great arteries after the arterial switch operation compared with controls Variable d-TGA-ASO Control P Value Mean V max (m/s) Whole aorta Age-matched Whole cohort AAo Age-matched Whole cohort Arch Age-matched Whole cohort DAo Age-matched Whole cohort 1.48 [1.37–1.67] 1.46 [1.28–1.63] 2.34 [1.91–3.29] 2.28 [1.83–2.77] 2.20 [1.59–2.63] 1.83 [1.37–2.44] 2.50 [1.93–3.17] 2.05 [1.75–2.99] 1.29 [1.15–1.44] 1.29 [1.15–1.44] 1.58 [1.35–2.08] 1.58 [1.35–2.08] 1.26 [1.06–1.54] 1.26 [1.06–1.54] 1.57 [1.34-2.00] 1.57 [1.34-2.00] 0.0011 0.0185 0.0001 0.0001 < 0.0001 < 0.0001 < 0.0001 0.0005 Mean V mean (m/s) Age-matched Whole cohort 0.757 ± 0.118 0.758 [0.631–0.805] 0.757 ± 0.118 0.683 [0.608–0.785] 0.0483 0.1892 Mean stasis (%) Age-matched Whole cohort 31.6 ± 12.4 32.9 ± 12.1 34.7 ± 9.82 34.7 ± 9.82 0.3324 0.5086 Mean KE max (µJ) Age-matched Whole cohort 6.37 [4.35–8.61] 5.92 [3.80–7.47] 3.20 [2.51–5.49] 3.20 [2.51–5.49] 0.0008 0.0235 Mean KE mean (µJ) Age-matched Whole cohort 4.84 [3.24–6.44] 4.57 [2.84–5.86] 2.66 [1.84–4.31] 2.66 [1.84–4.31] 0.0026 0.0394 Mean EL (µJ) Age-matched Whole cohort 0.136 [0.104–0.381] 0.127 [0.0731–0.269] 0.0778 [4.48–9.33] 0.0778 [4.48–9.33] < 0.0001 0.0010 PWV (m/s) Age-matched Whole cohort 4.50 [4.07–4.92] 4.34 [3.79–4.93] 4.57 [4.04–4.95] 4.57 [4.05-5.00] 0.7940 0.3771 Aortic hemodynamic parameters were compared between controls and an age-matched group of patients with d-TGA after arterial switch operation (d-TGA-ASO), between the control and whole d-TGA-ASO cohorts. V max = maximum velocity, V mean = mean velocity, AAo = ascending aorta, DAo = descending aorta, KE max = maximum kinetic energy, KE mean = mean kinetic energy, EL = energy loss, PWV = pulse wave velocity, WSS = wall shear stress, PWV = pulse wave velocity Maximum wall shear stress was significantly higher in age-matched d-TGA patients compared to controls in the anterior ascending aorta, inferior and superior aortic arch, and anterior and posterior descending aorta (Table 4 , Fig. 6 b-g). Whole-cohort comparisons revealed significantly higher maximum wall shear stress in the same regions as the age-matched comparison, with the exception of the anterior ascending aorta ( P = 0.0521). Compared to controls, mean wall shear stress was higher in both age-matched d-TGA patients (Fig. 6 b-g) and the whole d-TGA cohort in three regions of interest: superior aortic arch (age-matched: P = 0.0042), anterior descending aorta (age-matched: P = 0.0359), and posterior descending aorta ( P = 0.0210). Table 4 Regional aortic wall shear stress in patients with dextro-transposition of the great arteries after the arterial switch operation compared with controls Variable d-TGA-ASO Control P Value Max WSS (N/m 2 ): Posterior AAo Age-matched Whole cohort 1.44 ± 0.386 1.28 [1.09–1.55] 1.24 ± 0.248 1.24 [1.03–1.46] 0.0635 0.5478 Anterior AAo Age-matched Whole cohort 1.45 [1.38–1.72] 1.40 [1.17–1.56] 1.19 [1.08–1.43] 1.19 [1.08–1.43] 0.0020 0.0521 Inferior arch Age-matched Whole cohort 1.40 [1.18–1.52] 1.30 [1.09–1.50] 1.13 [0.944–1.33] 1.13 [0.944–1.33] 0.0022 0.0457 Superior arch Age-matched Whole cohort 1.40 [1.18–1.76] 1.28 [1.09–1.58] 0.107 [0.896–1.22] 0.107 [0.896–1.22] < 0.0001 0.0032 Anterior DAo Age-matched Whole cohort 1.64 ± 0.429 1.49 [1.26–1.77] 1.26 ± 0.273 1.28 [1.07–1.38] 0.0012 0.0032 Posterior DAo Age-matched Whole cohort 1.65 ± 0.417 1.61 ± 0.395 1.30 ± 0.241 1.30 ± 0.241 0.0015 0.0002 Mean WSS (N/m 2 ): Posterior AAo Age-matched Whole cohort 0.596 ± 0.103 0.576 ± 0.117 0.574 ± 0.118 0.574 ± 0.118 0.5177 0.9530 Anterior AAo Age-matched Whole cohort 0.696 ± 0.164 0.576 ± 0.117 0.646 ± 0.0991 0.646 ± 0.0991 0.2211 0.9530 Inferior arch Age-matched Whole cohort 0.853 [0.711–0.895] 0.776 ± 0.172 0.7935 [0.7133–0.8802] 0.811 ± 0.149 0.5376 0.4004 Superior arch Age-matched Whole cohort 0.729 ± 0.131 0.689 ± 0.134 0.620 ± 0.111 0.620 ± 0.111 0.0052 0.0330 Anterior DAo Age-matched Whole cohort 0.953 [0.842–1.02] 0.925 [0.793–0.990] 0.832 [0.697–0.916] 0.832 [0.697–0.916] 0.0307 0.0483 Posterior DAo Age-matched Whole cohort 1.02 [0.895-1.10] 0.974 [0.855–1.07] 0.863 [0.760–0.961] 0.863 [0.760–0.961] 0.0310 0.0174 Regional aortic wall shear stress (WSS) was compared between controls and a group of age-matched patients with d-TGA after arterial switch operation (d-TGA-ASO), and between the control and whole d-TGA-ASO cohorts. AAo = ascending aorta, DAo = descending aorta We found no difference between d-TGA patients and controls in pulse wave velocity in either age-matched (4.50 m/s [4.07–4.92] vs. 4.57 m/s [4.04–4.95]; P = 0.7314) or whole-group (4.34 m/s [3.79–4.93] vs. 4.57 m/s [4.05-5.00], P = 0.3771) comparisons (Table 3 ). Discussion Our aim was to provide a comprehensive evaluation of pulmonary arterial and aortic hemodynamics in patients with d-TGA after the arterial switch operation. We compared eight hemodynamic parameters within the pulmonary arteries and nine within the aorta between control patients with normal cardiac anatomy (N = 25) and both a whole cohort (N = 44) and age-matched sub-group (N = 25) of patients with d-TGA after the arterial switch operation to identify hemodynamic abnormalities in this patient population. Our main finding is that patients with d-TGA after the arterial switch operation demonstrate abnormal pulmonary artery and aortic velocity, kinetic energy, energy loss, and wall shear stress, suggesting the potential utility of these 4D flow parameters for clarifying the pathophysiology underlying complications of the arterial switch operation and for predicting the need for pulmonary arterial or aortic reintervention. In the main and branch pulmonary arteries, we found maximum velocity was significantly higher in patients with d-TGA after the arterial switch operation than in age-matched controls, consistent with findings from Geiger et al. Even among d-TGA patients with normal Z-scores for main and branch pulmonary artery diameters, we found higher maximum velocities in the pulmonary arteries compared with the average value among controls. Geiger et al. similarly noted that maximum velocities were elevated in patients with d-TGA after the arterial switch operation without apparent MPA stenosis. They therefore propose elevated maximum velocity in patients with d-TGA after the arterial switch operation could be caused by transient compression of the branch pulmonary arteries by the ascending aorta during systole, due to the position of the pulmonary arteries posterior to the sternum and anterior to the ascending aorta after the LeCompte maneuver. In addition, our study found higher mean systolic velocity within the pulmonary arteries of d-TGA patients, which could also be explained by systolic compression by the ascending aorta. Aortic maximum velocity was significantly higher in d-TGA patients compared with age-matched controls when quantified over the entire aorta as well as each region individually. These findings differ from those of Geiger et al., possibly because our quantification was performed over entire 3D volumes and not 2D planes. In our study, mean aortic velocity was also significantly higher in age-matched d-TGA patients compared with controls, but whole cohort comparisons did not show evidence of a difference in mean velocity ( P = 0.1892). Similarly, Sotelo et al. did not find evidence of a difference in mean velocity within any region of the aortic root when comparing patients with d-TGA after the arterial switch operation with unmatched controls. Mechanical energetics were also abnormal in the main and branch pulmonary arteries of d-TGA patients, with elevated maximum and mean kinetic energy and energy loss ( P < 0.0001 for all) compared with age-matched controls. These findings suggest inefficient pulmonary arterial flow following the arterial switch operation and thus increased right ventricular workload. This could explain why right ventricular performance has been shown to be impaired in d-TGA patients at postoperative follow-up [ 29 ]. In three regions of the aortic root, Sotelo et al. found no significant difference in mean kinetic energy or energy loss between patients with d-TGA after the arterial switch operation and unmatched controls. However, when quantifying these parameters over the entire aorta, we found significantly higher maximum kinetic energy, mean kinetic energy, and energy loss in d-TGA patients compared with age-matched controls. Together, our findings could indicate that elevated kinetic energy and energy loss only occurs distal to the aortic root, which might be explained by increasingly abnormal flow patterns as aortic diameter acutely decreases distal to the neoaortic root. In patients with d-TGA after the arterial switch operation, the pathogenesis of neoaortic root dilatation remains unknown, but contributing factors might include the systemic pressure load on native pulmonary artery tissue [ 30 ], or loss of aortic distensibility due to scarring following coronary button transfer [ 10 ]. Although many d-TGA patients in our cohort demonstrated neoaortic dilatation, pulse wave velocity did not significantly differ between d-TGA patients and age-matched controls ( P = 0.7314). This could be explained by the younger age of our patient cohort (mean age 15.3 years ± 4.9 [SD]), as pulse wave velocity is known to increase with age [ 31 ]. Using 2D cine phase-contrast with through-plane velocity encoding, Voges et al. also found no evidence of a difference in pulse wave velocity between patients with d-TGA after the arterial switch operation under 18 years old and age-matched controls, but did find higher pulse wave velocity in adult compared with younger patients with d-TGA after the arterial switch operation [ 32 ]. Wall shear stress is known to contribute to the development of many vascular pathologies through its effects on endothelial function [ 11 , 33 ], and may offer insight into the relationship between hemodynamics and the pathogenesis of aortic and pulmonary arterial complications of the arterial switch operation. Patients with pulmonary arterial hypertension have been shown to have lower wall shear stress in the pulmonary arteries, which is believed to induce vascular remodeling that causes main pulmonary artery dilation and wall thickening [ 34 ]. Here, we found significantly higher maximum and mean wall shear stress between d-TGA patients and age-matched controls. From these findings, we hypothesize flow abnormalities within the main and branch pulmonary arteries result in elevated wall shear stress, which induces remodeling that leads to pulmonary artery stenosis. Prior studies comparing aortic wall shear stress between patients with d-TGA after the arterial switch operation and controls have found elevated maximum and mean wall shear stress in regions of the neoaortic root and ascending aorta of patients with d-TGA after the arterial switch operation [ 11 , 12 ]. In our volumetric quantification of wall shear stress, we also found significantly higher maximum wall shear stress within the anterior ascending aorta of d-TGA patients compared to age-matched controls, but did not find evidence of a difference in mean wall shear stress in the ascending aorta, as described by Sotelo et al. Importantly, although Sotelo et al. also quantified wall shear stress using the 3D volumes of each region, their regional definitions differed. They report a significant difference in mean 3D wall shear stress only within the right anterior region of the ascending aorta before decomposing the WSS vector field into its axial and circumferential components [ 11 ]. Therefore, the difference in our results may be attributed to our inclusion of both the right and left sides of the anterior ascending aorta, as well as the incorporation of the aortic root within this region. Sotelo et al. propose that elevated wall shear stress in the ascending aorta may be explained by a more acute aortic arch curvature in patients who undergo the arterial switch operation with the LeCompte maneuver compared with controls, as circumferential wall shear stress is highly correlated with arch curvature [ 11 ]. Van der Palen et al. (2020) also found a correlation in patients with d-TGA after the arterial switch operation between wall shear stress and vessel geometry, specifically change in aortic diameter from the root to the mid-ascending aorta, and therefore suggest elevated wall shear stress is due to flow displacement and higher near-wall velocity gradient in this caliber change [ 12 ]. Although we did not investigate the relationship between aortic geometry and wall shear stress, our study also quantified wall shear stress within the aortic arch and descending aorta and found higher maximum and mean wall shear stress in these regions in d-TGA patients compared with controls. Elevated wall shear stress in the aortic arch and descending aorta may also be explained by flow aberrancies due to acute arch curvature, coupled by caliber change from the aortic root to more distal parts of the aorta. Limitations First, since aortic velocity decreases with age until middle adulthood [ 35 ], unmatched (whole cohort) comparisons could overestimate differences in velocity between patients with d-TGA after the arterial switch operation and controls due to the younger age of the d-TGA cohort. However, the agreement between whole cohort and age-matched comparisons for the majority of parameters suggests age differences had little effect. Our control group also featured a significantly higher proportion of female participants. Although no significant differences in maximum velocity and 3D wall shear stress in the aorta have been found between biological males and females [ 36 ], comparative data for pulmonary arterial hemodynamics is unavailable, and kinetic energy has shown to be higher in the left ventricles of males, which could affect great arterial blood flow to some degree [ 37 ]. Lastly, since only four patients in our d-TGA cohort underwent reintervention, two involving the aorta and two on the pulmonary arteries, we could not compare hemodynamic parameters between d-TGA patients who ultimately required reintervention and those who did not. Additional studies will be necessary to investigate the association between outcomes and abnormalities in these hemodynamic parameters in patient with d-TGA after the arterial switch operation. Conclusions In conclusion, our comprehensive great artery hemodynamic assessment demonstrates abnormalities in seven of nine hemodynamic parameters quantified within the aorta and/or pulmonary arteries of patients with d-TGA after the arterial switch operation. In the pulmonary arteries, in addition to finding further evidence of increased velocity, we also found evidence of increased kinetic energy, energy loss, and wall shear stress. In the aorta, we found additional evidence of increased wall shear stress in the ascending aorta, as well as evidence of increased velocity, kinetic energy, and energy loss; and increased wall shear stress in the aortic arch and descending aorta. These 4D flow parameters may serve as useful tools for further investigating the mechanisms underlying postoperative artery stenosis and aortic dilatation and insufficiency, and for predicting which patients will require reintervention. Declarations Author Contribution K.C. reviewed existing literature, contributed to study design, assembled the cohort of d-TGA patients from a hospital database, collected data (segmentation step in Mimics, quantification in MATLAB), ran statistical analysis, prepared figures, and wrote the main manuscript text.A.S. collected data (retrieval of 4D flow data in Conquest, pre-processing through Velomap and SuperTool), assisted with statistical analysis, contributed to study design, helped to troubleshoot issues, and provided guidance for each step in the project.E.J. wrote the code for pre-processing and quantification in MATLAB, did troubleshooting to resolve errors in MATLAB, assisted with statistical analysis, contributed to study design, and provided guidance for each step in the project.J.R. and M.M. contributed to study design and provided guidance for each step in the project; they reviewed data and assisted with statistical analysis.C.R. was Principal Investigator for the study; led study design, provided guidance for each step in the project, and helped to troubleshoot issues.All authors reviewed the manuscript. Data Availability The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to data sets containing information that could compromise research participant privacy/consent. References Morfaw F, Leenus A, Mbuagbaw L, Anderson LN, Dillenburg R, Thabane L (2020) Outcomes after corrective surgery for congenital dextro-transposition of the arteries using the arterial switch technique: a scoping systematic review. Syst Rev 2020, 9(1):231.10.1186/s13643-020-01487-3 Sobczak-Budlewska K, Lubisz M, Moll M, Moszura T, Moll JA, Korabiewska-Pluta S, Moll JJ, Michalak KW (2023) 30 years' experience with the arterial switch operation: risk of pulmonary stenosis and its impact on post-operative prognosis. Cardiol Young 2023, 33(9):1550-1555.10.1017/S1047951122002670 Co-Vu JG, Ginde S, Bartz PJ, Frommelt PC, Tweddell JS, Earing MG (2013) Long-term outcomes of the neoaorta after arterial switch operation for transposition of the great arteries. Ann Thorac Surg 2013, 95(5):1654-1659.10.1016/j.athoracsur.2012.10.081 Kirzner J, Pirmohamed A, Ginns J, Singh HS (2018) Long-term Management of the Arterial Switch Patient. Curr Cardiol Rep 2018, 20(8):68.10.1007/s11886-018-1012-9 Khairy P, Clair M, Fernandes SM, Blume ED, Powell AJ, Newburger JW, Landzberg MJ, Mayer JE, Jr. (2013) Cardiovascular outcomes after the arterial switch operation for D-transposition of the great arteries. Circulation 2013, 127(3):331-339.10.1161/CIRCULATIONAHA.112.135046 Zhu MZL, Fricke TA, Buratto E, Chowdhuri KR, Brizard CP, Konstantinov IE (2024) Outcomes of neo-aortic valve and root surgery late after arterial switch operation. J Thorac Cardiovasc Surg 2024, 167(4):1391-1401 e1393.10.1016/j.jtcvs.2023.09.038 Jarvis K, Vonder M, Barker AJ, Schnell S, Rose M, Carr J, Robinson JD, Markl M, Rigsby CK (2016) Hemodynamic evaluation in patients with transposition of the great arteries after the arterial switch operation: 4D flow and 2D phase contrast cardiovascular magnetic resonance compared with Doppler echocardiography. J Cardiovasc Magn Reson 2016, 18(1):59.10.1186/s12968-016-0276-8 Cohen MS, Eidem BW, Cetta F, Fogel MA, Frommelt PC, Ganame J, Han BK, Kimball TR, Johnson RK, Mertens L et al (2016) Multimodality Imaging Guidelines of Patients with Transposition of the Great Arteries: A Report from the American Society of Echocardiography Developed in Collaboration with the Society for Cardiovascular Magnetic Resonance and the Society of Cardiovascular Computed Tomography. J Am Soc Echocardiogr 2016, 29(7):571-621.10.1016/j.echo.2016.04.002 Gutberlet M, Boeckel T, Hosten N, Vogel M, Kuhne T, Oellinger H, Ehrenstein T, Venz S, Hetzer R, Bein G et al (2000) Arterial switch procedure for D-transposition of the great arteries: quantitative midterm evaluation of hemodynamic changes with cine MR imaging and phase-shift velocity mapping-initial experience. Radiology 2000, 214(2):467-475.10.1148/radiology.214.2.r00fe45467 Geiger J, Hirtler D, Burk J, Stiller B, Arnold R, Jung B, Langer M, Markl M (2014) Postoperative pulmonary and aortic 3D haemodynamics in patients after repair of transposition of the great arteries. Eur Radiol 2014, 24(1):200-208.10.1007/s00330-013-2998-4 Sotelo J, Valverde I, Martins D, Bonnet D, Boddaert N, Pushparajan K, Uribe S, Raimondi F (2022) Impact of aortic arch curvature in flow haemodynamics in patients with transposition of the great arteries after arterial switch operation. Eur Heart J Cardiovasc Imaging 2022, 23(3):402-411.10.1093/ehjci/jeaa416 van der Palen RLF, Deurvorst QS, Kroft LJM, van den Boogaard PJ, Hazekamp MG, Blom NA, Lamb HJ, Westenberg JJM, Roest AAW (2020) Altered Ascending Aorta Hemodynamics in Patients After Arterial Switch Operation for Transposition of the Great Arteries. J Magn Reson Imaging 2020, 51(4):1105-1116.10.1002/jmri.26934 van der Palen RLF, Juffermans JF, Kroft LJM, Hazekamp MG, Lamb HJ, Blom NA, Roest AAW, Westenberg JJM (2021) Wall shear stress in the thoracic aorta at rest and with dobutamine stress after arterial switch operation. Eur J Cardiothorac Surg 2021, 59(4):814-822.10.1093/ejcts/ezaa392 Callaghan FM, Burkhardt B, Valsangiacomo Buechel ER, Kellenberger CJ, Geiger J (2021) Assessment of ventricular flow dynamics by 4D-flow MRI in patients following surgical repair of d-transposition of the great arteries. Eur Radiol 2021, 31(10):7231-7241.10.1007/s00330-021-07813-0 Belhadjer Z, Soulat G, Ladouceur M, Pitocco F, Legendre A, Bonnet D, Iserin L, Mousseaux E (2020) Neopulmonary Outflow Tract Obstruction Assessment by 4D Flow MRI in Adults With Transposition of the Great Arteries After Arterial Switch Operation. J Magn Reson Imaging 2020, 51(6):1699-1705.10.1002/jmri.27012 Falahatpisheh A, Rickers C, Gabbert D, Heng EL, Stalder A, Kramer HH, Kilner PJ, Kheradvar A (2016) Simplified Bernoulli's method significantly underestimates pulmonary transvalvular pressure drop. J Magn Reson Imaging 2016, 43(6):1313-1319.10.1002/jmri.25097 Shiina Y, Inai K, Nagao M (2021) Non-physiological Aortic Flow and Aortopathy in Adult Patients with Transposition of the Great Arteries after the Jatene Procedure: A Pilot Study Using Echo Planar 4D Flow MRI. Magn Reson Med Sci 2021, 20(4):439-449.10.2463/mrms.mp.2020-0101 Warmerdam EG, Westenberg JJM, Voskuil M, Rijnberg FM, Roest AAW, Lamb HJ, van Wijk B, Sieswerda GT, Doevendans PA, Ter Heide H et al (2023) Comparison of Four-Dimensional Flow MRI, Two-Dimensional Phase-Contrast MRI and Echocardiography in Transposition of the Great Arteries. Pediatr Cardiol 2023.10.1007/s00246-023-03238-2 Rickers C, Kheradvar A, Sievers HH, Falahatpisheh A, Wegner P, Gabbert D, Jerosch-Herold M, Hart C, Voges I, Putman LM et al (2016) Is the Lecompte technique the last word on transposition of the great arteries repair for all patients? A magnetic resonance imaging study including a spiral technique two decades postoperatively. Interact Cardiovasc Thorac Surg 2016, 22(6):817-825.10.1093/icvts/ivw014 Potters WV, van Ooij P, Marquering H, vanBavel E, Nederveen AJ (2015) Volumetric arterial wall shear stress calculation based on cine phase contrast MRI. J Magn Reson Imaging 2015, 41(2):505-516.10.1002/jmri.24560 Dyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhall CJ, Ebbers T, Francios CJ, Frydrychowicz A, Geiger J, Giese D et al (2015) 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson 2015, 17(1):72.10.1186/s12968-015-0174-5 Rijnberg FM, Westenberg JJM, van Assen HC, Juffermans JF, Kroft LJM, van den Boogaard PJ, Terol Espinosa de Los Monteros C, Warmerdam EG, Leiner T, Grotenhuis HB et al (2022) 4D flow cardiovascular magnetic resonance derived energetics in the Fontan circulation correlate with exercise capacity and CMR-derived liver fibrosis/congestion. J Cardiovasc Magn Reson 2022, 24(1):21.10.1186/s12968-022-00854-4 Elbaz MS, van der Geest RJ, Calkoen EE, de Roos A, Lelieveldt BP, Roest AA, Westenberg JJ (2017) Assessment of viscous energy loss and the association with three-dimensional vortex ring formation in left ventricular inflow: In vivo evaluation using four-dimensional flow MRI. Magn Reson Med 2017, 77(2):794-805.10.1002/mrm.26129 Sluysmans TC, S. D.: Structural measurements and adjustment for growth. In: Echocardiography in Pediatric and Congenital Heart Disease. Edited by Lai WWM, S. C.; Geva, T.; Mertens, L. L., 1st edn. West Sussex, UK: WIley-Blackwell; 2009. Colan SD: Normal echocardiographic values for cardiovascular structures. In: Echocardiography in Pediatric and Congenital Heart Disease. Edited by Lai WWM, S. C.; Geva, T.; Mertens, L. L., 1st edn. West Sussex, UK: Wiley-Blackwell; 2009: 765-785. Markl M, Harloff A, Bley TA, Zaitsev M, Jung B, Weigang E, Langer M, Hennig J, Frydrychowicz A (2007) Time-resolved 3D MR velocity mapping at 3T: improved navigator-gated assessment of vascular anatomy and blood flow. J Magn Reson Imaging 2007, 25(4):824-831.10.1002/jmri.20871 Jarvis K, Pruijssen JT, Son AY, Allen BD, Soulat G, Vali A, Barker AJ, Hoel AW, Eskandari MK, Malaisrie SC et al (2020) Parametric Hemodynamic 4D Flow MRI Maps for the Characterization of Chronic Thoracic Descending Aortic Dissection. J Magn Reson Imaging 2020, 51(5):1357-1368.10.1002/jmri.26986 Jarvis K, Soulat G, Scott M, Vali A, Pathrose A, Syed AA, Kinno M, Prabhakaran S, Collins JD, Markl M (2021) Investigation of Aortic Wall Thickness, Stiffness and Flow Reversal in Patients With Cryptogenic Stroke: A 4D Flow MRI Study. J Magn Reson Imaging 2021, 53(3):942-952.10.1002/jmri.27345 Klitsie LM, Roest AA, Kuipers IM, Hazekamp MG, Blom NA, Ten Harkel AD (2014) Left and right ventricular performance after arterial switch operation. J Thorac Cardiovasc Surg 2014, 147(5):1561-1567.10.1016/j.jtcvs.2013.07.048 Pees C, Laufer G, Michel-Behnke I (2013) Similarities and differences of the aortic root after arterial switch and ross operation in children. Am J Cardiol 2013, 111(1):125-130.10.1016/j.amjcard.2012.08.059 Diaz A, Galli C, Tringler M, Ramirez A, Cabrera Fischer EI (2014) Reference values of pulse wave velocity in healthy people from an urban and rural argentinean population. Int J Hypertens 2014, 2014:653239.10.1155/2014/653239 Voges I, Jerosch-Herold M, Hedderich J, Hart C, Petko C, Scheewe J, Andrade AC, Pham M, Gabbert D, Kramer HH et al (2013) Implications of early aortic stiffening in patients with transposition of the great arteries after arterial switch operation. Circ Cardiovasc Imaging 2013, 6(2):245-253.10.1161/CIRCIMAGING.112.000131 Zhang J, Rothenberger SM, Brindise MC, Markl M, Rayz VL, Vlachos PP (2022) Wall Shear Stress Estimation for 4D Flow MRI Using Navier-Stokes Equation Correction. Ann Biomed Eng 2022, 50(12):1810-1825.10.1007/s10439-022-02993-2 Schafer M, Kheyfets VO, Schroeder JD, Dunning J, Shandas R, Buckner JK, Browning J, Hertzberg J, Hunter KS, Fenster BE (2016) Main pulmonary arterial wall shear stress correlates with invasive hemodynamics and stiffness in pulmonary hypertension. Pulm Circ 2016, 6(1):37-45.10.1086/685024 Garcia J, van der Palen RLF, Bollache E, Jarvis K, Rose MJ, Barker AJ, Collins JD, Carr JC, Robinson J, Rigsby CK et al (2018) Distribution of blood flow velocity in the normal aorta: Effect of age and gender. J Magn Reson Imaging 2018, 47(2):487-498.10.1002/jmri.25773 Scott MB, Huh H, van Ooij P, Chen V, Herrera B, Elbaz M, McCarthy P, Malaisrie SC, Carr J, Fedak PWM et al (2020) Impact of age, sex, and global function on normal aortic hemodynamics. Magn Reson Med 2020, 84(4):2088-2102.10.1002/mrm.28250 Rutkowski DR, Barton GP, Francois CJ, Aggarwal N, Roldan-Alzate A (2020) Sex Differences in Cardiac Flow Dynamics of Healthy Volunteers. Radiol Cardiothorac Imaging 2020, 2(1).10.1148/ryct.2020190058 Additional Declarations No competing interests reported. Supplementary Files supplemental2.docx Cite Share Download PDF Status: Published Journal Publication published 20 Dec, 2024 Read the published version in Pediatric Radiology → Version 1 posted Editorial decision: Revision requested 29 Oct, 2024 Reviews received at journal 13 Oct, 2024 Reviews received at journal 01 Oct, 2024 Reviewers agreed at journal 30 Sep, 2024 Reviewers agreed at journal 25 Sep, 2024 Reviewers agreed at journal 23 Sep, 2024 Reviewers invited by journal 23 Sep, 2024 Editor assigned by journal 23 Sep, 2024 Submission checks completed at journal 23 Sep, 2024 First submitted to journal 22 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5133875","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":371814131,"identity":"3f2b0525-e113-424e-8868-0ce4edf6c48a","order_by":0,"name":"Kylie Calderon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYBACCQYGxsd/KphBDAYGHiK1MBvwnCFRC5sEbxspWiTbmx8bSM6zTpzZ3sD44G0bEVqkeY4ZPjDclp44m+cAs+FcYrTISeQwGyRuO5w4TyKBTZqXKC3yb9gkDs4BapF/wP6bKC3SEjxsko0NhxNnSzCwMROlRbInzdiY4Vi68cyexGbJOeeI0CJx/PDDxww11rIzjh8++OFNGRFakABjA2nqR8EoGAWjYBTgBgDjEjKt4CTlfAAAAABJRU5ErkJggg==","orcid":"","institution":"Duke University","correspondingAuthor":true,"prefix":"","firstName":"Kylie","middleName":"","lastName":"Calderon","suffix":""},{"id":371814132,"identity":"d7fbfd09-ed7a-4a94-9bd1-d09859df772f","order_by":1,"name":"Aparna Sodhi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Aparna","middleName":"","lastName":"Sodhi","suffix":""},{"id":371814134,"identity":"6b8d8aa2-bb5b-4bce-8602-f97e76d880e6","order_by":2,"name":"Ethan M.I. Johnson","email":"","orcid":"","institution":"Northwestern University","correspondingAuthor":false,"prefix":"","firstName":"Ethan","middleName":"M.I.","lastName":"Johnson","suffix":""},{"id":371814135,"identity":"d6ab5498-f444-4653-b7d2-8767cb07b0a4","order_by":3,"name":"Michael Markl","email":"","orcid":"","institution":"Northwestern University","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Markl","suffix":""},{"id":371814136,"identity":"d05c7e1c-d5e8-417c-8ba8-075f00b19413","order_by":4,"name":"Joshua D. Robinson","email":"","orcid":"","institution":"Lurie Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"D.","lastName":"Robinson","suffix":""},{"id":371814138,"identity":"4ff4912b-7f85-41b5-af4c-e4237e82eb6a","order_by":5,"name":"Cynthia K. Rigsby","email":"","orcid":"","institution":"Lurie Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cynthia","middleName":"K.","lastName":"Rigsby","suffix":""}],"badges":[],"createdAt":"2024-09-22 20:21:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5133875/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5133875/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00247-024-06110-4","type":"published","date":"2024-12-20T15:57:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69058350,"identity":"33fb17f5-d3a9-4179-88ee-bc251d16c795","added_by":"auto","created_at":"2024-11-15 06:57:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2372053,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for selection of cohort of patients with d-TGA after the arterial switch operation. Patients with additional cardiac lesions at birth were excluded (“Not isolated d-TGA”), except for those with ventricular and/or atrial septal defect. Patients who had undergone intervention(s) in addition to the arterial switch operation were also excluded, except for those with history of balloon atrial septostomy. L-TGA = levo-transposition of the great arteries, TOF = tetralogy of Fallot, s/p = status post, ASO = arterial switch operation, OSH = outside hospital, CS-4D = compressed sensing 4D flow study\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/0c38d5300d499e523615a3e6.png"},{"id":69057328,"identity":"053b1643-5d2d-4aa9-a186-dd18b31a0aa7","added_by":"auto","created_at":"2024-11-15 06:49:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13798401,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of workflow for pre- and post-processing of 4D flow data. Four time-resolved 4D flow data sets (one magnitude dataset and three flow data sets representing 3D velocity) underwent preprocessing, including phase correction, noise masking, and velocity anti-aliasing. A mean sum square phase contrast magnetic resonance angiogram (PCMRA) was then generated and used to manually segment the aorta and pulmonary arteries. These segmentations were used in this study for quantification of the parameters shown, in addition to mean velocity and maximum kinetic energy. Example images shown are from a cardiac MRI (sagittal plane) in a control patient with normal cardiac anatomy (female, age 15.3 years years). PCMRA = phase contrast magnetic resonance angiogram, PWV = pulse wave velocity, ROI = region of interest, WSS = wall shear stress, V\u003csub\u003emax\u003c/sub\u003e = maximum velocity, KE\u003csub\u003emean\u003c/sub\u003e = mean kinetic energy, EL = energy loss\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/d67651df75017f87b024a460.png"},{"id":69057324,"identity":"857880eb-c76f-42c0-9cab-260c6b6a67e7","added_by":"auto","created_at":"2024-11-15 06:49:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2117362,"visible":true,"origin":"","legend":"\u003cp\u003eVelocity, stasis, kinetic energy (KE), and energy loss (EL) within the pulmonary arteries of patients with dextro-transposition of the great arteries (d-TGA) after arterial switch operation (ASO) compared with control patients. (\u003cstrong\u003ea\u003c/strong\u003e) Example quantitative maps (generated from cardiac MRI, sagittal plane) for each parameter in a control patient (male, age 16.2 years, gadobutrol) compared with an age-matched d-TGA-ASO patient (male, age 16.5 years, non-contrast); the main pulmonary artery (MPA), right pulmonary artery (RPA), and left pulmonary artery (LPA) are labeled in the first image. Comparisons of maximum and mean velocity, stasis, maximum and mean KE, and EL in the pulmonary arteries (\u003cstrong\u003eb\u003c/strong\u003e) between controls and age-matched d-TGA-ASO patients, and (\u003cstrong\u003ec\u003c/strong\u003e) between the control and whole d-TGA-ASO cohorts. Box borders represent the 25\u003csup\u003eth\u003c/sup\u003e and 75\u003csup\u003eth\u003c/sup\u003e percentiles, midlines represent the median, and whiskers represent the minimum and maximum values. D-TGA-ASO = d-transposition of the great arteries after the arterial switch operation, V\u003csub\u003emax\u003c/sub\u003e = maximum velocity, V\u003csub\u003emean\u003c/sub\u003e = mean velocity, KE\u003csub\u003emax\u003c/sub\u003e = maximum kinetic energy, and KE\u003csub\u003emean \u003c/sub\u003e= mean kinetic energy\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/075da532e34eeba4c2807b8a.png"},{"id":69057326,"identity":"fa56c7e4-6615-4b66-b8f0-08e67a258adb","added_by":"auto","created_at":"2024-11-15 06:49:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":10494706,"visible":true,"origin":"","legend":"\u003cp\u003eWall shear stress (WSS) within the pulmonary arteries of patients with dextro-transposition of the great arteries after arterial switch operation (d-TGA-ASO) compared with control patients.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003ea\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eExample of WSS pathlines, 3D maps for WSS maximum intensity projection (MIP), and WSS histograms over the course of a cardiac cycle for a d-TGA-ASO patient (male, age 16.5 years) compared with a control patient (male, age 16.2 years); the main pulmonary artery (MPA), right pulmonary artery (RPA), and left pulmonary artery (LPA) are labeled. Comparisons of maximum and mean WSS in the pulmonary arteries (\u003cstrong\u003eb\u003c/strong\u003e) between controls and age-matched d-TGA-ASO patients, and (\u003cstrong\u003ec\u003c/strong\u003e) between the control and whole d-TGA-ASO cohorts. Box borders represent the 25\u003csup\u003eth\u003c/sup\u003e and 75\u003csup\u003eth\u003c/sup\u003e percentiles, midlines represent the median, and whiskers represent the minimum and maximum values. D-TGA-ASO = d-transposition of the great arteries after the arterial switch operation, MPA = main pulmonary artery, RPA = right pulmonary artery, LPA = left pulmonary artery, WSS = wall shear stress, MIP = maximum intensity projection\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/4bc76ff5bcc8cbb5adf9f100.png"},{"id":69057330,"identity":"a0823ded-ec0c-4cb0-8ec2-f14abcee89a7","added_by":"auto","created_at":"2024-11-15 06:49:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":14434803,"visible":true,"origin":"","legend":"\u003cp\u003eAortic velocity, stasis, kinetic energy (KE), and energy loss (EL) in patients with dextro-transposition of the great arteries (d-TGA) after arterial switch operation (ASO) compared with control patients.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003ea\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eExample quantitative maps (generated from cardiac MRI, sagittal plane) for each parameter in a control patient (male, age 16.2 years, gadobutrol) compared with an age-matched d-TGA-ASO patient (male, age 16.5 years, non-contrast); the ascending aorta (AAo), aortic arch (arch), and descending aorta (DAo). Comparisons of aortic maximum and mean velocity, stasis, maximum and mean kinetic energy (KE), and energy loss (EL) (\u003cstrong\u003eb\u003c/strong\u003e) between controls and age-matched d-TGA-ASO patients, and (\u003cstrong\u003ec\u003c/strong\u003e) between the control and whole d-TGA-ASO cohorts. Box borders represent the 25\u003csup\u003eth\u003c/sup\u003e and 27\u003csup\u003eth\u003c/sup\u003e percentiles, midlines represent the median, and whiskers represent the minimum and maximum values. V\u003csub\u003emax\u003c/sub\u003e = maximum velocity, V\u003csub\u003emean\u003c/sub\u003e = mean velocity, KE\u003csub\u003emax\u003c/sub\u003e = maximum kinetic energy, KE\u003csub\u003emean \u003c/sub\u003e= mean kinetic energy, EL = energy loss\u0026nbsp;\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/8483e849514e15142114c317.png"},{"id":69057331,"identity":"c5151c52-f20f-46e7-867f-acd20fe1d025","added_by":"auto","created_at":"2024-11-15 06:49:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":13043580,"visible":true,"origin":"","legend":"\u003cp\u003eAortic wall shear stress (WSS) in patients with dextro-transposition of the great arteries after arterial switch operation (d-TGA-ASO) compared with control patients. (\u003cstrong\u003ea\u003c/strong\u003e) Example of WSS pathlines, 3D maps for WSS maximum intensity projection (MIP), and WSS histograms over the course of a cardiac cycle for a d-TGA-ASO patient (male, age 16.5 years) compared with a control patient (male, age 16.2 years); the ascending aorta (AAo), aortic arch (arch), and descending aorta (DAo) are labeled. (\u003cstrong\u003eb-g\u003c/strong\u003e) Comparisons of maximum and mean WSS in six regions of the aorta between controls and age-matched d-TGA-ASO patients. Box borders represent the 25\u003csup\u003eth\u003c/sup\u003e and 27\u003csup\u003eth\u003c/sup\u003e percentiles, midlines represent the median, and whiskers represent the minimum and maximum values\u0026nbsp;\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/45d19773dfc8b9e04a10de3a.png"},{"id":72202749,"identity":"8cb1cea1-b9cc-4e01-9223-5e57c732877b","added_by":"auto","created_at":"2024-12-23 16:16:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":54493809,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/c62a1271-2f56-49b9-bd58-c902a163297f.pdf"},{"id":69057325,"identity":"701448c4-c6c9-4458-9ec1-6c45c8d98d9e","added_by":"auto","created_at":"2024-11-15 06:49:39","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":161799,"visible":true,"origin":"","legend":"","description":"","filename":"supplemental2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5133875/v1/15e2a2dcd87f4453f336710b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hemodynamic evaluation of the pulmonary arteries and aorta using 4D flow cardiac MRI in children and young adults with dextro-transposition of the great arteries after the arterial switch operation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eComplications following the arterial switch operation for repair of dextro-transposition of the great arteries (d-TGA) include pulmonary artery stenosis, progressive neoaortic root dilatation, and neo-aortic valve insufficiency [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although reintervention rates decreased after introduction of the LeCompte maneuver [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], pulmonary artery stenosis, either supravalvular or involving the right or left branch pulmonary arteries, remains the most common indication for reintervention [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Neoaortic root dilatation and valve insufficiency may require reintervention for aortic valve and/or neo-aortic root replacement, often late in follow-up [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStandard tools for postoperative evaluation and monitoring of patients after the arterial switch operation include Doppler echocardiography and cardiac MRI including 2D phase contrast imaging [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although widely available and inexpensive, echocardiography is limited by acoustic windows, which can be challenging due to somatic growth [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and the position of the pulmonary arteries posterior to the sternum after the LeCompte maneuver [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Echocardiography therefore has limited sensitivity for branch pulmonary artery stenosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Cardiac MRI allows for better branch pulmonary artery visualization following the arterial switch operation but relies on an operator-defined 2D imaging plane with unidirectional velocity encoding and does not provide full volumetric great artery coverage [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThree-dimensional cine (time-resolved) phase contrast cardiac MRI with three-directional velocity encoding (4D flow MRI) offers more comprehensive great artery evaluation and could thereby allow for improved great artery monitoring in d-TGA after arterial switch operation. Prior studies have used 4D flow MRI to assess hemodynamics in patients with d-TGA after the arterial switch operation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and found abnormalities in systolic flow displacement [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]; wall shear stress [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], a measure of the force exerted on a vessel wall due to blood flow [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; oscillatory shear index [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]; viscous dissipation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]; helical density [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]; and regurgitant fraction [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] in the aorta. However, prior studies have been limited by small cohorts of controls and/or patients with d-TGA after the arterial switch operation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, pulse wave velocity, an established marker of arterial stiffness [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], is one parameter not been previously quantified within the aorta using 4D flow MRI in patients with d-TGA after the arterial switch operation.\u003c/p\u003e \u003cp\u003eAlthough many aortic flow parameters have been investigated, the hemodynamic pulmonary artery profile has yet to be thoroughly characterized. To our knowledge, kinetic energy, a measure of the energy of blood flow due to motion, used as an indicator of cardiovascular efficiency [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]; energy loss, another metric for cardiovascular efficiency, equal to kinetic energy lost as thermal energy due to viscosity-driven friction [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]; and wall shear stress, a measure of shear forces exerted on the vessel wall by blood flow that serves as an indicator of risk for vascular remodeling [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], have not previously been studied in the pulmonary arteries of patients with d-TGA after the arterial switch operation. These hemodynamic parameters could provide valuable insights into the mechanisms underlying pulmonary arterial stenosis.\u003c/p\u003e \u003cp\u003eWe hypothesized that d-TGA after the arterial switch operation patients demonstrate abnormal flow, such as increased velocity, kinetic energy, and energy loss within the aorta and pulmonary arteries, which results in vascular remodeling that leads to aortic pathologies and pulmonary artery stenosis. Abnormal hemodynamic parameters in patients with d-TGA after the arterial switch operation patients could solidify the utility of 4D flow MRI in long-term monitoring of this patient population. The aim of this study was thus to use 4D flow MRI to compare pulmonary arterial and aortic hemodynamics between patients with d-TGA after the arterial switch operation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and patients with normal cardiac anatomy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cstrong\u003eStudy Cohort\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eThis retrospective cohort study included 44 children and young adults under 24 years old with d-TGA after the arterial switch operation (d-TGA group) and 25 children and young adults under 24 years old with normal cardiac anatomy (control group) who were age-matched to a subgroup of 25 d-TGA subjects. All d-TGA and control subjects were patients who underwent cardiac MRI at Lurie Children\u0026rsquo;s Hospital between June 2012 and January 2024. Cardiac MRI was clinically indicated for all d-TGA patients. For the d-TGA group, written consent or assent was obtained for 4D flow sequences prior to 2018, and 4D flow sequences were clinically indicated as part of the cardiac MRI examination after 2018. Controls included patients undergoing MRI for other indications who consented or assented to the addition of a 4D flow sequence for research purposes, as well as patients who underwent clinically indicated 4D flow MRI. All controls were found to have normal cardiac anatomy and function on MRI. All studies were retrospectively reviewed with a waiver of consent. This study is health insurance and accountability act compliant and was approved by the Institutional Review Board of Lurie Children\u0026rsquo;s Hospital.\u003c/p\u003e\n \u003cp\u003eFor the d-TGA group, exclusion criteria were other cardiac lesions at birth (26 patients), except for atrial septal defect and/or ventricular septal defect; and history of other surgical or catheter-based intervention affecting the great arteries prior to cardiac MRI (16 patients), except for balloon atrial septostomy. Other inclusion and exclusion criteria are summarized in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. For patients with more than one 4D flow scan, the most recent exam was used.\u003c/p\u003e\n \u003cp\u003eDemographic information collected for each patient included sex and age, weight, height, and body surface area at the time of the exam. Patient charts were also reviewed for history of catheter-based or surgical reintervention affecting the great arteries and/or semilunar valves at any date after the exam.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eCardiac MRI Acquisition\u003c/h3\u003e\n\u003cp\u003eAll cardiac MRI examinations were performed on a 1.5T MRI scanner (Aera, Siemens Healthineers, Malvern PA). Each patient underwent cardiac MRI including multiplanar balanced steady state free precession cine imaging followed by 4D flow MRI. The 4D flow MRI parameters were tailored to each patient with the following ranges: FOV (mm\u003csup\u003e2\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;260\u0026ndash;400 x 195\u0026ndash;280, spatial resolution (mm\u003csup\u003e3\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;1.97\u0026ndash;3.59 x 1.35\u0026ndash;2.5 x 1.4\u0026ndash;2.8, temporal resolution (ms)\u0026thinsp;=\u0026thinsp;40-62.76, TE (ms)\u0026thinsp;=\u0026thinsp;2.32-3.0009, flip angle (\u0026deg;)\u0026thinsp;=\u0026thinsp;8\u0026ndash;25, venc (cm/s)\u0026thinsp;=\u0026thinsp;80\u0026ndash;250.\u003c/p\u003e\n\u003cp\u003eStudies were respiratory navigator gated and performed with free breathing. Electrocardiographic synchronization was via retrospective gating for 32 d-TGA patients and 13 controls, and prospective triggering for 12 d-TGA patients and 13 controls. For the d-TGA group, prior to the 4D flow sequence, a gadolinium-based contrast agent (Gadavist, Bayer, Whippany, USA; or Ablavar, Lantheus Medical, Billerica, USA) was administered per the clinical protocol to 13 patients and ferumoxytol (Ferahame, AMAG Pharmaceuticals, Waltham, USA) to 11 patients per the clinical indication. For the control group, a gadolinium-based contrast agent was administered to 23 patients prior to the 4D flow sequence. Twenty d-TGA patients and two controls were imaged without contrast.\u003c/p\u003e\n\u003ch3\u003eCardiac MRI Anatomic Measurements\u003c/h3\u003e\n\u003cp\u003eNeoaortic root, main pulmonary artery, and proximal left and right pulmonary artery diameters for d-TGA patients were measured for clinical purposes at the time of the exam using double-oblique short axis vessel views generated on an independent workstation (Vitrea Software, Canon Medical Systems Corporation, Tustin, CA) from a fast low angle shot gradient echo MRI (FLASH) sequence. To account for age and body size differences in, Z-scores were determined for each vessel using Boston Children\u0026rsquo;s Hospital Z-score system [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. The largest neoaortic root diameter and smallest main pulmonary artery, right pulmonary artery, and left pulmonary artery diameters for were used for Z-score determination. Z-scores less than \u0026minus;\u0026thinsp;2 and greater than +\u0026thinsp;2 were considered abnormal.\u003c/p\u003e\n\u003ch3\u003e4D Flow MRI Analysis\u003c/h3\u003e\n\u003cp\u003ePre- and post-processing 4D flow workflow is shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. An in-house MATLAB (version R2017b; Mathworks, Natick, USA) software tool was used for 4D flow data pre-processing, including correction for phase offset errors (Maxwell terms, eddy currents), noise masking, and velocity-antialiasing. As previously described [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e], a mean sum square phase contrast magnetic resonance angiogram was calculated for each exam and was used for manual thoracic aorta and main and branch pulmonary artery 3D segmentation (Mimics, Materialize, Leuven, Belgium). Pulmonary artery segmentations included the main, left, and right pulmonary arteries, terminating at the proximal segmental branches.\u003c/p\u003e\n\u003cp\u003eAn automated quantification tool programmed in MATLAB was used to mask 4D flow data using the aorta and pulmonary artery segmentations to quantify nine hemodynamic parameters during systole summarized in Online Resource \u003cstrong\u003e1\u003c/strong\u003e, including mean and maximum velocity, mean and maximum kinetic energy, stasis, energy loss, and maximum and mean wall shear stress, and pulse wave velocity. Data were interpolated to isotropic 1mm\u003csup\u003e2\u003c/sup\u003e voxels for quantification of voxel-wise parameters. For each voxel, velocity magnitudes were measured at each time point and then averaged over all time points to determine the mean velocity. Flow stasis was calculated as the percentage of time frames for which velocity\u0026thinsp;\u0026lt;\u0026thinsp;0.10 m/s. Kinetic energy and energy loss were calculated as previously described [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. All voxel-wise parameters were averaged over the segmented volumes of the aorta and pulmonary arteries and are reported as means.\u003c/p\u003e\n\u003cp\u003eFor aortic regional analysis, a centerline was automatically calculated, and 2D analysis planes were manually placed to divide the aorta into three regions of interest, including the ascending aorta from the aortic valve to the brachiocephalic trunk, the aortic arch including proximal branch vessels, and descending aorta from the left subclavian artery through the distal thoracic aorta (Online Resource \u003cstrong\u003e2\u003c/strong\u003e). 3D wall shear stress at each time point was quantified using an in-house developed tool based on a previously described technique [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. Maximum wall shear stress was defined as the highest value within the region at any time point. Mean wall shear stress was determined by averaging wall shear stress over each region of the segmented aorta (Online Resource \u003cstrong\u003e2\u003c/strong\u003e), and over the entire pulmonary artery segmentation. Voxel-wise maximum velocity was also measured within each aortic region and is reported as a mean average.\u003c/p\u003e\n\u003cp\u003eAs previously described [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e], pulse wave velocity was quantified in the aorta using custom software programmed in MATLAB. Analysis planes were automatically placed perpendicular to the centerline of the aorta. Through-plane flow curves were calculated, from which pulse wave velocity was determined through cross-correlation analysis.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eStatistical analysis was performed in Graph Pad Prism (version 10.2.3; Graph Pad Software, Boston, MA). A Shapiro-Wilk test was used to determine normality. Normally distributed data are reported as means and SDs, and non-normal data are reported as medians and IQRs. For normally distributed data, an unpaired t-test with Welch\u0026rsquo;s correction was used for comparisons between controls and a subgroup of age-matched d-TGA patients, and between controls and the whole d-TGA cohort. For non-normal data, a Mann-Whitney test was used for between-group comparisons. Fisher\u0026rsquo;s exact test was used for comparison of sex, d-TGA type at birth, and location of maximum velocity in the pulmonary arteries between groups. Significance for all statistical analyses was defined as a \u003cem\u003eP\u003c/em\u003e value less than 0.05.\u003c/p\u003e\n"},{"header":"Results","content":"\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eStudy Cohort\u003c/h2\u003e\n \u003cp\u003eForty-four d-TGA patients (mean age 15.3 years\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 [SD), age range 2.7 to 23.8 years; 9 [20.5%] female and 35 [79.5%] male patients) were included in this study. Twenty-five control patients (mean age 15.5 years\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 [SD], range 10.6 to 20.0 years; 14 [56.0%] female and 11 [44.0%] male patients) were age-matched to a subgroup of 25 d-TGA-ASO patients (mean age 15.7 years\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 [SD], age range 11.3 to 20.3 years; two [8.0%] female and 23 [92.0%] male patients) for paired comparisons. Quantification of pulse wave velocity, wall shear stress, and/or regional maximum velocity within the aorta failed for several patients (four d-TGA patients and three controls) due to errors in MATLAB that could not be resolved; when these patients were part of an age-matched pair, the entire pair was excluded from analysis (Online Resource \u003cstrong\u003e3\u003c/strong\u003e). Baseline characteristics for the d-TGA groups compared with the control cohort are summarized in Table \u003cspan\u003e1\u003c/span\u003e. Average body surface area did not significantly differ between the d-TGA group and control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19). The mean age difference between age-matched d-TGA and control pairs was 0.39 years\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23 [SD]. Twelve (48%) of age-matched were also matched for sex (Online Resource \u003cstrong\u003e4\u003c/strong\u003e). Of note, the arterial switch operation included the LeCompte maneuver for all patients within the d-TGA cohort. Four (9%) d-TGA patients underwent reintervention following 4D flow cardiac MRI, including two patients for pulmonary regurgitation and two patients for neo-aortic valve insufficiency with aortic root dilatation (Online Resource \u003cstrong\u003e5\u003c/strong\u003e). Online Resource \u003cstrong\u003e6\u003c/strong\u003e displays averages and ranges for Z-scores of the aortic root, main pulmonary artery, right pulmonary artery, and left pulmonary artery diameters in d-TGA patients. The average Z-score for aortic root diameter was abnormally large at 3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64 [SD]. The average Z-scores for main pulmonary artery (median \u0026minus;\u0026thinsp;2.02 [IQR, -2.44-(-1.15)]) and right pulmonary artery (median \u0026minus;\u0026thinsp;1.13 [IQR, -2.14-(-0.358)]) diameters were abnormally small.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eBaseline characteristics of the control cohort compared with the whole cohort and age-matched sub-group of patients with dextro-transposition of the great arteries after the arterial switch operation\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ed-TGA-ASO\u003c/p\u003e\n \u003cp\u003eAge-Matched Sub-Group\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ed-TGA-ASO\u003c/p\u003e\n \u003cp\u003eWhole Cohort\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl Cohort\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8228)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(\u003cstrong\u003eP\u003c/strong\u003e\u0026thinsp;\u003cstrong\u003e=\u0026thinsp;0.006\u003c/strong\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(\u003cstrong\u003eP\u003c/strong\u003e\u0026thinsp;\u003cstrong\u003e=\u0026thinsp;0.0037\u003c/strong\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (92.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (79.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.8\u0026thinsp;\u0026plusmn;\u0026thinsp;18.2\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3350)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.8\u0026thinsp;\u0026plusmn;\u0026thinsp;24.6\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.9796)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.0\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e168\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1840)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e161\u0026thinsp;\u0026plusmn;\u0026thinsp;21.9\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7075)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e163.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBSA (m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1943)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8934)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD-TGA type at birth:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e----\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD-TGA-IVS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (72.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (65.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e----\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD-TGA-VSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e----\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD-TGA, type unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e----\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eBaseline characteristics were compared between controls and an age-matched group of patients with d-TGA after the arterial switch operation (d-TGA-ASO), and between the control and whole d-TGA cohorts. For patient sex and d-TGA type at birth, the number of patients is provided for each characteristic with the percentage of the group in parentheses. \u003cem\u003eP\u003c/em\u003e values of significance are shown in bold (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). BSA\u0026thinsp;=\u0026thinsp;body surface area (Mosteller formula), d-TGA-IVS\u0026thinsp;=\u0026thinsp;d-TGA with intact interventricular septum, d-TGA-VSD\u0026thinsp;=\u0026thinsp;d-TGA with ventricular septal defect, ASO\u0026thinsp;=\u0026thinsp;arterial switch operation, PA\u0026thinsp;=\u0026thinsp;main and branch pulmonary arteries\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eComparison of Pulmonary Arterial Hemodynamic Parameters Between d-TGA-ASO Patients and Controls\u003c/h3\u003e\n\u003cp\u003eAverage values for all hemodynamic parameters quantified in the main and branch pulmonary arteries of d-TGA patients compared with controls are summarized in Table \u003cspan\u003e2\u003c/span\u003e. As shown in Fig. \u003cspan\u003e3\u003c/span\u003e, maximum and mean velocity, maximum and mean, and energy loss within the pulmonary arteries were significantly higher in the age-matched sub-group of d-TGA-ASO patients (N\u0026thinsp;=\u0026thinsp;25) compared with controls (Fig. \u003cspan\u003e3\u003c/span\u003eb). The same pulmonary arterial flow parameters were significantly higher in the whole d-TGA cohort (N\u0026thinsp;=\u0026thinsp;44) when compared to the control cohort (N\u0026thinsp;=\u0026thinsp;25) (Fig. \u003cspan\u003e3\u003c/span\u003ec). The voxel with the highest maximum velocity was most commonly located in the right pulmonary artery for both d-TGA patients (34 patients, 77.3% of cohort) and controls (13 patients, 52.0% cohort) (Table \u003cspan\u003e2\u003c/span\u003e). We found no evidence of differences in stasis in the pulmonary arteries between the d-TGA and control patients in either age-matched (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4788) or whole-group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2143) comparisons.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003e4D flow hemodynamic parameters in the main and branch pulmonary arteries in patients with dextro-transposition of the great arteries after the arterial switch operation compared with controls\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ed-TGA-ASO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo. of patients\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e----\u003c/p\u003e\n \u003cp\u003e----\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eMean V\u003csub\u003emax\u003c/sub\u003e (m/s)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003cp\u003eLocation of V\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003eMPA\u003c/p\u003e\n \u003cp\u003eRPA\u003c/p\u003e\n \u003cp\u003eLPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.68 [1.54\u0026ndash;1.87]\u003c/p\u003e\n \u003cp\u003e1.63 [1.43\u0026ndash;1.82]\u003c/p\u003e\n \u003cp\u003e5 (11.4)\u003c/p\u003e\n \u003cp\u003e34 (77.3)\u003c/p\u003e\n \u003cp\u003e5 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.873 [0.814\u0026ndash;1.03]\u003c/p\u003e\n \u003cp\u003e0.873 [0.814\u0026ndash;1.03]\u003c/p\u003e\n \u003cp\u003e9 (36.0)\u003c/p\u003e\n \u003cp\u003e13 (52.0)\u003c/p\u003e\n \u003cp\u003e3 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0497\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean V\u003csub\u003emean\u003c/sub\u003e (m/s)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.644 [0.5696\u0026ndash;0.7058]\u003c/p\u003e\n \u003cp\u003e0.596 [0.5399\u0026ndash;0.6964]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.476 [0.423\u0026ndash;0.569]\u003c/p\u003e\n \u003cp\u003e0.476 [0.423\u0026ndash;0.569]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean stasis (%)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\n \u003cp\u003e32.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78\u003c/p\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5206\u003c/p\u003e\n \u003cp\u003e0.2143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean KE\u003csub\u003emax\u003c/sub\u003e (\u0026micro;J)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.24 [3.94\u0026ndash;7.22]\u003c/p\u003e\n \u003cp\u003e4.53 [3.40\u0026ndash;6.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75 [1.10\u0026ndash;2.89]\u003c/p\u003e\n \u003cp\u003e1.75 [1.10\u0026ndash;2.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean KE\u003csub\u003emean\u003c/sub\u003e (\u0026micro;J)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.84 [3.20\u0026ndash;5.79]\u003c/p\u003e\n \u003cp\u003e3.59 [2.62\u0026ndash;5.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39 [8.89\u0026ndash;2.38]\u003c/p\u003e\n \u003cp\u003e1.39 [8.89\u0026ndash;2.38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean EL (\u0026micro;J)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.374 [0.231\u0026ndash;0.477]\u003c/p\u003e\n \u003cp\u003e0.290 [2.03\u0026ndash;4.58]]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0527 [0.0294\u0026ndash;0.0802]\u003c/p\u003e\n \u003cp\u003e0.0527 [0.0294\u0026ndash;0.0802]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMax WSS (N/m2)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.59 [2.24\u0026ndash;3.19]\u003c/p\u003e\n \u003cp\u003e2.55 [2.09-3.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29 [1.04\u0026ndash;1.45]\u003c/p\u003e\n \u003cp\u003e1.29 [1.04\u0026ndash;1.45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean WSS (N/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.693\u0026thinsp;\u0026plusmn;\u0026thinsp;0.130\u003c/p\u003e\n \u003cp\u003e0.675\u0026thinsp;\u0026plusmn;\u0026thinsp;0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.514\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0963\u003c/p\u003e\n \u003cp\u003e0.514\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHemodynamic parameters in the pulmonary arteries were compared between controls and an age-matched group of patients with d-TGA after arterial switch operation (d-TGA-ASO), and between the control and whole d-TGA-ASO cohort. For the location of Vmax, the number of patients is provided for each region with the percentage of the group in parentheses. V\u003csub\u003emax\u003c/sub\u003e = maximum velocity, MPA\u0026thinsp;=\u0026thinsp;main pulmonary artery, RPA\u0026thinsp;=\u0026thinsp;right pulmonary artery, LPA\u0026thinsp;=\u0026thinsp;left pulmonary artery, V\u003csub\u003emean\u003c/sub\u003e = mean velocity, KE\u003csub\u003emax\u003c/sub\u003e = maximum kinetic energy, KE\u003csub\u003emean\u003c/sub\u003e = mean kinetic energy, EL\u0026thinsp;=\u0026thinsp;energy loss, PWV\u0026thinsp;=\u0026thinsp;pulse wave velocity, WSS\u0026thinsp;=\u0026thinsp;wall shear stress.\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. \u003cspan\u003e4\u003c/span\u003eb, maximum and mean wall shear stress were significantly higher in the age-matched sub-group of d-TGA patients compared to controls. Whole-group comparisons revealed similar findings, with significantly higher maximum and mean wall shear stress in the d-TGA cohort compared with controls (Fig. \u003cspan\u003e4\u003c/span\u003ec).\u003c/p\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eComparison of Aortic Hemodynamic Parameters Between d-TGA-ASO Patients and Controls\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan\u003e3\u003c/span\u003e contains average values for all aortic flow parameters quantified for d-TGA patients compared with controls. Age-matched d-TGA patients (N\u0026thinsp;=\u0026thinsp;25) had significantly higher maximum velocity in both the whole aorta and within all three regions of interest (ascending aorta, arch, and descending aorta) compared with controls. Mean velocity, maximum and mean kinetic energy, and energy loss were also significantly higher in the aorta of d-TGA patients compared with controls (Fig. \u003cspan\u003e5\u003c/span\u003eb). These parameters were also significantly higher in the whole d-TGA cohort (N\u0026thinsp;=\u0026thinsp;44) when compared to the control cohort (N\u0026thinsp;=\u0026thinsp;25), with the exception of mean velocity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1892). Stasis did not significantly differ between d-TGA patients and controls in either age-matched (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2865) or whole-group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.5086) comparisons.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAortic velocity, stasis, kinetic energy, energy loss, and pulse wave velocity in patients with dextro-transposition of the great arteries after the arterial switch operation compared with controls\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ed-TGA-ASO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean V\u003csub\u003emax\u003c/sub\u003e (m/s)\u003c/p\u003e\n \u003cp\u003eWhole aorta\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003cp\u003eAAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003cp\u003eArch\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003cp\u003eDAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48 [1.37\u0026ndash;1.67]\u003c/p\u003e\n \u003cp\u003e1.46 [1.28\u0026ndash;1.63]\u003c/p\u003e\n \u003cp\u003e2.34 [1.91\u0026ndash;3.29]\u003c/p\u003e\n \u003cp\u003e2.28 [1.83\u0026ndash;2.77]\u003c/p\u003e\n \u003cp\u003e2.20 [1.59\u0026ndash;2.63]\u003c/p\u003e\n \u003cp\u003e1.83 [1.37\u0026ndash;2.44]\u003c/p\u003e\n \u003cp\u003e2.50 [1.93\u0026ndash;3.17]\u003c/p\u003e\n \u003cp\u003e2.05 [1.75\u0026ndash;2.99]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29 [1.15\u0026ndash;1.44]\u003c/p\u003e\n \u003cp\u003e1.29 [1.15\u0026ndash;1.44]\u003c/p\u003e\n \u003cp\u003e1.58 [1.35\u0026ndash;2.08]\u003c/p\u003e\n \u003cp\u003e1.58 [1.35\u0026ndash;2.08]\u003c/p\u003e\n \u003cp\u003e1.26 [1.06\u0026ndash;1.54]\u003c/p\u003e\n \u003cp\u003e1.26 [1.06\u0026ndash;1.54]\u003c/p\u003e\n \u003cp\u003e1.57 [1.34-2.00]\u003c/p\u003e\n \u003cp\u003e1.57 [1.34-2.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0011\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0185\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean V\u003csub\u003emean\u003c/sub\u003e (m/s)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.757\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e\n \u003cp\u003e0.758 [0.631\u0026ndash;0.805]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.757\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e\n \u003cp\u003e0.683 [0.608\u0026ndash;0.785]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0483\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.1892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean stasis (%)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e\n \u003cp\u003e32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.82\u003c/p\u003e\n \u003cp\u003e34.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3324\u003c/p\u003e\n \u003cp\u003e0.5086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean KE\u003csub\u003emax\u003c/sub\u003e (\u0026micro;J)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.37 [4.35\u0026ndash;8.61]\u003c/p\u003e\n \u003cp\u003e5.92 [3.80\u0026ndash;7.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.20 [2.51\u0026ndash;5.49]\u003c/p\u003e\n \u003cp\u003e3.20 [2.51\u0026ndash;5.49]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0008\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0235\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean KE\u003csub\u003emean\u003c/sub\u003e (\u0026micro;J)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.84 [3.24\u0026ndash;6.44]\u003c/p\u003e\n \u003cp\u003e4.57 [2.84\u0026ndash;5.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.66 [1.84\u0026ndash;4.31]\u003c/p\u003e\n \u003cp\u003e2.66 [1.84\u0026ndash;4.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0026\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0394\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean EL (\u0026micro;J)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.136 [0.104\u0026ndash;0.381]\u003c/p\u003e\n \u003cp\u003e0.127 [0.0731\u0026ndash;0.269]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0778 [4.48\u0026ndash;9.33]\u003c/p\u003e\n \u003cp\u003e0.0778 [4.48\u0026ndash;9.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePWV (m/s)\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.50 [4.07\u0026ndash;4.92]\u003c/p\u003e\n \u003cp\u003e4.34 [3.79\u0026ndash;4.93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.57 [4.04\u0026ndash;4.95]\u003c/p\u003e\n \u003cp\u003e4.57 [4.05-5.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7940\u003c/p\u003e\n \u003cp\u003e0.3771\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eAortic hemodynamic parameters were compared between controls and an age-matched group of patients with d-TGA after arterial switch operation (d-TGA-ASO), between the control and whole d-TGA-ASO cohorts. V\u003csub\u003emax\u003c/sub\u003e = maximum velocity, V\u003csub\u003emean\u003c/sub\u003e = mean velocity, AAo\u0026thinsp;=\u0026thinsp;ascending aorta, DAo\u0026thinsp;=\u0026thinsp;descending aorta, KE\u003csub\u003emax\u003c/sub\u003e = maximum kinetic energy, KE\u003csub\u003emean\u003c/sub\u003e = mean kinetic energy, EL\u0026thinsp;=\u0026thinsp;energy loss, PWV\u0026thinsp;=\u0026thinsp;pulse wave velocity, WSS\u0026thinsp;=\u0026thinsp;wall shear stress, PWV\u0026thinsp;=\u0026thinsp;pulse wave velocity\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eMaximum wall shear stress was significantly higher in age-matched d-TGA patients compared to controls in the anterior ascending aorta, inferior and superior aortic arch, and anterior and posterior descending aorta (Table \u003cspan\u003e4\u003c/span\u003e, Fig. \u003cspan\u003e6\u003c/span\u003eb-g). Whole-cohort comparisons revealed significantly higher maximum wall shear stress in the same regions as the age-matched comparison, with the exception of the anterior ascending aorta (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0521). Compared to controls, mean wall shear stress was higher in both age-matched d-TGA patients (Fig. \u003cspan\u003e6\u003c/span\u003eb-g) and the whole d-TGA cohort in three regions of interest: superior aortic arch (age-matched: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0042), anterior descending aorta (age-matched: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0359), and posterior descending aorta (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0210).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eRegional aortic wall shear stress in patients with dextro-transposition of the great arteries after the arterial switch operation compared with controls\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ed-TGA-ASO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMax WSS (N/m\u003csup\u003e2\u003c/sup\u003e):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePosterior AAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.386\u003c/p\u003e\n \u003cp\u003e1.28 [1.09\u0026ndash;1.55]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.248\u003c/p\u003e\n \u003cp\u003e1.24 [1.03\u0026ndash;1.46]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0635\u003c/p\u003e\n \u003cp\u003e0.5478\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnterior AAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.45 [1.38\u0026ndash;1.72]\u003c/p\u003e\n \u003cp\u003e1.40 [1.17\u0026ndash;1.56]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19 [1.08\u0026ndash;1.43]\u003c/p\u003e\n \u003cp\u003e1.19 [1.08\u0026ndash;1.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0020\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.0521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior arch\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40 [1.18\u0026ndash;1.52]\u003c/p\u003e\n \u003cp\u003e1.30 [1.09\u0026ndash;1.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13 [0.944\u0026ndash;1.33]\u003c/p\u003e\n \u003cp\u003e1.13 [0.944\u0026ndash;1.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0022\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0457\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuperior arch\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40 [1.18\u0026ndash;1.76]\u003c/p\u003e\n \u003cp\u003e1.28 [1.09\u0026ndash;1.58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.107 [0.896\u0026ndash;1.22]\u003c/p\u003e\n \u003cp\u003e0.107 [0.896\u0026ndash;1.22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnterior DAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.429\u003c/p\u003e\n \u003cp\u003e1.49 [1.26\u0026ndash;1.77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.273\u003c/p\u003e\n \u003cp\u003e1.28 [1.07\u0026ndash;1.38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0012\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePosterior DAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.417\u003c/p\u003e\n \u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.241\u003c/p\u003e\n \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0015\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean WSS (N/m\u003csup\u003e2\u003c/sup\u003e):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePosterior AAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.596\u0026thinsp;\u0026plusmn;\u0026thinsp;0.103\u003c/p\u003e\n \u003cp\u003e0.576\u0026thinsp;\u0026plusmn;\u0026thinsp;0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.574\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e\n \u003cp\u003e0.574\u0026thinsp;\u0026plusmn;\u0026thinsp;0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5177\u003c/p\u003e\n \u003cp\u003e0.9530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnterior AAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.696\u0026thinsp;\u0026plusmn;\u0026thinsp;0.164\u003c/p\u003e\n \u003cp\u003e0.576\u0026thinsp;\u0026plusmn;\u0026thinsp;0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.646\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0991\u003c/p\u003e\n \u003cp\u003e0.646\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2211\u003c/p\u003e\n \u003cp\u003e0.9530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior arch\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.853 [0.711\u0026ndash;0.895]\u003c/p\u003e\n \u003cp\u003e0.776\u0026thinsp;\u0026plusmn;\u0026thinsp;0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7935 [0.7133\u0026ndash;0.8802]\u003c/p\u003e\n \u003cp\u003e0.811\u0026thinsp;\u0026plusmn;\u0026thinsp;0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5376\u003c/p\u003e\n \u003cp\u003e0.4004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuperior arch\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.729\u0026thinsp;\u0026plusmn;\u0026thinsp;0.131\u003c/p\u003e\n \u003cp\u003e0.689\u0026thinsp;\u0026plusmn;\u0026thinsp;0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.620\u0026thinsp;\u0026plusmn;\u0026thinsp;0.111\u003c/p\u003e\n \u003cp\u003e0.620\u0026thinsp;\u0026plusmn;\u0026thinsp;0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0052\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0330\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnterior DAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.953 [0.842\u0026ndash;1.02]\u003c/p\u003e\n \u003cp\u003e0.925 [0.793\u0026ndash;0.990]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.832 [0.697\u0026ndash;0.916]\u003c/p\u003e\n \u003cp\u003e0.832 [0.697\u0026ndash;0.916]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0307\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0483\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePosterior DAo\u003c/p\u003e\n \u003cp\u003eAge-matched\u003c/p\u003e\n \u003cp\u003eWhole cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 [0.895-1.10]\u003c/p\u003e\n \u003cp\u003e0.974 [0.855\u0026ndash;1.07]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.863 [0.760\u0026ndash;0.961]\u003c/p\u003e\n \u003cp\u003e0.863 [0.760\u0026ndash;0.961]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0310\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.0174\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eRegional aortic wall shear stress (WSS) was compared between controls and a group of age-matched patients with d-TGA after arterial switch operation (d-TGA-ASO), and between the control and whole d-TGA-ASO cohorts. AAo\u0026thinsp;=\u0026thinsp;ascending aorta, DAo\u0026thinsp;=\u0026thinsp;descending aorta\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eWe found no difference between d-TGA patients and controls in pulse wave velocity in either age-matched (4.50 m/s [4.07\u0026ndash;4.92] vs. 4.57 m/s [4.04\u0026ndash;4.95]; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7314) or whole-group (4.34 m/s [3.79\u0026ndash;4.93] vs. 4.57 m/s [4.05-5.00], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3771) comparisons (Table \u003cspan\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur aim was to provide a comprehensive evaluation of pulmonary arterial and aortic hemodynamics in patients with d-TGA after the arterial switch operation. We compared eight hemodynamic parameters within the pulmonary arteries and nine within the aorta between control patients with normal cardiac anatomy (N\u0026thinsp;=\u0026thinsp;25) and both a whole cohort (N\u0026thinsp;=\u0026thinsp;44) and age-matched sub-group (N\u0026thinsp;=\u0026thinsp;25) of patients with d-TGA after the arterial switch operation to identify hemodynamic abnormalities in this patient population. Our main finding is that patients with d-TGA after the arterial switch operation demonstrate abnormal pulmonary artery and aortic velocity, kinetic energy, energy loss, and wall shear stress, suggesting the potential utility of these 4D flow parameters for clarifying the pathophysiology underlying complications of the arterial switch operation and for predicting the need for pulmonary arterial or aortic reintervention.\u003c/p\u003e \u003cp\u003eIn the main and branch pulmonary arteries, we found maximum velocity was significantly higher in patients with d-TGA after the arterial switch operation than in age-matched controls, consistent with findings from Geiger et al. Even among d-TGA patients with normal Z-scores for main and branch pulmonary artery diameters, we found higher maximum velocities in the pulmonary arteries compared with the average value among controls. Geiger et al. similarly noted that maximum velocities were elevated in patients with d-TGA after the arterial switch operation without apparent MPA stenosis. They therefore propose elevated maximum velocity in patients with d-TGA after the arterial switch operation could be caused by transient compression of the branch pulmonary arteries by the ascending aorta during systole, due to the position of the pulmonary arteries posterior to the sternum and anterior to the ascending aorta after the LeCompte maneuver. In addition, our study found higher mean systolic velocity within the pulmonary arteries of d-TGA patients, which could also be explained by systolic compression by the ascending aorta.\u003c/p\u003e \u003cp\u003eAortic maximum velocity was significantly higher in d-TGA patients compared with age-matched controls when quantified over the entire aorta as well as each region individually. These findings differ from those of Geiger et al., possibly because our quantification was performed over entire 3D volumes and not 2D planes. In our study, mean aortic velocity was also significantly higher in age-matched d-TGA patients compared with controls, but whole cohort comparisons did not show evidence of a difference in mean velocity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1892). Similarly, Sotelo et al. did not find evidence of a difference in mean velocity within any region of the aortic root when comparing patients with d-TGA after the arterial switch operation with unmatched controls.\u003c/p\u003e \u003cp\u003eMechanical energetics were also abnormal in the main and branch pulmonary arteries of d-TGA patients, with elevated maximum and mean kinetic energy and energy loss (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for all) compared with age-matched controls. These findings suggest inefficient pulmonary arterial flow following the arterial switch operation and thus increased right ventricular workload. This could explain why right ventricular performance has been shown to be impaired in d-TGA patients at postoperative follow-up [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In three regions of the aortic root, Sotelo et al. found no significant difference in mean kinetic energy or energy loss between patients with d-TGA after the arterial switch operation and unmatched controls. However, when quantifying these parameters over the entire aorta, we found significantly higher maximum kinetic energy, mean kinetic energy, and energy loss in d-TGA patients compared with age-matched controls. Together, our findings could indicate that elevated kinetic energy and energy loss only occurs distal to the aortic root, which might be explained by increasingly abnormal flow patterns as aortic diameter acutely decreases distal to the neoaortic root.\u003c/p\u003e \u003cp\u003eIn patients with d-TGA after the arterial switch operation, the pathogenesis of neoaortic root dilatation remains unknown, but contributing factors might include the systemic pressure load on native pulmonary artery tissue [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], or loss of aortic distensibility due to scarring following coronary button transfer [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Although many d-TGA patients in our cohort demonstrated neoaortic dilatation, pulse wave velocity did not significantly differ between d-TGA patients and age-matched controls (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7314). This could be explained by the younger age of our patient cohort (mean age 15.3 years\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 [SD]), as pulse wave velocity is known to increase with age [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Using 2D cine phase-contrast with through-plane velocity encoding, Voges et al. also found no evidence of a difference in pulse wave velocity between patients with d-TGA after the arterial switch operation under 18 years old and age-matched controls, but did find higher pulse wave velocity in adult compared with younger patients with d-TGA after the arterial switch operation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWall shear stress is known to contribute to the development of many vascular pathologies through its effects on endothelial function [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and may offer insight into the relationship between hemodynamics and the pathogenesis of aortic and pulmonary arterial complications of the arterial switch operation. Patients with pulmonary arterial hypertension have been shown to have lower wall shear stress in the pulmonary arteries, which is believed to induce vascular remodeling that causes main pulmonary artery dilation and wall thickening [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Here, we found significantly higher maximum and mean wall shear stress between d-TGA patients and age-matched controls. From these findings, we hypothesize flow abnormalities within the main and branch pulmonary arteries result in elevated wall shear stress, which induces remodeling that leads to pulmonary artery stenosis.\u003c/p\u003e \u003cp\u003ePrior studies comparing aortic wall shear stress between patients with d-TGA after the arterial switch operation and controls have found elevated maximum and mean wall shear stress in regions of the neoaortic root and ascending aorta of patients with d-TGA after the arterial switch operation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In our volumetric quantification of wall shear stress, we also found significantly higher maximum wall shear stress within the anterior ascending aorta of d-TGA patients compared to age-matched controls, but did not find evidence of a difference in mean wall shear stress in the ascending aorta, as described by Sotelo et al. Importantly, although Sotelo et al. also quantified wall shear stress using the 3D volumes of each region, their regional definitions differed. They report a significant difference in mean 3D wall shear stress only within the right anterior region of the ascending aorta before decomposing the WSS vector field into its axial and circumferential components [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, the difference in our results may be attributed to our inclusion of both the right and left sides of the anterior ascending aorta, as well as the incorporation of the aortic root within this region.\u003c/p\u003e \u003cp\u003eSotelo et al. propose that elevated wall shear stress in the ascending aorta may be explained by a more acute aortic arch curvature in patients who undergo the arterial switch operation with the LeCompte maneuver compared with controls, as circumferential wall shear stress is highly correlated with arch curvature [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Van der Palen et al. (2020) also found a correlation in patients with d-TGA after the arterial switch operation between wall shear stress and vessel geometry, specifically change in aortic diameter from the root to the mid-ascending aorta, and therefore suggest elevated wall shear stress is due to flow displacement and higher near-wall velocity gradient in this caliber change [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although we did not investigate the relationship between aortic geometry and wall shear stress, our study also quantified wall shear stress within the aortic arch and descending aorta and found higher maximum and mean wall shear stress in these regions in d-TGA patients compared with controls. Elevated wall shear stress in the aortic arch and descending aorta may also be explained by flow aberrancies due to acute arch curvature, coupled by caliber change from the aortic root to more distal parts of the aorta.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eFirst, since aortic velocity decreases with age until middle adulthood [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], unmatched (whole cohort) comparisons could overestimate differences in velocity between patients with d-TGA after the arterial switch operation and controls due to the younger age of the d-TGA cohort. However, the agreement between whole cohort and age-matched comparisons for the majority of parameters suggests age differences had little effect. Our control group also featured a significantly higher proportion of female participants. Although no significant differences in maximum velocity and 3D wall shear stress in the aorta have been found between biological males and females [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], comparative data for pulmonary arterial hemodynamics is unavailable, and kinetic energy has shown to be higher in the left ventricles of males, which could affect great arterial blood flow to some degree [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Lastly, since only four patients in our d-TGA cohort underwent reintervention, two involving the aorta and two on the pulmonary arteries, we could not compare hemodynamic parameters between d-TGA patients who ultimately required reintervention and those who did not. Additional studies will be necessary to investigate the association between outcomes and abnormalities in these hemodynamic parameters in patient with d-TGA after the arterial switch operation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our comprehensive great artery hemodynamic assessment demonstrates abnormalities in seven of nine hemodynamic parameters quantified within the aorta and/or pulmonary arteries of patients with d-TGA after the arterial switch operation. In the pulmonary arteries, in addition to finding further evidence of increased velocity, we also found evidence of increased kinetic energy, energy loss, and wall shear stress. In the aorta, we found additional evidence of increased wall shear stress in the ascending aorta, as well as evidence of increased velocity, kinetic energy, and energy loss; and increased wall shear stress in the aortic arch and descending aorta. These 4D flow parameters may serve as useful tools for further investigating the mechanisms underlying postoperative artery stenosis and aortic dilatation and insufficiency, and for predicting which patients will require reintervention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK.C. reviewed existing literature, contributed to study design, assembled the cohort of d-TGA patients from a hospital database, collected data (segmentation step in Mimics, quantification in MATLAB), ran statistical analysis, prepared figures, and wrote the main manuscript text.A.S. collected data (retrieval of 4D flow data in Conquest, pre-processing through Velomap and SuperTool), assisted with statistical analysis, contributed to study design, helped to troubleshoot issues, and provided guidance for each step in the project.E.J. wrote the code for pre-processing and quantification in MATLAB, did troubleshooting to resolve errors in MATLAB, assisted with statistical analysis, contributed to study design, and provided guidance for each step in the project.J.R. and M.M. contributed to study design and provided guidance for each step in the project; they reviewed data and assisted with statistical analysis.C.R. was Principal Investigator for the study; led study design, provided guidance for each step in the project, and helped to troubleshoot issues.All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to data sets containing information that could compromise research participant privacy/consent.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMorfaw F, Leenus A, Mbuagbaw L, Anderson LN, Dillenburg R, Thabane L (2020) Outcomes after corrective surgery for congenital dextro-transposition of the arteries using the arterial switch technique: a scoping systematic review. Syst Rev 2020, 9(1):231.10.1186/s13643-020-01487-3\u003c/li\u003e\n\u003cli\u003eSobczak-Budlewska K, Lubisz M, Moll M, Moszura T, Moll JA, Korabiewska-Pluta S, Moll JJ, Michalak KW (2023) 30 years\u0026apos; experience with the arterial switch operation: risk of pulmonary stenosis and its impact on post-operative prognosis. Cardiol Young 2023, 33(9):1550-1555.10.1017/S1047951122002670\u003c/li\u003e\n\u003cli\u003eCo-Vu JG, Ginde S, Bartz PJ, Frommelt PC, Tweddell JS, Earing MG (2013) Long-term outcomes of the neoaorta after arterial switch operation for transposition of the great arteries. Ann Thorac Surg 2013, 95(5):1654-1659.10.1016/j.athoracsur.2012.10.081\u003c/li\u003e\n\u003cli\u003eKirzner J, Pirmohamed A, Ginns J, Singh HS (2018) Long-term Management of the Arterial Switch Patient. Curr Cardiol Rep 2018, 20(8):68.10.1007/s11886-018-1012-9\u003c/li\u003e\n\u003cli\u003eKhairy P, Clair M, Fernandes SM, Blume ED, Powell AJ, Newburger JW, Landzberg MJ, Mayer JE, Jr. (2013) Cardiovascular outcomes after the arterial switch operation for D-transposition of the great arteries. Circulation 2013, 127(3):331-339.10.1161/CIRCULATIONAHA.112.135046\u003c/li\u003e\n\u003cli\u003eZhu MZL, Fricke TA, Buratto E, Chowdhuri KR, Brizard CP, Konstantinov IE (2024) Outcomes of neo-aortic valve and root surgery late after arterial switch operation. J Thorac Cardiovasc Surg 2024, 167(4):1391-1401 e1393.10.1016/j.jtcvs.2023.09.038\u003c/li\u003e\n\u003cli\u003eJarvis K, Vonder M, Barker AJ, Schnell S, Rose M, Carr J, Robinson JD, Markl M, Rigsby CK (2016) Hemodynamic evaluation in patients with transposition of the great arteries after the arterial switch operation: 4D flow and 2D phase contrast cardiovascular magnetic resonance compared with Doppler echocardiography. J Cardiovasc Magn Reson 2016, 18(1):59.10.1186/s12968-016-0276-8\u003c/li\u003e\n\u003cli\u003eCohen MS, Eidem BW, Cetta F, Fogel MA, Frommelt PC, Ganame J, Han BK, Kimball TR, Johnson RK, Mertens L et al (2016) Multimodality Imaging Guidelines of Patients with Transposition of the Great Arteries: A Report from the American Society of Echocardiography Developed in Collaboration with the Society for Cardiovascular Magnetic Resonance and the Society of Cardiovascular Computed Tomography. J Am Soc Echocardiogr 2016, 29(7):571-621.10.1016/j.echo.2016.04.002\u003c/li\u003e\n\u003cli\u003eGutberlet M, Boeckel T, Hosten N, Vogel M, Kuhne T, Oellinger H, Ehrenstein T, Venz S, Hetzer R, Bein G et al (2000) Arterial switch procedure for D-transposition of the great arteries: quantitative midterm evaluation of hemodynamic changes with cine MR imaging and phase-shift velocity mapping-initial experience. Radiology 2000, 214(2):467-475.10.1148/radiology.214.2.r00fe45467\u003c/li\u003e\n\u003cli\u003eGeiger J, Hirtler D, Burk J, Stiller B, Arnold R, Jung B, Langer M, Markl M (2014) Postoperative pulmonary and aortic 3D haemodynamics in patients after repair of transposition of the great arteries. Eur Radiol 2014, 24(1):200-208.10.1007/s00330-013-2998-4\u003c/li\u003e\n\u003cli\u003eSotelo J, Valverde I, Martins D, Bonnet D, Boddaert N, Pushparajan K, Uribe S, Raimondi F (2022) Impact of aortic arch curvature in flow haemodynamics in patients with transposition of the great arteries after arterial switch operation. Eur Heart J Cardiovasc Imaging 2022, 23(3):402-411.10.1093/ehjci/jeaa416\u003c/li\u003e\n\u003cli\u003evan der Palen RLF, Deurvorst QS, Kroft LJM, van den Boogaard PJ, Hazekamp MG, Blom NA, Lamb HJ, Westenberg JJM, Roest AAW (2020) Altered Ascending Aorta Hemodynamics in Patients After Arterial Switch Operation for Transposition of the Great Arteries. J Magn Reson Imaging 2020, 51(4):1105-1116.10.1002/jmri.26934\u003c/li\u003e\n\u003cli\u003evan der Palen RLF, Juffermans JF, Kroft LJM, Hazekamp MG, Lamb HJ, Blom NA, Roest AAW, Westenberg JJM (2021) Wall shear stress in the thoracic aorta at rest and with dobutamine stress after arterial switch operation. Eur J Cardiothorac Surg 2021, 59(4):814-822.10.1093/ejcts/ezaa392\u003c/li\u003e\n\u003cli\u003eCallaghan FM, Burkhardt B, Valsangiacomo Buechel ER, Kellenberger CJ, Geiger J (2021) Assessment of ventricular flow dynamics by 4D-flow MRI in patients following surgical repair of d-transposition of the great arteries. Eur Radiol 2021, 31(10):7231-7241.10.1007/s00330-021-07813-0\u003c/li\u003e\n\u003cli\u003eBelhadjer Z, Soulat G, Ladouceur M, Pitocco F, Legendre A, Bonnet D, Iserin L, Mousseaux E (2020) Neopulmonary Outflow Tract Obstruction Assessment by 4D Flow MRI in Adults With Transposition of the Great Arteries After Arterial Switch Operation. J Magn Reson Imaging 2020, 51(6):1699-1705.10.1002/jmri.27012\u003c/li\u003e\n\u003cli\u003eFalahatpisheh A, Rickers C, Gabbert D, Heng EL, Stalder A, Kramer HH, Kilner PJ, Kheradvar A (2016) Simplified Bernoulli\u0026apos;s method significantly underestimates pulmonary transvalvular pressure drop. J Magn Reson Imaging 2016, 43(6):1313-1319.10.1002/jmri.25097\u003c/li\u003e\n\u003cli\u003eShiina Y, Inai K, Nagao M (2021) Non-physiological Aortic Flow and Aortopathy in Adult Patients with Transposition of the Great Arteries after the Jatene Procedure: A Pilot Study Using Echo Planar 4D Flow MRI. Magn Reson Med Sci 2021, 20(4):439-449.10.2463/mrms.mp.2020-0101\u003c/li\u003e\n\u003cli\u003eWarmerdam EG, Westenberg JJM, Voskuil M, Rijnberg FM, Roest AAW, Lamb HJ, van Wijk B, Sieswerda GT, Doevendans PA, Ter Heide H et al (2023) Comparison of Four-Dimensional Flow MRI, Two-Dimensional Phase-Contrast MRI and Echocardiography in Transposition of the Great Arteries. Pediatr Cardiol 2023.10.1007/s00246-023-03238-2\u003c/li\u003e\n\u003cli\u003eRickers C, Kheradvar A, Sievers HH, Falahatpisheh A, Wegner P, Gabbert D, Jerosch-Herold M, Hart C, Voges I, Putman LM et al (2016) Is the Lecompte technique the last word on transposition of the great arteries repair for all patients? A magnetic resonance imaging study including a spiral technique two decades postoperatively. Interact Cardiovasc Thorac Surg 2016, 22(6):817-825.10.1093/icvts/ivw014\u003c/li\u003e\n\u003cli\u003ePotters WV, van Ooij P, Marquering H, vanBavel E, Nederveen AJ (2015) Volumetric arterial wall shear stress calculation based on cine phase contrast MRI. J Magn Reson Imaging 2015, 41(2):505-516.10.1002/jmri.24560\u003c/li\u003e\n\u003cli\u003eDyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhall CJ, Ebbers T, Francios CJ, Frydrychowicz A, Geiger J, Giese D et al (2015) 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson 2015, 17(1):72.10.1186/s12968-015-0174-5\u003c/li\u003e\n\u003cli\u003eRijnberg FM, Westenberg JJM, van Assen HC, Juffermans JF, Kroft LJM, van den Boogaard PJ, Terol Espinosa de Los Monteros C, Warmerdam EG, Leiner T, Grotenhuis HB et al (2022) 4D flow cardiovascular magnetic resonance derived energetics in the Fontan circulation correlate with exercise capacity and CMR-derived liver fibrosis/congestion. J Cardiovasc Magn Reson 2022, 24(1):21.10.1186/s12968-022-00854-4\u003c/li\u003e\n\u003cli\u003eElbaz MS, van der Geest RJ, Calkoen EE, de Roos A, Lelieveldt BP, Roest AA, Westenberg JJ (2017) Assessment of viscous energy loss and the association with three-dimensional vortex ring formation in left ventricular inflow: In vivo evaluation using four-dimensional flow MRI. Magn Reson Med 2017, 77(2):794-805.10.1002/mrm.26129\u003c/li\u003e\n\u003cli\u003eSluysmans TC, S. D.: Structural measurements and adjustment for growth. In: Echocardiography in Pediatric and Congenital Heart Disease. Edited by Lai WWM, S. C.; Geva, T.; Mertens, L. L., 1st edn. West Sussex, UK: WIley-Blackwell; 2009. \u003c/li\u003e\n\u003cli\u003eColan SD: Normal echocardiographic values for cardiovascular structures. In: Echocardiography in Pediatric and Congenital Heart Disease. Edited by Lai WWM, S. C.; Geva, T.; Mertens, L. L., 1st edn. West Sussex, UK: Wiley-Blackwell; 2009: 765-785. \u003c/li\u003e\n\u003cli\u003eMarkl M, Harloff A, Bley TA, Zaitsev M, Jung B, Weigang E, Langer M, Hennig J, Frydrychowicz A (2007) Time-resolved 3D MR velocity mapping at 3T: improved navigator-gated assessment of vascular anatomy and blood flow. J Magn Reson Imaging 2007, 25(4):824-831.10.1002/jmri.20871\u003c/li\u003e\n\u003cli\u003eJarvis K, Pruijssen JT, Son AY, Allen BD, Soulat G, Vali A, Barker AJ, Hoel AW, Eskandari MK, Malaisrie SC et al (2020) Parametric Hemodynamic 4D Flow MRI Maps for the Characterization of Chronic Thoracic Descending Aortic Dissection. J Magn Reson Imaging 2020, 51(5):1357-1368.10.1002/jmri.26986\u003c/li\u003e\n\u003cli\u003eJarvis K, Soulat G, Scott M, Vali A, Pathrose A, Syed AA, Kinno M, Prabhakaran S, Collins JD, Markl M (2021) Investigation of Aortic Wall Thickness, Stiffness and Flow Reversal in Patients With Cryptogenic Stroke: A 4D Flow MRI Study. J Magn Reson Imaging 2021, 53(3):942-952.10.1002/jmri.27345\u003c/li\u003e\n\u003cli\u003eKlitsie LM, Roest AA, Kuipers IM, Hazekamp MG, Blom NA, Ten Harkel AD (2014) Left and right ventricular performance after arterial switch operation. J Thorac Cardiovasc Surg 2014, 147(5):1561-1567.10.1016/j.jtcvs.2013.07.048\u003c/li\u003e\n\u003cli\u003ePees C, Laufer G, Michel-Behnke I (2013) Similarities and differences of the aortic root after arterial switch and ross operation in children. Am J Cardiol 2013, 111(1):125-130.10.1016/j.amjcard.2012.08.059\u003c/li\u003e\n\u003cli\u003eDiaz A, Galli C, Tringler M, Ramirez A, Cabrera Fischer EI (2014) Reference values of pulse wave velocity in healthy people from an urban and rural argentinean population. Int J Hypertens 2014, 2014:653239.10.1155/2014/653239\u003c/li\u003e\n\u003cli\u003eVoges I, Jerosch-Herold M, Hedderich J, Hart C, Petko C, Scheewe J, Andrade AC, Pham M, Gabbert D, Kramer HH et al (2013) Implications of early aortic stiffening in patients with transposition of the great arteries after arterial switch operation. Circ Cardiovasc Imaging 2013, 6(2):245-253.10.1161/CIRCIMAGING.112.000131\u003c/li\u003e\n\u003cli\u003eZhang J, Rothenberger SM, Brindise MC, Markl M, Rayz VL, Vlachos PP (2022) Wall Shear Stress Estimation for 4D Flow MRI Using Navier-Stokes Equation Correction. Ann Biomed Eng 2022, 50(12):1810-1825.10.1007/s10439-022-02993-2\u003c/li\u003e\n\u003cli\u003eSchafer M, Kheyfets VO, Schroeder JD, Dunning J, Shandas R, Buckner JK, Browning J, Hertzberg J, Hunter KS, Fenster BE (2016) Main pulmonary arterial wall shear stress correlates with invasive hemodynamics and stiffness in pulmonary hypertension. Pulm Circ 2016, 6(1):37-45.10.1086/685024\u003c/li\u003e\n\u003cli\u003eGarcia J, van der Palen RLF, Bollache E, Jarvis K, Rose MJ, Barker AJ, Collins JD, Carr JC, Robinson J, Rigsby CK et al (2018) Distribution of blood flow velocity in the normal aorta: Effect of age and gender. J Magn Reson Imaging 2018, 47(2):487-498.10.1002/jmri.25773\u003c/li\u003e\n\u003cli\u003eScott MB, Huh H, van Ooij P, Chen V, Herrera B, Elbaz M, McCarthy P, Malaisrie SC, Carr J, Fedak PWM et al (2020) Impact of age, sex, and global function on normal aortic hemodynamics. Magn Reson Med 2020, 84(4):2088-2102.10.1002/mrm.28250\u003c/li\u003e\n\u003cli\u003eRutkowski DR, Barton GP, Francois CJ, Aggarwal N, Roldan-Alzate A (2020) Sex Differences in Cardiac Flow Dynamics of Healthy Volunteers. Radiol Cardiothorac Imaging 2020, 2(1).10.1148/ryct.2020190058\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Transposition of the great arteries, Arterial switch operation, 4D flow MRI, Wall shear stress, Cardiac MRI","lastPublishedDoi":"10.21203/rs.3.rs-5133875/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5133875/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePulmonary artery stenosis, neoaortic dilatation, and neoaortic valve insufficiency are among the most frequent complications of the arterial switch operation for repair of dextro-transposition of the great arteries (d-TGA). It remains difficult to predict which patients will require great arterial reintervention.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eWe aimed to characterize hemodynamics within the great arteries using 4D flow MRI in patients with d-TGA after the arterial switch operation.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003ePatients with d-TGA after the arterial switch operation and controls with normal cardiac anatomy who underwent 4D flow MRI between 2012 and 2024 were included. Velocity, stasis, kinetic energy, energy loss, wall shear stress, and pulse wave velocity were quantified in the aorta and pulmonary arteries.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePatients with d-TGA after the arterial switch operation (15.7 years\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4) demonstrated significantly higher maximum and mean velocity, maximum and mean kinetic energy, energy loss, and maximum and mean wall shear stress within the pulmonary arteries (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for all parameters) compared with age-matched controls (15.5 years\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4). Aortic maximum (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0011) and mean (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0483) velocity, maximum (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0008) and mean (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0026) kinetic energy, energy loss (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), maximum wall shear stress in five of six regions (range \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 to \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0022), and mean wall shear stress in three regions (range \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0052 to \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0310) were significantly higher in patients with d-TGA after the arterial switch operation patients compared with age-matched controls.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePatients with d-TGA after the arterial switch operation demonstrate hemodynamic abnormalities within the great arteries, which may provide insight into the mechanisms underlying postoperative consequences of the arterial switch operation and the need for reintervention.\u003c/p\u003e","manuscriptTitle":"Hemodynamic evaluation of the pulmonary arteries and aorta using 4D flow cardiac MRI in children and young adults with dextro-transposition of the great arteries after the arterial switch operation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-15 06:49:33","doi":"10.21203/rs.3.rs-5133875/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-29T14:39:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-13T11:20:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-01T20:41:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282818452625615735536086649854658138079","date":"2024-09-30T11:00:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39801098462992878961613669618467340696","date":"2024-09-25T20:36:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170932310785963108485339008790795543924","date":"2024-09-23T17:22:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-23T17:03:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-23T15:12:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-23T15:11:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pediatric Radiology","date":"2024-09-22T20:18:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ca3cad26-8bc2-49af-afc8-7706024f5980","owner":[],"postedDate":"November 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:10:56+00:00","versionOfRecord":{"articleIdentity":"rs-5133875","link":"https://doi.org/10.1007/s00247-024-06110-4","journal":{"identity":"pediatric-radiology","isVorOnly":false,"title":"Pediatric Radiology"},"publishedOn":"2024-12-20 15:57:45","publishedOnDateReadable":"December 20th, 2024"},"versionCreatedAt":"2024-11-15 06:49:33","video":"","vorDoi":"10.1007/s00247-024-06110-4","vorDoiUrl":"https://doi.org/10.1007/s00247-024-06110-4","workflowStages":[]},"version":"v1","identity":"rs-5133875","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5133875","identity":"rs-5133875","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}