Increased aortic pressures and pulsatile afterload components promote concentric left ventricular remodeling in adults with transposition of the great arteries and arterial switch operation.

BACKGROUND: Functional abnormalities of the ascending aorta (AA) have been mainly reported in young patients who underwent arterial switch operation (ASO) for transposition of the great arteries (TGA). OBJECTIVES: To compare systolic, diastolic brachial and central blood pressures (bSBP, bDBP, cSBP, cDBP), aortic biomechanical parameters, and left ventricular (LV) afterload criteria in adult ASO patients with healthy controls and to assess their relationships with LV remodeling and aortic size. MATERIALS AND METHODS: Forty-one prospectively enrolled patients (16.8 to 35.8 years) and 41 age- and sex-matched healthy volunteers underwent cardiac MRI to assess LV remodeling with simultaneous brachial BP estimation. After MRI, carotid-femoral tonometry was performed to measure pulse wave velocity (cfPWV), cSBP and cDBP for further calculation of pulse pressure (cPP), AA distensibility (AAD), and AA and LV elastance (AAE, LVE). RESULTS: bSBP, bDBP, cSBP,cDBP and cPP were all significantly higher in ASO group than in controls: cSBP (116.5 ± 13.8 vs 106.1 ± 12.0, p < 0.001), cDBP (72.5 ± 6.9 vs 67.1 ± 9.4, p = 0.002), cPP (44.0 ± 12.1 vs 39.1 ± 8.9, p = 0.003) and not related to aortic size. AAD were decreased in ASO patients vs controls (4.70 ± 2.72 vs 6.69 ± 2.16, p < 0.001). LV mass was correlated with bSBP, cSBP, cPP (ρ = 0.48; p < 0.001), while concentric LV remodeling was correlated with AAE (ρ = 0.60, p < 0.001) and LVE (ρ = 0.32, p = 0.04), but not with distensibility. CONCLUSION: Even without reaching arterial hypertension, aortic sBP and PP are increased in the adult TGA population after ASO, altering the pulsatile components of afterload and contributing to LV concentric remodeling.

Four-dimensional flow cardiovascular magnetic resonance aortic cross-sectional pressure changes and their associations with flow patterns in health and ascending thoracic aortic aneurysm.

BACKGROUND: Ascending thoracic aortic aneurysm (ATAA) is a silent and threatening dilation of the ascending aorta (AscAo). Maximal aortic diameter which is currently used for ATAA patients management and surgery planning has been shown to inadequately characterize risk of dissection in a large proportion of patients. Our aim was to propose a comprehensive quantitative evaluation of aortic morphology and pressure-flow-wall associations from four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) data in healthy aging and in patients with ATAA. METHODS: We studied 17 ATAA patients (64.7 ± 14.3 years, 5 females) along with 17 age- and sex-matched healthy controls (59.7 ± 13.3 years, 5 females) and 13 younger healthy subjects (33.5 ± 11.1 years, 4 females). All subjects underwent a CMR exam, including 4D flow and three-dimensional anatomical images of the aorta. This latter dataset was used for aortic morphology measurements, including AscAo maximal diameter (iDMAX) and volume, indexed to body surface area. 4D flow MRI data were used to estimate 1) cross-sectional local AscAo spatial (∆PS) and temporal (∆PT) pressure changes as well as the distance (∆DPS) and time duration (∆TPT) between local pressure peaks, 2) AscAo maximal wall shear stress (WSSMAX) at peak systole, and 3) AscAo flow vorticity amplitude (VMAX), duration (VFWHM), and eccentricity (VECC). RESULTS: Consistency of flow and pressure indices was demonstrated through their significant associations with AscAo iDMAX (WSSMAX:r = -0.49, p < 0.001; VECC:r = -0.29, p = 0.045; VFWHM:r = 0.48, p < 0.001; ∆DPS:r = 0.37, p = 0.010; ∆TPT:r = -0.52, p < 0.001) and indexed volume (WSSMAX:r = -0.63, VECC:r = -0.51, VFWHM:r = 0.53, ∆DPS:r = 0.54, ∆TPT:r = -0.63, p < 0.001 for all). Intra-AscAo cross-sectional pressure difference, ∆PS, was significantly and positively associated with both VMAX (r = 0.55, p = 0.002) and WSSMAX (r = 0.59, p < 0.001) in the 30 healthy subjects (48.3 ± 18.0 years). Associations remained significant after adjustment for iDMAX, age, and systolic blood pressure. Superimposition of ATAA patients to normal aging trends between ∆PS and WSSMAX as well as VMAX allowed identifying patients with substantially high pressure differences concomitant with AscAo dilation. CONCLUSION: Local variations in pressures within ascending aortic cross-sections derived from 4D flow MRI were associated with flow changes, as quantified by vorticity, and with stress exerted by blood on the aortic wall, as quantified by wall shear stress. Such flow-wall and pressure interactions might help for the identification of at-risk patients.

Deep Learning-Based Analysis of Aortic Morphology From Three-Dimensional MRI.

BACKGROUND: Quantification of aortic morphology plays an important role in the evaluation and follow-up assessment of patients with aortic diseases, but often requires labor-intensive and operator-dependent measurements. Automatic solutions would help enhance their quality and reproducibility. PURPOSE: To design a deep learning (DL)-based automated approach for aortic landmarks and lumen detection derived from three-dimensional (3D) MRI. STUDY TYPE: Retrospective. POPULATION: Three hundred ninety-one individuals (female: 47%, age = 51.9 ± 18.4) from three sites, including healthy subjects and patients (hypertension, aortic dilation, Turner syndrome), randomly divided into training/validation/test datasets (N = 236/77/78). Twenty-five subjects were randomly selected and analyzed by three operators with different levels of expertise. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T, 3D spoiled gradient-recalled or steady-state free precession sequences. ASSESSMENT: Reinforcement learning and a two-stage network trained using reference landmarks and segmentation from an existing semi-automatic software were used for aortic landmark detection and segmentation from sinotubular junction to coeliac trunk. Aortic segments were defined using the detected landmarks while the aortic centerline was extracted from the segmentation and morphological indices (length, aortic diameter, and volume) were computed for both the reference and the proposed segmentations. STATISTICAL TESTS: Segmentation: Dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetrical surface distance (ASSD); landmark detection: Euclidian distance (ED); model robustness: Spearman correlation, Bland-Altman analysis, Kruskal-Wallis test for comparisons between reference and DL-derived aortic indices; inter-observer study: Williams index (WI). A WI 95% confidence interval (CI) lower bound >1 indicates that the method is within the inter-observer variability. A P-value <0.05 was considered statistically significant. RESULTS: DSC was 0.90 ± 0.05, HD was 12.11 ± 7.79 mm, and ASSD was 1.07 ± 0.63 mm. ED was 5.0 ± 6.1 mm. A good agreement was found between all DL-derived and reference aortic indices (r >0.95, mean bias <7%). Our segmentation and landmark detection performances were within the inter-observer variability except the sinotubular junction landmark (CI = 0.96;1.04). DATA CONCLUSION: A DL-based aortic segmentation and anatomical landmark detection approach was developed and applied to 3D MRI data for achieve aortic morphology evaluation. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Aortic Stiffness Measured from Either 2D/4D Flow and Cine MRI or Applanation Tonometry in Coronary Artery Disease: A Case-Control Study.

BACKGROUND AND OBJECTIVE: Aortic stiffness can be evaluated by aortic distensibility or pulse wave velocity (PWV) using applanation tonometry, 2D phase contrast (PC) MRI and the emerging 4D flow MRI. However, such MRI tools may reach their technical limitations in populations with cardiovascular disease. Accordingly, this work focuses on the diagnostic value of aortic stiffness evaluated either by applanation tonometry or MRI in high-risk coronary artery disease (CAD) patients. METHODS: 35 patients with a multivessel CAD and a myocardial infarction treated 1 year before were prospectively recruited and compared with 18 controls with equivalent age and sex distribution. Ascending aorta distensibility and aortic arch 2D PWV were estimated along with 4D PWV. Furthermore, applanation tonometry carotid-to-femoral PWV (cf PWV) was recorded immediately after MRI. RESULTS: While no significant changes were found for aortic distensibility; cf PWV, 2D PWV and 4D PWV were significantly higher in CAD patients than controls (12.7 ± 2.9 vs. 9.6 ± 1.1; 11.0 ± 3.4 vs. 8.0 ± 2.05 and 17.3 ± 4.0 vs. 8.7 ± 2.5 m·s-1 respectively, p < 0.001). The receiver operating characteristic (ROC) analysis performed to assess the ability of stiffness indices to separate CAD subjects from controls revealed the highest area under the curve (AUC) for 4D PWV (0.97) with an optimal threshold of 12.9 m·s-1 (sensitivity of 88.6% and specificity of 94.4%). CONCLUSIONS: PWV estimated from 4D flow MRI showed the best diagnostic performances in identifying severe stable CAD patients from age and sex-matched controls, as compared to 2D flow MRI PWV, cf PWV and aortic distensibility.

Associations of aortic stiffness and intra-aortic flow parameters with epicardial adipose tissue in patients with type-2 diabetes.

Background: It has been shown that increased aortic stiffness is related to type-2 diabetes (T2D) which is considered as a risk factor for cardiovascular disease. Among other risk factors is epicardial adipose tissue (EAT) which is increased in T2D and is a relevant biomarker of metabolic severity and adverse outcome. Purpose: To assess aortic flow parameters in T2D patients as compared to healthy individuals and to evaluate their associations with EAT accumulation as an index of cardiometabolic severity in T2D patients. Materials and methods: Thirty-six T2D patients as well as 29 healthy controls matched by age and sex were included in this study. Participants had cardiac and aortic MRI exams at 1.5 T. Imaging sequences included cine SSFP for left ventricle (LV) function and EAT assessment and aortic cine and phase-contrast imaging for strain and flow parameters quantification. Results: In this study, we found LV phenotype to be characterized by concentric remodeling with decreased stroke volume index despite global LV mass within a normal range. EAT was increased in T2D patients compared to controls (p<0.0001). Moreover, EAT, a biomarker of metabolic severity, was negatively correlated to ascending aortic (AA) distensibility (p=0.048) and positively to the normalized backward flow volume (p=0.001). These relationships remained significant after further adjustment for age, sex and central mean blood pressure. In a multivariate model, presence/absence of T2D and AA normalized backward flow (BF) to forward flow (FF) volumes ratio are both significant and independent correlates of EAT. Conclusion: In our study, aortic stiffness as depicted by an increased backward flow volume and decreased distensibility seems to be related to EAT volume in T2D patients. This observation should be confirmed in the future on a larger population while considering additional biomarkers specific to inflammation and using a longitudinal prospective study design.

Value of aortic volumes assessed by automated segmentation of 3D MRI data in patients with thoracic aortic dilatation: A case-control study.

PURPOSE: The purpose of this study was to investigate the benefit of aortic volumes compared to diameters or cross-sectional areas on three-dimensional (3D) magnetic resonance imaging (MRI) in discriminating between patients with dilated aorta and matched controls. MATERIALS AND METHODS: Sixty-two patients (47 men and 15 women; median age, 66 years; age range: 33-86 years) with tricuspid aortic valve and ascending thoracic aorta aneurysm (TAV-ATAA) and 43 patients (35 men and 8 women; median age, 51 years; age range: 17-76 years) with bicuspid aortic valve and dilated ascending aorta (BAV) were studied. One group of 54 controls matched for age and sex to patients with TAV-ATAA (39 men and 15 women; median age, 68 years; age range: 33-81 years) and one group of 42 controls matched for age and sex to patients with BAV (34 men and 8 women; median age, 50 years; age range: 17-77 years) were identified. All participants underwent 3D MRI, used for 3D-segmentation for measuring aortic length, maximal diameter, maximal cross-sectional area (CSA) and volume for the ascending aorta. RESULTS: An increase in ascending aorta volume (TAV-ATAA: +107%; BAV: +171% vs. controls; P < 0.001) was found, which was three times greater than the increase in diameter (TAV-ATAA: +29%; BAV: +40% vs. controls; P < 0.001). In differentiating patients with TAV-ATAA from their controls, the indexed ascending aorta volume showed better performances (AUC, 0.935 [95% confidence interval (CI): 0.882-0.989]; accuracy, 88.7% [95% CI: 82.9-94.5]) than indexed ascending aorta length (P < 0.001), indexed ascending aorta maximal diameter (P = 0.003) and indexed ascending aorta maximal CSA (P = 0.03). In differentiating patients with BAV from matched controls, indexed ascending aorta volume showed significantly better performances performance (AUC, 0.908 [95% CI: 0.829-0.987]; accuracy, 88.0% [95% CI: 80.9-95.0]) than indexed ascending aorta length (P = 0.02) and not different from indexed ascending aorta maximal diameter (P = 0.07) or from indexed ascending aorta maximal CSA (P = 0.27) CONCLUSION: Aortic volume measured by 3D-MRI integrates both elongation and luminal dilatation, resulting in greater classification performance than maximal diameter and length in differentiating patients with dilated ascending aorta or aneurysm from controls.

Abdominal adipose tissue components quantification in MRI as a relevant biomarker of metabolic profile.

INTRODUCTION: Abnormal accumulation of adipose tissue (AT) alters the metabolic profile and underlies cardiovascular complications. Conventional measures provide global measurements for the entire body. The purpose of this study was to propose a new approach to quantify the amount and type of truncal AT automatically from MRI in metabolic patients and controls. MATERIALS AND METHODS: DIXON acquisitions were performed at 1.5 T in 30 metabolic syndrome (MS) (59 ± 6 years), 12 obese (50 ± 11 years), 35 type 2 diabetes (T2DM) patients (56 ± 11 years) and 19 controls (52 ± 11 years). AT was segmented into: subcutaneous AT "SAT", visceral AT "VAT", deep VAT "dVAT", peri-organ VAT "pVAT" using active contours and k-means clustering algorithms. Subsequently, organ AT infiltration index "oVAT" was calculated as the normalized fat signal magnitude in organs. RESULTS: Excellent intra- and inter-operator reproducibility was obtained for AT segmentation. MS and obese patients had the highest amount of total AT. SAT increased in MS (1144 ± 621 g) and T2DM patients (1024 ± 634 g), and twice the level of SAT in controls (505 ± 238 g), and further increased in obese patients (1429 ± 621 g). While VAT, pVAT and dVAT increased to a similar degree in the metabolic patients compared to controls, the oVAT index was able to differentiate controls from MS and T2DM patients and to discriminate the three metabolic patient groups (p < 0.01). Local AT sub-types were not related to BMI in all groups except for SAT in controls (p = 0.03). CONCLUSION: Reproducible truncal AT sub-types quantification using 3D MRI was able to characterize patients with metabolic diseases. It may serve in the future as a non-invasive predictor of cardiovascular complications in such patients.

Quantitative magnetic resonance imaging measures of three-dimensional aortic morphology in healthy aging and hypertension.

Automated segmentation of three-dimensional (3D) aortic magnetic resonance imaging (MRI) renders a possible retrospective selection of any location to perform quantification of aortic caliber perpendicular to its centerline and provides regional and global 3D biomarkers such as length, diameter, or volume. However, normative age-related values of such measures are still lacking. The aim of this study was to provide normal values for 3D aortic morphological measures and investigate their changes in aging and hypertension. This was a retrospective study, in which 119 healthy controls (HC: 48 ± 14 years, 61 men) and 82 hypertensive patients (HT: 60 ± 14 years, 43 men) were enrolled. 1.5 and 3 T/3D steady state free precession or spoiled gradient echo were used. Automated 3D aortic segmentation provided aortic length, diameter, volume for the ascending (AAo), and descending aorta (DAo), along with cross-sectional diameters at three aortic landmarks. Age, sex, body surface area (BSA), smoking, and blood pressures were recorded. Both groups were divided into two subgroups (≤50 years, >50 years). Statistical tests performed were linear regression for age-related normal values and confidence intervals, Wilcoxon rank sum test for differences between groups (HC or HT), and multivariate analysis to identify main determinants of aortic morphological changes. In HC, linear regression revealed an increase in the AAo (respectively DAo) length by 2.84 mm (7.78 mm), maximal diameter by 1.36 mm (1.29 mm), and volume by 4.28 ml (8.71 ml) per decade. AAo morphological measures were higher in HT patients than in HC both ≤50 years but did not reach statistical significance (length: +2 mm, p = 0.531; diameter: +1.4 mm, p = 0.2936; volume:+6.8 ml, p = 0.1857). However, length (+6 mm, p = 0.003), maximal diameter (+4 mm, p < 0.001) and volume (+12 ml, p < 0.001) were significantly higher in HT patients than in HC, both >50 years. In a multivariate analysis, age, sex, and BSA were the major determinants of aortic morphology, irrespective of the presence of hypertension. Global and segmental aortic length, volume, and diameters at specific landmarks were automatically measured from 3D MRI to serve as normative measures of 3D aortic morphology. Such indices increased significantly with age and hypertension among the elderly subjects. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Non-invasive evaluation of retinal vascular remodeling and hypertrophy in humans: intricate effect of ageing, blood pressure and glycaemia.

BACKGROUND: Ageing, hypertension and diabetes have an intricate effect on microvascular structure. In the retina, the respective contribution of remodeling and hypertrophy in such process is still unclear. We aimed at disentangling age, blood pressure and glycaemia effects on retinal microcirculation using the non-invasive adaptive optics ophthalmoscopy (AOO). METHODS: We included 429 subjects, distributed into 4 groups according to normal (nBP) or high blood pressure (hBP) and/or normal (nGly) or high fasting glycaemia (hGly). The nBP/nGly group was stratified in age tertiles to isolate the effect of ageing. AOO was used to measure arteriolar wall thickness (WT, µm), arteriolar (aID, µm) and venular internal diameter (vID, µm) and calculate arteriolar wall-to-lumen ratio (WLR), wall cross-sectional area (WCSA, µm2). One-way ANOVA for parametric variables and Kruskal-Wallis test for non-parametric variables were used for comparison among groups. A multivariate regression analysis including age, gender, BP, hGly and antihypertensive treatment was performed to calculate independent predictors of retinal remodeling. RESULTS: WT was increased with ageing (tertile1: 22.5 ± 3.2, tertile2: 24.2 ± 3.5, tertile 3: 25.2 ± 3.8, p = 0.001) and BP (hBP: 25.2 ± 4.1 vs nBP: 23.9 ± 3.7, p = 0.003). aID decreased with BP (hBP: 90.2 ± 13.4 vs nBP: 93.6 ± 11.6, p = 0.013) and increased with glycaemia (hGly: 97.7 ± 12.5 vs nGly: 93.6 ± 11.6, p = 0.002). A multivariate analysis showed independent association of hBP with WLR; hGly with WCSA; ageing with WLR and WCSA. CONCLUSIONS: AOO non-invasively identifies retinal structural changes in human confirming that microvascular remodeling is exclusively related to hypertension, whereas vascular growth is related to ageing and hyperglycaemia.

Comprehensive assessment of local and regional aortic stiffness in patients with tricuspid or bicuspid aortic valve aortopathy using magnetic resonance imaging.

BACKGROUND: We aimed to provide a comprehensive aortic stiffness description using magnetic resonance imaging (MRI) in patients with ascending thoracic aorta aneurysm and tricuspid (TAV-ATAA) or bicuspid (BAV) aortic valve. METHODS: This case-control study included 18 TAV-ATAA and 19 BAV patients, with no aortic valve stenosis/severe regurgitation, who were 1:1 age-, gender- and central blood pressures (BP)-matched to healthy volunteers. Each underwent simultaneous aortic MRI and BP measurements. 3D anatomical MRI provided aortic diameters. Stiffness indices included: regional ascending (AA) and descending (DA) aorta pulse wave velocity (PWV) from 4D flow MRI; local AA and DA strain, distensibility and theoretical Bramwell-Hill (BH) model-based PWV, as well as regional arch PWV from 2D flow MRI. RESULTS: Patient groups had significantly higher maximal AA diameter (median[interquartile range], TAV-ATAA: 47.5[42.0-51.3]mm, BAV: 45.0[41.0-47.0]mm) than their respective controls (29.1[26.8-31.8] and 28.1[26.0-32.0]mm, p < 0.0001), while BP were similar (p ≥ 0.25). Stiffness indices were significantly associated with age (ρ ≥ 0.33), mean BP (arch PWV: ρ = 0.25, p = 0.05; DA distensibility: ρ = -0.30, p = 0.02) or AA diameter (arch PWV: ρ = 0.28, p = 0.03; DA PWV: ρ = 0.32, p = 0.009). None of them, however, was significantly different between TAV-ATAA or BAV patients and their matched controls. Finally, while direct PWV measures were significantly correlated to BH-PWV estimates in controls (ρ ≥ 0.40), associations were non-significant in TAV-ATAA and BAV groups (p ≥ 0.18). CONCLUSIONS: The overlap of MRI-derived aortic stiffness indices between patients with TAV or BAV aortopathy and matched controls highlights another heterogeneous feature of aortopathy, and suggests the urgent need for more sensitive indices which might help better discriminate such diseases.

Comparison of different methods for the estimation of aortic pulse wave velocity from 4D flow cardiovascular magnetic resonance.

BACKGROUND: Arterial pulse wave velocity (PWV) is associated with increased mortality in aging and disease. Several studies have shown the accuracy of applanation tonometry carotid-femoral PWV (Cf-PWV) and the relevance of evaluating central aorta stiffness using 2D cardiovascular magnetic resonance (CMR) to estimate PWV, and aortic distensibility-derived PWV through the theoretical Bramwell-Hill model (BH-PWV). Our aim was to compare various methods of aortic PWV (aoPWV) estimation from 4D flow CMR, in terms of associations with age, Cf-PWV, BH-PWV and left ventricular (LV) mass-to-volume ratio while evaluating inter-observer reproducibility and robustness to temporal resolution. METHODS: We studied 47 healthy subjects (49.5 ± 18 years) who underwent Cf-PWV and CMR including aortic 4D flow CMR as well as 2D cine SSFP for BH-PWV and LV mass-to-volume ratio estimation. The aorta was semi-automatically segmented from 4D flow data, and mean velocity waveforms were estimated in 25 planes perpendicular to the aortic centerline. 4D flow CMR aoPWV was calculated: using velocity curves at two locations, namely ascending aorta (AAo) and distal descending aorta (DAo) aorta (S1, 2D-like strategy), or using all velocity curves along the entire aortic centreline (3D-like strategies) with iterative transit time (TT) estimates (S2) or a plane fitting of velocity curves systolic upslope (S3). For S1 and S2, TT was calculated using three approaches: cross-correlation (TTc), wavelets (TTw) and Fourier transforms (TTf). Intra-class correlation coefficients (ICC) and Bland-Altman biases (BA) were used to evaluate inter-observer reproducibility and effect of lower temporal resolution. RESULTS: 4D flow CMR aoPWV estimates were significantly (p < 0.05) correlated to the CMR-independent Cf-PWV, BH-PWV, age and LV mass-to-volume ratio, with the strongest correlations for the 3D-like strategy using wavelets TT (S2-TTw) (R = 0.62, 0.65, 0.77 and 0.52, respectively, all p < 0.001). S2-TTw was also highly reproducible (ICC = 0.99, BA = 0.09 m/s) and robust to lower temporal resolution (ICC = 0.97, BA = 0.15 m/s). CONCLUSIONS: Reproducible 4D flow CMR aoPWV estimates can be obtained using full 3D aortic coverage. Such 4D flow CMR stiffness measures were significantly associated with Cf-PWV, BH-PWV, age and LV mass-to-volume ratio, with a slight superiority of the 3D strategy using wavelets transit time (S2-TTw).

Analysis of aortic pressure fields from 4D flow MRI in healthy volunteers: Associations with age and left ventricular remodeling.

BACKGROUND: Aging-related arterial stiffness is associated with substantial changes in global and local arterial pressures. The subsequent early return of reflected pressure waves leads to an elevated left ventricular (LV) afterload and ultimately to a deleterious concentric LV remodeling. PURPOSE: To compute aortic time-resolved pressure fields of healthy subjects from 4D flow MRI and to define relevant pressure-based markers while investigating their relationship with age, LV remodeling, as well as tonometric augmentation index (AIx) and pulse wave velocity (PWV). STUDY TYPE: Retrospective. POPULATION: Forty-seven healthy subjects (age: 49.5 ± 18 years, 24 women). FIELD STRENGTH/SEQUENCE: 3 T/4D flow MRI. ASSESSMENT: Spatiotemporal pressure fields were computed by integrating velocity-derived pressure gradients using Navier-Stokes equations, while assuming zero pressure at the sino-tubular junction. To quantify aortic pressure spatiotemporal variations, we defined the following markers: 1) volumetric aortic pressure propagation rates ΔP E1 /ΔV and ΔP E2 /ΔV, representing variations of early and late systolic relative pressure peaks along the aorta, respectively, according to the cumulated aortic volume; 2) ΔA PE1-PE2 defined in four aortic regions as the absolute difference between early and late systolic relative pressure peaks amplitude. STATISTICAL TESTS: Linear regression, Wilcoxon rank sum test, Bland-Altman analysis, and intraclass correlation coefficients (ICC). RESULTS: Spatiotemporal variations of aortic pressure peaks were moderately to highly reproducible (ICC ≥0.50) and decreased significantly with age, in terms of absolute magnitude: ΔP E1 /ΔV (r = 0.70, P < 0.005), ΔP E2 /ΔV (r = -0.45, P < 0.005) and ΔA PE1-PE2 (|r| > 0.39, P < 0.005). ΔP E1 /ΔV was associated with LV remodeling (r = 0.53, P < 0.001) and ascending aorta ΔA PE1-PE2 was associated with AIx (r = -0.59, P < 0.001). Both associations were independent of age and systolic blood pressures. Only weak associations were found between pressure indices and PWV (r ≤ 0.40). DATA CONCLUSION: 4D flow MRI relative aortic pressures were consistent with physiological knowledge as demonstrated by their significant volumetric and temporal variations with age and their independent association with LV remodeling and augmentation index. Level of Evidence 2 Technical Efficacy Stage 3 J. Magn. Reson. Imaging 2019;50:982-993.

3D aortic morphology and stiffness in MRI using semi-automated cylindrical active surface provides optimized description of the vascular effects of aging and hypertension.

BACKGROUND: Clinically, aortic geometry assessment is mainly based on the measurement of maximal diameters at different anatomic locations, which are subsequently used to indicate prophylactic aortic surgery. However, 3D evaluation of aortic morphology could provide volumetric quantification, which integrates both aortic dilatation and elongation and might thus be more sensitive to early geometric changes than diameters. Precise aortic morphology is also required for the calculation of pulse wave velocity (PWVMRI), an established marker of aortic stiffness. Accordingly, we proposed a 3D semi-automated analysis of thoracic aorta MRI data optimizing morphological and subsequent stiffness assessment. METHODS: We studied 74 individuals (40 males, 50 ± 12years): 21 healthy volunteers and 53 patients with hypertension in whom aortic 3D MRI angiography and 2D + t phase-contrast and cine imaging were performed. A semi-automated method was proposed for volumetric aortic segmentation and was evaluated by studying resulting measurements (length, diameters, volumes and PWVMRI) in terms of: 1) reproducibility, 2) correlations with well-established 2D aortic length and diameters, 3) associations with age, carotid-femoral PWV (cf-PWV) and presence of hypertension. RESULTS: The measurements obtained with the proposed method were reproducible (coefficients of variation ≤ 5.1%) and were highly correlated with 2D measurements (arch length: r = 0.80, Bland-Altman mean bias [limits]: 2.7 mm [-25; 30]; PWVMRI: r = 0.95, 0.22 m/s [-1.9; 2.4]). Higher or similar correlations with age were found for the proposed 3D method compared to the 2D approach (arch length: r = 0.47 (2D), r = 0.60 (3D); PWVMRI: r = 0.63 (2D), r = 0.64 (3D)). Moreover, a significant association was found between PWVMRI and cf-PWV (r = 0.49, p < 0.001). All aortic measurements increased with hypertension (p < 0.05) and with age: arch length (+9mm/decade); diameters: ascending (+1.2mm/decade) and descending aorta (+1.0mm/decade); volumes: ascending (+2.6mL/decade) and descending aorta (+4.0mL/decade); PWVMRI (+1.7  m s-1/decade). CONCLUSIONS: A semi-automated method based on cylindrical active surfaces was proposed for the 3D segmentation of the aorta using a single MRI dataset, providing aortic diameters at anatomical landmarks, aortic volumes and the aortic centerline length used for PWV estimation. Such measurements were reproducible and comparable to expert measurements, which required time-consuming centerline delineation. Furthermore, expected relationships with age and hypertension were found indicating the consistency of our measurements.

heartBEATS: A hybrid energy approach for real-time B-spline explicit active tracking of surfaces.

In this manuscript a novel method is presented for left ventricle (LV) tracking in three-dimensional ultrasound data using a hybrid approach combining segmentation and tracking-based clues. This is accomplished by coupling an affine motion model to an existing LV segmentation framework and introducing an energy term that penalizes the deviation to the affine motion estimated using a global Lucas-Kanade algorithm. The hybrid nature of the proposed solution can be seen as using the estimated affine motion to enhance the temporal coherence of the segmented surfaces, by enforcing the tracking of consistent patterns, while the underlying segmentation algorithm allows to locally refine the estimated global motion. The proposed method was tested on a dataset composed of 24 4D ultrasound sequences from both healthy volunteers and diseased patients. The proposed hybrid tracking platform offers a competitive solution for fast assessment of relevant LV volumetric indices, by combining the robustness of affine motion tracking with the low computational burden of the underlying segmentation algorithm.

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces.

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

Quantification of left ventricular volume and global function using a fast automated segmentation tool: validation in a clinical setting.

Real-time 3D echocardiography (RT3DE) has already been shown to be an accurate tool for left ventricular (LV) volume assessment. However, LV border detection in RT3DE remains a time-consuming task jeopardizing the application of this modality in routine practice. We have recently developed a 3D automated segmentation framework (BEAS) able to capture the LV morphology in real-time. The goal of this study was to assess the accuracy of this approach in extracting volumetric parameters in a clinical setting. 24 RT3DE exams were acquired in a group of healthy volunteers (# = 5) and diseased patients (# = 19), with LV volume/function within a range typically measured in a clinical setting. End-diastolic and end-systolic volumes (EDV, ESV) were manually contoured by 3 expert sonographers from which the stroke volume and ejection fraction (SV, EF) were calculated. The values extracted with BEAS were compared to the average of the 3 experts measurements using correlation and Bland-Altman statistics. Linear regression analysis showed a strong correlation between the automated algorithm and the reference values (R = 0.963, 0.947, 0.944 and 0.853 for EDV, ESV, SV and EF respectively). Bland-Altman analysis revealed a bias (limits of agreement) of 2.59 (-25.39, 30.57) ml, -2.11 (-24.91, 20.69) ml, 4.70 (12.93, 22.34) ml and 3.45 (-8.96, 15.87) %, for EDV, ESV, SV and EF respectively. Total analysis time using BEAS was 30.7 ± 7.5 s. BEAS allows for a fast and accurate quantification of 3D cardiac volumes and global function with minimal user input. It may therefore contribute to the integration of 3D echocardiography in routine clinical practice.

Fast and fully automatic 3-d echocardiographic segmentation using B-spline explicit active surfaces: feasibility study and validation in a clinical setting.

A novel framework to efficiently deal with three-dimensional (3-D) segmentation of challenging inhomogeneous data in real-time has been recently introduced by the authors. However, the existing framework still relied on manual initialization, which prevented taking full advantage of the computational speed of the method. In the present article, an automatic initialization scheme adapted to 3-D, echocardiographic data is proposed. Moreover, a novel segmentation functional, which explicitly takes the darker appearance of the blood into account, is also introduced. The resulting automatic segmentation framework provides an efficient, fast and accurate solution for quantification of the main left ventricular volumetric indices used in clinical routine. In practice, the observed computation times are in the order of 1 s.

B-spline explicit active surfaces: an efficient framework for real-time 3-D region-based segmentation.

A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also show that this framework allows evolving the active contour using local region-based terms, thereby overcoming the limitations of the original method while preserving computational speed. The feasibility of real-time 3-D segmentation is demonstrated using simulated and medical data such as liver computer tomography and cardiac ultrasound images.