Clinical impact on treatment and prognosis of advanced cardiac imaging with echocardiography in the acute setting of a COVID-19 infection

Background and objectives

Despite myocardial injury being related to excess mortality in acute COVID-19 infection, its impact on imaging findings remains unclear. This study aimed to characterize transthoracic echocardiographic (TTE) findings in patients admitted with COVID-19 infections and its impact on management and prognosis.

Methods

A prospective observational cohort study was performed among 66 COVID-19 patients who were admitted to a tertiary center between March 1 and May 25, 2020 and underwent TTE. High-sensitivity troponin I (hs-cTnI) data, echocardiographic assessment of right and left ventricular (LV) functional parameters, strain, and myocardial work analysis were obtained.

Results

2025 patients were admitted with COVID-19 and in 200 a complete TTE study was performed. Due to poor image quality, only 66 studies were included in the final analysis. The median age was 62 years (IQR, 55–70) and 59.1% of patients were males. The most common comorbidity was hypertension (47%), followed by smoking history (30.3%), atrial fibrillation (9.1%), and chronic obstructive pulmonary disease (7.9%). More than half of the patients (39, 59%) were admitted to the ICU, and half of them (33, 50%) required invasive mechanical ventilation. TTE was mainly indicated because of concerns for systemic conditions (50%) and evaluation of hemodynamic assessment (30%). Thirty-six patients (54.5%) had an abnormal TTE result and 57% had elevated hs-cTnI levels. The most common cardiac abnormality was LV diastolic dysfunction in 33% of the patients, followed by right ventricular dysfunction (12%) and LV dysfunction (6%) (Figure 1). LV GLS was reduced in 48.5% of the cases. Myocardial work performance indices were all reduced in patients with an abnormal TTE (GWI 30%, GCW 30%, GWW 40%, and GWE 40%), although differences were not significant (P>0.2 for all parameters). Patients with an abnormal TTE were older and presented a higher cardiovascular risk profile. There were no significant differences in the levels of D-dimer, NTproBNP, and hs-cTnI between patients with and without diastolic dysfunction, RV, or LV dysfunction (P>0.3 for all parameters). Using Spearman rank correlation, there was an inverse relationship between hs-cTnI and LV strain and myocardial work analysis. TTE results impacted clinical management in 60 patients, mainly de-escalation of medical treatment (Figure 2). Abnormal TTE results did not impact in-hospital outcomes.

Conclusions

Severe echocardiographic abnormalities are uncommon in hospitalized patients with COVID-19 infections, presenting mostly with subclinical myocardial changes, such as diastolic dysfunction, reduced LV GLS, and myocardial work indices, both associated with high-sensitivity troponin I elevation. An echocardiographic study should be limited to rule out long-term ICU complications or to evaluate hemodynamic instability. Although TTE was a valuable tool for guiding management, it had no significant impact on prognosis.

Funding Acknowledgement

Type of funding sources: None. Figure 1. Findings on TTE studies.Figure 2. Changes in management.

Routine advanced echocardiography in the evaluation of cardiovascular sequelae of COVID19 survivors with elevated cardiovascular biomarkers

Background

COVID19 has been related to elevated CVB and biventricular dysfunction during hospitalization. However, it is unknown whether patients with biomarker elevation exhibit long-lasting abnormalities in cardiac function.

Purpose

To determine, using advanced echocardiography, the prevalence and type of cardiovascular sequelae after COVID19 infection with marked elevation of cardiovascular biomarkers (CVB), and their prognostic implications.

Methods

All patients admitted from March 1st to May 25th, 2020 to a tertiary referral hospital were included. Patients with cardiovascular disease antecedent, death during admission, or the first 30 days after discharge were excluded. Patients with hs-TnI >45 ng/L, NT-proBNP >300 pg/ml, and D-dimer >8000 ng/ml were separated based on each CVB elevation and matched with COVID controls (three biomarkers within the normal range) based on intensive care requirements and age.

Results

From a total of 2025 hospitalized COVID19 patients, 80 patients with significantly elevated CVB and 29 controls were finally included. No differences in baseline characteristics were observed among groups, but elevated CVB patients were sicker. Follow-up echocardiograms showed no differences among groups regarding LVEF or RV diameters, but TAPSE was lower if hs-TnI or D-dimer were elevated. Hs-TnI patients also had lower global myocardial work and global longitudinal strain. The presence of an abnormal echocardiogram was more frequent in the elevated CVB group compared to controls (23.8 vs 10.3%, P=0.123) but mainly associated with mild abnormalities in deformation parameters. Management did not change in any case and no major cardiovascular events except deep vein thrombosis occurred after a median follow-up of 7 months (Figure 1).

Conclusions

Minimal abnormalities in cardiac structure and function are observed in COVID19 survivors without previous cardiovascular diseases who presented a significant CVB rise at admission, with no impact on patient management or short-term prognosis. These results do not support a routine screening program after discharge in this population.

Funding Acknowledgement

Type of funding sources: None.

Automatic segmentation of the aorta on multi-center and multi-vendor phase-contrast enhanced magnetic resonance angiographies and the advantages of transfer learning

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Guala A. received funding from the Spanish Ministry of Science, Innovation and Universities

Background

Phase-contrast (PC) enhanced magnetic resonance (MR) angiography (MRA) is a class of angiogram exploiting velocity data to increase the signal-to-noise ratio, thus avoiding the administration of external contrast agent, normally used to segment 4D flow MR data. To train deep-learning algorithms to segment PC-MRA a large amount of manually annotated data is needed: however, the relatively novelty of the sequence, its rapid evolution and the extensive time needed to manually segment data limit its availability.

Purpose

The aim of this study was to test a deep learning algorithm in the segmentation of multi-center and multi-vendor PC-MRA and to test if transfer learning (TL) improves performance.

Methods

A large dataset (LD) of 262 and a small one (SD) of 22 PC-MRA, acquired without contrast agent at 1.5 T in a General Electric and a Siemens scanner, respectively, were manually annotated and divided into training (232 and 15 cases) and testing (30 and 7) sets. They both included PC-MRA of healthy subjects and patients with aortic diseases (excluding dissections) and native aorta. A convolutional neural networks (CNN) based on nnU-Net framework [1] was trained in the LD and another in the SD. The left ventricle was removed semi-automatically from the DL segmentations of the LD as it was not relevant for this application. Networks were then tested on the test sets of the dataset there were trained and the other dataset to assess generalizability. Finally, a fine-tuning transfer learning approach was applied to LD network and the performance on both test sets were tested. Dice score, Hausdorff distance, Jaccard score and Average Symmetrical Surface Distance were used as segmentation quality metrics.

Results

LD network achieved good performance in LD test set, with a DS of 0.904, ASSD of 1.47, J of 0.827 and HD of 6.35, which further improve after removing the left ventricle in the post-processing to a DS of 0.942, ASSD of 0.93, J of 0.892 and HD of 3.32. SD network results in an average DS of 0.895, ASSD of 0.59, J of 0.812 and HD of 2.05. Once tested on the testing set of the other dataset, LD network resulted in a DS of 0.612 while SD network in DS of 0.375, thus showing limited generalizability. However, the application of transfer learning to LD network resulted in the improvement of the evaluation metrics on the SD from a DS of 0.612 to 0.858, while slightly worsening in the first one without post-processing to 0.882.

Conclusions

nnU-net framework is effective for fast automatic segmentation of the aorta from multi-center and multi-vendor PC-MRA, showing performance comparable with the state of the art. The application of transfer learning allows for increased generalization to data from center not included in the original training. These results unlock the possibility for fully-automatic analysis of multi-vendor multi-center 4D flow MR.

Machine learning to automatically detect anatomical landmarks on phase-contrast enhanced magnetic resonance angiography

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Guala A. received funding from the Spanish Ministry of Science, Innovation and Universities

Introduction

The heterogeneous characteristic of the thoracic aorta implies that all biomarkers with potential for risk stratification need to be references to a specific location. This is the case, for example, of diameter [1], stiffness [2] and wall shear stress [3]. This is normally achieved by the manual identification of a limited number of key anatomic landmarks [4], which is a time-demanding task and may impact biomarkers accuracy and reproducibility. Automatic identification of these anatomic landmarks may speed-up the analysis and allow for the creation of fully automatic image analysis pipelines. Machine learning (ML) algorithms might be suitable for this task.

Purpose

The aim of this study was to test the performance of a ML algorithm in localizing key thoracic anatomical landmarks on phase-contrast enhanced magnetic resonance angiograms (PC-MRA).

Methods

PC-MRA of 323 patients with native aorta and aortic valve and a variety of aortic conditions (141 bicuspid aortic valve patients, 60 patients with degenerative aortic aneurysms, 82 patients with genetic aortopathy and 40 healthy volunteers) were included in this study. Four anatomical landmarks were manually identified on PC-MRA by an experienced researcher: sinotubular junction, the pulmonary artery bifurcation and the first and third supra-aortic vessel braches. A reinforcement learning algorithm (DQN), combining Q-learning with deep neural networks, was trained. The algorithm was tested in a separate set of 30 PC-MRA with similar distribution of aortic conditions in which human intra-observer reproducibility was quantified. The distance between points was used as quality metric and human annotation was considered as ground-truth. Repeated-measures ANOVA was used for statistical testing.

Results

ML algorithm resulted in performance similar to the intra-observer variability obtained by the experienced human reader in the identification of the sinotubular junction (11.1 ± 8.6 vs 11.0 ± 8.1 mm, p = 0.949) and first (6.8 ± 5.6 vs 6.6 ± 3.9 mm, p = 0.886) and third (8.4 ± 7.4 vs 6.8 ± 4.0 mm, p = 0.161) supra-aortic vessels branches. However, the algorithm did not reach human-level performance in the localization of the pulmonary artery bifurcation (15.2 ± 13.1 vs 10.2 ± 7.0 mm, p = 0.008). The time needed to the ML algorithm to locate all points ranged between 0.8 and 1.6 seconds on a standard computer while manual annotation required around two minutes to be performed.

Conclusions

The rapid identification of key aortic anatomical landmarks by a reinforced learning algorithm is feasible with human-level performance. This approach may thus be used for the design of fully-automatic pipeline for 4D flow CMR analysis.

Bicuspid aortic valve fusion length correlates with maximum aortic diameter and heamodynamic abnormalities: a 4D flow CMR study

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Guala A. received funding from the Spanish Ministry of Science, Innovation and Universities.

Background

Bicuspid aortic valve (BAV), a congenital heart defect, is associated with ascending aorta dilation, possibly via alteration of aortic blood flow [1]. In BAV abnormal flow condition have been associated with aortic extracellular matrix dysregulation and elastic fiber degeneration [2]. Current morphological classification of BAV patients with aortic valve with a single fusion between two adjacent leaflets does not allow for risk stratification.

Purpose

This research work tested whether the extent of fusion between leaflets is related to AAo diameter and flow alterations.

Methods

Ninety BAV patients free from moderate and severe aortic valve disease and with no previous aortic or aortic valve surgery or replacement were prospectively enrolled. A comprehensive magnetic resonance protocol comprised a stack of double-oblique 2D balanced steady-state free-precession (bSSFP) cine CMR of the aortic valve, which was used to measure the length of the fusion between leaflets, a cine CMR at the level of the pulmonary bifurcation to assess aortic diameter and 4D flow MRI sequence to assess flow characteristics and regional stiffness [3]. Jet angle and flow radial displacement, quantifying the extent of flow eccentricity, and systolic flow reversal ratio (SFRR), assessing the relative amount of backward flow during systole, were computed at 8 equidistant planes in the ascending aorta and 4 equidistant planes in the aortic arch [4]. A two-tailed p-value < 0.05 was considered statistically significant.

Results

The length of leaflet fusion varied widely (median 7.7 mm, inter-quartile range [5.5; 10.2]), Table 1). In bivariate analysis, fusion length was also associated to ascending aortic diameter (R = 0.391, p < 0.001), age (R = 0.313, p = 0.005) and body surface area (R = 0.396, p < 0.001). It was also positively related to flow abnormalities: like displacement in the proximal and distal ascending aorta, jet angle in the mid ascending aorta, and SFRR in the ascending aorta and the aortic arch (see Figure 1). The association between fusion length and ascending aorta diameter persisted in multivariate analysis after correction for age (p = 0.006).

Conclusions

Bicuspid aortic valve fusion extent varies greatly and it is associated with aortic diameter, possibly through flow alterations. Prospective longitudinal studies are needed to establish whether fusion length may allow for risk stratification in bicuspid aortic valve patients.

Aortic root longitudinal strain by speckle-tracking echocardiography predicts progressive aortic root dilation in Marfan syndrome patients

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Spanish Ministry of Science, Innovation and Universities; Instituto de Salud Carlos III

Introduction

In Marfan syndrome (MFS) patients reduced longitudinal strain of the ascending aorta (AAo) as measured by applying feature-tracking on cine cardiac magnetic resonance (CMR) images predicts aortic root dilation and aortic events during the follow-up. Speckle-tracking is well established for cardiac deformation assessment but proximal aorta applications are challenging due to limited wall thickness and substantial cardiac motion. Moreover, echocardiography is widely used in the clinical assessment aortic diseases.

Purpose

We aimed to test a speckle-tracking tool for root longitudinal strain analysis in terms of comparison with CMR-derived AAo longitudinal strain and reproducibility and as predictor of dilation in MFS patients.

Methods

Thirty-five MFS patients diagnosed by original GHENT criteria, with maximum aortic root diameter of 45 mm and free from previous aortic dissection or cardiac/aortic surgery and non-severe aortic regurgitation were consecutive enrolled and followed-up. CMR and echocardiography were performed less than 2 months apart. Baseline and final aortic root diameter were measured on CMR images. To quantify aortic root cyclic elongation by echocardiography, two regions of interests were manually created covering both walls in a parasternal long-axis view and tracked along the cardiac cycle (Figure 1). Longitudinal strain was computed as the average of maximum increase in relative distance of several sub-regions covering both walls. CMR-derived AAo longitudinal strain was available in 29 patients. Intra-observer reproducibility was tested in 15 patients via intraclass correlation coefficient (ICC) for single-rater absolute agreement.

Results

Aortic root longitudinal strain by echocardiography was mildly related to CMR-derived AAo longitudinal strain (R = 0.27) and was larger compared to CMR-derived values (16.2 ± 6.0 vs 11.3 ± 4.3). Reproducibility was high, with ICC of 0.811, R = 0.802, p < 0.001. After a mean follow up of 76 ± 13 months, aortic root diameter grew in 20 patients with a rate of 0.29± 0.24 mm/year. Overall mean growth-rate was 0.87 ± 0.33 mm/year. In multivariable analysis corrected for age and baseline aortic root diameter, baseline longitudinal strain by echocardiography was independently and inversely related to progressive dilation (p = 0.033).

Conclusions

The measurement of aortic root longitudinal strain by speckle-tracking echocardiography is feasible. Aortic root longitudinal strain is an independent predictor of progressive dilation in MFS patients. This may permit the improvement of risk-stratification in aortic diseases in large scale studies.

Abstract Figure 1

Regional curvature in thoracic aortic aneurysms of different aetiologies and its relationship with established risk factors

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Spanish Ministry of Science, Innovation and Universities ; Instituto de Salud Carlos III

Introduction

The aorta is a 3D hollow, curvilinear elastic structure whose diseases have life-threatening consequences. Despite much effort has been paid to study aortic diameter, diameter is a poor predictor of events. Conversely, much less is known about aortic curvature, its distribution in the thoracic aorta and the potential impact of risk factors in aneurysms associated with different conditions. Currently, 4D flow magnetic resonance imaging (4D flow CMR) allows to obtain 3D geometry, 4D flow data and regional aortic stiffness.

Purpose

We aim to study regional aortic curvature in thoracic aorta aneurysms of different aetiologies and define its relationship with established risk factors.

Methods

One-hundred twenty patients (40 for each group, selected out of prospective cohorts of 156 bicuspid aortic valve – BAV-, 77 Marfan –MFS- and 67 patients with a degenerative aneurysm – TAVdeg-) were matched for age, sex and BSA via propensity score with 40 healthy volunteers (HV). The thoracic aorta was semi-automatically segmented from angiograms and the centreline was computed. Local curvature was assessed at 20 planes covering the thoracic aorta from the sinotubular junction to the proximal descending aorta (DAo) at the level of the pulmonary artery bifurcation. Local curvature was normalized by subject mean thoracic aorta curvature. Length was measured as centreline length. Aortic stiffness was measured in the DAo by pulse wave velocity (PWV). Aneurysm was defined by z-score ≥ 2 using diameters measured by double-oblique cine CMR.

Results

Matching was successful in all groups with the exception of a residual age difference between HV and TAVdeg. Curvature in HV showed a fairly smooth transition between the straighter ascending aorta (AAo) and DAo to a more curved aortic arch, with a peak in the mid aortic arch (Figure 1A).  Conversely, all patients’ groups presented a peak in curvature in the proximal DAo and a decreased local curvature in the aortic arch and mid DAo close to the level of the pulmonary artery. BAV and TAVdeg patients showed also increased curvature in the mid AAo, were dilation is prevalent. Conversely, in the same area MFS showed a reduced curvature and limited prevalence of aneurysm. In the overall population, age, AAo and root diameters, mean blood pressure, DAo PWV and aortic length, all established risk factors for aortic events, were inversely related to curvature in the distal AAo and aortic arch (Figure 1B).

Conclusions

Aneurysms related to different aetiologies show similar abnormalities in aortic curvature, with limited curvature in the aortic arch and a peak soon after the third supra-aortic vessel. Age, aortic diameter, length, stiffness and blood pressure, all known risk factors, are all related to reduced curvature in the distal ascending aorta and aortic arch.

Abstract Figure.

Reinforcement machine learning-based aortic anatomical landmarks detection from phase-contrast enhanced magnetic resonance angiography

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Spanish Ministry of Science, Innovation and Universities; La Marató de TV3

Introduction

Automatic analysis of medical imaging data may improve their clinical impact by reducing analysis time and improving reproducibility. Many medical imaging data, like 4D-flow magnetic resonance imaging (MRI), are often quantified regionally, implying the need for anatomical landmark identification to locate correspondences in the extracted data and compare among patients. Machine learning (ML) techniques hold potential for automatic analysis of medical imaging. Phase-contrast enhanced magnetic resonance angiography (PC-MRA) is a class of angiograms not requiring the administration of contrast agents.

Purpose

We aimed to test whether a machine learning algorithm can be trained to identify key anatomical cardiovascular landmarks on PC-MRA images and compare its performance with humans.

Methods

Three-hundred twenty-three aortic PC-MRA were manually annotated with the location of 4 landmarks: sinotubular junction, pulmonary artery bifurcation and first and third supra-aortic vessels (Figure 1), often used to separate the aorta in sub-regions. Patients included in the training dataset comprised healthy volunteers (40), bicuspid aortic valve patients (141), patients with degenerative aortic disease (60) and patients with genetically-triggered aortic disease (82), all without previous aortic surgery and with native aortic valve. PC-MRA images and manual annotations were used to train a DQN, a reinforcement learning algorithm that combines Q-learning with deep neural networks. The agents can navigate the images and optimally find the landmarks by following the policies learned during training. Data from thirty patients, distributed in terms of aortic condition as the training set, unseen by the algorithm in the training phase, were used to quantify intra-observer reproducibility and to assess ML algorithm performance. Distance between points was used as metric for comparisons, original human annotation was used as ground-truth and repeated-measures ANOVA was used for statistical testing.

Results

Human and machine learning performed similarly in the identification of the sinotubular junction (distance between points of 11.0 ± 8.1 vs. 11.1 ± 8.6 mm, respectively, p = 0.949) and first (6.6 ± 3.9 vs. 6.8 ± 5.6 mm, p = 0.886) and third (6.8 ± 4.0 vs. 8.4 ± 7.4 mm, p = 0.161) supra-aortic vessels branches but human annotation outperformed ML landmark detection in the identification of the pulmonary artery bifurcation (10.2 ± 7.0 vs. 15.2 ± 13.1 mm, p = 0.008). Computation time for landmark detection by ML was between 0.8 and 1.6 seconds on a standard computer while human annotation took approximatively two minutes.

Conclusions

ML-based aortic landmarks detection from phase-contrast enhanced magnetic resonance angiography is feasible and fast and performs similarly to human. Reinforced learning anatomical landmark identification unlock automatic extraction of a variety of regional aortic data, including complex 4D flow parameters.

Abstract Figure

Iron deficiency is associated with larger infarcts and with adverse remodeling in STEMI patients and reduces myocardial tolerance to ischemia/reperfusion by inhibiting the eNOS/sGC/PKG pathway in mice

Background

Iron deficiency (ID) interferes with the cardioprotective pathway endothelial nitric oxide synthase/soluble guanylate cyclase/protein kinase G (eNOS/sGC/PKG), but its role in acute myocardial infarction remains unclear.

Methods

Patients (n=125) with a first anterior STEMI treated with PCI underwent magnetic resonance imaging in the acute phase and at 6 months. We assessed whether ID (ferritin level <100 μg/L or <300 μg/L if transferrin saturation was <20%) was associated with infarct size acutely or with adverse left ventricular (LV) remodeling (LV end-diastolic volume increase at 6 months >20%, n=105). C57BL6/N mice were fed with standard diet or iron-deficient diet for 4 weeks before undergoing 45-min coronary occlusion/24-h reperfusion.

Results

Patients with ID (43.2%) had larger infarcts (22.8±10.2 vs 16.8±9.8% of LV mass, P=0.002) and more frequent microvascular obstruction (70.0 vs 43.3%, P=0.004) in the initial exam than the rest. They also developed adverse LV remodeling more often (38.6 vs 14.8%, P=0.005), even after adjusting by infarct size and final TIMI flow grade (OR 3.1, 95% CI 1.1–8.6, P=0.027). In mice, ID diet reduced myocardial iron content, serum ferritin and hemoglobin levels without reaching anemic values and without inducing echocardiographic alterations. ID diet reduced myocardial eNOS protein content, its dimeric form, and nitrites/nitrates and cGMP levels. eNOS decrease was associated with reduced HSP90 levels and increased eNOS ubiquitination in correlation with oxidative and nitrosative stress. Weekly iv administration of iron sucrose effectively reverted the ID-diet effects. Infarct size was larger in the ID group than in controls (58.8±3.0 vs. 40.3±3.6%, P=0.03) but was not increased in ID-diet animals treated with iron sucrose (36.3±4.0%) or receiving the sGC activator ataciguat before ischemia (31.0±2.5%).

Conclusions

ID is associated with larger infarcts and with more frequent adverse LV remodeling in patients with STEMI and reduces myocardial tolerance to ischemia/reperfusion in mice by attenuating eNOS/sGC/PKG pathway activity. Iron sucrose treatment and sGC activation reverted these deleterious effects of ID in mice. Iron supplementation might be beneficial in STEMI patients with ID.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): CIBER-CV. Instituto de Salud Carlos III (PI16/00232), co-financed by the ERDF

P1447 Ascending aorta longitudinal strain in bicuspid aortic valve patients: a comparison with healthy volunteers and patients with degenerative aortic aneurysm

Funding Acknowledgements

Spanish Ministry of Economy and Competitiveness RTC-2016-5152-1, ISCIII PI17/00381, La Marató de TV3 (20151330), Eur FP7/People 267128 and CIBERCV

Background

Histological findings of fibrillin-1 deficiency in bicuspid aortic valve (BAV) ascending aorta (AAo), as observed in Marfan (MFS), supported the existence of intrinsic aortic wall abnormalities, but recent studies reported the absence of an intrinsic impairment in stiffness. A recent study in MFS showed that AAo longitudinal strain was reduced in MFS and predicted dilation and aortic events. This parameter has not been studied in BAV.

Purpose

We investigated whether ascending aorta longitudinal strain is intrinsically altered in BAV with respect to tricuspid aortic valve (TAV) individuals.

Methods

80 BAV, 31 healthy volunteers (HV) and 29 TAV with AAo aneurysm, all without moderate valvular disease, were consecutively included. AAo dilation was defined as a z-score > 2. The 1.5T CMR protocol included a set of 2D cine CMR stacks covering the proximal aorta in saggital, coronal and axial views. AAo longitudinal strain was computed by an in-house Matlab code performing a feature tracking of the aortic valve in each of the cine images.

Results

Twenty (25%) of BAV had AAo dilation. AAo longitudinal strain was lower in non-dilated BAV compared to HV, but the difference was not significant in multivariate analysis adjusted for AAo diameter and systolic blood pressure. Similarly, the difference between dilated BAV and dilated TAV found in univariate analysis was not confirmed by multivariate analysis. On the other hand, both dilated BAV and TAV showed decreased AAo longitudinal strain compared to HV, which were confirmed in multivariate analyses.

Conclusions

AAo longitudinal strain, a marker of aortic stiffness with predictive value in MFS, is not altered in BAV patients compared to TAV matched for dilation prevalence. Reduced AAo longitudinal strain was independently associated with dilation in both BAV and TAV.

Table 1 HV vs. NON-DILATED BAV DILATED BAV vs DILATED TAV HV vs. DILATED BAV HV vs. DILATED TAV HV NON-DILATED BAV Univariate /multivariate p-value DILATED TAV DILATED BAV Univariate /multivariate p-value Univariate/ Multivariate p-value Univariate p-value N 31 20 29 60 Age [years 35 ± 8 49 ± 16 <0.001/ NS 66 ± 13 49 ± 14 <0.001 / <0.001 <0.001 / 0.052 <0.001 / NS Sex [% male] 42 35 0.629 24 42 0.097 / NS 0.969 0.149 BSA [m2] 1.83 ± 0.17 1.81 ± 0.14 0.702 1.95 ± 0.24 1.82 ± 0.22 0.015 / <0.001 0.881 0.030 / NS SBP [mmHg] 119 ± 11 132 ± 16 0.002 / 0.029 133 ± 17 138 ± 19 0.304 <0.001 / NS <0.001 / NS DBP [mmHg] 69 ± 11 73 ± 6 0.099 / NS 77 ± 9 79 ± 11 0.455 <0.001 / 0.016 0.004 / 0.023 Ascending aorta diameter [mm] 26 ± 4 33 ± 3 <0.001 / 0.006 46 ± 7 43 ± 6 0.032 / NS <0.001 / 0.001 <0.001 /0.007 AAo long strain [%] 10.5 ± 3.6 8.4 ± 4.1 0.067/ NS 5.9 ± 2.7 7.7 ± 3.6 0.023 / NS 0.001 / 0.002 <0.001 / 0.023 Demographics and uni- and multivariate analyses of AAo longitudinal strain

Decreased rotational flow and circumferential wall shear stress as early markers of descending aorta dilation in Marfan syndrome: a 4D flow CMR study

BACKGROUND

Diseases of the descending aorta have emerged as a clinical issue in Marfan syndrome following improvements in proximal aorta surgical treatment and the consequent increase in life expectancy. Although a role for hemodynamic alterations in the etiology of descending aorta disease in Marfan patients has been suggested, whether flow characteristics may be useful as early markers remains to be determined.

METHODS

Seventy-five Marfan patients and 48 healthy subjects were prospectively enrolled. In- and through-plane vortexes were computed by 4D flow cardiovascular magnetic resonance (CMR) in the thoracic aorta through the quantification of in-plane rotational flow and systolic flow reversal ratio, respectively. Regional pulse wave velocity and axial and circumferential wall shear stress maps were also computed.

RESULTS

In-plane rotational flow and circumferential wall shear stress were reduced in Marfan patients in the distal ascending aorta and in proximal descending aorta, even in the 20 patients free of aortic dilation. Multivariate analysis showed reduced in-plane rotational flow to be independently related to descending aorta pulse wave velocity. Conversely, systolic flow reversal ratio and axial wall shear stress were altered in unselected Marfan patients but not in the subgroup without dilation. In multivariate regression analysis proximal descending aorta axial (p = 0.014) and circumferential (p = 0.034) wall shear stress were independently related to local diameter.

CONCLUSIONS

Reduced rotational flow is present in the aorta of Marfan patients even in the absence of dilation, is related to aortic stiffness and drives abnormal circumferential wall shear stress. Axial and circumferential wall shear stress are independently related to proximal descending aorta dilation beyond clinical factors. In-plane rotational flow and circumferential wall shear stress may be considered as an early marker of descending aorta dilation in Marfan patients.

6126Peripheral aneurysms in Marfan patients are common and are related to age and advanced aortic disease

Background

Peripheral aneurysms are not included in the diagnostic criteria for Marfan syndrome (MFS); however, their real prevalence in MFS is unknown. Furthermore, they are commonly seen in other genetic entities such as Loeys-Dietz syndrome.

We aimed to investigate the prevalence of peripheral aneurysm in Marfan syndrome.

Methods

Patients with clinical criteria of Marfan syndrome and identified FBN1 mutation were evaluated. Only patients with either MRI or CT angiography assessing peripheral vessels were included in this study. MRI and CT angiography studies were retrospectively evaluated to detect the presence of peripheral aneurysms. Aortic dissection-related arterial dilations were excluded. Aortic events and those related to aneurysm complications were collected during follow-up.

Results

Two hundred and nine patients with Marfan and FBN1 mutation were evaluated. Of these 136 (65.1%) had undergone either MRA or CTA with peripheral artery study during follow-up. Mean age at the last follow-up visit was 42.4±14.1yrs; 54.4% were men, and mean follow-up 7.3±3.1 years. Sixty-six aneurysms were identified in 42 (30.9%) patients. The most common locations were the iliac arteries in 23. The rest were: renal (7), vertebral (5), splenic (5), coeliac (3), brachiocephalic (1), subclavian (3), carotid (3), axillary (2), internal mammary (3), femoral (2), hypogastric (3), bronchial (2), coronary (1), hepatic (1), lumbar (1), gastroduodenal (1) and popliteal (1). Twenty-six patients (61.9%) had more than one peripheral aneurysm, and only 4 required surgery.

Patients with peripheral aneurysms were older (47.2±14.3yrs vs 40.2±13.6yrs, p=0.06) and more frequently men (69.0% vs 47.9% p=0.026). Although patients with peripheral aneurysms did not more frequently have aortic dissection (16.7% vs 17.0%, p=0.586), they did more frequently have aortic surgery (73.8% vs 47.9% p=0.05).

Conclusions

Peripheral aneurysms are present in one third of Marfan syndrome patients and are related to age and more advanced aortic disease. Systematic use of whole-body vascular assessment in Marfan patients can provide a comprehensive evaluation of the entire arterial system, identifying other sites of vascular involvement at risk of potential complications, and the subgroup of patients with more aggressive vascular disease expression.