Imaging-Based 4D Aortic Pressure Mapping in Marfan Syndrome Patients: A Matched Case-Control Study

Clinical application of four-dimensional flow cardiovascular magnetic resonance in Marfan syndrome: A systematic review and meta-analysis

This study aims to fill this gap by assessing the application of 4D flow CMR in MFS through a systematic review and meta-analysis. We conducted a comprehensive search of databases from their inception to May 1, 2023. Eligibility criteria were established based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS), with studies scoring above five deemed high quality. Meta-analyses were performed using Stata 15.1 software. Nine studies were analyzed. Findings indicate MFS patients had increased vortex flow in the descending aorta (DAo), larger aortic root diameter (ARD) and Z-scores, lower inner wall shear stress (WSS) in the proximal descending aorta (pDAo), reduced in-plane rotational flow (IRF) in the aortic arch and proximal descending aorta (pDAo), and increased pulse wave velocity (PWV) in the ascending aorta (AAo) and DAo compared to healthy subjects. No significant difference in systolic flow reversal ratio was observed. Sensitivity analysis showed no heterogeneity and Egger's test revealed no publication bias. This meta-analysis underscores the effectiveness of 4D flow CMR in detecting MFS, particularly through indicators such as vortex flow, WSS, IRF, ARD, and PWV. The findings provide insights into diagnosing cardiovascular diseases and predicting cardiovascular events in MFS patients. Further case-control studies are needed to establish measurement standards and explore potential indicators for improved diagnosis and treatment of MFS.

bnormal aortic hemodynamics are associated with risk factors for aortic complications in patients with marfan syndrome

Background

It is difficult to assess the risk for aortic dissection beyond the aortic root in patients with Marfan syndrome (MFS). To aid risk assessment in these patients, we investigated aortic flow and wall shear stress (WSS) by 4D flow magnetic resonance imaging (MRI) in patients with MFS and compared the results with healthy volunteers. We hypothesized that MFS patients with a high-risk profile for aortic dissection would show abnormal hemodynamics in aortic regions associated with aortic dissection.

Methods

MFS patients (n = 55) and healthy subjects (n = 25), matched for age and sex, prospectively underwent 4D flow MRI. 4D flow maps were constructed to detect elevated (defined as higher than the three-dimensional 95 % confidence interval) and deviant directed (defined as vector angle differences higher than 120°) WSS in MFS patients as compared to the controls. Univariate and multivariate associations with risk factors for aortic dissection in MFS patients were assessed.

Results

The maximum incidence for elevated WSS was 20 % (CI 9 %-31 %) and found in the ascending aorta. The maximum for deviant directed WSS was 39 % (CI 26 %-52 %) and found in the inner descending aorta. Significantly more male patients had deviant directed WSS in the inner proximal descending aorta (63 % vs 24 %, p = 0.014). Multivariate analysis showed that deviant directed WSS was associated with male sex (p = 0.019), and a haplo-insufficient FBN1 mutation type (p = 0.040). In 60 % of MFS patients with a previous aortic root replacement surgery, abnormal hemodynamics were found in the ascending aorta. No significant differences between hemodynamics were found in the descending aorta between operated and non-operated patients.

Conclusion

Deviant directed WSS in the proximal descending aorta is associated with known risk factors for aortic dissection in MFS patients, namely male sex and a haploinsufficient FBN1 mutation type.

SRflow: Deep learning based super-resolution of 4D-flow MRI data

Exploiting 4D-flow magnetic resonance imaging (MRI) data to quantify hemodynamics requires an adequate spatio-temporal vector field resolution at a low noise level. To address this challenge, we provide a learned solution to super-resolve in vivo 4D-flow MRI data at a post-processing level. We propose a deep convolutional neural network (CNN) that learns the inter-scale relationship of the velocity vector map and leverages an efficient residual learning scheme to make it computationally feasible. A novel, direction-sensitive, and robust loss function is crucial to learning vector-field data. We present a detailed comparative study between the proposed super-resolution and the conventional cubic B-spline based vector-field super-resolution. Our method improves the peak-velocity to noise ratio of the flow field by 10 and 30% for in vivo cardiovascular and cerebrovascular data, respectively, for 4 × super-resolution over the state-of-the-art cubic B-spline. Significantly, our method offers 10x faster inference over the cubic B-spline. The proposed approach for super-resolution of 4D-flow data would potentially improve the subsequent calculation of hemodynamic quantities.

Potential predictors of severe cardiovascular involvement in Marfan syndrome: the emphasized role of genotype-phenotype correlations in improving risk stratification-a literature review

BACKGROUND

Marfan syndrome (MFS) is a genetically determined systemic connective tissue disorder, caused by a mutation in the FBN1 gene. In MFS mainly the cardiovascular, musculoskeletal and ocular systems are affected. The most dangerous manifestation of MFS is aortic dissection, which needs to be prevented by a prophylactic aortic root replacement.

MAIN BODY

The indication criteria for the prophylactic procedure is currently based on aortic diameter, however aortic dissections below the threshold defined in the guidelines have been reported, highlighting the need for a more accurate risk stratification system to predict the occurrence of aortic complications. The aim of this review is to present the current knowledge on the possible predictors of severe cardiovascular manifestations in MFS patients, demonstrating the wide range of molecular and radiological differences between people with MFS and healthy individuals, and more importantly between MFS patients with and without advanced aortic manifestations. These differences originating from the underlying common molecular pathological processes can be assessed by laboratory (e.g. genetic testing) and imaging techniques to serve as biomarkers of severe aortic involvement. In this review we paid special attention to the rapidly expanding field of genotype-phenotype correlations for aortic features as by collecting and presenting the ever growing number of correlations, future perspectives for risk stratification can be outlined.

CONCLUSIONS

Data on promising biomarkers of severe aortic complications of MFS have been accumulating steadily. However, more unifying studies are required to further evaluate the applicability of the discussed predictors with the aim of improving the risk stratification and therefore the life expectancy and quality of life of MFS patients.

4D flow imaging of the thoracic aorta: is there an added clinical value?

Four-dimensional (4D) flow MRI has emerged as a powerful non-invasive technique in cardiovascular imaging, enabling to analyse in vivo complex flow dynamics models by quantifying flow parameters and derived features. Deep knowledge of aortic flow dynamics is fundamental to better understand how abnormal flow patterns may promote or worsen vascular diseases. In the perspective of an increasingly personalized and preventive medicine, growing interest is focused on identifying those quantitative functional features which are early predictive markers of pathological evolution. The thoracic aorta and its spectrum of diseases, as the first area of application and development of 4D flow MRI and supported by an extensive experimental validation, represents the ideal model to introduce this technique into daily clinical practice. The purpose of this review is to describe the impact of 4D flow MRI in the assessment of the thoracic aorta and its most common affecting diseases, providing an overview of the actual clinical applications and describing the potential role of derived advanced hemodynamic measures in tailoring follow-up and treatment.