Ascending aorta curvature and flow displacement are associated with accelerated aortic growth at long-term follow-up: A MRI study in Marfan and thoracic aortic aneurysm patients

Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate

OBJECTIVE

ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth.

MATERIAL AND METHODS

70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmentation, three local shape features are computed: (1) the ratio between maximum diameter and length of the ascending aorta centerline, (2) the ratio between the length of external and internal lines on the ascending aorta and (3) the tortuosity of the ascending tract. By exploiting longitudinal data, the aneurysm growth rate is derived. Using radial basis function mesh morphing, iso-topological surface meshes are created. Statistical shape analysis is performed through unsupervised principal component analysis (PCA) and supervised partial least squares (PLS). Two types of global shape features are identified: three PCA-derived and three PLS-based shape modes. Three regression models are set for growth prediction: two based on gaussian support vector machine using local and PCA-derived global shape features; the third is a PLS linear regression model based on the related global shape features. The prediction results are assessed and the aortic shapes most prone to growth are identified.

RESULTS

the prediction root mean square error from leave-one-out cross-validation is: 0.112 mm/month, 0.083 mm/month and 0.066 mm/month for local, PCA-based and PLS-derived shape features, respectively. Aneurysms close to the root with a large initial diameter report faster growth.

CONCLUSION

global shape features might provide an important contribution for predicting the aneurysm growth.

Endothelial dysfunction in Marfan syndrome mice is restored by resveratrol

Patients with Marfan syndrome (MFS) develop thoracic aortic aneurysms as the aorta presents excessive elastin breaks, fibrosis, and vascular smooth muscle cell (vSMC) death due to mutations in the FBN1 gene. Despite elaborate vSMC to aortic endothelial cell (EC) signaling, the contribution of ECs to the development of aortic pathology remains largely unresolved. The aim of this study is to investigate the EC properties in Fbn1^C1041G/+ MFS mice. Using en face immunofluorescence confocal microscopy, we showed that EC alignment with blood flow was reduced, EC roundness was increased, individual EC surface area was larger, and EC junctional linearity was decreased in aortae of Fbn1^C1041G/+ MFS mice. This modified EC phenotype was most prominent in the ascending aorta and occurred before aortic dilatation. To reverse EC morphology, we performed treatment with resveratrol. This restored EC blood flow alignment, junctional linearity, phospho-eNOS expression, and improved the structural integrity of the internal elastic lamina of Fbn1^C1041G/+ mice. In conclusion, these experiments identify the involvement of ECs and underlying internal elastic lamina in MFS aortic pathology, which could act as potential target for future MFS pharmacotherapies.

4D Flow MRI in Ascending Aortic Aneurysms: Reproducibility of Hemodynamic Parameters

(1) Background: Aorta hemodynamics have been associated with aortic remodeling, but the reproducibility of its assessment has been evaluated marginally in patients with thoracic aortic aneurysm (TAA). The current study evaluated intra- and interobserver reproducibility of 4D flow MRI-derived hemodynamic parameters (normalized flow displacement, flow jet angle, wall shear stress (WSS) magnitude, axial WSS, circumferential WSS, WSS angle, vorticity, helicity, and local normalized helicity (LNH)) in TAA patients; (2) Methods: The thoracic aorta of 20 patients was semi-automatically segmented on 4D flow MRI data in 5 systolic phases by 3 different observers. Each time-dependent segmentation was manually improved and partitioned into six anatomical segments. The hemodynamic parameters were quantified per phase and segment. The coefficient of variation (COV) and intraclass correlation coefficient (ICC) were calculated; (3) Results: A total of 2400 lumen segments were analyzed. The mean aneurysm diameter was 50.8 ± 2.7 mm. The intra- and interobserver analysis demonstrated a good reproducibility (COV = 16–30% and ICC = 0.84–0.94) for normalized flow displacement and jet angle, a very good-to-excellent reproducibility (COV = 3–26% and ICC = 0.87–1.00) for all WSS components, helicity and LNH, and an excellent reproducibility (COV = 3–10% and ICC = 0.96–1.00) for vorticity; (4) Conclusion: 4D flow MRI-derived hemodynamic parameters are reproducible within the thoracic aorta in TAA patients.