In:
European Journal of Cardio-Thoracic Surgery, Oxford University Press (OUP), Vol. 57, No. 1 ( 2020-01-01), p. 133-141
Kurzfassung:
OBJECTIVES Complex blood flow profiles in the aorta are known to contribute to vessel dilatation. We studied flow profiles in the aorta in patients with aortic valve disease before and after surgical aortic valve replacement (AVR). METHODS Thirty-four patients with aortic valve disease underwent 4-dimensional velocity-encoded magnetic resonance imaging before and after AVR (biological valve = 27, mechanical valve = 7). Seven healthy volunteers served as controls. Eccentricity (ES) and complex flow scores (CFS) were determined from the degree of helicity, vorticity and eccentricity of flow profiles in the aorta. Model-based therapy planning was used in 4 cases to improve in silico postoperative flow profiles by personalized adjustment of size, rotation and angulation of the valve as well as aorta diameter. RESULTS Patients with aortic valve disease showed more complex flow than controls [median ES 2.5 (interquartile range (IQR) 2.3–2.7) vs 1.0 (IQR 1.0–1.0), P & lt; 0.001, median CFS 4.7 (IQR 4.3–4.8) vs 1.0 (IQR 1.0–2.0), P & lt; 0.001]. After surgery, flow complexity in the total patient cohort was reduced, but remained significantly higher compared to controls [median ES 2.3 (IQR 1.9–2.3) vs 1.0 (IQR 1.0–1.0), P & lt; 0.001, median CFS 3.8 (IQR 3.0–4.3) vs 1.0 (IQR 1.0–2.0), P & lt; 0.001]. In patients after mechanical AVR, flow complexity fell substantially and showed no difference from controls [median ES 1.0 (IQR 1.0–2.3) vs 1.0 (IQR 1.0–1.0), P = 0.46, median CFS 1.0 (IQR 1.0–3.3) vs 1.0 (IQR 1.0–2.0), P = 0.71] . In all 4 selected cases (biological, n = 2; mechanical, n = 2), model-based therapy planning reduced in silico complexity of flow profiles compared to the existing post-surgical findings [median ES 1.7 (IQR 1.4–1.7) vs 2.3 (IQR 2.3–2.3); CFS 1.7 (IQR 1.4–2.5) vs 3.8 (IQR 3.3–4.3)]. CONCLUSIONS Abnormal flow profiles in the aorta more frequently persist after surgical AVR. Model-based therapy planning might have the potential to optimize treatment for best possible individual outcome. Clinical trial registration number clinicaltrials.gov NCT03172338, 1 June 2017, retrospectively registered; NCT02591940, 30 October 2015, retrospectively registered.
Materialart:
Online-Ressource
ISSN:
1010-7940
,
1873-734X
DOI:
10.1093/ejcts/ezz149
Sprache:
Englisch
Verlag:
Oxford University Press (OUP)
Publikationsdatum:
2020
ZDB Id:
1500330-9
