Aortic diameter is a poor predictor of aortic tissue failure metrics in patients with ascending aneurysms.
aortic aneurysm
ascending aorta
bicuspid aortopathy
biomechanics
dissection risk
Journal
The Journal of thoracic and cardiovascular surgery
ISSN: 1097-685X
Titre abrégé: J Thorac Cardiovasc Surg
Pays: United States
ID NLM: 0376343
Informations de publication
Date de publication:
25 Oct 2022
25 Oct 2022
Historique:
received:
28
01
2022
revised:
19
09
2022
accepted:
13
10
2022
entrez:
17
12
2022
pubmed:
18
12
2022
medline:
18
12
2022
Statut:
aheadofprint
Résumé
There is growing consensus that aortic diameter is a flawed predictor of aortic dissection risk. We hypothesized that aortic tissue metrics would be better predicted by clinical metrics other than aortic diameter. Our objectives were to (1) characterize circumferential aortic failure stress and stretch as a result of aortic size and patient demographics, and (2) identify the influence of bicuspid aortic valve on failure metrics. From February 2018 to January 2021, 136 aortic tissue samples were obtained from 86 adults undergoing elective ascending aorta repair. Uniaxial biomechanical testing to failure, defined as a full-thickness central tear, was performed to obtain tissue failure stress and failure stretch and compared with clinical data and preoperative computed tomography imaging. The relationships among aortic diameter, patient demographics, and failure metrics were assessed using random forest regression models. Median failure stress was 1.46 (1.02-1.94) megapascals, and failure stretch was 1.36 (1.27-1.54). Regression models correlated moderately with failure stress (R Aneurysmal ascending aortic tissue failure metrics correlated with available clinical metrics. Greater tissue thickness, older age, and tricuspid aortic valve morphology outperformed aortic diameter, warranting further investigation into the role of a patient-specific multifactorial dissection risk assessment over aortic diameter as a sole marker of aortic tissue integrity.
Identifiants
pubmed: 36528437
pii: S0022-5223(22)01140-0
doi: 10.1016/j.jtcvs.2022.10.021
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Investigateurs
Frank Cikach
(F)
Emidio Germano
(E)
Kelly Emerton
(K)
Jennifer Hargrave
(J)
Ria Richardson
(R)
Informations de copyright
Copyright © 2022. Published by Elsevier Inc.