In vivo assessment of aortic root geometry in normal controls using 3D analysis of computed tomography

Eur Heart J Cardiovasc Imaging. 2017 Jul 1;18(7):780-786. doi: 10.1093/ehjci/jew146.

Abstract

Aims: Understanding normal asymmetry in the aortic root could aid in the development of new surgical repair techniques or devices with improved haemodynamic performance. The purpose of this study was to assess geometric asymmetry and age-related changes in the normal aortic root using 3D computed tomography.

Methods and results: The institutional review board approved this retrospective study of 130 normal subjects (mean age, 51.4 years; 58 men). Specialized 3D software measured individual cusp sinus volumes (CSVs), cusp surface areas (CSAs), and intercommissural distances (ICDs). Age-related aortic root changes were evaluated with simple correlation, ANOVA test among age groups, and multivariable linear regression analyses. The CSV and CSA of left coronary cusp (LCC) were significantly smaller than those of right coronary cusp (RCC) and non-coronary cusp (NCC) (both, P < 0.001) in all age groups. The mean ratios of RCC or NCC-to-LCC were 1.38 and 1.36 for CSV, 1.19 and 1.20 for CSA, and 1.21 and 1.06 for ICD, respectively. The CSV and ICD increased in older age with weak-to-moderate correlation coefficients in both men and women. By multivariable linear regression, CSVs and ICDs of all cusps showed a positive correlation with age (P < 0.05), and the female gender was associated with a smaller size of the CSV and CSA.

Conclusions: The LCC was significantly smaller than the other two cusps, and the aortic root size increased with age.

Keywords: aortic root; computed tomography; three-dimensional analysis.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aging / physiology
  • Analysis of Variance
  • Aorta, Thoracic / diagnostic imaging*
  • Aortic Valve / diagnostic imaging*
  • Aortography / methods*
  • Cohort Studies
  • Computed Tomography Angiography / methods*
  • Female
  • Humans
  • Imaging, Three-Dimensional*
  • Linear Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Retrospective Studies
  • Risk Assessment
  • Sensitivity and Specificity
  • Sex Factors