Finite element analysis in symptomatic and asymptomatic abdominal aortic aneurysms for aortic disease risk stratification

Int Angiol. 2018 Dec;37(6):479-485. doi: 10.23736/S0392-9590.18.03994-9. Epub 2018 Sep 10.

Abstract

Background: Advanced biomechanical models can provide additional information concerning rupture risk in abdominal aortic aneurysms (AAA). Here we evaluated the predictive value of finite element analysis (FEA) to assess AAA rupture risk.

Methods: In a case-control study, we compared FEA parameters in a group of symptomatic AAA (sAAA) patients, considered as a high risk of rupture group, with FEA parameters in asymptomatic AAA patients (aAAA).

Results: We included 15 sAAA and 28 aAAA patients matched for age- and maximum diameter diagnosed with infrarenal non-ruptured AAA at our center between 2009 and 2013. Mean age was 75±69 years and mean maximum diameter was 77±17 mm. Peak wall stress (PWS) was significantly higher in sAAA patients than in aAAA patients (354.3±139.6 kPa vs. 248.6±81.9 kPa; P=0.001). The C statistic for the ROC curve based on PWS was 0.748 (95% CI: 0.592-0.903; P=0.008). CART analysis classified patients into high and low PWS groups. The high-PWS group (>305.15 kPa; N.=15) had a higher incidence of sAAA (33.3% aAAA, 66.7% sAAA) than the low-PWS-group (≤305.15 kPa; N.=28. 82.1% aAAA, 17.9% sAAA).

Conclusions: In conclusion, PWS was significantly higher in sAAA patients. Measuring PWS may help estimate the individual rupture risk in patients with AAA, but larger studies are needed to confirm our results.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Aorta, Abdominal / diagnostic imaging*
  • Aorta, Abdominal / physiopathology
  • Aortic Aneurysm, Abdominal / complications
  • Aortic Aneurysm, Abdominal / diagnostic imaging*
  • Aortic Aneurysm, Abdominal / physiopathology
  • Aortic Rupture / etiology*
  • Aortic Rupture / physiopathology
  • Aortography / methods*
  • Asymptomatic Diseases
  • Biomechanical Phenomena
  • Case-Control Studies
  • Computed Tomography Angiography*
  • Decision Support Techniques*
  • Finite Element Analysis
  • Hemodynamics*
  • Humans
  • Models, Cardiovascular*
  • Patient-Specific Modeling*
  • Predictive Value of Tests
  • Prognosis
  • Radiographic Image Interpretation, Computer-Assisted
  • Regional Blood Flow
  • Risk Assessment
  • Risk Factors
  • Stress, Mechanical