Annals of Biomedical Engineering

, Volume 34, Issue 7, pp 1098–1106

Towards A Noninvasive Method for Determination of Patient-Specific Wall Strength Distribution in Abdominal Aortic Aneurysms

  • Jonathan P. Vande Geest
  • David H. J. Wang
  • Stephen R. Wisniewski
  • Michel S. Makaroun
  • David A. Vorp
Article

Abstract

The spatial distributions of both wall stress and wall strength are required to accurately evaluate the rupture potential for an individual abdominal aortic aneurysm (AAA). The purpose of this study was to develop a statistical model to non-invasively estimate the distribution of AAA wall strength. Seven parameters–namely age, gender, family history of AAA, smoking status, AAA size, local diameter, and local intraluminal thrombus (ILT) thickness–were either directly measured or recorded from the patients hospital chart. Wall strength values corresponding to these predictor variables were calculated from the tensile testing of surgically procured AAA wall specimens. Backwards–stepwise regression techniques were used to identify and eliminate insignificant predictors for wall strength. Linear mixed-effects modeling was used to derive a final statistical model for AAA wall strength, from which 95% confidence intervals on the model parameters were formed. The final statistical model for AAA wall strength consisted of the following variables: sex, family history, ILT thickness, and normalized transverse diameter. Demonstrative application of the model revealed a unique, complex wall strength distribution, with strength values ranging from 56 N/cm2 to 133 N/cm2. A four-parameter statistical model for the noninvasive estimation of patient-specific AAA wall strength distribution has been successfully developed. The currently developed model represents a first attempt towards the noninvasive assessment of AAA wall strength. Coupling this model with our stress analysis technique may provide a more accurate means to estimate patient-specific rupture potential of AAA.

Keywords

Stress Rupture Statistical modeling Aneurysm Strength 

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Copyright information

© Biomedical Engineering Society 2006

Authors and Affiliations

  • Jonathan P. Vande Geest
    • 1
    • 2
    • 5
  • David H. J. Wang
    • 1
    • 2
  • Stephen R. Wisniewski
    • 3
  • Michel S. Makaroun
    • 1
  • David A. Vorp
    • 1
    • 2
    • 4
    • 6
  1. 1.Department of SurgeryDivision of Vascular SurgeryPittsburghUSA
  2. 2.Department of BioengineeringUniversity of PittsburghPittsburghUSA
  3. 3.Department of EpidemiologyUniversity of PittsburghPittsburghUSA
  4. 4.The McGowan Institute for Regenerative MedicinePittsburghUSA
  5. 5.Department of Aerospace and Mechanical EngineeringUniversity of ArizonaTucsonUSA
  6. 6.Department of Surgery, Division of Vascular Surgery, Vascular Surgery and Vascular Biomechanics LaboratoryMcGowan Institute for Regenerative MedicinePittsburghUSA

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