UCSF

Background

Pulmonary autograft dilatation after Ross operation often necessitates reoperation. To understand autograft remodeling, a biomechanical understanding of human autografts after exposure to systemic pressure is required. We previously developed an ex vivo human pulmonary autograft finite element (FE) model to predict wall stress after exposure to systemic pressure. However, autograft material properties vary significantly among individuals. Our study aim was to quantify range of wall stress changes in a human autograft after Ross operation prior to remodeling based upon normal variation in human autograft mechanical properties.

Methods

A normal human autograft FE model was loaded to pulmonary and systemic arterial pressures. Stress-strain data of normal human autografts (n=24) were incorporated into an Ogden hyper-elastic model to describe autograft mechanical behavior. Autograft wall stresses at pulmonary vs. systemic pressures were examined. Autograft volume-based stress analysis was performed, based on percentage of autograft element volume exceeding 1 standard deviation (SD) above group mean stress at systemic systole.

Results

Mean first principal wall stresses (FPS) at systole of systemic versus pulmonary pressures were 129.29±17.47kPa versus 24.42±3.85kPa (p<0.001) at the annulus, 187.53±20.06kPa versus 35.98±2.15kPa at sinuses (p<0.001), and 268.68±23.40kPa versus 50.15±5.90kPa (p<0.001) at sinotubuluar junction (STJ). The percentage of autograft element volume that exceeded one SD above the group mean was 14.3±5.6% for FPS and 12.6±10.1% for second principal stresses.

Conclusion

We quantified normal human autograft biomechanical responses to systemic pressure based on patient-specific material properties. Regions of peak stresses were observed in autograft sinuses and STJ regions, which corresponded clinically to locations of autograft dilation. Our results provide valuable information on predicting variations in patient-specific ex vivo FE models when population-based material properties are used in settings where patient-specific properties are unknown.