Abdominal aortic aneurysm wall stress: A 7-line code in MATLAB and a one-click software application
<|reference_start|>Abdominal aortic aneurysm wall stress: A 7-line code in MATLAB and a one-click software application: An abdominal aortic aneurysm (AAA) is a life-threatening condition characterized by the irreversible dilation of the lower aorta, usually detected incidentally during imaging for other health issues. Current clinical practice for managing AAA relies on a one-size-fits-all approach, based on the aneurysm's maximum diameter and growth rate, which can lead to underestimation or overestimation of AAA rupture risk. Patient-specific AAA wall stress, computed using biomechanical models derived from medical images without needing patient-specific material properties, has been widely investigated for developing individualized AAA rupture risk predictors. Therefore, AAA wall stress, determined reliably and quickly, has the potential to enhance patient-specific treatment plans. This paper presents a 7-line code, written in MATLAB using the Partial Differential Equation Toolbox, for AAA wall stress computations via finite element analysis. The code takes AAA wall geometry as input and outputs stress components over the AAA wall domain. Additionally, we present a one-click standalone software application for AAA wall stress computation, developed based on our 7-line code using MATLAB Compiler. After verification, we used our code to compute AAA wall stress in ten patients. Our analysis indicated that the 99th percentile of maximum principal stress across all patients ranged from 0.320 MPa to 0.522 MPa, with an average of 0.401 MPa and a standard deviation of 0.056 MPa. Moreover, for every case, the MATLAB simulation time was less than a minute on a laptop workstation.<|reference_end|>
@article{jamshidian2024abdominal,
    title={Abdominal aortic aneurysm wall stress: A 7-line code in MATLAB and a
  one-click software application},
    author={Mostafa Jamshidian, Saeideh Sekhavat, Adam Wittek, Karol Miller},
    journal={arXiv preprint arXiv:2407.05242},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.05242},
    primaryClass={cs.CE}
}