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Research Papers

The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

[+] Author and Article Information
Samarth S. Raut

Carnegie Mellon University,
Department of Mechanical Engineering,
5000 Forbes Avenue,
Pittsburgh, PA 15213;
The University of Texas at San Antonio,
Department of Biomedical Engineering,
AET 1.360,
One UTSA Circle,
San Antonio, TX 78249

Anirban Jana

Pittsburgh Supercomputing Center,
Scientific Applications and User Services,
300 S. Craig Street,
Pittsburgh, PA 15213

Victor De Oliveira

The University of Texas at San Antonio,
Department of Management Science and Statistics,
One UTSA Circle,
San Antonio, TX 78249

Satish C. Muluk

Western Pennsylvania Allegheny Health System,
Allegheny General Hospital,
Division of Vascular Surgery,
320 East North Avenue,
Pittsburgh, PA 15212

Ender A. Finol

The University of Texas at San Antonio,
Department of Biomedical Engineering,
AET 1.360,
One UTSA Circle,
San Antonio, TX 78249
e-mail: ender.finol@utsa.edu

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received November 28, 2012; final manuscript received April 14, 2013; accepted manuscript posted May 15, 2013; published online June 12, 2013. Assoc. Editor: Naomi Chesler.

J Biomech Eng 135(8), 081010 (Jun 12, 2013) (10 pages) Paper No: BIO-12-1587; doi: 10.1115/1.4024578 History: Received November 28, 2012; Revised April 14, 2013; Accepted May 15, 2013

Abdominal aortic aneurysm (AAA) is a vascular condition where the use of a biomechanics-based assessment for patient-specific risk assessment is a promising approach for clinical management of the disease. Among various factors that affect such assessment, AAA wall thickness is expected to be an important factor. However, regionally varying patient-specific wall thickness has not been incorporated as a modeling feature in AAA biomechanics. To the best our knowledge, the present work is the first to incorporate patient-specific variable wall thickness without an underlying empirical assumption on its distribution for AAA wall mechanics estimation. In this work, we present a novel method for incorporating regionally varying wall thickness (the “PSNUT” modeling strategy) in AAA finite element modeling and the application of this method to a diameter-matched cohort of 28 AAA geometries to assess differences in wall mechanics originating from the conventional assumption of a uniform wall thickness. For the latter, we used both a literature-derived population average wall thickness (1.5 mm; the “UT” strategy) as well as the spatial average of our patient-specific variable wall thickness (the “PSUT” strategy). For the three different wall thickness modeling strategies, wall mechanics were assessed by four biomechanical parameters: the spatial maxima of the first principal stress, strain, strain-energy density, and displacement. A statistical analysis was performed to address the hypothesis that the use of any uniform wall thickness model resulted in significantly different biomechanical parameters compared to a patient-specific regionally varying wall thickness model. Statistically significant differences were obtained with the UT modeling strategy compared to the PSNUT strategy for the spatial maxima of the first principal stress (p = 0.002), strain (p = 0.0005), and strain-energy density (p = 7.83 e–5) but not for displacement (p = 0.773). Likewise, significant differences were obtained comparing the PSUT modeling strategy with the PSNUT strategy for the spatial maxima of the first principal stress (p = 9.68 e–7), strain (p = 1.03 e–8), strain-energy density (p = 9.94 e–8), and displacement (p = 0.0059). No significant differences were obtained comparing the UT and PSUT strategies for the spatial maxima of the first principal stress (p = 0.285), strain (p = 0.152), strain-energy density (p = 0.222), and displacement (p = 0.0981). This work strongly recommends the use of patient-specific regionally varying wall thickness derived from the segmentation of abdominal computed tomography (CT) scans if the AAA finite element analysis is focused on estimating peak biomechanical parameters, such as stress, strain, and strain-energy density.

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Figures

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Fig. 1

Framework for image segmentation with capability for variable wall thickness estimation [15]

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Fig. 4

Intermediate steps in wall thickness implementation and qualitative assessment with final mesh; (a) superposition of splines and surface mesh; (b) interpolated wall thickness; (c) qualitative assessment of thickness modeling by comparing interpolated thickness distribution and final FE volume mesh

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Fig. 3

Schematic of cosine correction for mesh extrusion

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Fig. 2

Estimated wall thickness distribution (in mm) in a point cloud resulting from a segmented CT dataset [17]

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Fig. 5

Outcome of the mesh sensitivity study showing incremental percentage differences (y-axis) in the biomechanical parameters as a function of the average edge length of the surface tessellation (x-axis; a larger edge length indicates a coarser mesh). An increase in the edge length depicted along the x-axis results in a quadratic increase in the number of elements in the mesh.

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Fig. 6

Box-and-whisker plots highlighting differences for the three wall thickness modeling strategies; (a) maximum first principal stress (N/cm2); (b) maximum first principal strain; (c) maximum strain energy density (105 erg/cm3); (d) maximum displacement (cm)

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Fig. 7

Comparison of the regional distribution of biomechanical parameters for a representative AAA model obtained with UT—uniform thickness (0.15 cm), PSUT—patient-specific uniform thickness (0.2044 cm), PSNUT—patient-specific nonuniform thickness (0.2044 ± 0.0487 cm). σmax—maximum principal stress, εmax—maximum principal strain, ψmax—strain energy density, δmax—maximum displacement magnitude.

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Fig. 8

Limitations of a mask dilation approach for wall thickness modeling; (a) errors due to inherent differences in rectangular image grid and circular shape of the anatomy; (b) effective thickness along the local normal direction is a function of the slope in the plane normal to the image for the same dilation t in the image plane (L denotes the direction of image stacking); (c) schematic with 1 px dilation showing nonuniform dilation around the periphery (Px—pixel resolution)

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