Patient-specific biomechanical profiling in abdominal aortic aneurysm development and rupture

Malkawi, Amir H.; Hinchliffe, Robert J.; Xu, Yun; Holt, Peter; Loftus, Ian; Thompson, Matt

doi:10.1016/j.jvs.2010.01.029

Cited by 45 publications

(33 citation statements)

References 110 publications

(176 reference statements)

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“…15,70 DISCUSSION AAA development and rupture are a combined result of the interaction of biological and biomechanical changes, leading to degradation and remodeling of the extracellular matrix. 71 The biomechanical approach offers a new insight into the estimation of AAA rupture risk. 72 Although more complex to obtain, the patient-specific biomechanical profile can more accurately estimate the rupture risk than maximum diameter, morphological indices, and serum markers, 71 as showed by the aforementioned studies.…”

Section: Advances In Aneurysm Computational Modelsmentioning

confidence: 99%

“…Generally, the sites of rupture have been shown to correlate well with regions of high wall stress, underscoring the biomechanical principles of rupture at sites where stress exceeds the local failure strength. 71 Moreover, such sites of elevated PWS have been postulated to be sites of accelerated metabolism since they are associated with high levels of 18F-fluorodeoxyglucose uptake in the aneurysm wall, as detected by positron emission tomographic computed tomography. 72 It has been shown that the simultaneous calculation of an individual's AAA wall strength and conjugation with the PWS in a rupture potential index (RPI) can better differentiate between electively repaired and ruptured AAA cases when compared with either PWS or maximum diameter alone.…”

Section: Advances In Aneurysm Computational Modelsmentioning

confidence: 99%

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Computational Evaluation of Aortic Aneurysm Rupture Risk: What Have We Learned So Far?

Georgakarakos

Ioannou

Papaharilaou

et al. 2011

Journal of Endovascular Therapy

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In current clinical practice, aneurysm diameter is one of the primary criteria used to decide when to treat a patient with an abdominal aortic aneurysm (AAA). It has been shown that simple association of aneurysm diameter with the probability of rupture is not sufficient, and other parameters may also play a role in causing or predisposing to AAA rupture. Peak wall stress (PWS), intraluminal thrombus (ILT), and AAA wall mechanics are the factors most implicated with rupture risk and have been studied by computational risk evaluation techniques. The objective of this review is to examine these factors that have been found to influence AAA rupture. The prediction rate of rupture among computational models depends on the level of model complexity and the predictive value of the biomechanical parameters used to assess risk, such as PWS, distribution of ILT, wall strength, and the site of rupture. There is a need for simpler geometric analogues, including geometric parameters (e.g., lumen tortuosity and neck length and angulation) that correlate well with PWS, conjugated with clinical risk factors for constructing rupture risk predictive models. Such models should be supported by novel imaging techniques to provide the required patient-specific data and validated through large, prospective clinical trials.

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Section: Advances In Aneurysm Computational Modelsmentioning

confidence: 99%

Section: Advances In Aneurysm Computational Modelsmentioning

confidence: 99%

Computational Evaluation of Aortic Aneurysm Rupture Risk: What Have We Learned So Far?

Georgakarakos

Ioannou

Papaharilaou

et al. 2011

Journal of Endovascular Therapy

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“…Acknowledging that there are limitations inherent to image acquisition sequences and resolution, deriving accurate segmentation and geometric modeling algorithms are highlighted as open problems in computational vascular biomechanics [7]. Thickness, nonlinear material behavior, strength of the AAA wall, and the spatial distribution of these variables are said to be essential for achieving accurate finite element (FE) simulations and, therefore, also for a realistic prediction of AAA rupture risk [8,9].…”

Section: Introductionmentioning

confidence: 99%

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

Raut

Jana

Oliveira

et al. 2013

Journal of Biomechanical Engineering

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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 ¼ 0.002), strain (p ¼ 0.0005), and strain-energy density (p ¼ 7.83 e-5) but not for displacement (p ¼ 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 ¼ 9.68 e-7), strain (p ¼ 1.03 e-8), strain-energy density (p ¼ 9.94 e-8), and displacement (p ¼ 0.0059). No significant differences were obtained comparing the UT and PSUT strategies for the spatial maxima of the first principal stress (p ¼ 0.285), strain (p ¼ 0.152), strain-energy density (p ¼ 0.222), and displacement (p ¼ 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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“…Patient specific biomechanical profiling has been suggested as a potentially valuable tool in rupture risk assessment [8,9]. Additionally, peak wall stress (PWS) has been reported to be greater in ruptured and symptomatic AAAs compared to asymptomatic AAAs [10], and PWS has been reported to predict location of future rupture [9,11].…”

Section: Introductionmentioning

confidence: 99%

Infra-renal abdominal aortic calcification volume does not predict small abdominal aortic aneurysm growth

et al. 2015

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a b s t r a c tBackground: Vascular calcification is a common finding in abdominal aortic aneurysms (AAA) however whether it predicts aneurysm expansion is controversial. Objectives: 1) To establish a reproducible method of assessing AAA calcification using computed tomography (CT); 2) To investigate the association between AAA calcification and growth. Method: Patients were identified from a prospectively maintained small AAA surveillance database. To be included patients required at least two CT scans a minimum of 6 months apart. All patients had a maximal AAA diameter of 55 mm on their initial scan. Infra-renal aortic calcification volume, total infra-renal aortic volume and maximal AAA diameter were measured. Reproducibility was assessed from repeat scans performed on 31 patients. AAA growth, estimated by volume change per year, was compared between patients with baseline infra-renal aortic calcification volumes< and !median. Results: 95% agreement limits (lower, upper) for intra and inter-observer error in measuring infra-renal aortic calcification volume were 0.68, 97 mm 3 and À140, 5.8 mm 3 , respectively. Concordance correlation coefficients for inter and intra-observer variability in measuring infra-renal aortic calcification volume were 0.99 and 0.99, respectively. Patients with infra-renal aortic calcification volume < median (n ¼ 44) and !median (n ¼ 44) had an infra-renal aortic volume increase of 6.0 cm 3 /yr and 7.8 cm 3 /yr, respectively (p ¼ 0.66). Mean percentage infra-renal aortic volume increase/yr was found to be 4.2 ± 6.4 and 8.9 ± 6.2 for patients with and without diabetes, respectively (p ¼ 0.003). Conclusion: Infra-renal aortic calcification volume can be assessed reproducibly from CT images. Infrarenal aortic calcification volume did not predict small AAA growth.Crown

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Patient-specific biomechanical profiling in abdominal aortic aneurysm development and rupture

Cited by 45 publications

References 110 publications

Computational Evaluation of Aortic Aneurysm Rupture Risk: What Have We Learned So Far?

Computational Evaluation of Aortic Aneurysm Rupture Risk: What Have We Learned So Far?

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

Infra-renal abdominal aortic calcification volume does not predict small abdominal aortic aneurysm growth

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