ErhartPRoyJde VriesJP. Prediction of rupture sites in abdominal aortic aneurysms after finite element analysis. J Endovasc Ther. 2016;23:115–120.
2.
DoyleBJMcGloughlinTM. Computer-aided diagnosis of abdominal aortic aneurysm. In: McGloughlinTM. Biomechanics and Mechanobiology of Aneurysms. Heidelberg, Germany: Springer; 2011:119–138.
3.
DoyleBJMcGloughlinTMMillerK. Regions of high wall stress can predict the future location of abdominal aortic aneurysm rupture. Cardiovasc Intervent Radiol. 2014;37:815–818.
4.
DoyleBJCallananAGracePA. On the influence of patient-specific material properties on computational simulations: a case study of a large ruptured abdominal aortic aneurysm. Int J Numer Methods Biomed Eng. 2013;29:150–164.
5.
XenosMRambhiaSHAlemuY. Patient-based abdominal aortic aneurysm rupture risk prediction with fluid structure interaction modeling. Ann Biomed Eng. 2010;38:3323–3337.
6.
GasserTCAuerMLabrutoF. Biomechanical rupture risk assessment of abdominal aortic aneurysms: model complexity versus predictability of finite element simulations. Eur J Vasc Endovasc Surg. 2010;40:176–185.
7.
ErhartPHyhlik-DurrAGeisbuschP. Finite element analysis in asymptomatic, symptomatic, and ruptured abdominal aortic aneurysms: in search of new rupture risk predictors. Eur J Vasc Endovasc Surg. 2015;49:239–245.
8.
MaierAGeeMWReepsC. A comparison of diameter, wall stress and rupture potential index for abdominal aortic aneurysm rupture risk prediction. Ann Biomed Eng. 2010;38:3124–3134.
9.
GasserTCNchimiASwedenborgJ. A novel strategy to translate the biomechanical rupture risk of abdominal aortic aneurysm to their equivalent diameter risk: method and retrospective validation. Eur J Vasc Endovasc Surg. 2015;47:288–295.
10.
DoyleBJHoskinsPRMcGloughlinTM. Computational rupture prediction of AAA: what needs to be done next?J Endovasc Ther. 2011;18:226–229.
11.
GeorgakarakosEIoannouCVPapaharilaouY. Computational evaluation of aortic aneurysm rupture risk: what have we learned so far?J Endovasc Ther. 2011;18:214–225.
12.
Vande GeestJPSacksMSVorpDA. A planar biaxial constitutive relation for the intraluminal thrombus in abdominal aortic aneurysms. J Biomech. 2006;39:2347–2354.
13.
O’LearySKavanaghEGGracePA. The biaxial mechanical behaviour of abdominal aortic aneurysm intraluminal thrombus: classification of morphology and the determination of layer and region specific properties. J Biomech. 2014;47:1430–1437.
14.
TongJHolzapfelGA. Structure, mechanics, and histology of intraluminal thrombi in abdominal aortic aneurysms. Ann Biomed Eng. 2015;43:1488–1501.
15.
WangDHMakarounMWebsterMW. Mechanical properties and microstructure of intraluminal thrombus from abdominal aortic aneurysm. J Biomech Eng. 2001;123:536–539.
ShumJDi MartinoESGoldhammerA. Semi-automatic vessel wall detection and quantification of wall thickness in CT images of human abdominal aortic aneurysm. Med Phys. 2010;37:638–648.
18.
MensalBQuadratASchneiderT. MRI-based determination of reference values of thoracic aortic wall thickness in a generation population. Eur Radiol. 2014;24:2038–2044.
19.
JoldesGRMillerKWittekA. A simple, effective and clinically-applicable method to compute abdominal aortic aneurysm wall stress [published online August5, 2015]. J Mech Behav Biomed Mater. doi:10.1016/j.jmbbm.2015.07.029.
20.
ReepsCMaierAPelisekJ. Measuring and modelling patient-specific distributions of material properties in abdominal aortic aneurysm wall. Biomech Model Mechanobiol. 2013;12:717–733.
21.
RichardsJMSempleSIMacGillivrayTJ. Abdominal aortic aneurysm growth predicted by ultrasmall superparamagnetic particles of iron oxide: a pilot study. Circ Cardiovasc Imaging. 2011;4:274–281.
22.
McBrideOMBerryCBurnsP. MRI using ultrasmall superparamagnetic particles of iron oxide in patients under surveillance for abdominal aortic aneurysms to predict rupture or surgical repair: MRI for abdominal aortic aneurysms to predict rupture or surgery—the MA3RS study. OpenHeart. 2015;2:e000190.
23.
Vande GeestJPDi MartinoESBohraA. A biomechanics-based rupture potential index for abdominal aortic aneurysm risk assessment: demonstrative application. Ann N Y Acad Sci. 2006;1085:11–21.
24.
Vande GeestJPSacksMSVorpDA. The effects of aneurysm on the biaxial mechanical behavior of human abdominal aorta. J Biomech. 2006;39:1324–1334.
25.
O’LearySHealeyDAKavanaghEG. The biaxial biomechanical behaviour of abdominal aortic aneurysm tissue. Ann Biomed Eng. 2014;42:2440–2450.
26.
TongJCohnertTHolzapfelGA. Diameter-related changes variations of geometrical, mechanical, and mass fraction data in the anterior portion of abdominal aortic aneurysms. Eur J Vasc Endovasc Surg. 2015;49:262–270.
27.
MillerKLuJ. On the prospect of patient-specific biomechanics without patient-specific properties of tissues. J Mech Behav Biomed Mater. 2013;27:154–166.
28.
Hyhlik-DürrAKriegerTGeisbüschP. Reproducibility of deriving parameters of AAA rupture risk from patient-specific 3D finite element models. J Endovasc Ther. 2011;18:289–298.
29.
SpeelmanLBohraABosboomEM. Effects of wall calcifications in patient-specific wall stress analyses of abdominal aortic aneurysms. J Biomech Eng. 2007;129:1–5.
30.
LiZYU-King-ImJTangTY. Impact of calcification and intraluminal thrombus on the computed wall stresses of abdominal aortic aneurysm. J Vasc Surg. 2008;47:928–935.
31.
MaierAGeeMWReepsC. Impact of calcifications on patient-specific wall stress analysis of abdominal aortic aneurysms. Biomech Model Mechanbiol. 2010;9:511–521.
32.
O’LearySMulvihillJBarrettH. Determining the influence of calcification on the failure properties of abdominal aortic aneurysm (AAA) tissue. J Mech Behav Biomed Mater. 2015;42:154–167.
33.
JoshiNVVeseyATWilliamsMC. 18F-fluoride positron emission tomography for identification of ruptured and high-risk coronary atherosclerotic plaques: a prospective clinical trial. Lancet. 2014;383:705–713.
