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Genetic Risk Factors for Abdominal Aortic Aneurysms (AAA)
27
[121] Wild JB, Stather PW, Sylvius N, Choke E, Sayers RD, Bown MJ: Low density
lipoprotein receptor related protein 1 and abdominal aortic aneurysms. Eur J Vasc
Endovasc Surg 2012, 44:127-132.
[122] Boucher P, Gotthardt M, Li WP, Anderson RG, Herz J: LRP: role in vascular wall
integrity and protection from atherosclerosis. Science 2003, 300:329-332.
[123] Kho AN, Pacheco JA, Peissig PL, Rasmussen L, Newton KM, Weston N, Crane PK,
Pathak J, Chute CG, Bielinski SJ et al: Electronic medical records for genetic research:
results of the eMERGE consortium. Sci Transl Med 2011, 3:79re71.
[124] Kho AN, Hayes MG, Rasmussen-Torvik L, Pacheco JA, Thompson WK, Armstrong
LL, Denny JC, Peissig PL, Miller AW, Wei WQ et al: Use of diverse electronic
medical record systems to identify genetic risk for type 2 diabetes within a genome-
wide association study. J Am Med Inform Assoc 2012, 19:212-218.
[125] Peissig PL, Rasmussen LV, Berg RL, Linneman JG, McCarty CA, Waudby C, Chen L,
Denny JC, Wilke RA, Pathak J et al: Importance of multi-modal approaches to
effectively identify cataract cases from electronic health records. J Am Med Inform
Assoc 2012, 19:225-234.
[126] Ritchie MD, Denny JC, Crawford DC, Ramirez AH, Weiner JB, Pulley JM, Basford
MA, Brown-Gentry K, Balser JR, Masys DR et al: Robust replication of genotype-
phenotype associations across multiple diseases in an electronic medical record. Am J
Hum Genet 2010, 86:560-572.
[127] Chaikof EL, Brewster DC, Dalman RL, Makaroun MS, Illig KA, Sicard GA, Timaran
CH, Upchurch GR, Jr., Veith FJ: The care of patients with an abdominal aortic
aneurysm: the Society for Vascular Surgery practice guidelines. J Vasc Surg 2009,
50:S2-49.
[128] Deka R, Koller DL, Lai D, Indugula SR, Sun G, Woo D, Sauerbeck L, Moomaw CJ,
Hornung R, Connolly ES et al: The relationship between smoking and replicated
sequence variants on chromosomes 8 and 9 with familial intracranial aneurysm. Stroke
2010, 41:1132-1137.
[129] Mackey J, Brown RD, Jr., Moomaw CJ, Hornung R, Sauerbeck L, Woo D, Foroud T,
Gandhi D, Kleindorfer D, Flaherty ML et al: Familial intracranial aneurysms: Is
anatomic vulnerability heritable? Stroke 2013, 44:38-42.
[130] Visel A, Zhu Y, May D, Afzal V, Gong E, Attanasio C, Blow MJ, Cohen JC, Rubin
EM, Pennacchio LA: Targeted deletion of the 9p21 non-coding coronary artery disease
risk interval in mice. Nature 2010 464:409-412.
[131] Harismendy O, Notani D, Song X, Rahim NG, Tanasa B, Heintzman N, Ren B, Fu XD,
Topol EJ, Rosenfeld MG et al: 9p21 DNA variants associated with coronary artery
disease impair interferon-gamma signalling response. Nature 2011, 470:264-268.
[132] Kotake Y, Nakagawa T, Kitagawa K, Suzuki S, Liu N, Kitagawa M, Xiong Y: Long
non-coding RNA ANRIL is required for the PRC2 recruitment to and silencing of
p15(INK4B) tumor suppressor gene. Oncogene 2011, 30:1956-1962.
[133] Johnson AD, Hwang S-J, Voorman A, Morrison A, Peloso GM, Hu Y-H, Thanassoulis
G, Newton-Cheh C, Rogers IS, Hoffman U et al: Resequencing and clinical
associations of the 9p21.3 region: A comprehensive investigation in the Framingham
Heart Study. Circulation 2013 (in press).
[134] Schermerhorn M: A 66-year-old man with an abdominal aortic aneurysm: review of
screening and treatment. JAMA 2009, 302:2015-2022.
https://t.me/med1917
Helena Kuivaniemi, Evan J. Ryer, H. Richard Yoon et al.
28
[135] Beckman JA, Creager MA: Clinical evaluation of aortic aneurysms. In: Vascular
Medicine. Edited by Creager MA, Beckman JA, Loscalzo J, 2nd edn. Philadelphia:
Elsevier Saunders; 2013: 471-478.
[136] Sgaard R, Laustsen J, Lindholt JS: Cost effectiveness of abdominal aortic aneurysm
screening and rescreening in men in a modern context: evaluation of a hypothetical
cohort using a decision analytical model. BMJ 2012, 345:e4276.
[137] Chaudhry R, Tulledge-Scheitel SM, Parks DA, Angstman KB, Decker LK, Stroebel RJ:
Use of a Web-based clinical decision support system to improve abdominal aortic
aneurysm screening in a primary care practice. J Eval Clin Pract 2012, 18:666-670.
[138] Blois B: Office-based ultrasound screening for abdominal aortic aneurysm. Can Fam
Physician 2012, 58:e172-178.
[139] Cole CW, Barber GG, Bouchard AG, McPhail NV, Roberge C, Waddell WG,
Wellington JL: Abdominal aortic aneurysm: consequences of a positive family history.
Can J Surg 1989, 32:117-120.
[140] Darling RC, 3rd, Brewster DC, Darling RC, LaMuraglia GM, Moncure AC, Cambria
RP, Abbott WM: Are familial abdominal aortic aneurysms different? J Vasc Surg 1989,
10:39-43.
[141] Lawrence PF, Wallis C, Dobrin PB, Bhirangi K, Gugliuzza N, Galt S, Kraiss L:
Peripheral aneurysms and arteriomegaly: is there a familial pattern? J Vasc Surg 1998,
28:599-605.
[142] Salkowski A, Greb A, Al-Aouar R, Tromp G, Berguer R, Olson JM, Kuivaniemi H:
Familial incidence of abdominal aortic aneurysms. J Genet Counsel 1999, 8:407.
[143] Rossaak JI, Hill TM, Jones GT, Phillips LV, Harris EL, van Rij AM: Familial
abdominal aortic aneurysms in the Otago region of New Zealand. Cardiovasc Surg
2001, 9:241-248.
[144] Larsson E, Granath F, Swedenborg J, Hultgren R: A population-based case-control
study of the familial risk of abdominal aortic aneurysm. J Vasc Surg 2009, 49:47-50;
discussion 51.
[145] Bengtsson H, Norrgård O, Angquist KA, Ekberg O, Oberg L, Bergqvist D:
Ultrasonographic screening of the abdominal aorta among siblings of patients with
abdominal aortic aneurysms. Br J Surg 1989, 76:589-591.
[146] Collin J, Walton J: Is abdominal aortic aneurysm familial? BMJ 1989, 299:493.
[147] Webster MW, St Jean PL, Steed DL, Ferrell RE, Majumder PP: Abdominal aortic
aneurysm: results of a family study. J Vasc Surg 1991, 13:366-372.
[148] Adamson J, Powell JT, Greenhalgh RM: Selection for screening for familial aortic
aneurysms. Br J Surg 1992, 79:897-898.
[149] Bengtsson H, Sonesson B, Lanne T, Nilsson P, Solvig J, Loren I, Bergqvist D:
Prevalence of abdominal aortic aneurysm in the offspring of patients dying from
aneurysm rupture. Br J Surg 1992, 79:1142-1143.
[150] van der Lugt A, Kranendonk SE, Baars AM: [Screening for familial occurrence of
abdominal aortic aneurysm]. Ned Tijdschr Geneeskd 1992, 136:1910-1913.
[151] Adams DC, Tulloh BR, Galloway SW, Shaw E, Tulloh AJ, Poskitt KR: Familial
abdominal aortic aneurysm: prevalence and implications for screening. Eur J Vasc Surg
1993, 7:709-712.
[152] Moher D, Cole CW, Hill GB: Definition and management of abdominal aortic
aneurysms: results from a Canadian survey. Can J Surg 1994, 37:29-32.
https://t.me/med1917
Genetic Risk Factors for Abdominal Aortic Aneurysms (AAA)
29
[153] Fitzgerald P, Ramsbottom D, Burke P, Grace P, McAnena O, Croke DT, Collins P,
Johnson A, Bouchier-Hayes D: Abdominal aortic aneurysm in the Irish population: a
familial screening study. Br J Surg 1995, 82:483-486.
[154] Larcos G, Gruenewald SM, Fletcher JP: Ultrasound screening of families with
abdominal aortic aneurysm. Australas Radiol 1995, 39:254-256.
[155] Baird PA, Sadovnick AD, Yee IM, Cole CW, Cole L: Sibling risks of abdominal aortic
aneurysm. Lancet 1995, 346:601-604.
[156] Jaakkola P, Kuivaniemi H, Partanen K, Tromp G, Liljeström B, Ryynänen M: Familial
abdominal aortic aneurysms: screening of 71 families. Eur J Surg 1996, 162:611-617.
[157] van der Graaf Y, Akkersdijk GJ, Hak E, Godaert GL, Eikelboom BC: Results of aortic
screening in the brothers of patients who had elective aortic aneurysm repair. Br J Surg
1998, 85:778-780.
[158] Salo JA, Soisalon-Soininen S, Bondestam S, Mattila PS: Familial occurrence of
abdominal aortic aneurysm. Ann Intern Med 1999, 130:637-642.
[159] Frydman G, Walker PJ, Summers K, West M, Xu D, Lightfoot T, Codd C, Dique T,
Nataatmadja M: The value of screening in siblings of patients with abdominal aortic
aneurysm. Eur J Vasc Endovasc Surg 2003, 26:396-400.
[160] Ogata T, MacKean GL, Cole CW, Arthur C, Andreou P, Tromp G, Kuivaniemi H: The
lifetime prevalence of abdominal aortic aneurysms among siblings of aneurysm patients
is eightfold higher than among siblings of spouses: an analysis of 187 aneurysm
families in Nova Scotia, Canada. J Vasc Surg 2005, 42:891-897.
[161] Badger SA, O'Donnell ME, Boyd CS, Hannon RJ, Lau LL, Lee B, Soong CV: The low
prevalence of abdominal aortic aneurysm in relatives in Northern Ireland. Eur J Vasc
Endovasc Surg 2007, 34:163-168.
[162] Linne A, Lindström D, Hultgren R: High prevalence of abdominal aortic aneurysms in
brothers and sisters of patients despite a low prevalence in the population. J Vasc Surg
2012, 56:305-310.
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In: Aortic Aneurysms ISBN: 978-1-62618-458-9
Editors: Daniel Fischhof and Franz Hatig © 2013 Nova Science Publishers, Inc.
Chapter 2
ASSESSMENT OF AORTIC ANEURYSM RUPTURE RISK
AND SURGICAL REPAIR
Clement Kleinstreuer
1,2*
,
Emily Childress
2
and Mark Farber
3
1
Joint UNC-NCSU Department of Biomedical Engineering, NCSU, Raleigh, NC, US
2
Department of Mechanical and Aerospace Engineering, NCSU, Raleigh, NC, US
3
Department of Surgery, UNC-Chapel Hill, NC, US
ABSTRACT
Contributions to rupture-risk assessment and surgical repair of abdominal aortic
aneurysms (AAAs) are reviewed. AAA-rupture occurs when the local wall stress exceeds
the -wall strength. Such an event is quite unpredictable and rarely
foreshadowed by warning symptoms, but lethal in 80-90% of all cases. Typically, open
surgery or endovascular aneurysm repair (EVAR) by stent-graft insertion are
recommended if the maximum AAA-diameter exceeds 5.5cm. Still, a high degree of
uncertainty regarding the management of AAAs remains, especially for smaller AAAs.
Hence, reliable rupture-risk assessments as well as the development of criteria for well
anchored and durable stent-graft implantation are important ongoing research tasks.
Clearly, predictive accurate and realistic computer simulations of the transient three-
dimensional blood flow and affected AAA-wall dynamics can greatly contribute to the
solution of these problems.
Through multiple studies aimed at AAA rupture risk assessment, the peak wall stress
has emerged as a widely accepted rupture predictor. These studies have focused on
comparing clinical/experimental findings with computational analyses of determining
factors, such as changes in maximum wall stress magnitude, wall stress distribution, and
annual growth rate of the maximum AAA-diameter. Most recently, modeling and
simulation of two-way fluid-structure interactions of anisotropic, patient-specific AAAs
have improved the accuracy of AAA rupture predictions. In addition, advanced EVAR
techniques have successfully expanded the target population.
*
Corresponding Author: C. Kleinstreuer, E-mail: ck@ncsu.edu.
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Clement Kleinstreuer, Emily Childress and Mark Farber
32
1. INTRODUCTION
Abdominal aortic aneurysms (AAAs) are permanent pathological dilatations of the aorta
with maximum diameters at least 50% greater than in the healthy state. Often asymptomatic
for much of their lifespan, AAAs can grow and rupture without any warning, leading to
fatalities in 80-90% of all cases [Bengtsson and Bergqvist 1993]. To prevent such
occurrences, open surgery (OPEN) and endovascular aneurysm repair (EVAR) by stent-graft
insertion are available. However, due to their associated risks, these treatments are usually
withheld until the risk of rupture surpasses the risk of the best procedure. In many clinical
practices, this condition is considered satisfied when the maximum AAA diameter exceeds
5.5cm. However, AAAs below this diameter have also succumbed to rupture [Powell et al.
2011]. Thus, over the last few decades, alternative rupture-risk predictors and improved
treatment techniques have been proposed and implemented.
2. AAA RUPTURE-RISK ASSESSMENT
Like the normal abdominal aorta, AAAs must endure pulsatile blood flow with pressures
ranging from 80 to 120 mmHg, or even higher. Unlike normal aorta, the ability of the AAA-
wall to withstand such pressures may be compromised because of the presence of an
intraluminal thrombus (ILT) plus localized calcifications, asymmetry (i.e., curved centerline)
and larger diameters of AAAs, and variable wall thickness and material properties (see Figure
1). Thus, these and other characteristics have been investigated as potential AAA-rupture
predictors. In addition to these biomechanics-based parameters, physicians and researchers
have also proposed phenomenological parameters which can more readily be determined in
vivo, such as AAA growth rate and biomarkers. This section will review these parameters and
the methods used to determine them.
Figure 1. Characteristics of a Representative Abdominal Aortic Aneurysm.
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Assessment of Aortic Aneurysm Rupture Risk and Surgical Repair
33
2.1. AAA Maximum Diameter and Growth Rate
In the late 1980s, physicians were noticing an increase in the number of hospitalizations,
ruptures, and fatalities of AAA patients despite an increase in the number of elective repairs
[Powell et al. 1993]. As a result, the United Kingdom Small Aneurysm Trial (UKSAT) was
initiated in 1991 to investigate whether early elective surgery was appropriate for patients
with small AAAs. In this study, 1,090 patients with AAAs initially ranging from 4.0 5.5 cm
were randomly selected to either undergo early surgical repair or ultrasound surveillance
[U.K. Small Aneurysm Trial Participants 1998, 1999]. After an average follow-up period of
4.6 years, they found that elective repair did not provide a long-term survival benefit over
surveillance (6 year survival was 64% for both groups). Because of this and the high 30-day
mortality rate of patients in the elective repair group (5.8%), it was concluded that AAAs
below 5.5 cm (measured axially) should not undergo open surgery. Around the same time, a
similar trial, the Aneurysm Detection and Management (ADAM) study, was conducted
among 1,136 United States veterans with AAAs ranging from 4.0 to 5.4 cm, and the same
conclusion was made [Lederle et al. 2002a]. With the advent of endovascular aneurysm repair
(EVAR), it was again postulated whether early treatment of small AAAs provided an
advantage over surveillance. In the Positive Impact of Endovascular Options for Treating
Aneurysms Early (PIVOTAL) trial, 728 patients with small AAAs (4.0 5.0 cm) were
randomly selected to undergo either early EVAR or ultrasound surveillance and were
subsequently followed for an average of 20 months [Ouriel et al. 2010]. While the early
EVAR group exhibited a much lower 30-day mortality rate (0.6%) than open surgery, no
advantage was observed over the surveillance group, and they concluded that both protocols
could safely manage small AAAs. Thus, to minimize unnecessary repairs, the 5.5 cm
maximum axial diameter criterion is still widely used among vascular surgeons today. As the
measurement is impacted significantly by angulation, many specialists in the field use a
threshold of 5 cm orthogonally for treatment intervention. However, while these and other
studies [Nevitt et al. 1989, Lederle et al. 2002b] have demonstrated that AAA-rupture risk
increases with increasing diameter, there is still the potential for small ones to rupture while
large ones remain intact. Specifically, in a study of 370 AAAs, Nevitt et al. 1989 found that,
despite an increasing AAA growth rate with increasing diameter, this parameter was not
significantly associated with rupture. Confirming these findings in 233 AAAs, Stonebridge et
al. 1996 also concluded that the growth was an inadequate parameter for rupture prediction
because it was rather sporadic over time. While Lederle et al. 2002b found that the growth
rate was associated with rupture; this association was not significant when the last screened
AAA diameter was considered. Based on their findings from 63 AAA patients who
experienced growth of 0.5 cm or more in a 6-month period, Sharp and Collin 2003 also
concluded that AAA growth rate should not be used as a rupture predictor when they found
that the growth rates stabilized to the average value after they experienced this period of
increased growth. However, in a study of 467 AAA patients, Brown et al. 2003 found
increased mean and median growth rates among patients with ruptured AAAs. More recently,
Thompson et al. 2010 found a significant correlation between clinical events and an adjusted
yearly growth rate of 2 mm or more. Thus, they suggested that the growth rate should be
considered in addition to the diameter criterion and other risk factors. As a result, physicians
still often use the yearly growth rate when determining whether to recommend repair. Clearly,
there is a pressing need for more comprehensive and accurate rupture predictors.
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Clement Kleinstreuer, Emily Childress and Mark Farber
34
2.2. AAA Biomarkers
In recent years, biomarkers which can be detected through imaging or blood tests have
been sought for use in AAA diagnosis and rupture risk. One of the most studied of such
markers is 18F-fluorodeoxyglucose (FDG) which has been correlated with metabolic activity.
Demonstrating the efficacy of this biomarker, Truijers et al. 2008 found that FDG uptake was
increased in AAAs over sex and age-matched non-aneurysmal aortas. Additionally, Reeps et
al. 2008 found increased FDG uptake in symptomatic AAAs over asymptomatic AAAs and
nonaneurysmal aortas. The predictability of FDG uptake was further tested in patient-specific
AAAs where correlations were found with rapid AAA expansion in Reeps et al. 2009 and
Kotze et al. 2011. Most convincingly, Xu et al. 2009 compared images of FDG uptake with
wall stress analyses in 5 aneurysms and found that regions of elevated FDG uptake correlated
with regions of elevated wall stress.
In addition to FDG, other studies have proposed alternative biomarkers. By detecting
proteins released by ILT, Martinez-Pinna et al. 2011 found peroxiredoxin-1 to be increased in
AAA patients and suggested it as a possible AAA biomarker. Hellenthal et al. 2012, on the
other hand, suggested high-sensitivity C-reactive protein, high-density lipoprotein, and
immunoglobulin G concentrations due to their correlations with AAA size. Alternatively, Lv
et al. 2012 proposed cathepsin S and cystatin C as biomarkers.
Despite this encouraging work, Golledge et al. 2008 concluded that, while biomarkers
such as plasma fibrinogen, D-dimer, and IL-6 have been associated with AAAs, there is
inadequate evidence to suggest that any single biomarker can be used to diagnose AAA
development. In another review, Urbonavicius et al. 2008 essentially came to the same
conclusion, although they found that serum elastin peptides, plasmin-antiplasmin complexes,
matrix-degrading metalloproteinase 9, and interferon-gamma showed promise. Still, both
teams concluded that larger studies should be performed to assess the adequacy of these
biomarkers.
2.3. AAA Biomechanics
Given that AAA rupture is a consequence of the wall stress exceeding the wall strength,
peak wall stress (PWS) and the stress-to-strength ratio are considered to be more accurate
rupture predictors than the previously discussed geometric and biological parameters. With
the advent and increase of computational fluid, particle, and structural dynamics analyses,
these biomechanics-based parameters have been the focus of much research over the last
decade. This section reviews the accuracy of these parameters in predicting AAA rupture as
well as the advances made in modeling AAA biomechanics.
2.3.1 Peak Wall Stress
To assess the efficacy of peak wall stress as a rupture predictor, several analyses have
compared the stresses of ruptured versus unruptured AAAs. In a study by Fillinger et al.
2002, AAAs were separated into those that ruptured or required emergency repair (n = 10 and
8, respectively) and those that were electively repaired (n = 30). Using finite element
analyses, they found that, among diameter-matched AAAs, the PWS was significantly higher
in the ruptured/emergency repaired group (46.8 ± 4.5 N/cm
2
) compared to the electively
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Assessment of Aortic Aneurysm Rupture Risk and Surgical Repair
35
repaired group (38.1 ± 1.3 N/cm
2
). Additionally, for cases in which the rupture location was
known, they observed a correlation between the PWS location and the rupture site. To better
assess the accuracy of wall stress in rupture prediction, the same group [Fillinger et al. 2003]
performed finite element studies in AAAs that were initially asymptomatic. Of the 103 AAAs
monitored, 42 remained in the surveillance group after 1 year, 39 underwent elective repair,
and 22 experienced rupture or emergency surgery. Comparing the results of each group, they
found that PWS was a better predictor of eventual rupture or emergency surgery than
maximum diameter. Also, they again found that, for AAAs in which the rupture location was
known, PWS correlated with the site of rupture. A separate group, Venkatasubramaniam et al.
2004, confirmed these findings using 15 unruptured AAAs and 12 ruptured ones (PWS: 102
N/cm
2
for ruptured vs. 62 N/cm
2
for unruptured). While Truijers et al. 2007 also found the
PWS to be significantly higher in their ruptured group compared to their asymptomatic group
when the patient-specific systolic pressure was applied. They found that the elevated PWS
was not significant among these groups when a uniform systolic pressure of 120 mmHg was
applied. Nevertheless, Heng et al. 2008 strengthened the case for PWS when they compared
wall stresses between their surveillance and ruptured/symptomatic groups. Using a different
approach, Doyle et al. 2010 further strengthened the case for PWS when they compared
experimental and computational studies of 5 AAA configurations (1 ideal AAA, 4 patient-
specific AAAs). Pressurizing silicone rubber models until rupture (4 models for each
configuration were tested, total of 20), they found that, for 16 of the 20 models, the rupture
site correlated with the computed PWS location. The other 4 models either ruptured at high
stress locations or at sites of wall defects incurred during manufacturing.
Despite these encouraging results, biomechanics tells us that wall stress must exceed wall
strength for rupture to occur. As a result, PWS alone may not be the best indicator of AAA
rupture risk. Thus, the stress-to-strength ratio is a better predictor; however, it requires both
an accurate measurement of the wall strength as well as the induced wall stress.
2.3.2. Wall Strength and the Stress-to-Strength Ratio
One of the first measurements of AAA-wall strength was provided in Raghavan et al.
1996 (also given in Vorp et al. 1996a) who reported the mean ultimate strengths in the
longitudinal and circumferential directions to be 86.4 ± 10.2 N/cm
2
(for 52 samples from 45
AAAs) and 101.9 ± 16.0 N/cm
2
(for 19 samples from 16 AAAs), respectively. Later studies
reported mean ultimate strengths of 53 N/cm
2
(for 96 samples from 24 AAAs in Vallabhaneni
et al. 2004), 80.5 N/cm
2
(for 60 samples from 29 AAAs in Vande Geest et al. 2006a), and
95.2 N/cm
2
(for 143 samples from 50 AAAs in Reeps et al. 2012).
Studying the spatial variation of wall strength, Thubrikar et al. 2001a performed uniaxial
tension tests on 21 longitudinally oriented and 26 circumferentially oriented tissue samples
from the anterior, posterior, and lateral regions of 5 AAAs. They found that the
circumferentially oriented samples in the lateral region exhibited the greatest mean yield
strength (73 ± 22 N/cm
2
) while the longitudinally oriented samples in the anterior region
exhibited the smallest (38 ± 18 N/cm
2
). However, testing 48 longitudinal samples from 4
AAAs, Raghavan et al. 2006a did not find a pattern in the strengths along the AAA
circumference. This was later confirmed in a subsequent study by the same group [Raghavan
et al. 2011]. Contrary to intuition, this study also found no significant differences between the
mean strengths of ruptured and unruptured AAA samples (95 ± 28 and 98 ± 23 N/cm
2
,
respectively). However, they did find significant variation in strength both between and
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Clement Kleinstreuer, Emily Childress and Mark Farber
36
within individual AAAs. This may partly be explained by the variation of ILT presence and
thickness which has been associated with decreasing wall strength [Vorp et al. 2001].
Given these variations in strength, the use of uniformly distributed, population-averaged
values would not be sufficient when assessing rupture risk. However, the spatially varying,
patient-specific AAA wall strength still cannot be determined without destructive methods.
Thus, a noninvasive technique for specifying spatially varying wall strength was proposed in
Vande Geest et al. 2006a which considers local intraluminal thickness (ILT), normalized local
diameter (NORD), family history (HIST), and sex in a statistical model:
(1)
Here, the measurements from uniaxial tension tests of 60 samples from 29 AAAs were
used to determine the parameters for the model. Using the remaining 21 samples from 9
AAAs, they demonstrated that this model could provide adequate strength prediction.
Subsequently, Maier et al. 2010a was able to compare the diameter, PWS, local stress-to-
strength ratio (called RPI in Vande Geest et al. 2006a), peak wall displacement, and peak wall
strain between 30 unruptured and 23 ruptured/symptomatic AAAs. While they found
significant differences in these parameters between the two groups, the RPI provided the most
significant distinction. Xenos et al. 2010a further demonstrated the usefulness of the RPI
when they showed that the maximum RPI coincided with the rupture site. However, in Reeps
et al. 2012, no correlation was found between strength and three of the four noninvasive
parameters used in the Vande Geest strength model (local ILT thickness, normalized local
diameter, and sex). Thus, more studies should be undertaken to validate, revise, or replace
this model. Alternatively, non-destructive techniques for measuring patient-specific wall
strength are needed.
2.3.3. Wall Material Properties and Modeling
In addition to wall strength, knowledge of the AAA stress-strain behavior is required for
correct wall stress calculations. To better understand the behavior of these tissues, it is first
important to examine their composition. A healthy abdominal aorta consists of elastin,
collagen, smooth muscle, and ground substance. With elastin and collagen providing most of
the structural support, the aorta exhibits nonlinear stiffening when subjected to increasing
stretch. In studying iliac arteries, Roach and Burton 1957 concluded that this behavior was
attributed to the continuous stretch and recruitment of initially wavy collagen fibers,
explaining that the elastin provides the structural support at low pressures while the collagen
provides most of the support at higher, physiological pressures. In contrast to the healthy
state, He and Roach 1994 found that AAA tissue has significantly increased collagen and
ground substance (96.5 ± 2.5% versus 54.8 ± 4.5% in nonaneurysmal tissue) and significantly
decreased elastin (2.4 ± 2.2% versus 22.7 ± 5.7%) and smooth muscle (2.2 ± 2.0% versus
22.6 ± 5.5%). This may explain why studies have shown AAA specimen to exhibit a stiffer
response than nonaneurysmal aorta.
Using ultrasound to detect in vivo changes in diameter, Lanne et al. 1992 was one of the
first studies to demonstrate the stiffer response of AAAs over nonaneurysmal aortas.
Subsequent studies using uniaxial tensile tests confirmed this finding and also demonstrated
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