Diss. (sammanfattning) Stockholm : Karol. inst., 2005. / Härtill 4 uppsatser.

Objectives: Clinical implementation of 3D ultrasound (3D-US) in vascular surgery is in its infancy. The aim of this thesis was to develop novel clinical applications for 3D-US in the diagnosis and management of abdominal aortic aneurysm (AAA). Methods: Four principle clinical applications were investigated. 1) Intraoperative imaging – The ability of 3D-US to detect and classify endoleaks was compared with digital subtraction angiography in patients undergoing EVAR. 2) Detection and classification of endoleaks following endovascular aneurysm repair (EVAR) – The abilityof 3D-US to accurately detect and classify endoleaks following EVAR was compared to CTA and the final multi-disciplinary team decision. 3) AAA volume measurement – measurements using magnetic and optically-tracked 3D-US were compared to CTA. 4) Biomechanical analysis – the challenges of using 3D-US to generate surface models for biomechanical simulation was explored by development of an interactive segmentation technique and comparison of paired CT and 3D-US datasets. Optimal results were used in finite element analysis (FEA) and computational fluid dynamic(CFD) simulations. Results: 3D-US out-performed uniplanar angiography for the detection of endoleaks during EVAR. This approach allowed contrast-free EVAR to be performed in patients with poor renal function. 3D contrast-enhanced ultrasound was superior to CTA for endoleak detection and classification when compared with the final decision of the multi-disciplinary team. Optimal results for AAA volume measurements were gained using an optically tracked 3D-US system in EVAR surveillance. However, there remained a significant mean difference of 13.6ml between CT and 3D-US. Complete technical success of generating geometries for use in biomechanical analysis using 3D-US was only 5%. When the optimal results were used, a comparable CFD analysis under the conditions of steady, laminar and Newtonian flow was achieved. Using basic modelling assumptions in FEA, peak von Mises and principle wall stress was found to be at the same anatomical location on both the CT and 3D-US models but the 3D-US model overestimated the wall stress values by 41% and 51% respectively. Conclusions: 3D-US could be clinically implemented for intra-operative imaging and EVAR surveillance in specific cases. 3D-US volume measurement is feasible but future work should aim to improve accuracy and inter-observer reliability. Although the results of biomechanical analysis using the optimal results was encouraging and provided a proof-of-principal, there are a number of technical developments required to make this approach feasible in a larger number of patients.

<div>An abdominal aortic aneurysm (AAA) is a pathological dilation of the abdominal aorta, as defined by a 50% increase in diameter or a diameter greater than 3 cm. While typically asymptomatic, there is a risk that the AAA will rupture, causing massive hemorrhaging and high mortality rates. Thus, once detected, the clinician must choose between surveillance and elective surgical repair. The first option carries the risk of rupture; the second risks complications and graft failure. Currently, clinical metrics of rupture risk are dependent on diameter and growth rate. However, a number of studies have indicated that, although rupture risk does increase with increased diameter, there are also a large number of patients with aneurysms for which the diameter criteria is insufficient. There remains a strong need to 1) determine better estimates of rupture risk in order to accurately assess the need for surgery and 2) improve surgical treatment to reduce perioperative risk. </div><div><br></div><div>Herein, we use ultrasound in mice to address these two prevalent uncertainties in aneurysm development and treatment. First, we further develop a murine aneurysm model that forms large aneurysms with distal thrombus. To increase the applicability of the model, we modulate aneurysm growth by altering elastase concentration and lysyl oxidase inhibition. We show that initial elastase concentration impacts aneurysm size, which is driven in part by a change in the degree of initial degradation of the aortic wall. We also demonstrate that lysyl oxidase inhibition (via BAPN) remains necessary for expansion even after the initial aneurysm formation and that removal of the lysyl oxidase inhibitor effectively stops growth in this model. As a final point, we show that female mice develop larger aneurysms than the males using this model. Then, with the aim of improving surgical treatment options, we explore the patency of various design parameters involved in tissue-engineered vascular grafts. To do so, we assess the allowable parameter design space of murine textile arterial grafts, so as to lead to better selection of key design components. Overall, the findings in this thesis demonstrate the applicability of ultrasound in small animals to improve aneurysm diagnostic and treatment options.</div>

Cerebral aneurysms occur due to the ballooning of blood vessels in the brain. Rupture of aneurysms can cause a subarachnoid hemorrhage, which, if not fatal, can cause permanent neurologic deficits. Minimally invasive neurovascular devices, such as embolization coils and flow diverters, are methods of treatment utilized to prevent aneurysm rupture. The rapidly growing market for neurovascular devices necessitates the development of accurate aneurysm models for preclinical testing. In vivo models, such as the rabbit elastase model, are commonly chosen for preclinical device testing; however, these studies are expensive, and aneurysm geometries are difficult to control and often do not replicate the variety of geometries found in clinical cases. A promising alternative for preclinical testing of neurovascular devices is an aneurysm blood vessel mimic (aBVM), which is an in vitro tissue-engineered model of a human blood vessel composed of an electrospun scaffold with an aneurysm geometry and human vascular cells. Previous work in the Cal Poly Tissue Engineering Lab has established a process for creating different aneurysm scaffolds based on the shape of different geometries, and this work aimed to further advance these aneurysm geometries in order to enhance the versatility of the in vitro model. The overall goal of this thesis was to customize the aBVM model through variations of different dimensions and to validate the scaffold variations for neurovascular device testing. First, a literature review was performed to identify critical ranges of aneurysm neck diameters and heights that are commonly seen in rabbit elastase models and in human clinical settings in order to set a foundation for creating new geometries. Based on the results, aneurysm geometries with varying neck sizes and heights were modeled and molded, and scaffolds were fabricated through electrospinning. Methods were developed to characterize scaffolds with internal measurements through imaging techniques using a scanning electron microscope. To validate these scaffolds for use as aBVMs for neurovascular device testing, constructs were created by dual-sodding human endothelial cells and smooth muscle cells into scaffolds with varying neck sizes. Finally, flow diverters were deployed in constructs with varying neck sizes in order to evaluate feasibility and initial healing. Customized aneurysm scaffolds can eventually be used with a variety of device studies for screening of neurovascular devices or as a predecessor for in vivo preclinical testing.

Intracranial Aneurysms are a prevalent vascular pathology present in 3-4% of the population with an inherent risk of rupture. The growing accessibility of angiography has led to a rising incidence of detected aneurysms. An accurate assessment of the rupture risk is of utmost importance for the very high disability and mortality rates in case of rupture and the non-negligible risk inherent to surgical treatment. However, human evaluation is rather subjective, and current treatment guidelines, such as the PHASES score, remain inefficient. Therefore we aimed to develop an automatic machine learning-based rupture prediction model. Our study utilized 686 CTA scans, comprising 844 intracranial aneurysms. Among these aneurysms, 579 were classified as ruptured, while 265 were categorized as non-ruptured. Notably, the CTAs of ruptured aneurysms were obtained within a week after rupture, during which negligible morphological changes were observed compared to the aneurysm’s pre-rupture shape, as established by previous research. Based on this observation, our rupture risk assessment focused on the models’ ability to classify between ruptured and unruptured IAs. In our investigation, we implemented an automated vessel and aneurysm segmentation, vessel labeling, and feature extraction framework. The rupture risk prediction involved the use of deep learning-based vessel and aneurysm shape features, along with a combination of demographic features (patient sex and age) and morphological features (aneurysm location, size, surface area, volume, sphericity, etc.). An ablation-type study was conducted to evaluate these features. Eight different machine learning models were trained with the objective of identifying ruptured aneurysms. The best performing model achieved an area under the receiver operating characteristic curve (AUC) of 0.833, utilizing a random forest algorithm with feature selection based on Spearman’s rank correlation thresholding, which effectively eliminated highly correlated and anti-correlated features...:1 Introduction 1.1 Intracranial aneurysms 1.1.1 Treatment strategy 1.1.2 Rupture risk assesment 1.2 Artificial Intelligence 1.3 Thesis structure 1.4 Contribution of the author 2 Theory 2.1 Rupture risk assessment guidelines 2.1.1 PHASES score 2.1.2 ELAPSS score 2.2 Literature review: Aneurysm rupture prediction 2.3 Machine learning classifiers 2.3.1 Decision Tree 2.3.2 Random Forests 2.3.3 XGBoost 2.3.4 K-Nearest-Neighbor 2.3.5 Multilayer Perceptron 2.3.6 Logistic Regression 2.3.7 Support Vector Machine 2.3.8 Naive Bayes 2.4 Latent feature vectors in deep learning 2.5 PointNet++ 3 Methodology 3.1 Data 3.2 Vessel segmentation 3.3 Feature extraction 3.3.1 Deep vessel features 3.3.2 Deep aneurysm features 3.3.3 Conventional features 3.4 Rupture classification 3.4.1 Univariate approach 3.4.2 Multivariate approach 3.4.3 Deep learning approach 3.4.4 Deep learning amplified multivariate approach 3.5 Feature selection 3.5.1 Correlation-based feature selection 3.5.2 Permutation feature importance 3.6 Implementation 3.7 Evaluation 4 Results 4.1 Univariate approach 4.2 Multivariate approach 4.3 Deep learning approach 4.3.1 Deep vessel features 4.3.2 Deep aneurysm features 4.3.3 Deep vessel and deep aneurysm features 4.4 Deep learning amplified multivariate approach 4.4.1 Conventional and deep vessel features 4.4.2 Conventional and deep aneurysm features 4.4.3 Conventional, deep vessel, and deep aneurysm features 5 Discussion and Conclusions 5.1 Overview of results 5.2 Feature selection 5.3 Feature analysis 5.3.1 Deep vessel features 5.3.2 Deep aneurysm features 5.3.3 Conventional features 5.3.4 Summary 5.4 Comparison to other methods 5.5 Outlook Bibliography / Intrakranielle Aneurysmen sind eine weit verbreitete vaskuläre Pathologie, die bei 3 bis 4% der Bevölkerung auftritt und ein inhärentes Rupturrisiko birgt. Mit der zunehmenden Verfügbarkeit von Angiographie wird eine steigende Anzahl von Aneurysmen entdeckt. Angesichts der sehr hohen permanenten Beeinträchtigungs- und Sterblichkeitsraten im Falle einer Ruptur und des nicht zu vernachlässigenden Risikos einer chirurgischen Behandlung ist eine genaue Bewertung des Rupturrisikos von größter Bedeutung. Die Beurteilung durch den Menschen ist jedoch sehr subjektiv, und die derzeitigen Behandlungsrichtlinien, wie der PHASES-Score, sind nach wie vor ineffizient. Daher wollten wir ein automatisches, auf maschinellem Lernen basierendes Modell zur Rupturvorhersage entwickeln. Für unsere Studie wurden 686 CTA-Scans von 844 intrakraniellen Aneurysmen verwendet, von denen 579 rupturiert waren und 265 nicht rupturiert waren. Dabei ist zu beachten, dass die CTAs der rupturierten Aneurysmen innerhalb einer Woche nach der Ruptur gewonnen wurden, in der im Vergleich zur Form des Aneurysmas vor der Ruptur nur geringfügige morphologische Veränderungen zu beobachten waren, wie in vorhergegangenen Studient festgestellt wurde. Im Rahmen unserer Untersuchung haben wir eine automatische Segmentierung von Adern und Aneurysmen, ein Aderlabeling und eine Merkmalsextraktion implementiert. Für die Vorhersage des Rupturrisikos wurden auf Deep Learning basierende Ader- und Aneurysmaformmerkmale zusammen mit einer Kombination aus demografischen Merkmalen (Geschlecht und Alter des Patienten) und morphologischen Merkmalen (u. A. Lage, Größe, Oberfläche, Volumen, Sphärizität des Aneurysmas) verwendet. Zur Bewertung dieser Merkmale wurde eine Ablationsstudie durchgeführt. Acht verschiedene maschinelle Lernmodelle wurden mit dem Ziel trainiert, rupturierte Aneurysmen zu erkennen...:1 Introduction 1.1 Intracranial aneurysms 1.1.1 Treatment strategy 1.1.2 Rupture risk assesment 1.2 Artificial Intelligence 1.3 Thesis structure 1.4 Contribution of the author 2 Theory 2.1 Rupture risk assessment guidelines 2.1.1 PHASES score 2.1.2 ELAPSS score 2.2 Literature review: Aneurysm rupture prediction 2.3 Machine learning classifiers 2.3.1 Decision Tree 2.3.2 Random Forests 2.3.3 XGBoost 2.3.4 K-Nearest-Neighbor 2.3.5 Multilayer Perceptron 2.3.6 Logistic Regression 2.3.7 Support Vector Machine 2.3.8 Naive Bayes 2.4 Latent feature vectors in deep learning 2.5 PointNet++ 3 Methodology 3.1 Data 3.2 Vessel segmentation 3.3 Feature extraction 3.3.1 Deep vessel features 3.3.2 Deep aneurysm features 3.3.3 Conventional features 3.4 Rupture classification 3.4.1 Univariate approach 3.4.2 Multivariate approach 3.4.3 Deep learning approach 3.4.4 Deep learning amplified multivariate approach 3.5 Feature selection 3.5.1 Correlation-based feature selection 3.5.2 Permutation feature importance 3.6 Implementation 3.7 Evaluation 4 Results 4.1 Univariate approach 4.2 Multivariate approach 4.3 Deep learning approach 4.3.1 Deep vessel features 4.3.2 Deep aneurysm features 4.3.3 Deep vessel and deep aneurysm features 4.4 Deep learning amplified multivariate approach 4.4.1 Conventional and deep vessel features 4.4.2 Conventional and deep aneurysm features 4.4.3 Conventional, deep vessel, and deep aneurysm features 5 Discussion and Conclusions 5.1 Overview of results 5.2 Feature selection 5.3 Feature analysis 5.3.1 Deep vessel features 5.3.2 Deep aneurysm features 5.3.3 Conventional features 5.3.4 Summary 5.4 Comparison to other methods 5.5 Outlook Bibliography

Diss. (sammanfattning) Stockholm : Karol. inst., 2006. / Härtill 6 uppsatser.

A cerebral aneurysm (CA) is an abnormal distension of the wall of an artery in the brain, which results from arterial wall weakening. CAs are poorly understood, but are believed to be the result of a combination of biological and life-style factors. The low incidence of rupture coupled with risks of interventional treatments provide motivation for identifying and treating only those aneurysms at risk of rupture. Computational models of aneurysm evolution may provide great insight into CA disease mechanisms, and guide clinical decision-making. It is well known that vascular cells sense mechanical forces exerted by bloodflow (i.e. haemodynamic forces), which are translated into a myriad of intra- and inter-cellular responses. In this thesis, hypotheses on the role of the patient-specific haemodynamic environment on the evolution of CAs is examined. Arterial geometries are obtained from images of patient-specific vasculature, and the physiological aneurysm is virtually removed and replaced by a novel, fluid-solid-growth (FSG) model. The model incorporates a constitutive model for the artery, growth and remodelling (G&R) hypotheses for arterial wall constituents, and links between G&R and the haemodynamic environment, which is simulated utilising computational fluid dynamics. It is observed that coupling G&R to the patient-specific haemodynamic environment profoundly impacts the shape and size of the evolving aneurysm geometry; in some cases, the model aneurysm is qualitatively similar to the corresponding physiological aneurysm. This provides tentative support for the hypotheses on haemodynamics-induced G&R investigated here, and motivates the need for improved understanding of arterial adaptation to physiological conditions. This will facilitate the improvement and validation of the model, and may ultimately lead to predictive models with clinical application on a patient-specific basis.

The current study focuses on finding differential expression between circulating microRNAs in plasma from patients with abdominal aortic aneurysms compared to un-diseased individuals by using a qPCR-based array. In addition, we evaluated the expression of deregulated microRNAs in human tissue samples as well as microarray data from two independent mouse models of aneurysm development. Fifteen miRNAs were found to be significantly differentially expressed, with four of them surviving multiple testing. Interestingly all four of them were substantially different in murine aneurysm development.

Matrix metalloproteinase-2 (MMP-2, gelatinase A, type IV collagenase) is a member of a family of zinc-dependent metalloendopeptidases that functions in the degradation of elastin, collagens, and other components of extracellular matrix (ECM). Both secretion and activation of MMP-2 are elevated in human atherosclerotic lesions and abdominal aortic aneurysms (AAA). In this dissertation project, we sought to test the hypothesis that MMP-2 plays a critical role in both atherosclerosis and AAA. We also sought to determine the detailed mechanism. We first examined the atherosclerosis and AngII-induced AAAs development in MMP-2-/- x apolipoprotein (apoE)-/- mice in vivo. It was surprising that MMP-2 deficiency did not reduce the incidence of AngII-induced AAAs or the size of atherosclerosis in apoE-/- mice. However, the cellular and ECM content of atherosclerotic plaques were modified in MMP-2-/- x apoE-/- mice as compared to MMP-2+/+ x apoE-/- control mice. To explain the apparent paradox between this result and the hypothesis, we investigated the morphological characteristics of the aortic wall of MMP-2-/- mice. We detected an enhanced MMP-9 level in the aortic wall of MMP-2-/- x apoE-/- mice compared with MMP-2+/+ x apoE-/- mice. Interestingly, we also observed more branching of the elastin fibers in aortic wall of MMP-2-/- mice as compared with aorta of wild type mice. We also examined the behavior of macrophages from MMP-2-/- mice. Reduced adhesion, migration, and expression of integrin beta 3 were detected in MMP-2 deficient macrophages compared with wild type macrophages. Lastly, we examined whether MMP-2 deficiency in bone marrow-derived cells may influence AAAs and atherosclerosis using bone marrow transplantation technique. There was a significant reduction of both atherosclerosis development and AAAs formation in mice that were reconstituted MMP-2-/- bone marrow cells. In conclusion, the findings in this dissertation suggest that MMP-2 might play an important role in atherosclerosis and aneurysm through influencing inflammatory cell infiltration.

Summary of the work Abdominal aortic aneurysm (AAA) is a chronic degenerative disease that usually affects men over 65 years with an estimated prevalence of 5%. Aneurysm rupture represents a catastrophic event which carries a mortality rate of almost 90%. Current therapeutic options for AAAs measuring 5.5 cm in diameter or larger are based on prophylactic surgery, including conventional open reconstruction and endovascular stent-graft insertion. For patients with small asymptomatic AAAs (4.0 up to 5.5 cm in diameter), evidence from two recent large randomized controlled trials indicates no long-term survival benefit from immediate elective surgical repair as compared to imaging surveillance until aneurysm expands to 5.5 cm. This highlights the need for development of novel medical management strategies, including selective pharmacologic approaches, directed at preventing aneurysm expansion. In this regard, it is expected that a detailed knowledge of the pathobiology of human AAA lesion and a better understanding of pathophysiological mechanisms underlying initiation and progression of aneurysmal degeneration, particularly the specific involvement of T lymphocytes, will have special relevance to this challenging issue. Inflammatory and helper T-cell responses in abdominal aortic aneurysm : controversial issues Innate and inflammatory responses to endovascular versus open AAA repair. The occurrence of early acute systemic inflammatory responses after conventional open AAA repair is widely recognized and is thought to lead to the development of organ dysfunction and multiple organ failure, responsible for a large proportion of morbidity and mortality associated with aortic surgery. New therapeutic strategies designed to avoid ischemia-reperfusion injury related to aortic cross-clamping and to minimize the degree of tissue damage have thus been developed recently. Specifically, the advent of endovascular techniques has radically extended management options for patients with AAA. Although the method is believed to offer a clear short-term benefit over open repair, notably as regards restricted perioperative haemodynamic parameter fluctuations, reduced blood loss, briefer duration of surgery, shorter hospital stay, and lower 30-day mortality and complication rates, conflicting data are available regarding the exact nature and extent of the inflammatory events arising after such endoluminal procedures ; while several authors have indeed reported that endovascular AAA repair can determine a less intense and extensive inflammatory response, others have unexpectedly observed that the method may elicit a strong inflammatory response, the so-called « postimplantation syndrome ». Adaptive cellular immune responses in human aneurysmal aortic lesion. The inflammatory nature of AAA disease has long been suggested by the presence of a great number of CD4+ T lymphocytes in the outer media and adventitia of human AAA lesion. Interestingly, such infiltrating T-cell populations may have significant implications in the process of aneurysm dilation, since cytokines produced by T cells, notably IFN-gamma, have previously been shown to modulate production of matrix-degrading enzymes by resident macrophages and to induce apoptosis of medial SMCs. Through these key pathological mechanisms, T cells could potentially contribute to orchestrate aortic wall connective tissue disordered remodeling and degradation, and promote extensive disruption of elastic media, ultimately leading to aneurysmal degeneration. Nevertheless, despite their relative abundance in human AAA wall tissues, there is limited and controversial information as regards the functional profile of lesional lymphocytes, the exact nature of aortic wall adaptive cellular responses, and the etiologic role of T cells and their cytokines in initiation and progression of the aneurysmal process. Indeed, both Th1-type and Th2-type responses have been identified in human studies and experimental animal models of AAA. Aims of the work The main objectives of our work were to explore the innate and adaptive cellular immune responses in human AAA. In the first part of our work, we aimed to examine prospectively innate and inflammatory responses arising in a non-randomised cohort of patients undergoing endovascular versus open AAA repair. In the second part of our work, we focused our efforts on characterizing the nature of adaptive cellular immune responses and the phenotypic and functional repertoire of T cells in human AAA wall tissues obtained from a consecutive series of patients undergoing open AAA repair. Specifically, we sought to determine whether type 1 or type 2 responses occur predominantly in advanced AAA lesion. Main experimental findings Limited inflammatory response after endovascular AAA repair. Serial peripheral venous blood samples were collected preoperatively, immediately after declamping or insertion of endograft, and after 1, 3, 6, 12, 24, 48, and 72 hours. We first examined the acute phase reaction and liberation of complement cascade products using turbidimetric method and nephelometry. We found that endovascular repair produced lower postoperative CRP, leucocytosis, neutrophilia, and C3d/C3 ratio as compared to open surgery. We next analyzed surface expression of activation markers on peripheral CD3+ T cells using flow cytometry. We observed a strong upregulation of CD38 after open but not endovascular repair. Analysis of CD69 and CD25 molecules revealed no perioperative fluctuations in any group. We then investigated release of various circulating soluble cell adhesion molecules, proinflammatory cytokines, and chemokines using enzyme-linked immunosorbent assays. We demonstrated that both procedures are characterized by similar increases in ICAM-1 and IL-6 levels. Finally, tendency towards high levels of TNF-alpha and IL-8 was detected in endovascular repair, but data failed to reach statistical significance. Predominance of type 1 CD4+ T cells in human aneurysmal aortic lesion. We have developed a tissue enzymatic digestion and cell extraction procedure to isolate intact mononuclear cells from aortic wall segments. This original cell isolation protocol enabled us to examine ex vivo the presence, phenotype, and cytokine secretion profile of infiltrating T lymphocytes freshly isolated from human AAA tissues for comparison with their circulating counterparts using flow cytometry. We found that both populations of infiltrating CD4+ and CD8+ T cells display a unique activated memory phenotype, as assessed by an increased expression of CD69 and HLA-DR activation antigens, downregulation of CD62L molecule, and predominant expression of the CD45RO isoform characteristics of memory cells. In addition, we identified the presence in human aneurysmal aortic wall lesion of CD4+ T cells producing high levels of IFN-gamma but not IL-4, reflecting their type 1 nature. In an additional series of experiments, cytokine gene expression was determined in whole aneurysmal and non-diseased aortic samples using LightCycler-based quantitative real-time reverse transcription-polymerase chain reaction. The molecular basis of type 1 or type 2 dominant responses was further specified by analyzing mRNA levels of transcription factors specifically involved in Th1 or Th2 differentiation such as T-bet and GATA-3. We demonstrated that aneurysmal aortic specimens exhibit high transcript levels of IFN-gamma but not IL-4, and consistently overexpressed the IFN-g-promoting cytokine IL-12 and the type 1-restricted transcription factor T-bet, further establishing the prominent type 1 nature of aortic wall responses. Moreover, such selective tissue expression of IL-12 and T-bet in the vessel microenvironment points to a potential role for these signals in directing aortic wall responses towards a type 1 phenotype. Conclusions Our findings indicate that endovascular AAA repair is associated with a lesser degree of acute phase reaction, peripheral T-cell activation, and release of complement proteins as compared to conventional open surgery, suggesting that the innate and inflammatory responses to AAA repair are significantly attenuated by the endovascular approach as compared to the traditional open reconstruction. These results support the view that the endoluminal procedure represents an attractive alternative to open surgery for the treatment of large aneurysms. On the other hand, we have demonstrated that Th1 cell infiltrates predominate in human end-stage AAA lesion. These observations are relevant for helping clarify the pathobiology of human AAA tissues and defining prospects for the prevention of aneurysm expansion. Indeed, identification of such infiltrating populations of IFN-gamma-producing CD4+ T cells not only provide new insights into the pathogenesis of the disorder, but could also serve as a basis for the development of novel medical management strategies directed at preventing aneurysm formation and progression, including therapeutic approaches based on the modulation of aortic wall responses and designed to selectively target T-cell activation and cytokine production. In this respect, the present work provides experimental evidence in support of the emerging concept that, although multifactorial, aneurysm disease may be regarded as a Th1-driven immunopathological condition, and suggests that strategies targeting IFN-gamma could be a particularly exciting and fruitful avenue for further investigation. Ongoing clinical and basic research in these areas can be expected to yield design of promising pharmacologic approaches to control AAA expansion. From a clinical perspective, such efforts have the potential to dramatically influence both the outcome and management of this common and life threatening condition.