Unbiased Shape Compactness for Segmentation

We propose to constrain segmentation functionals with a dimensionless, unbiased and position-independent shape compactness prior, which we solve efficiently with an alternating direction method of multipliers (ADMM). Involving a squared sum of pairwise potentials, our prior results in a challenging high-order optimization problem, which involves dense (fully connected) graphs. We split the problem into a sequence of easier sub-problems, each performed efficiently at each iteration: (i) a sparse-matrix inversion based on Woodbury identity, (ii) a closed-form solution of a cubic equation and (iii) a graph-cut update of a sub-modular pairwise sub-problem with a sparse graph. We deploy our prior in an energy minimization, in conjunction with a supervised classifier term based on CNNs and standard regularization constraints. We demonstrate the usefulness of our energy in several medical applications. In particular, we report comprehensive evaluations of our fully automated algorithm over 40 subjects, showing a competitive performance for the challenging task of abdominal aorta segmentation in MRI.Comment: Accepted at MICCAI 201

Molecular imaging of abdominal aortic aneurysms

Abdominal aortic aneurysm (AAA) disease is characterised by an asymptomatic, permanent, focal dilatation of the abdominal aorta progressing towards rupture, which confers significant mortality. Patient management and surgical decisions currently rely on aortic diameter measurements via abdominal ultrasound screening. However, AAA rupture can occur at small diameters or may never occur at large diameters. Therefore, there is a need to develop molecular imaging-based biomarkers independent of aneurysm diameter that may help stratify patients with early-stage AAA to reduced surveillance. AAA uptake of [18F]fluorodeoxyglucose on positron emission tomography (PET) has been demonstrated previously; however, its glucose-dependent uptake may overlook other key mechanisms. The cell proliferation marker [18F]fluorothymidine ([18F]FLT) is primarily used in tumour imaging. The aim of the overall study for this thesis was to explore the feasibility of [18F]FLT PET / computed tomography (CT) to visualise and quantify AAA in the angiotensin II (AngII)-infused mouse model. The experiments presented in this thesis revealed increased uptake of [18F]FLT in the 14-day AngII AAA model than in saline controls, followed by a decrease in this uptake at 28 days. Moreover, in line with the in vivo PET/CT findings, Western blotting of aortic tissue revealed increased levels of thymidine kinase-1 (the substrate of [18F]FLT) and nucleoside transporters in the 14-day AngII AAA model than in saline controls, followed by decreased expression levels at 28 days. A pilot experiment further demonstrated that [18F]FLT PET/CT could be used to detect an early therapeutic response to oral imatinib treatment in the AngII AAA model. Therefore, [18F]FLT PET/CT may be a feasible modality to detect and quantify cell proliferation in the AngII AAA murine model. The findings of this thesis are encouraging for the application of [18F]FLT PET/CT in patients with small AAA

Computational fluid dynamics indicators to improve cardiovascular pathologies

In recent years, the study of computational hemodynamics within anatomically complex vascular regions has generated great interest among clinicians. The progress in computational fluid dynamics, image processing and high-performance computing haveallowed us to identify the candidate vascular regions for the appearance of cardiovascular diseases and to predict how this disease may evolve. Medicine currently uses a paradigm called diagnosis. In this thesis we attempt to introduce into medicine the predictive paradigm that has been used in engineering for many years. The objective of this thesis is therefore to develop predictive models based on diagnostic indicators for cardiovascular pathologies. We try to predict the evolution of aortic abdominal aneurysm, aortic coarctation and coronary artery disease in a personalized way for each patient. To understand how the cardiovascular pathology will evolve and when it will become a health risk, it is necessary to develop new technologies by merging medical imaging and computational science. We propose diagnostic indicators that can improve the diagnosis and predict the evolution of the disease more efficiently than the methods used until now. In particular, a new methodology for computing diagnostic indicators based on computational hemodynamics and medical imaging is proposed. We have worked with data of anonymous patients to create real predictive technology that will allow us to continue advancing in personalized medicine and generate more sustainable health systems. However, our final aim is to achieve an impact at a clinical level. Several groups have tried to create predictive models for cardiovascular pathologies, but they have not yet begun to use them in clinical practice. Our objective is to go further and obtain predictive variables to be used practically in the clinical field. It is to be hoped that in the future extremely precise databases of all of our anatomy and physiology will be available to doctors. These data can be used for predictive models to improve diagnosis or to improve therapies or personalized treatments.En els últims anys, l'estudi de l'hemodinàmica computacional en regions vasculars anatòmicament complexes ha generat un gran interès entre els clínics. El progrés obtingut en la dinàmica de fluids computacional, en el processament d'imatges i en la computació d'alt rendiment ha permès identificar regions vasculars on poden aparèixer malalties cardiovasculars, així com predir-ne l'evolució. Actualment, la medicina utilitza un paradigma anomenat diagnòstic. En aquesta tesi s'intenta introduir en la medicina el paradigma predictiu utilitzat des de fa molts anys en l'enginyeria. Per tant, aquesta tesi té com a objectiu desenvolupar models predictius basats en indicadors de diagnòstic de patologies cardiovasculars. Tractem de predir l'evolució de l'aneurisma d'aorta abdominal, la coartació aòrtica i la malaltia coronària de forma personalitzada per a cada pacient. Per entendre com la patologia cardiovascular evolucionarà i quan suposarà un risc per a la salut, cal desenvolupar noves tecnologies mitjançant la combinació de les imatges mèdiques i la ciència computacional. Proposem uns indicadors que poden millorar el diagnòstic i predir l'evolució de la malaltia de manera més eficient que els mètodes utilitzats fins ara. En particular, es proposa una nova metodologia per al càlcul dels indicadors de diagnòstic basada en l'hemodinàmica computacional i les imatges mèdiques. Hem treballat amb dades de pacients anònims per crear una tecnologia predictiva real que ens permetrà seguir avançant en la medicina personalitzada i generar sistemes de salut més sostenibles. Però el nostre objectiu final és aconseguir un impacte en l¿àmbit clínic. Diversos grups han tractat de crear models predictius per a les patologies cardiovasculars, però encara no han començat a utilitzar-les en la pràctica clínica. El nostre objectiu és anar més enllà i obtenir variables predictives que es puguin utilitzar de forma pràctica en el camp clínic. Es pot preveure que en el futur tots els metges disposaran de bases de dades molt precises de tota la nostra anatomia i fisiologia. Aquestes dades es poden utilitzar en els models predictius per millorar el diagnòstic o per millorar teràpies o tractaments personalitzats.Postprint (published version

Biomechanical and morphological aspects of abdominal aortic aneurysm growth and rupture

Abdominal aortic aneurysms (AAAs) are dilatations of the abdominal aorta that pose a risk of rupture. The only effective treatment is intervention prior to rupture, but this is also associated with mortality and morbidity. It is therefore important to weigh the risks of intervention with the potential benefit. Current treatment guidelines recommend using the maximal aneurysm diameter (Dmax) as the indicator for rupture risk, and rec- ommend considering intervention in men with AAAs > 55 mm, and >50 mm in women. Patients with small AAAs are put in surveillance, and the Dmax is followed until it reaches the threshold. The current policy is relatively efficient on a population-level but lacks specificity for individuals. Some patients rupture before this threshold, and many remain stable despite passing it. Aneurysm growth is often described as erratic, but measure- ments are affected by several levels of uncertainty. Biomechanical assessment, where 3D models of AAAs from computed tomography angiographies (CTAs) are analysed by finite element analysis, may improve risk prediction. In the first study a population-based cohort of 192 patients with ruptured AAAs and CT imaging available at rupture were studied. A significant portion of patients ruptured with AAAs smaller than 60 mm, 10% of men and 27 % of women. When normalizing Dmax for body surface area (so-called aortic size index) there was, however, was not difference between the sexes. In an analysis of small, ruptured AAAs compared to Dmax, age and sex-matched asymptomatic AAAs, peak wall rupture index (PWRI), but not peak wall stress (PWS) was increased in the ruptured AAAs. In the second study, a cohort of 100 patients with at least three computed tomog- raphy examinations were analysed with 3D morphological and biomechanical analysis. The growth pattern of AAAs appeared continuous and conferred well to a linear growth model. The evolution of the different analysed indices, Dmax, aneurysm volume and bio- mechanical stress did, however, not parallel each other. Intraluminal thrombus (ILT) grew faster than the lumen, but lumen volume growth was more closely related to increase in biomechanical stress. In the third study, a cohort of 67 patients with 109 CTA examinations prior to rupture were identified. The relation between biomechanical variables and time-to-rupture was investigated. In small and medium sized AAAs (< 70 mm), PWRI, but not PWS, was associ- ated with time-to-rupture, also when adjusting for potential confounders, aneurysm size and sex. The results further show that women have an approximately two-fold increased hazard ratio for AAA rupture, compared to men, when adjusted for AAA size. In the fourth study lumen area is indicated as a potentially useful rupture risk marker. Ruptured AAAs, compared to Dmax-matched asymptomatic AAAs, have a larger luminal area, and the luminal area is related to biomechanical stress, even when adjusting for an- eurysm size, or ILT area. In conclusion, the results of this thesis indicate areas of potential improvement in the current care of patients with AAAs, explores the 3D growth of AAAs, and strengthens the potential role for biomechanical analysis. These results may in the future have rele- vance for personalizing timing of treatment for patients with AAAs, and the evaluation of pharmacological therapy for AAAs