FAST PHYSICS-BASED SIMULATION OF VASCULAR SURGERY

Ph.DDOCTOR OF PHILOSOPH

Visualization of large medical volume data

Ph.DDOCTOR OF PHILOSOPH

Interactive Three-Dimensional Simulation and Visualisation of Real Time Blood Flow in Vascular Networks

One of the challenges in cardiovascular disease management is the clinical decision-making process. When a clinician is dealing with complex and uncertain situations, the decision on whether or how to intervene is made based upon distinct information from diverse sources. There are several variables that can affect how the vascular system responds to treatment. These include: the extent of the damage and scarring, the efficiency of blood flow remodelling, and any associated pathology. Moreover, the effect of an intervention may lead to further unforeseen complications (e.g. another stenosis may be “hidden” further along the vessel). Currently, there is no tool for predicting or exploring such scenarios. This thesis explores the development of a highly adaptive real-time simulation of blood flow that considers patient specific data and clinician interaction. The simulation should model blood realistically, accurately, and through complex vascular networks in real-time. Developing robust flow scenarios that can be incorporated into the decision and planning medical tool set. The focus will be on specific regions of the anatomy, where accuracy is of the utmost importance and the flow can develop into specific patterns, with the aim of better understanding their condition and predicting factors of their future evolution. Results from the validation of the simulation showed promising comparisons with the literature and demonstrated a viability for clinical use

Image-Based Force Estimation and Haptic Rendering For Robot-Assisted Cardiovascular Intervention

Clinical studies have indicated that the loss of haptic perception is the prime limitation of robot-assisted cardiovascular intervention technology, hindering its global adoption. It causes compromised situational awareness for the surgeon during the intervention and may lead to health risks for the patients. This doctoral research was aimed at developing technology for addressing the limitation of the robot-assisted intervention technology in the provision of haptic feedback. The literature review showed that sensor-free force estimation (haptic cue) on endovascular devices, intuitive surgeon interface design, and haptic rendering within the surgeon interface were the major knowledge gaps. For sensor-free force estimation, first, an image-based force estimation methods based on inverse finite-element methods (iFEM) was developed and validated. Next, to address the limitation of the iFEM method in real-time performance, an inverse Cosserat rod model (iCORD) with a computationally efficient solution for endovascular devices was developed and validated. Afterward, the iCORD was adopted for analytical tip force estimation on steerable catheters. The experimental studies confirmed the accuracy and real-time performance of the iCORD for sensor-free force estimation. Afterward, a wearable drift-free rotation measurement device (MiCarp) was developed to facilitate the design of an intuitive surgeon interface by decoupling the rotation measurement from the insertion measurement. The validation studies showed that MiCarp had a superior performance for spatial rotation measurement compared to other modalities. In the end, a novel haptic feedback system based on smart magnetoelastic elastomers was developed, analytically modeled, and experimentally validated. The proposed haptics-enabled surgeon module had an unbounded workspace for interventional tasks and provided an intuitive interface. Experimental validation, at component and system levels, confirmed the usability of the proposed methods for robot-assisted intervention systems

Complexity Reduction in Image-Based Breast Cancer Care

The diversity of malignancies of the breast requires personalized diagnostic and therapeutic decision making in a complex situation. This thesis contributes in three clinical areas: (1) For clinical diagnostic image evaluation, computer-aided detection and diagnosis of mass and non-mass lesions in breast MRI is developed. 4D texture features characterize mass lesions. For non-mass lesions, a combined detection/characterisation method utilizes the bilateral symmetry of the breast s contrast agent uptake. (2) To improve clinical workflows, a breast MRI reading paradigm is proposed, exemplified by a breast MRI reading workstation prototype. Instead of mouse and keyboard, it is operated using multi-touch gestures. The concept is extended to mammography screening, introducing efficient navigation aids. (3) Contributions to finite element modeling of breast tissue deformations tackle two clinical problems: surgery planning and the prediction of the breast deformation in a MRI biopsy device

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

Morphologic evaluation of ruptured abdominal aortic aneurysm by 3D modeling

This thesis was created in Word and converted to PDF using Mac OS X 10.7.5 Quartz PDFContext.Abdominal aortic aneurysm (AAA) is defined as a dilatation of the abdominal aorta exceeding the normal diameter by more than 50%. The standard and widely used approach to assess AAA size is by measuring the maximal diameter (Dmax). Currently, the main predictors of rupture risk are the Dmax, sex, and the expansion rate of the aneurysm. Yet, Dmax has some limitations. AAAs of vastly different shapes may have the same maximal diameter. Dmax lacks sensitivity for rupture risk, especially among smaller AAAs. Thus, there is a need to evaluate the susceptibility of a given AAA to rupture on a patient-specific basis. We present the design concept and workflow of the AAA segmentation software developed at our institution. We describe the previous validation steps in which we evaluated the reproducibility of manual Dmax, compared software Dmax against manual Dmax, validated reproducibility of software Dmax and volume in cross-sectional and longitudinal studies for detection of AAA growth, and evaluated the reproducibility of software measurements in unenhanced computed tomographic angiography (CTA) and in the presence of stent-graft. In order to define new geometric features associated with rupture, we performed a case-control study in which we compared 63 cases with ruptured or symptomatic AAA and 94 controls with asymptomatic AAA. Univariate logistic regression analysis revealed 14 geometric indices associated with AAA rupture. In the multivariate logistic regression analysis, adjusting for Dmax and sex, the AAA with a higher bulge location and higher mean averaged surface area were associated with AAA rupture. Our preliminary results suggest that incorporating geometrical indices obtained by segmentation of CT shows a trend toward improvement of the classification accuracy of AAA with high rupture risk at CT over a traditional model based on Dmax and sex alone. Larger longitudinal studies are needed to verify the validity of the proposed model. Addition of flow and biomechanical simulations should be investigated to improve rupture risk prediction based on AAA modeling.Un anévrysme de l'aorte abdominale (AAA) est défini par une dilatation de plus de 50% par rapport au diamètre normal. La méthode standard et largement répandue pour mesurer la dimension d'un AAA consiste à mesurer le diamètre maximal (Dmax). Présentement, les principaux prédicteurs de risque de rupture sont le Dmax, le sexe et le taux d'expansion d'un anévrysme. Toutefois, le Dmax a certaines limitations. Des AAAs de formes très différentes peuvent avoir le même diamètre maximal. Le Dmax manque de sensibilité pour détecter le risque de rupture, en particulier pour les petits anévrysmes. Par conséquent, il y a un besoin d'évaluer de manière spécifique et individuelle la susceptibilité de rupture d'un AAA. Nous présentons le concept et le flux de travail d'un logiciel de segmentation des AAAs développé à notre institution. Nous décrivons les étapes antérieures de validation: évaluation de la reproductibilité du Dmax manuel, comparaison de Dmax par logiciel avec Dmax manuel, validation de la reproductibilité du Dmax et volume par logiciel dans des études transversale et longitudinale pour la détection de croissance et évaluation de la reproductibilité de mesures sur angiographie par tomodensitométrie et en présence d'endoprothèse. En vue d’identifier de nouveaux paramètres géométrique associés avec le risque de rupture, nous avons réalisé une étude cas-témoin comparant 63 cas avec AAA rompu ou symptomatique et 94 contrôles avec AAA asymptomatique. Une analyse de régression logistique univariée a identifié 14 indices géométriques associés avec une rupture de AAA. Dans l'analyse de régression logistique multivariée, en ajustant pour le Dmax et le sexe, les AAA avec un bombement plus haut situé et une surface moyenne plus élevée étaient associés à une rupture. Nos résultats préliminaires suggèrent que l'inclusion d'indices géométriques obtenus par segmentation de tomodensitométrie tend à améliorer la classification de AAA avec un risque de rupture par rapport à un modèle traditionnel seulement basé sur le Dmax et le sexe. De plus larges études longitudinales sont requises pour vérifier la validité du modèle proposé. Des simulations de flux et biomécaniques devraient être envisagées pour améliorer la prédiction du risque de rupture basée sur la modélisation d'anévrysmes