Aortic Coarctation: Recent Developments in Experimental and Computational Methods to Assess Treatments for this Simple Condition

Coarctation of the aorta (CoA) is often considered a relatively simple disease, but long-term outcomes suggest otherwise as life expectancies are decades less than in the average population and substantial morbidity often exists. What follows is an expanded version of collective work conducted by the authors\u27 and numerous collaborators that was presented at the 1st International Conference on Computational Simulation in Congenital Heart Disease pertaining to recent advances for CoA. The work begins by focusing on what is known about blood flow, pressure and indices of wall shear stress (WSS) in patients with normal vascular anatomy from both clinical imaging and the use of computational fluid dynamics (CFD) techniques. Hemodynamic alterations observed in CFD studies from untreated CoA patients and those undergoing surgical or interventional treatment are subsequently discussed. The impact of surgical approach, stent design and valve morphology are also presented for these patient populations. Finally, recent work from a representative experimental animal model of CoA that may offer insight into proposed mechanisms of long-term morbidity in CoA is presented

Geometric Modeling of Thoracic Aortic Surface Morphology - Implications for Pathophysiology and Clinical Interventions

Vascular disease risk factors such as hypertension, hyperlipidemia and old age are all\ua0results of modern-day lifestyle, and these diseases are getting more and more common. One\ua0treatment option for vascular diseases such as aneurysms and dissections is endovascular\ua0aortic repair introduced in the early 1990s. This treatment uses tubular fabric covered\ua0metallic structures (endografts) that are implanted using a minimally invasive approach\ua0and placed to serve as an articial vessel in a damaged portion of the vasculature. To ensure\ua0that the interventions are successful, the endograft must be placed in the correct location,\ua0and designed to sustain the hostile biological, chemical, and mechanical conditions in the\ua0body for many years. This is an interaction that goes both ways, and keeping in mind\ua0that the endograft is a foreign object placed in the sensitive vascular system, it is also\ua0important that it does not disrupt the native conditions more than necessary.This thesis presents a segmentation and quantication methodology to accurately\ua0describe the complex morphology and motion of diseased blood vessels in vivo through a\ua0natural and intuitive description of their luminal surfaces. After methodology validation,\ua0a series of important clinical applications are performed, all based on non-invasive imaging.\ua0Firstly, it is shown that explicit surface curvature quantication is necessary when\ua0compared to relying solely on centerline curvature and estimation methods. Secondly, it is\ua0shown that endograft malapposition severity can be predicted from preoperative geometric\ua0analysis of thoracic aortic surfaces. Thirdly, a multiaxial dynamics analysis of cardiac\ua0induced thoracic aortic surface motion shows how thoracic endovascular aortic repair\ua0affects the deformations of the dierent portions of the thoracic aorta. Fourthly, the helical\ua0propagation pattern of type B aortic dissection is determined, and two distinct modes of\ua0chirality are revealed, i.e., achiral and right-handed chiral groups. Finally, the effects of\ua0thoracic endovascular aortic repair on helical and cross-sectional morphology of type B\ua0dissections are investigated revealing how acuity and chirality affects the alteration due to\ua0intraluminal lining with endografts. Thus, the work presented in this thesis contributes\ua0by adding knowledge about pathology and pathophysiology through better geometric\ua0description of surface conditions of diseased thoracic aortas. This gives clinicians insights\ua0to use in their treatment planning and provides more nuanced boundary conditions for\ua0endograft manufacturers. Comprehensive knowledge about diseases, better treatment\ua0planning, and better devices are all crucial in order to improve the outcomes of performed\ua0interventions and ultimately the quality of life for the treated patients

Including Aortic Valve Morphology in Computational Fluid Dynamics Simulations: Initial Findings and Application to Aortic Coarctation

Computational fluid dynamics (CFD) simulations quantifying thoracic aortic flow patterns have not included disturbances from the aortic valve (AoV). 80% of patients with aortic coarctation (CoA) have a bicuspid aortic valve (BAV) which may cause adverse flow patterns contributing to morbidity. Our objectives were to develop a method to account for the AoV in CFD simulations, and quantify its impact on local hemodynamics. The method developed facilitates segmentation of the AoV, spatiotemporal interpolation of segments, and anatomic positioning of segments at the CFD model inlet. The AoV was included in CFD model examples of a normal (tricuspid AoV) and a post-surgical CoA patient (BAV). Velocity, turbulent kinetic energy (TKE), time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI) results were compared to equivalent simulations using a plug inlet profile. The plug inlet greatly underestimated TKE for both examples. TAWSS differences extended throughout the thoracic aorta for the CoA BAV, but were limited to the arch for the normal example. OSI differences existed mainly in the ascending aorta for both cases. The impact of AoV can now be included with CFD simulations to identify regions of deleterious hemodynamics thereby advancing simulations of the thoracic aorta one step closer to reality

Modeling of Intraluminal Surfaces of Thoracic Aortas

Vascular diseases are getting more and more common as a result of modern-day lifestyle and the fact that the population is getting older. One of the newest treatments for vascular diseases such as aneurysms and dissections is endovascular repair with endografting. This treatment uses a fabric covered metallic structure that is implanted using a minimally invasive approach to serve as an artificial vessel in a damaged region. To ensure that the interventions are successful, the endograft must be placed in the correct location, and be designed to sustain the hostile biological, chemical, and mechanical conditions in the body for many years.To accurately describe the complex mechanical conditions of the intraluminal surfaces of diseased blood vessels inside the body, this thesis presented a segmentation and quantification methodology for a natural and intuitive vessel surface description. The thesis also included some important clinical applications, all based on non-invasive temporal imaging. The results emphasized the need for explicit surface curvature quantification, as compared to relying solely on centerline curvature and estimation methods. Methods for preoperative prediction of endograft malapposition severity based on geometric analysis of thoracic aortic surfaces were introduced. Finally, a multiaxial dynamic analysis of cardiac induced thoracic aortic surface deformation showed how a thoracic endovascular aortic repair is a↵ecting the deformations of the thoracic aorta.Thus, the work presented in this thesis contributes by giving surgeons a tool to use in their treatment planning to minimize complications. Moreover, this method provides more nuanced boundary conditions so that endograft manufacturers can improve their designs to improve the quality of life for the treated patients

Virtual reality surgery simulation: A survey on patient specific solution

For surgeons, the precise anatomy structure and its dynamics are important in the surgery interaction, which is critical for generating the immersive experience in VR based surgical training applications. Presently, a normal therapeutic scheme might not be able to be straightforwardly applied to a specific patient, because the diagnostic results are based on averages, which result in a rough solution. Patient Specific Modeling (PSM), using patient-specific medical image data (e.g. CT, MRI, or Ultrasound), could deliver a computational anatomical model. It provides the potential for surgeons to practice the operation procedures for a particular patient, which will improve the accuracy of diagnosis and treatment, thus enhance the prophetic ability of VR simulation framework and raise the patient care. This paper presents a general review based on existing literature of patient specific surgical simulation on data acquisition, medical image segmentation, computational mesh generation, and soft tissue real time simulation

A (Near) Real-Time Simulation Method of Aneurysm Coil Embolization

International audienceA (Near) Real-Time Simulation Method of Aneurysm Coil Embolizatio

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Patient-specific simulation environment for surgical planning and preoperative rehearsal

Surgical simulation is common practice in the fields of surgical education and training. Numerous surgical simulators are available from commercial and academic organisations for the generic modelling of surgical tasks. However, a simulation platform is still yet to be found that fulfils the key requirements expected for patient-specific surgical simulation of soft tissue, with an effective translation into clinical practice. Patient-specific modelling is possible, but to date has been time-consuming, and consequently costly, because data preparation can be technically demanding. This motivated the research developed herein, which addresses the main challenges of biomechanical modelling for patient-specific surgical simulation. A novel implementation of soft tissue deformation and estimation of the patient-specific intraoperative environment is achieved using a position-based dynamics approach. This modelling approach overcomes the limitations derived from traditional physically-based approaches, by providing a simulation for patient-specific models with visual and physical accuracy, stability and real-time interaction. As a geometrically- based method, a calibration of the simulation parameters is performed and the simulation framework is successfully validated through experimental studies. The capabilities of the simulation platform are demonstrated by the integration of different surgical planning applications that are found relevant in the context of kidney cancer surgery. The simulation of pneumoperitoneum facilitates trocar placement planning and intraoperative surgical navigation. The implementation of deformable ultrasound simulation can assist surgeons in improving their scanning technique and definition of an optimal procedural strategy. Furthermore, the simulation framework has the potential to support the development and assessment of hypotheses that cannot be tested in vivo. Specifically, the evaluation of feedback modalities, as a response to user-model interaction, demonstrates improved performance and justifies the need to integrate a feedback framework in the robot-assisted surgical setting.Open Acces