Towards Cognition-Guided Patient-Specific Numerical Simulation for Cardiac Surgery Assistance

Motivation. Patient-specific, knowledge-based, holistic surgical treatment planning is of utmost importance when dealing with complex surgery. Surgeons need to account for all available medical patient data, keep track of technical developments, and stay on top of current surgical expert knowledge to define a suitable surgical treatment strategy. There is a large potential for computer assistance, also, and in particular, regarding surgery simulation which gives surgeons the opportunity not only to plan but to simulate, too, some steps of an intervention and to forecast relevant surgical situations. Purpose. In this work, we particularly look at mitral valve reconstruction (MVR) surgery, which is to re-establish the functionality of an incompetent mitral valve (MV) through implantation of an artificial ring that reshapes the valvular morphology. We aim at supporting MVR by providing surgeons with biomechanical FEM-based MVR surgery simulations that enable them to assess the simulated behavior of the MV after an MVR. However, according to the above requirements, such surgery simulation is really beneficial to surgeons only if it is patient-specific, surgical expert knowledge-based, comprehensive in terms of the underlying model and the patient’s data, and if its setup and execution is fully automated and integrated into the surgical treatment workflow. Methods. This PhD work conducts research on simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance. First, we derive a biomechanical MV/MVR model and develop an FEM-based MVR surgery simulation using the FEM software toolkit HiFlow3. Following, we outline the functionality and features of the Medical Simulation Markup Language (MSML) and how it simplifies the biomechanical modeling workflow. It is then detailed, how, by means of the MSML and a set of dedicated MVR simulation reprocessing operators, patient-individual medical data can comprehensively be analyzed and processed in order for the fully automated setup of MVR simulation scenarios. Finally, the presented work is integrated into the cognitive system architecture of the joint research project Cognition-Guided Surgery. We particularly look at its semantic knowledge and data infrastructure as well as at the setup of its cognitive software components, which eventually facilitate cognition-guidance and patient-specifity for the overall simulation-enhanced MVR assistance pipeline. Results and Discussion. We have proposed and implemented, for the first time, a prototypic system for simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance. The overall system was evaluated in terms of functionality and performance. Through its cognitive, data-driven pipeline setup, medical patient data and surgical information is analyzed and processed comprehensively, efficiently and fully automatically, and the hence set-up simulation scenarios yield reliable, patient-specific MVR surgery simulation results. This indicates the system’s usability and applicability. The proposed work thus presents an important step towards a simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance, and can – once operative – be expected to significantly enhance MVR surgery. Concluding, we discuss possible further research contents and promising applications to build upon the presented work

A COMPUTATIONAL STUDY OF PATCH IMPLANTATION AND MITRAL VALVE MECHANICS

Myocardial infarction (i.e., a heart attack) is the most common heart disease in the United States. Mitral valve regurgitation, or the backflow of blood into the atrium from the left ventricle, is one of the complications associated with myocardial infarction. In this dissertation, a validated model of a sheep heart that has suffered myocardial infarction has been employed to study mitral valve regurgitation. The model was rebuilt with the knowledge of geometrical changes captured with MRI technique and is assigned with anisotropic, inhomogeneous, nearly incompressible and highly non-linear material properties. Patch augmentation was performed on its anterior leaflet, using a simplified approach, and its posterior leaflet, using a more realistic approach. In this finite element simulation, we virtually installed an elliptical patch within the central portion of the posterior leaflet. To the best of the author’s knowledge, this type of simulation has not been performed previously. In another simulation, the effect of patch within the anterior leaflet was simulated. The results from the two different surgical simulations show that patch implantation helps the free edges of the leaflets come close to one another, which leads to improved coaptation. Additionally, the changes in chordal force distributions are also reported. Finally, this study answers a few questions regarding mitral valve patch augmentation surgeries and emphasizes the importance of further investigations on the influence of patch positioning and material properties on key outcomes. The ultimate goal is to use the proposed techniques to assess human models that are patient-specific

Brain Tumour Classification Using Deep Features from Structural MRI

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Review of patient-specific simulations of transcatheter aortic valve implantation

International audienceTranscatheter Aortic Valve Implantation (TAVI) accounts for one of the most promising new cardiovascular procedures. This minimally invasive technique is still at its early stage and is constantly developing thanks to imaging techniques, computer science, biomechanics and technologies of prosthesis and delivery tools. As a result, patient-specific simulation can find an exciting playground in TAVI. It canexpress its potential by providing the clinicians with powerful decision support, offering great assistance in their workflow. Through a review of the current scientific field, we try to identify the challenges and future evolutions of patient-specific simulation for TAVI. This review article is an attempt to summarize and coordinate data scattered across the literature about patient-specific biomechanical simulation for TAVI

Entering a new era of surgical training : developing 3-dimensional print models for hands-on surgical training and its introduction into the congenital cardiac surgical curriculum

Congenital heart surgery is a technically challenging subspecialty of cardiothoracic surgery. This is due to a combination of factors including the rarity and variety of pathology and the small patient size. This coupled with the increasing public scrutiny and the expectation of excellent patient outcomes for even the most complex pathologies has led to limitations for surgical trainees to develop their surgical competencies in an efficient manner. Simulation has been used successfully to develop technical skills in other surgical specialities but is limited in congenital heart surgery. The objectives of this work were to develop and integrate hands-on simulation methods into the training of congenital heart surgeons using anatomically accurate 3D-printed heart models and to use validated, objective assessment methods to measure performance. The simulation programme was successfully developed and integrated into the regular training of congenital heart surgeons. The objective assessments demonstrated that there was an improvement in procedural performance and time across multiple complex procedures following deliberate practice and rehearsal. Furthermore, surgeons who had participated in the programme retained their technical skills following a prolonged delay supporting the value of simulation. Overall, there is value in the incorporation of hands-on simulation training into congenital heart surgery and it has the potential to be integrated into training programmes globally