Computational Modelling in the Management of Patients with Aortic Valve Stenosis

Background Stenosis of the aortic valve causes increased left ventricular pressure leading to adverse clinical outcomes. The selection and timing of intervention (surgical replacement or transcatheter implantation) is often unclear and is based upon limited data. Hypothesis A comprehensive and integrated personalised approach, including recognition of cardiac energetics parameters extracted from a personalised mathematical model, mapped to patient activity, has the potential to improve diagnosis and the planning and timing of interventions. Aims This project seeks to implement a simple, personalised, mathematical model of patients with aortic stenosis (AS), which can ‘measure’ cardiac work and power parameters that provide an effective characterisation of the demand on the heart in both rest and exercise conditions and can predict the changes of these parameters following an intervention. The specific aims of this project are: • to critically review current diagnostic methods • to evaluate the potential role of pre- and post-procedural measured patient activity • to implement a simple, personalised, mathematical model of patients with AS • to evaluate the potential role of a clinical decision support system Methods Twenty-two patients with severe AS according to ESC criteria were recruited. Relevant clinical, imaging, activity monitoring, six-minute walk test, and patient reported data were collected, before and early and after treatment. Novel imaging techniques were developed to help in the diagnosis of AS. A computational model was developed and executed using the data collected to create non-invasive pressure volume loops and study the global haemodynamic burden on the left ventricle. Simulations were run to predict the haemodynamic parameters both during exercise and following intervention. Modelled parameters were validated against clinically measured values. This information was then correlated with symptoms and activity data. A clinical decision support tool was created and populated with data obtained and its clinical utility evaluated. Outcomes The results of this project suggest that the combination of imaging and activity data with computational modelling provides a novel, patient-specific insight into patients’ haemodynamics and may help guide clinical decision making in patients with AS

Radiation dose optimisation in interventional cardiology.

The focus of this project has been to explore practical applications of radiation dose optimisation in the clinical setting of the cardiac catheterisation laboratory. The relevance of interventional procedures and hence fluoroscopy, to modern cardiology practice, is illustrated, and the clinical significance of radiation dose management outlined. Current radiation dose management techniques, as well as the proposals for further dose optimisation, are detailed in this thesis. The first experiment in this project aims to establish an automated method of data collection for the monitoring of radiation dose optimisation techniques. A combination of open source programming languages and database management software has been used to create software that receives information directly from the fluoroscopic systems following patient procedures in the form of Radiation Dose Structured reports. All information about radiation exposure as well as study type, length and patient demographics are collected and stored. A further application of the software is to calculate the patient skin dose to monitor the likelihood of adverse tissue reactions following any high dose procedures. This information is then analysed and disseminated to operators to drive radiation dose optimisation. The second experiment in this project assessed the accuracy of the reported radiation dose metrics for different manufacturers collected in the above experiment. Fluoroscopic units used for cardiac catheterisation procedures are tested routinely for compliance. However, under Australian regulations, it is not required to validate certain metrics that impact on patient dose management. This study aimed to assess the accuracy of standard DICOM values used in patient dose calculations through direct measurement. The results indicate that the accuracy of the table height was dependent on the age of the unit, with older units varying by up to 4 cm. The reference air kerma and DAP were all within 10%. The FOV showed the greatest discrepancy from the directly measured value with up to 20% inaccuracy. The results of this experiment show that table height, and FOV should be directly measured and accounted for when calculating patient skin dose. This chapter also presents recommendations regarding the frequency and tolerance of testing. The third experiment in this thesis addresses the feasibility of using a novel ‘ultralow’ fluoroscopic pulse rate during routine diagnostic coronary angiograms. Fluoroscopic pulse rate, one of the factors that influence patient dose in a coronary angiogram, is also under control of the operator and can thus be adjusted accordingly. Literature relating to reduction in fluoroscopic pulse rate as a means of radiation dose optimisation shows positive results. However, the resulting loss of diagnostic clarity has been a limiting factor. This study aimed to evaluate the effects of using an ultra low fluoroscopic pulse rate of 3 pulses per second on procedure duration, diagnostic clarity and radiation dose in an analysis of 50 coronary angiograms performed at a large metropolitan centre. The results showed a statistically significant reduction in DAP (58%) with no reduction in diagnostic clarity or increase in procedure length. The fourth experiment uses the above results in conjunction with educational talks to practically apply radiation dose optimisation techniques at a large teaching hospital. Dose optimisation is particularly pertinent in teaching hospitals, where longer procedure times may be necessary to accommodate the teaching needs of junior staff, and thus impart a greater dose. The aim of this study is to analyse the effects of varying optimisation protocols in conventional coronary angiograms, from the perspective of a large tertiary centre implementing a rapid dose reduction program. Routine coronary angiograms were chosen to compare baseline levels of radiation, and the dose imparted before and after dose optimisation techniques was measured. Such techniques included lowering dose per pulse, pulse rate, frame rate and encouraging larger field of views and collimation. The results showed up to 54% dose reduction from a lowering of both frame rate and dose per pulse, without any adverse impact on clinical outcomes or teaching of junior staff. The fifth experiment focuses on the radiation exposure received by the operators in the cardiac catheterisation laboratory. Established research indicates potential long-term harm from low dose protracted radiation exposure to operators of cardiac angiography, with increasing exposure imparting greater risk. This experiment used a phantom model and thermoluminescent dosimeters to measure radiation dose to operators in a conventional coronary angiogram procedure, specifically looking at radiation dose to target regions of the operator to better examine clinical effects. Correspondingly, the results allow for a deduction of a comprehensive list of factors that allow the conversion from readily available patient dose metrics to operator dose. The study also found that basic monitoring using only a single under apron dosimeter underestimates the radiation dose by up to 68%. Finally, the study provides recommendations to best mitigate the risk of radiation-induced disease through the use of radiation protection tools in high exposure regions of the body. The sixth and final experiment in this thesis outlines the production and evaluation of a real-time radiation dose detector for the purpose of educational simulation and furthering understanding of radiation safety, and eventually clinical applications. Current conventional dose measurement methods, while clinically useful, are usually limited to retrospective analysis of dose only. In the cases where a real-time dose can be measured and displayed, the onus to continually assess the radiation dose visually adds cognitive load to the operator. This project examines the creation of a real-time dose detector that can provide visual, audible and tactile feedback to the interventional cardiologist. The aim of such a device is to provide ongoing feedback to the operator which can result in dose savings to the patient in real time via procedural modifications. A prototype was created and tested, with calibration results showing that detector performance was comparable to available products and comfortable to wear for the operator. The vibration module providing tactile feedback can be programmed to either activate during increased dose rates (thus allowing procedural modifications) or following a set dose threshold, serving as a reminder that the procedure is resulting in a high patient and operator radiation exposure

Body sensor networks: smart monitoring solutions after reconstructive surgery

Advances in reconstructive surgery are providing treatment options in the face of major trauma and cancer. Body Sensor Networks (BSN) have the potential to offer smart solutions to a range of clinical challenges. The aim of this thesis was to review the current state of the art devices, then develop and apply bespoke technologies developed by the Hamlyn Centre BSN engineering team supported by the EPSRC ESPRIT programme to deliver post-operative monitoring options for patients undergoing reconstructive surgery. A wireless optical sensor was developed to provide a continuous monitoring solution for free tissue transplants (free flaps). By recording backscattered light from 2 different source wavelengths, we were able to estimate the oxygenation of the superficial microvasculature. In a custom-made upper limb pressure cuff model, forearm deoxygenation measured by our sensor and gold standard equipment showed strong correlations, with incremental reductions in response to increased cuff inflation durations. Such a device might allow early detection of flap failure, optimising the likelihood of flap salvage. An ear-worn activity recognition sensor was utilised to provide a platform capable of facilitating objective assessment of functional mobility. This work evolved from an initial feasibility study in a knee replacement cohort, to a larger clinical trial designed to establish a novel mobility score in patients recovering from open tibial fractures (OTF). The Hamlyn Mobility Score (HMS) assesses mobility over 3 activities of daily living: walking, stair climbing, and standing from a chair. Sensor-derived parameters including variation in both temporal and force aspects of gait were validated to measure differences in performance in line with fracture severity, which also matched questionnaire-based assessments. Monitoring the OTF cohort over 12 months with the HMS allowed functional recovery to be profiled in great detail. Further, a novel finding of continued improvements in walking quality after a plateau in walking quantity was demonstrated objectively. The methods described in this thesis provide an opportunity to revamp the recovery paradigm through continuous, objective patient monitoring along with self-directed, personalised rehabilitation strategies, which has the potential to improve both the quality and cost-effectiveness of reconstructive surgery services.Open Acces

Design, Modeling and Control of a Magnetostriction-based Force Feedback System for Robot-assisted Cardiovascular Intervention Systems

Magnetorheological elastomers (MREs), as a class of smart materials, have a property called Magnetostriction means mechanical properties, including deformation of MREs, could be changed in response to an external magnetic field. Because of the controllable deformation, MRE is a suitable candidate for rendering the loss of haptic feedback in Robot-Assisted Cardiovascular (RCI) applications. In the recently-designed such force feedback systems, i.e. TorMag, the effect of matrix shear modulus and filler volume percentage was not studied comprehensively. Tormag also exposed limitations in force range. In the current study, a previously proposed and validated constitutive model of MREs was adopted. Then, twelve MREs with three silicon rubber matrices and four filler volume fractions were fabricated and characterized to improve the limitations mentioned above in Tormag. The average relative error between analytical force range and experiment was 10.2\%, while the maximum force range was 5.29 N (stiffest matrix and 40\% filler), and the minimum range was 1.06 N (softest matrix and 10\% filler). Increasing filler percentage from 10\% to 40\% increased the force feedback range up to 288\%. The state-space analysis of Tormag revealed that this system did not fully cover the required force range and zero force rendering. As an approach, structural optimization of the system is performed using the local and global optimization process. Next, a neural network (NN)-based model as the control framework was proposed and validated to obtain the necessary force for the desired input data. Then, a nearest neighbour search (NNS) method was added to the NN model to find the required magnetic field for a force-displacement profile as input. The proposed neural network accurately predicted the force-displacement behaviour of three types of MREs ($R^2=0.97$, mean-absolute-error=1.26 N). Also, the NN+ NNS model successfully obtained the required magnetic field (mean-absolute error=3.64 mT)

Development of a prosthetic heart valve with inbuilt sensing technology, to aid in continuous monitoring of function under various stenotic conditions

In spite of technological advances in the design of prosthetic heart valves, they are still often subject to complications after implantation. One of the common complications is valve stenosis, which involves the obstruction of the valve orifice caused by biological processes. The greatest challenge in diagnosing the development of valve failure and complications is related to the fact that the valve is implanted and isolated. To continuously monitor the state of the valve and its performance would be of great benefit but practically can only be achieved by instrumenting the implanted valve. In this thesis, we explore the development of a prosthetic valve with inbuilt sensing technology to aid in continuous monitoring of valve function under various stenotic conditions. 22mm polyurethane valves were designed via dipcoating. A custom made mock circulatory system was designed and hydrodynamic testing of the polyurethane valves under different flow rates were performed with Effective orifice area (EOA) and Transvalvular Pressure Gradient (TVPG) being the parameters of interest. Valves were subjected to varying levels of obstruction to investigate the effect obstruction has on the pressure gradient across the valves. Similar tests were performed on a Carpentier Edwards SAV 2650 model bioprosthetic valve for comparison. Polyurethane valves were then instrumented with strain gauges to measure peak to peak strain difference, in response to varying levels of obstructions. All the polyurethane valves exhibited good hydrodynamic performance with EOA (>1cm2) under baseline physiological conditions. It was also discovered that pressure difference across the valves was directly proportional to the flow rate. The pressure difference also demonstrated a slow increase during the initial stages of simulated stenosis and a sudden increase as the obstruction became severe. This provides further evidence to support the ideal that stenosis is a slow progressive disease which may not present symptoms until severe. The peak to peak strain differences also tend to decrease as the severity of the obstruction was increased. The peak to peak strain difference is indicative of the pressures within the valve (intravalvular pressure). The results suggest that directly monitoring the pressures within the valve could be a useful diagnostic tool for detecting valve stenosis. Future works involves miniaturisation of the sensors and also the incorporation of telemetry into the sensor design.In spite of technological advances in the design of prosthetic heart valves, they are still often subject to complications after implantation. One of the common complications is valve stenosis, which involves the obstruction of the valve orifice caused by biological processes. The greatest challenge in diagnosing the development of valve failure and complications is related to the fact that the valve is implanted and isolated. To continuously monitor the state of the valve and its performance would be of great benefit but practically can only be achieved by instrumenting the implanted valve. In this thesis, we explore the development of a prosthetic valve with inbuilt sensing technology to aid in continuous monitoring of valve function under various stenotic conditions. 22mm polyurethane valves were designed via dipcoating. A custom made mock circulatory system was designed and hydrodynamic testing of the polyurethane valves under different flow rates were performed with Effective orifice area (EOA) and Transvalvular Pressure Gradient (TVPG) being the parameters of interest. Valves were subjected to varying levels of obstruction to investigate the effect obstruction has on the pressure gradient across the valves. Similar tests were performed on a Carpentier Edwards SAV 2650 model bioprosthetic valve for comparison. Polyurethane valves were then instrumented with strain gauges to measure peak to peak strain difference, in response to varying levels of obstructions. All the polyurethane valves exhibited good hydrodynamic performance with EOA (>1cm2) under baseline physiological conditions. It was also discovered that pressure difference across the valves was directly proportional to the flow rate. The pressure difference also demonstrated a slow increase during the initial stages of simulated stenosis and a sudden increase as the obstruction became severe. This provides further evidence to support the ideal that stenosis is a slow progressive disease which may not present symptoms until severe. The peak to peak strain differences also tend to decrease as the severity of the obstruction was increased. The peak to peak strain difference is indicative of the pressures within the valve (intravalvular pressure). The results suggest that directly monitoring the pressures within the valve could be a useful diagnostic tool for detecting valve stenosis. Future works involves miniaturisation of the sensors and also the incorporation of telemetry into the sensor design

Surgical Management of Gastroesophageal Reflux in Children: Risk Stratification and Prediction of Outcomes

Introduction: Since the 1980s fundoplication, an operation developed for adults with hiatus hernia and reflux symptoms, has been performed in children with gastroesophageal reflux disease (GORD). When compared to adult outcomes, paediatric fundoplication has resulted in higher failure and revision rates. In the first chapter we explore differences in paradigm, patient population and outcomes. Firstly, symptoms are poorly defined and are measured by instruments of varying quality. Secondly, neurological impairment (NI), prematurity and congenital anomalies (oesophageal atresia, congenital diaphragmatic hernia) are prevalent in children. / Purpose: To develop methods for stratifying paediatric fundoplication risk and predicting outcomes based on symptom profile, demographic factors, congenital and medical history. / Methods: Study objectives are addressed in three opera: a symptom questionnaire development (TARDIS:REFLUX), a randomised controlled trial (RCT) and a retrospective database study (RDS). TARDIS: REFLUX: In the second chapter, digital research methods are used to design and validate a symptom questionnaire for paediatric GORD. The questionnaire is a market-viable smartphone app hosted on a commercial platform and trialed in a clinical pilot study. / RCT: In the third chapter, the REMOS trial is reported. The trial addresses the subset of children with NI and feeding difficulties. Participants are randomized to gastrostomy with or without fundoplication. Notably, pre- and post-operative reflux is quantified using pH-impedance. / RDS: In the fourth chapter, data mining and machine learning strategies are applied to a retrospective paediatric GORD database. Predictive modelling techniques applied include logistic regression, decision trees, random forests and market basket analysis. / Results and conclusion: This work makes two key contributions. Firstly, an effective methodology for development of digital research tools is presented here. Secondly, a synthesis is made of literature, the randomised controlled trial and retrospective database modelling. The resulting product is an evidence-based algorithm for the surgical management of children with GORD