Personalised haemodynamic simulations of aortic dissection: towards clinical translation

Aortic dissection (AD) is a severe vascular condition in which an intramural tear results in blood flowing within the aortic wall. The optimal treatment of type-B dissections - those involving the arch and descending aorta - is still debated; when uncomplicated, they are commonly managed medically, but up to 50% of the cases will develop complications requiring invasive intervention. Patient-specific computational fluid dynamics (CFD) can provide insight into the pathology and aid clinical decisions by reproducing in detail the intra-aortic haemodynamics; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of simulation predictions and impede clinical translation. Moreover, the requirement of working with noisy and oftentimes minimal clinical datasets complicates the implementation of personalised models. In the present thesis, methods to overcome the aforementioned limitations and facilitate the clinical translation of CFD tools are presented and tested on type-B AD cases. A novel approach for patient-specific models of complex ADs informed by commonly available clinical datasets (including CT-scans and Doppler ultrasonography) is proposed. The approach includes an innovative way to account for arterial compliance in rigid-wall simulations using a lumped capacitor and a parameter estimation strategy for Windkessel boundary conditions. The approach was tested on three case-studies, and the results were successfully compared against invasive intra-aortic pressure measurements. A new and efficient moving boundary method (MBM) - tunable with non-invasive displacement data - is then proposed to capture wall motion in CFD simulations, necessary in certain AD settings for accurate haemodynamic predictions. The MBM was first applied and validated on a case-study previously investigated with a full fluid-structure interaction technique, and then employed in a patient-specific compliant model of a type-B AD informed by multi-modal imaging data. Extensive comparison between in silico and in vivo data demonstrated the reliability of the model predictions

Gas transfer model to design a ventilator for neonatal total liquid ventilation

The study was aimed to optimize the gas transfer in an innovative ventilator for neonatal Total Liquid Ventilation (TLV) that integrates the pumping and oxygenation functions in a non-volumetric pulsatile device made of parallel flat silicone membranes. A computational approach was adopted to evaluate oxygen (O2) and carbon dioxide (CO2) exchanges between the liquid perfluorocarbon (PFC) and the oxygenating gas, as a function of the geometrical parameter of the device. A 2D semi-empirical model was implemented to this purpose using Comsol Multiphysics to study both the fluid dynamics and the gas exchange in the ventilator. Experimental gas exchanges measured with a preliminary prototype were compared to the simulation outcomes to prove the model reliability. Different device configurations were modeled to identify the optimal design able to guarantee the desired gas transfer. Good agreement between experimental and simulation outcomes was obtained, validating the model. The optimal configuration, able to achieve the desired gas exchange (ΔpCO2 = 16.5 mmHg and ΔpO2 = 69 mmHg), is a device comprising 40 modules, 300 mm in length (total exchange area = 2.28 m(2)). With this configuration gas transfer performance is satisfactory for all the simulated settings, proving good adaptability of the device

Towards Reduced Order Models via Robust Proper Orthogonal Decomposition to capture personalised aortic haemodynamics

Data driven, reduced order modelling has shown promise in tackling the challenges associated with computational and experimental hemodynamic models. In this work, we focus on the use of Reduced Order Models (ROMs) to reconstruct velocity fields in a patient-specific dissected aorta, with the objective being to compare the ROMs obtained from Robust Proper Orthogonal Decomposition (RPOD) to those obtained from the traditional Proper Orthogonal Decomposition (POD). POD and RPOD are applied to in vitro, hemodynamic data acquired by Particle Image Velocimetry and compare the decomposed flows to those derived from Computational Fluid Dynamics (CFD) data for the same geometry and flow conditions. In this work, PIV and CFD results act as surrogates for clinical haemodynamic data eg. MR, helping to demonstrate the potential use of ROMS in real clinical scenarios. The flow is reconstructed using different numbers of POD modes and the flow features obtained throughout the cardiac cycle are compared to the original Full Order Models (FOMs). Robust Principal Component Analysis (RPCA), the first step of RPOD, has been found to enhance the quality of PIV data, allowing POD to capture most of the kinetic energy of the flow in just two modes similar to the numerical data that are free from measurement noise. The reconstruction errors differ along the cardiac cycle with diastolic flows requiring more modes for accurate reconstruction. In general, modes 1-10 are found sufficient to represent the flow field. The results demonstrate that the coherent structures that characterise this aortic dissection flow are described by the first few POD modes suggesting that it is possible to represent the macroscale behaviour of aortic flow in a low-dimensional space; thus significantly simplifying the problem, and allowing for more computationally efficient flow simulations or machine learning based flow predictions that can pave the way for translation of such models to the clinic

A method to estimate concrete hydraulic conductivity of underground tunnel to assess lining degradation

The determination of the degradation state of underground concrete tunnels is a crucial issue for maintaining and monitoring the performance of these infrastructures. In particular, if the tunnel is totally or partially submerged, concrete deterioration and consequent changes in both lining thickness and hydraulic conductivity can have dramatic effects on the amount of water inflow, leading to an increase in maintenance costs as well as to possible interruption of the infrastructure serviceability. The hydraulic conductivity of the concrete lining is here proposed as a proxy of the overall degradation state of the structure, being this property directly correlated to porosity and to the presence of interconnected fissures and cracks. The aim of this study is to propose a simple and completely non-destructive method to estimate the hydraulic conductivity of tunnel lining concrete. Provided the availability of easy-to-collect in situ geometrical and hydrogeological data (i.e. tunnel geometry, water inflow, water table level), the method relies on a back analysis to estimate the hydraulic conductivity of the concrete, performed via the finite element method to solve the seepage equations in porous media. Ground Penetration Radar technique is coupled to the modelling approach to gain accurate data about the current lining thickness. The proposed method has been applied to the study of a real case of underground tunnel, used to prove the model reliability. Moreover, once estimated the hydraulic conductivity and thickness of the concrete, the model can be used to generate curves linking the total water inflow in the tunnel as a function of the groundwater level variations, allowing a real-time monitoring of the current hydraulic state of the infrastructure. This methodology, which can be considered of general validity and easy to be extended for the study of any underground tunnel, provides a simple and effective tool useful to prioritize maintenance works and to evaluate the consequences of different hydraulic scenarios

Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry

Aortic Dissection (AD) is a complex pathology that affects the aorta. Diagnosis, management and treatment remain a challenge as it is a highly patient-specific pathology and there is still a limited understanding of the fluid-mechanics phenomena underlying clinical outcomes. Although in vitro models can allow the accurate study of AD flow fields in physical phantoms, they are currently scarce and almost exclusively rely on over simplifying assumptions. In this work, we present the first experimental study of a patient-specific case of AD. An anatomically correct phantom was produced and combined with a state-of-the-art in vitro platform, informed by clinical data, employed to accurately reproduce personalised conditions. The complex AD haemodynamics reproduced by the platform was characterised by flow rate and pressure acquisitions as well as Particle Image Velocimetry (PIV) derived velocity fields. Clinically relevant haemodynamic indices, that can be correlated with AD prognosis – such as velocity, shear rate, turbulent kinetic energy distributions – were extracted in two regions of interest in the aortic domain. The acquired data highlighted the complex nature of the flow (e.g. recirculation regions, low shear rate in the false lumen) and was in very good agreement with the available clinical data and the CFD results of a study conducted alongside, demonstrating the accuracy of the findings. These results demonstrate that the described platform constitutes a powerful, unique tool to reproduce in vitro personalised haemodynamic conditions, which can be used to support the evaluation of surgical procedures, medical devices testing and to validate state-of-the-art numerical models

A simplified method to account for wall motion in patient-specific blood flow simulations of aortic dissection : comparison with fluid-structure interaction

Aortic dissection (AD) is a complex and highly patient-specific vascular condition difficult to treat. Computational fluid dynamics (CFD) can aid the medical management of this pathology, yet its modelling and simulation are challenging. One aspect usually disregarded when modelling AD is the motion of the vessel wall, which has been shown to significantly impact simulation results. Fluid-structure interaction (FSI) methods are difficult to implement and are subject to assumptions regarding the mechanical properties of the vessel wall, which cannot be retrieved non-invasively. This paper presents a simplified 'moving-boundary method' (MBM) to account for the motion of the vessel wall in type-B AD CFD simulations, which can be tuned with non-invasive clinical images (e.g. 2D cine-MRI). The method is firstly validated against the 1D solution of flow through an elastic straight tube; it is then applied to a type-B AD case study and the results are compared to a state-of-the-art, full FSI simulation. Results show that the proposed method can capture the main effects due to the wall motion on the flow field: the average relative difference between flow and pressure waves obtained with the FSI and MBM simulations was less than 1.8% and 1.3%, respectively and the wall shear stress indices were found to have a similar distribution. Moreover, compared to FSI, MBM has the advantage to be less computationally expensive (requiring half of the time of an FSI simulation) and easier to implement, which are important requirements for clinical translatio

Metalliteollisuuden yritysten resurssitarvekartoitus

Tämän opinnäytetyön toimeksiantaja oli Kainuun Etu Oy. Opinnäytetyön tarkoituksena oli selvittää Kainuun ja lähialueiden metalliteollisuuden yritysten resurssitarpeita. Pääasiassa selvityksen alla oli yritysten erityiskoneistustarpeet ja suorittavan tason henkilökunnan koulutustarpeet. Resurssitarvekartoitus tehtiin osana Kajaanin Otanmäkeen suunnitteilla olleen koulutustehtaan perustamisselvitystä. Opinnäytetyön tavoite oli saada tietoa potentiaalisten asiakasyritysten tarpeista, että perustettavassa tehtaassa päätöksiä tekevät henkilöt saavat lisätietoa tai varmistavaa tietoa päätöksenteon tueksi. Tiedon pääasiallinen käyttötarkoitus oli tehtaan alkutuotannon suunnittelu asiakkaiden tarpeita varten. Kyselyn piiriin kuuluvilta Kainuulaisilta yrityksiltä tiedusteltiin myös yrityksen tai yrittäjän halukkuudesta lähteä osakkaaksi tehtaaseen. Resurssitarvekartoitus suoritettiin kvalitatiivisena tutkimuksena. Suunniteltu kyselylomake lähetettiin sähköpostilla ennakkoon päätettyihin yrityksiin, ja siten aineisto kerättiin kyselyyn vastanneiden yritysten vastausten pohjalta. Tutkimuksen tulokset heijastelevat koulutustarpeiden osalta toimialan työvoimapulan vaikutuksia. Tarvetta on etenkin joko suorittavan tason työntekijöistä, tai sitten halutaan tuotannon automaatioon liittyvää koulutusta. Koneistuspuolelta tarvetta löytyi lähinnä raskaasta aarporauksesta. Opinnäytetyön tuloksilla ei luultavasti ole myöhempiä käyttömahdollisuuksia muuten kuin opinnäytetyön toimeksiantajalle, tai vastaavanlaisen kartoituksen suunnittelijalle. Kaikki yritysten lähettämät vastaukset käsiteltiin opinnäytetyön raporttia tehdessä luottamuksellisesti ja nimettömänä.This thesis was commissioned by Kainuun Etu Oy. The purpose was to find out about the nature of resource demands at metal industry companies. The companies were mainly located in the Kainuu and Northern Ostrobothnia regions. The primary resource demands to be examined were the companies' special machining needs and training needs for the companies' executive personnel. The resource demand survey was made as a part of the foundation report for a training workshop that was planned to be founded in Otanmäki, Kajaani. The purpose was to gather information about the needs of the potential business clients, so that the workshop management would get information to support their decision making. The primary purpose of the information was the planning of the workshop production according to the clients' needs. The companies located in the Kainuu region were also asked about their interest in being a shareholder in the planned workshop. The resource demand survey was conducted as qualitative research. The questionnaire was e-mailed to the group of companies, which was decided beforehand. The data was gathered from the companies' answers to the questionnaire. The results of the survey seem to reflect the effects of the labor shortage in the metal industry, especially in the training needs. Companies seem to need either executive personnel or training associated with industrial automation. There were no major machining needs apart from reaming, especially when it comes to machining large and heavy objects. There are probably no later utilization possibilities for this thesis, apart from the client or someone who plans to conduct a similar survey. While writing this thesis report, all the companies' answers were reported with confidentiality and anonymously

Supplementary Material List from Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data

Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study an AD patient. A new moving boundary algorithm was implemented to capture wall displacement and a rich <i>in vivo</i> clinical dataset was used to tune model parameters and for validation. Comparisons between <i>in silico</i> and <i>in vivo</i> data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as potential tool for AD management and clinical support