Theses - Radiology

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Open Access
Clinical and biological validation of hyperpolarised MRI of prostate cancer
Sushentsev, Nikita
Prostate cancer (PCa) is the commonest male malignancy, with the global burden of disease expected to double by 2020. While the introduction of serum prostate-specific antigen testing has led to overdiagnosis of indolent disease, more than half of patients continue to present with locally advanced and/or metastatic PCa. Consequently, there is a pressing need to develop accurate diagnostic tools to detect and characterise clinically significant disease. The recent international adoption of pre-biopsy magnetic resonance imaging (MRI) as the first-line investigation in patients with suspected PCa has created a paradigm shift in PCa diagnostic pathway. With its negative predictive value above 90%, pre-biopsy MRI halves the number of unnecessary biopsies and significantly reduces over-detection of indolent disease. However, MRI is poor at differentiating indolent from clinically significant lesions, thereby necessitating histopathological confirmation limited by the potential for sampling error and procedure-associated complications. Therefore, improving the diagnostic performance of standard-of-care MRI and its specificity for aggressive disease could reduce the requirement for tissue sampling and associated patient morbidity. Imaging the metabolic alterations that occur during tumour development is a promising approach for improving the diagnostic potential of MRI. Hyperpolarised [1-13C]pyruvate MRI (HP-13C-MRI) is an emerging clinical metabolic imaging technique that can probe the exchange of the hyperpolarised 13C label between pyruvate and lactate, a biochemical reaction traditionally viewed as the metabolic hallmark of aggressive cancers. The first-in-man study of the technique showed increased [1-13C]lactate labelling in PCa areas compared to the benign prostate, with more recent studies highlighting the potential of HP-13C-MRI for tumour grade group differentiation and treatment response assessment. This dissertation builds on these early studies to advance clinical translation of HP-13C-MRI by conducting clinical and biological validation of its ability to detect and stratify PCa in patients with clinically challenging intermediate-risk disease. To do so, Chapter 1 first introduces the key clinical concepts of PCa epidemiology, diagnosis, and risk-stratification that are directly relevant to this dissertation. It then describes the role of standard-of-care MRI in PCa diagnosis and management and highlights three key clinical decision points where HP-13C-MRI could add value to routine imaging. The chapter ends with a detailed overview of PCa metabolism and its implications for the specific methodological framework used to analyse and interpret clinical HP-13C-MRI data obtained in this dissertation. Chapter 2 describes patient characteristics, along with imaging and biological methods used in this dissertation to assess prostate metabolism across different scales. In addition to clinical HP-13C-MRI, these methods include spatial metabolomics, immunohistochemistry, and spatial transcriptomics, with their combination critical for dissecting metabolic heterogeneity across different cellular compartments and histopathological entities. Chapter 3 details the use of these methods for understanding the ability of HP-13C-MRI to detect PCa and differentiate biopsy-proven tumour areas from the healthy prostatic tissue. Specifically, differential [1-13C]lactate labelling between the benign and malignant prostate is interpreted in the context of both metabolic and non-metabolic properties of the two tissue types, revealing the importance of epithelial cell density and vascularity for generating HP-13C-MRI signal. Chapter 4 uses similar methodological framework to identify clinical and biological correlates of differential [1-13C]lactate labelling between PCa of different aggressiveness, including tumours with varying percentage of Gleason pattern 4 disease and the presence of invasive cribriform component. Chapter 5 links pre-treatment HP-13C-MRI data with intermediate-term surgical outcome data to investigate the ability of lactate imaging to detect patients at risk of developing post-surgical biochemical recurrence. Finally, Chapter 6 uses the available imaging and biological data to identify an optimal approach for HP-13C-MRI segmentation that can also be used clinically to target biopsies towards highly glycolytic tumour areas. The final section of this chapter summarises the main findings of this dissertation and provides directions for future work in the field.
Open Access
Classification of atherosclerotic plaque vulnerability by mechano-radiomics
Meddings, Zakaria
Introduction: This work investigates the hypothesis that combined biomechanical and radiomic features (mechano-radiomics) from magnetic resonance (MR) images can help evaluate carotid plaque vulnerability better than conventional MR methods. Hemodynamic forces have long been associated with the destabilization of developed plaques near regions of complex blood flow e.g., the carotid bifurcation, which results in high wall shear stress. High structural stresses within the artery wall caused by the blood flow are directly associated with risk of plaque rupture. Radiomics is an emerging technique to evaluate tissue heterogeneity. Whilst extensively investigated in oncology, there is limited application of these techniques in MR carotid plaque characterisation. Radiomic features may provide better phenotyping of carotid plaques. Mechanics and radiomic analysis were compared against stenosis measurements and morphological plaque characteristics such as the volume of lipid core, intra-plaque haemorrhage (IPH) and calcification. Methods: Two-dimensional, multi-contrast carotid MR images of 110 patients from the CARE-II multi-centre carotid imaging trial (ClinicalTrials.gov Identifier: NCT02017756) were used to perform the analysis – 55 for the radiomics analysis, and 87 for the 3D modelling of the carotids. Standard radiomic analysis was used to compute over 100 radiomic features derived from each of the multi-slice 2D image stacks. The 2D images were pre-segmented into five plaque components and incorporated into the 3D models. Finite element analysis (FEA) was performed to quantify the wall structural and shear stresses under patient-specific physiological conditions. Radiomic feature analysis was related to patient outcome (culprit or non-culprit lesion) using logistic regression, and the radiomic predictive power was combined with MR-identified plaque components and stenosis measurements to assess the improvement over conventional MR methods. The vessel wall structural and shear stresses were compared between culprit and non-culprit carotid arteries. The robustness of the long-held opinion that culprit carotid arteries (cause of plaque rupture and subsequent TIA or stroke) are associated with higher wall stresses was investigated over a range of material properties. Results: Combining radiomics biomarkers with a conventional model comprised of geometric and plaque compositional metrics had higher predictive performance over the conventional model alone (area under the curve (AUC) of 0.819±0.002 and 0.689±0.019 respectively, p=0.014). Features within the Grey Level Co-occurrence Matrix (GLCM), Grey Level Dependence Matrix (GLDM) and Grey Level Size Zone Matrix (GLSZM) sub-types were found to be particularly useful in identifying textures which could identify vulnerable carotid plaques. In the mechanics analysis, the patient cohort was stratified against the degree of stenosis. In the group with mild to moderate stenosis ($<$ 70 \%), the maximum stress-P1 was consistently higher at critical locations relating to plaque rupture. Locations at the fibrous cap, plaque shoulder and the bifurcation region were considered to evaluate the critical stress. The hypothesis of higher stress on the culprit side was proved to be robust to different material parameters. Evaluations of wall shear stress and wall curvature in three dimensions were also predictors of the culprit side. Discussion and Conclusions: The results of show that MR radiomics improves upon conventional MR methods for distinguishing culprit and non-culprit plaques. Mechanics adds value by providing a dynamic analysis which combines the 3D artery geometry with patient-specific blood pressures. Recommendations are made for which multi-slice radiomic features should be used in terms of robustness to variations in carotid segmentations and their predictive ability. Radiomic analysis helps identify texture features of vulnerable plaque phenotypes, such as lipid-rich necrotic core or calcification distribution, while biomechanical analysis proved that over different material properties, the stress was found to be higher on culprit sides at critical locations which included the carotid bifurcation and multiple atherosclerotic plaques. A mechano-radiomic model for assessing the vulnerability of carotid plaque is then proposed to obtain the maximum benefit from both a mechanics and radiomic analysis.}
Open Access
The assessment of biomechanical modelling and PET/MR imaging in coronary atherosclerosis
Sun, Chang
The life-threatening acute coronary syndromes (ACSs) are caused mainly by the rupture of the coronary atherosclerotic plaques. Angiography-defined luminal stenosis is the only validated criterion for clinical decision making. However, post-mortem studies showed that only 14% of myocardial infarctions (MIs) were caused by plaques with >70% stenosis. Plaque vulnerability, characterised by morphological and compositional features, is more important than the luminal stenosis measurements. Mini-invasive virtual-histology intravascular ultrasound (VH-IVUS), optical coherence tomography (OCT), computed tomography angiography (CTA), magnetic resonance imaging (MRI) and positron emission tomography (PET) have been developed to characterise lesion morphology, composition, function and metabolism. However, the overall predictive power of an imaging-defined high risk feature for future ischaemic events is insufficient for clinical decision making. New biomarkers are therefore needed. Coronary atherosclerosis is a chronic inflammatory disease, and the plaque is subject to mechanical loading due to dynamic blood pressure and flow, as well as bending due to heart motion. The mechanical loading estimation and the inflammation quantification have the potential in generating new biomarkers for vulnerability assessment. An accurate mechanical analysis depends on many factors, such as material properties, loading conditions and modelling strategies. The influence of material properties and loading conditions has been widely studied, whilst modelling strategies are currently less investigated. A PET/MR system provides simultaneous anatomical and metabolic imaging. However, accurate attenuation correction is essential for quantitative PET reconstruction in the thorax, and the application of PET/MR in coronary imaging is limited due to the challenges of obtaining good quality images of the coronary vessels. The work presented in this thesis first investigates the influence of computation strategies and bending on the calculation of mechanical parameters, in particular, plaque structure stress (PSS). The hypothesis is that the 3D structure only finite element analysis (FEA) can accurately predict the PSS with good time efficiency, and bending is an important factor in coronary biomechanical analysis. Mechanical parameters calculated from the 3D fully coupled fluidstructure interaction (FSI) model with the patient-specific bending were used as references. 3D structure-only FEA showed a good agreement with the gold standard model and a shorter solution time (Chapter 3). The comparison of mechanical features with and without patientspecific coronary bending showed an increase in PSS due to the bending and revealed the importance of bending in coronary FEA (Chapter 4). For the imaging part, a hybrid bias correction method was proposed for the thoracic region using zero echo time (ZTE) images, which were converted to pseudo-CT images of the lung region. These images were integrated with the standard MR attenuation map to improve the accuracy of attenuation correction (AC) in PET reconstruction (Chapter 5). We hypothesise that non-Cartesian MR sequences could improve the coronary image quality in a PET/MR system, and the incorporation of ZTE based pseudo-CT in the lung can improve the PET attenuation correction. The imaging part of this work involved the development of 3D nonCartesian (spiral and radial) trajectory MR sequences for the PET/MR system (Chapter 6). Overall, the 3D structure only FEA with patient-specific bending can accurately estimate the coronary PSS with a reasonable computation time. The ZTE based pseudo-CT attenuation correction in the lung region can improve the accuracy of thoracic PET reconstruction. The application of non-Cartesian sequences for coronary imaging requires further development in the PET/MR system.
Open Access
Evaluating Artificial Intelligence in Breast Cancer Screening
Hickman, Sarah; Hickman, Sarah [0000-0002-4637-7300]
Abstract Evaluating Artificial Intelligence in Breast Cancer Screening Dr Sarah Elizabeth Hickman This thesis evaluates the application and performance of artificial intelligence (AI) in breast cancer screening. Breast cancer screening is conducted on a population scale using mammographic imaging for the earlier detection of breast cancer and has been shown to reduce mortality. A shortage of trained radiologists, as well as the demands of double reading, mean an approach to alleviate pressures within the breast screening workflow is sought. In addition, interval cancers occur at an estimated rate of 3.7/1000 women screened in the UK, thus methods to improve the sensitivity of screening and detect cancers earlier are also needed. Advances in AI over the past decade have demonstrated comparable performance to human readers and could provide a method for an adapted screening workflow to improve both efficiency and efficacy of screening. However, the 2021 National Screening Committee (NSC) report concluded that there was insufficient evidence to support the adoption of AI into the UK breast screening programme. This thesis aims to fill the gaps in evidence highlighted in the NSC report for the performance of AI algorithms within a UK breast cancer screening population, as well as explore the various potential workflow deployment approaches of AI in the screening programme. I start by conducting a systematic review and meta-analysis of the current literature investigating the performance of stand-alone AI applications in breast cancer screening for detection and diagnosis as well as triage approaches. I then describe the creation of a large scale independent medical imaging database which is used in the studies throughout this thesis. The remainder of the thesis describes the results of three retrospective studies evaluating three different commercial AI algorithms. The first study assesses the ability of AI to detect interval cancers at the previous screen. The second study investigates the performance of AI as a stand-alone screen reader. The third study evaluates the proportion of cases identified for both high sensitivity rule out and high specificity rule in triage, as well as the proportion of cancers missed at these thresholds. Overall the results of this thesis will inform discussions around the use of AI in the UK breast screening programme as well as the design of future prospective trials.
Open Access
Development of 89Zirconium-PET Tracers for Immune Cell Imaging
Lechermann, Laura; Lechermann, Laura [0000-0002-2742-6269]
The use of cell-based therapies as a living drug have gained considerable attention for the treatment of a range of conditions such as genetic diseases, autoimmune disorders and cancer. The emergence of genetically engineered T cells expressing chimeric antigen receptors (CAR T-cells), together with modulations of immune checkpoints have brought the rapidly advancing field of immunotherapy into a new, revolutionary spotlight with a renewed interest in cell-based therapies. In vivo imaging and tracking of cells can be used to non-invasively improve the accuracy, efficacy and safety of novel immune-modulatory treatments and cell therapies. Positron Emission Tomography (PET) is a powerful non-invasive imaging technique that can be utilised for spatial and longitudinal tracking of different cell types. The long half-life PET isotope zirconium-89 (t1/2 = 78.4 h) has become increasingly available and [89Zr]Zr-Oxine has recently emerged as a promising candidate for direct cell labelling and longitudinal cell tracking. However, the water insolubility and synthesis method of [89Zr]Zr-Oxine may limit its implementation as a routine clinical imaging tool and little work has been performed looking at alternatives to this compound. The aim of this thesis was to investigate alternative approaches and methods for the direct labelling of cells using zirconium-89. This work also describes the first use of zirconium-89 in Cambridge and the set-up of the infrastructure and methods. First, the sensitivity of detecting 89Zr-labelled cells on clinical PET systems was investigated that can inform on the minimal cellular radioactivity needed for detection in prospective clinical studies. Secondly, a peptide-based approach was developed whereby cell penetrating peptides were tested for 89Zr-labelling, purification, quality control and their in vitro properties. 89Zr-labelled peptides were subsequently employed for direct cell labelling in comparison to [89Zr]Zr-Oxine in preparation for preclinical studies.
Open Access
Novel multi-parametric, multi-modality imaging for the assessment of tumour biology in renal cell carcinoma
Ursprung, Stephan; Ursprung, Stephan [0000-0003-2476-178X]
Renal cancer (RCC) is the 7th commonest cancer in the UK and clinically, morphologically, genetically and metabolically heterogeneous. Inaccurate patient stratification limits the treatment of RCC. This thesis investigates imaging techniques and image-analysis methods ranging from easily transferrable to highly specialised and dependent on dedicated infrastructure. Artificial intelligence (AI) for diagnosis, prediction and prognostication of RCC experiences increasing scientific interest. However, methodological challenges prevent the validation and qualification of algorithms as imaging biomarkers. Texture features, quantitative descriptors of image composition, are sensitive to minor variations in the tumour segmentation, which future modelling approaches should consider. Twenty-one and 47% of features were poorly reproducible after manual and algorithmic re-segmentation. Measuring response to systemic treatment becomes increasingly important with more therapeutic options available. The poor sensitivity of size-based criteria in targeted and immuno-oncology treatment is well-documented. Three clinical trials investigated morphological and physiological 1H-MRI to detect early response and predict outcome. Multiparametric MRI demonstrated physiological changes after 12 days of anti-vascular therapy, which were compatible with its mechanism of action. The reduction in tumour diffusivity correlated with the long-term volumetric response and progression-free survival. Two trials demonstrated the ability of neoadjuvant antiangiogenic treatment to reduce the extent of venous tumour thrombi in 10/35 patients and enable a less morbid surgical approach in 41%. The most common genetic alteration in RCC impacts metabolism including glycolysis. Hyperpolarised [1-13C]pyruvate MRI (hpMRI) probed the spatially heterogeneous lactic acid fermentation in nine patients with renal tumours. Paired multi-regional tissue samples and imaging afforded a biological understanding of the hpMRI signal. The apparent reaction rate constant (kPL) correlated with the tumour grade, expression of MCT1, the membrane transporter taking up pyruvate, and total LDH, catalysing pyruvate-to-lactate conversion. Improved image analysis tools, physiological and novel metabolic MRI can support precision oncology through better patient stratification and early treatment response detection. The WIRE window-of-opportunity trial of novel treatments in RCC has adopted computational and imaging techniques investigated here as primary, secondary and exploratory endpoints.
Open Access
Quantitative Magnetic Resonance Imaging and Analysis of Articular Cartilage and Osteoarthritis
Kessler, Dimitri; Kessler, Dimitri [0000-0002-1813-1039]
MRI plays an important role in the continuing search for a sensitive osteoarthritis (OA) imaging biomarker able to detect early, pre-morphological alterations in cartilage composition. Determining the compositional recovery pattern of cartilage following acute joint loading could potentially present a more sensitive biomarker for defining cartilage health [1]. However, only a limited amount of studies have assessed both the immediate effect of joint loading on cartilage, as well as its post-loading recovery. In addition, when assessing the compositional responses of cartilage to joint loading, previous studies usually did not incorporate the measurement error of the used quantitative MRI technique into their analysis. Therefore, an uncertainty persists whether or not compositional MRI techniques are sensitive enough to measure changes in water and macromolecular content of cartilage, or if previous studies were merely measuring noise. Consequently, an objective of this thesis is to increase our understanding of and reliability in quantitative T2 and T1ρ relaxation time mapping to detect compositional responses of cartilage following a joint loading activity. Furthermore, to obtain the quantitative morphological and compositional measures of cartilage, detailed region-specific delineation of cartilage is required. This delineation (or segmentation) of cartilage is laborious and time-consuming as it is usually performed manually by an expert observer. Many new advances in image analysis, particularly those in convolutional neural networks (CNNs) and deep learning, have enabled a time-efficient semi- or fully-automated alternative to this process [2, 3]. This thesis explores the utility of deep CNNs generated segmentations for accurate surface-based analysis of cartilage morphology and composition from knee MRIs as well as of cortical bone thickness from knee CTs. Chapter 1 will provide an introduction into the structure and biomechanics of articular cartilage and the role of MRI in imaging the degenerative joint disorder, osteoarthritis as well as the effects of different joint loading activities on cartilage morphology and composition. Chapter 2 explains the principle of MRI and the pulse sequences used in the following chapter for the morphometric and compositional assessment of articular cartilage. Chapter 3 describes the use of 3D Cartilage Surface Mapping (3D-CaSM) [3] to assess variations in cartilage T1ρ and T2 relaxation times of young, healthy participants following a mild, unilateral stepping activity. By evaluating and incorporating the intrasessional repeatability of the T1ρ and T2 mapping techniques, I aim to highlight those cartilage areas experiencing exercise-induced compositional changes greater than measurement error. A significant amount of time is needed to manually segment the regions-of-interest required to perform the 3D-CaSM used in Chapter 3. Therefore, in Chapter 4, I assessed the use of deep convolutional neural networks for automating the segmentation process for multiple knee joint tissues simultaneous and increase the time-efficiency for evaluating knee MR datasets. I evaluated the use of a conditional Generative Adversarial Network (cGAN) as a potentially improved method for automated segmentation compared to the widely used convolutional neural network, U-Net. In Chapter 5 I combined the 3D-CaSM and automated segmentation methods presented in Chapters 3 and 4, respectively to assess the use of fully automatic segmentations of femoral and tibial bone-cartilage structures for accurate surface-based analysis of cartilage morphology and composition on knee MR images. This was performed on publicly available data from the Osteoarthritis Initiative, a multicentre observational study with expert manual segmentations provided by the Zuse Institute in Berlin. Chapter 6 describes an automated pipeline for subchondral cortical bone thickness mapping from knee CT data. I developed a method of using automated segmentations of articular cartilage and bone from knee MRI data to determine the periarticular bone surface which is covered by cartilage. This surface was then used to perform cortical bone thickness measurements on corresponding CT data. I validated this pipeline using data from the EU-funded, multi-centre observational study called Applied Private-Public partneRship enabling OsteoArthritis Clinical Headway (APPROACH). Chapter 7 summarises the main conclusions and contributions of the works presented in this thesis as well as providing directions for future work.
Open Access
PET-MR Imaging of Hypoxia and Vascularity in Breast Cancer
Carmona-Bozo, Julia Carlota
Breast cancer is the most common cancer in the UK and in women globally. Imaging methods like mammography, ultrasound (US) and magnetic resonance imaging (MRI) play an important role in the diagnosis and management of breast cancer; they are generally utilised to provide anatomical or structural description of tumours in the clinical setting. It is widely accepted that the tumour microenvironment influences the phenotype, progression and treatment of breast cancer. This gave the impetus to move beyond tumour visualization in images to radiomics in order to provide additional disease characterisation and early biomarkers of tumour response. Due to their ability to assess physiological processes in vivo, positron emission tomography (PET) and MRI can provide non-invasive characterisation of the tumour microenvironment, including perfusion, vascular permeability, cellularity and hypoxia, which is associated with poor clinical outcome and metastasis. Clinical imaging studies in breast tumours have hitherto assessed tumour physiological parameters separately, with only few directly comparing data from these modalities. To this end, hybrid PET-MRI represents an attractive option as it can allow examination of functional processes and features of tumours simultaneously, while also conferring methodological advantages to the way imaging information is combined. The main aim of this thesis is to provide a better understanding of breast cancer pathophysiology using simultaneous PET and multi-parametric MRI. In particular, this work aims to explore relationships between imaging biomarkers of tumour vascularity measured by dynamic contrast-enhanced (DCE) MRI, cellularity using diffusion-weighted imaging (DWI) and hypoxic status using 18F-fluoromisonidazole (18F-FMISO) PET. Correlations between functional PET-MRI parameters and immunohistochemical (IHC) biomarkers of hypoxia and vascularity as well as MRI morphological tumour descriptors are also presented. The thesis concludes with an investigation of the utility of MRI markers of perfusion and surrogate markers of hypoxia to quantitatively monitor and predict pathological response in patients undergoing neoadjuvant chemotherapy (NACT) and provides projections for future work.
Open Access
Imaging Biomarkers of Response to Immune Checkpoint Inhibition in Melanoma
Lau, Ai Hui Doreen; Lau, Ai Hui Doreen [0000-0002-7623-2401]
Immune checkpoint inhibition using monoclonal antibodies targeting cytotoxic T-lymphocyte antigen-4 (CTLA-4) and programmed cell death receptor-1 (PD-1) to enhance cytotoxic T-lymphocyte response against tumours has been used in the management of several malignancies including metastatic melanoma. Although preliminary studies in patients with untreated metastatic melanoma demonstrated significantly increased progression-free survival, there is an unmet need for clinical decision-making tools that can be used for monitoring the efficacy of these costly agents, their potential side effects and the identification of patients with the most suitable immunological profile for this treatment approach. The development of non-invasive imaging methods and imaging biomarkers of response to immune checkpoint inhibitors could therefore provide important diagnostic and prognostic information. This project builds on existing technologies in Cambridge to develop structural and functional imaging approaches for monitoring tumour response to immune checkpoint inhibitors. Magnetic resonance imaging (MRI), radiolabelling of neutrophils for single-photon emission computed tomography (SPECT) imaging and intravital imaging are explored as part of a co-clinical study on metastatic melanoma patients and syngeneic mouse models of cancer immunotherapy.
Open Access
Dental Development in a UK Population: Does Ethnicity Matter?
GALLIA, Sally Elizabeth
The aim of this study was to compare third molar development in a London population of self-assigned Black British or other Black ethnicity (the Black British group) with that of self-assigned White British subjects. The significance of population differences in dental age estimation (DAE) in these groups has been debated but not previously studied in the UK. This thesis reviews the literature associated with the maturation of children and young adults, the techniques and challenges associated with age estimation and establishing the 18-year-old threshold, and the evidence for and significance of ethnic variability in dental development. Data was collected from dental panoramic tomographs (DPTs) of 5,590 subjects aged 6.00 -23.99 years: 3,555 White British and 2,035 Black British, aiming for 50 male and 50 female subjects in each 6-monthly age band. At every Demirjian stage (TDS) A-H of all third molars, subjects of Black ancestry were younger compared to those of White ancestry with mean ages for males and females generally at least one year and 1.5 years apart respectively. For the lower left third molar the mean ages at TDS A-H, in both males and females, were highly significantly different (p<0.001). Wide age ranges were seen for all third molar TDS in both ethnic groups. In 17-year-old males, 75% of the Black British group and 43% of the White British group had lower left third molars at TDS G or H. In 18-year-old males, these figures were 88% and 61% respectively. Hypodontia, with or without third molar agenesis (TMA), was approximately twice as likely in the White British group compared to the Black British group, and TMA only was approximately three times as likely. Developmentally missing teeth were shown to be associated with delayed third molar development. These findings confirm the variability of third molar development, the limitations of DAE for determining the 18-year-old threshold, and the important significance of ethnicity in DAE.
Open Access
Functional Magnetic Resonance Imaging of Breast Cancer
Baxter, Gabrielle; Baxter, Gabrielle [0000-0002-8242-1559]
This thesis examines the use of magnetic resonance imaging (MRI) techniques in the detection of breast cancer and the prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NACT). This thesis compares the diagnostic performance of diffusion-weighted imaging (DWI) models in the breast using a systematic review and meta-analysis. Advanced diffusion models have been proposed that may improve the performance of standard DWI using the apparent diffusion coefficient (ADC) to discriminate between malignant and benign breast lesions. Pooling the results from 73 studies, comparable diagnostic accuracy is shown using the ADC and parameters from the intra-voxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) models. This work highlights a lack of standardisation in DWI protocols and methodology. Conventional acquisition techniques used in DWI often suffer from image artefacts and low spatial resolution. A multi-shot DWI technique, multiplexed sensitivity encoding (MUSE), can improve the image quality of DWI. A MUSE protocol has been optimised through a series of phantom experiments and validated in 20 patients. Comparing MUSE to conventional DWI, statistically significant improvements are shown in distortion and blurring metrics and qualitative image quality metrics such as lesion conspicuity and diagnostic confidence, increasing the clinical utility of DWI. This thesis investigates the use of dynamic contrast-enhanced MRI (DCE-MRI) in the detection of breast cancer and the prediction of pCR. Abbreviated MRI (ABB-MRI) protocols have gained increasing attention for the detection of breast cancer, acquiring a shortened version of a full diagnostic protocol (FDP-MRI) in a fraction of the time, reducing the cost of the examination. The diagnostic performance of abbreviated and full diagnostic protocols is systematically compared using a meta-analysis. Pooling 13 studies, equivalent diagnostic accuracy is shown for ABB-MRI in cohorts enriched with cancers, and lower but not significantly different diagnostic performance is shown in screening cohorts. Higher order imaging features derived from pre-treatment DCE-MRI could be used to predict pCR and inform decisions regarding targeted treatment, avoiding unnecessary toxicity. Using data from 152 patients undergoing NACT, radiomics features are extracted from baseline DCE-MRI and machine learning models trained to predict pCR with moderate accuracy. The stability of feature selection using logistic regression classification is demonstrated and a comparison of models trained using features from different time points in the dynamic series demonstrates that a full dynamic series enables the most accurate prediction of pCR.
Open Access
Magnetic Resonance Imaging of Susceptibility Effects in Carotid Atherosclerosis
Ruetten, Pascal; Ruetten, Pascal [0000-0001-7326-4590]
This thesis explores the use of susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM), to characterize carotid artery plaques with and without the use of ultrasmall superparamagnetic iron oxide (USPIO) nanoparticle contrast agents. The overall hypothesis is that QSM can serve to differentiate carotid artery plaque features of different susceptibility and provide a positive contrast mechanism for imaging the uptake of USPIOs. Chapter 1 describes the pathophysiology of carotid atherosclerosis. Vulnerable plaques, i.e. those at risk of rupture, can be characterized by the presence of a lipid rich necrotic core (LRNC), intraplaque haemorrhage (IPH), and inflammation. In addition, plaques may develop calcifications that may be protective of rupture. The chapter describes the established multi-contrast imaging protocols used for characterizing plaques. Furthermore, the use of USPIO-contrast agents to image inflammation is described. Chapter 2 describes the physical principles of MR image generation including the sensitivity to magnetic susceptibility. The principles of T2*w imaging, and susceptibility weighted imaging (SWI) are explained. Chapter 3 reviews the principles and post-processing steps involved in commonly used algorithms for QSM in terms of the underlying physical and mathematical principles which are then demonstrated in the form of numerical simulations. Chapter 4 presents the application of SWI to a group of patients who underwent USPIO enhanced MRI on a 1.5T MRI system. Images were acquired prior to infusion and 48 hours post infusion. SWI and gradient echo phase images were used to depict the field inhomogeneities generated by diamagnetic and paramagnetic materials within the plaques, calcification and USPIO-uptake. These results were then compared to a conventional carotid multi-contrast protocol, which includes R2*-mapping and T2*w imaging, and, where available, CT and histology. In chapter 5 QSM is performed in the carotid artery wall of a cohort of normal volunteers on a 1.5T MRI system. Unlike the brain, the neck contains fat which can cause severe errors in the field estimate, which propagate into the susceptibility map. Therefore, QSM was combined with water-fat separation for application in the neck to correct for these artifacts. This correctly estimated a high fat-fraction in fatty tissue in the neck and allowed for a detailed depiction of the anatomy of healthy volunteers. The susceptibility value measured in fatty tissue agreed with literature values. Chapter 6 applies QSM with water-fat separation to a subset of the patient group on a 1.5T MRI system. On pre-contrast scans QSM successfully identified calcification as diamagnetic tissue and the water-fat separation identified a lipid core. On the post-contrast susceptibility maps, USPIO-uptake was identified as hyperintense signal. This allows QSM to provide quantitative contrast in carotid imaging that can identify multiple features simultaneously and to simplify the imaging of USPIO-contrast. The results were confirmed using the multi-contrast carotid MRI protocol and, where available, histology and CT. Chapter 7 discusses the limitations of the current studies and the potential future improvements of the current methodology in terms of MR acquisition, post-processing algorithms and MR protocols. Future studies could serve to further evaluate the potential of QSM in carotid imaging and use it as a novel tool to quantify USPIO uptake in atherosclerotic carotid arteries.
Controlled Access
Intracranial Vascular Findings in a Tri-Ethnic Population – MR Phenotypes and Physiological Parameters
Rehwald, Rafael; Rehwald, Rafael [0000-0003-4357-3581]
Investigating and understanding the complex blood supply of the brain in health and disease has been a major challenge for scientists for many centuries, as in-depth, detailed knowledge of the intracranial vascular anatomy and cerebrovascular physiology is ultimately essential for accurate diagnosis and therapy. With the emerging availability of medical imaging and rapid technological advances, in particular concerning non-ionising magnetic resonance (MR) imaging techniques, brain imaging has become a firmly established tool for this purpose in both the clinical and research settings. However, current knowledge of the cerebral circulation still remains limited. Clear evidence of the anatomical differences between distinctive ethnic populations, particularly relating to the morphologic heterogeneity of the intracranial arterial network and the impact of its vari- able structure on intracranial haemodynamics, cerebral blood flow, and the pathogenesis of cerebrovascular disease is still lacking, while the continuous adoption and increasing avail- ability of non-invasive neuroimaging techniques has raised specific new challenges, such as the identification of incidental imaging findings. This thesis presents the first comprehensive evaluation of the vascular architecture of the Circle of Willis and its variation in a single tri-ethnic population-based sample including a total of 750 individuals, using standardised high-resolution 3-tesla time-of-flight MR angiography. In addition, this work investigates the population prevalence and risk factor profiles of incidental MR angiographic intracranial arterial imaging findings in a multi- ethnic cohort. In a subsample of 360 subjects, pseudo-continuous arterial spin labelling MR is further used to investigate global cerebral perfusion by evaluating blood flow and the pres- ence of arterial transit artefacts, and the impact of the vertebrobasilar vascular morphology and other cardiovascular factors on cerebral blood flow and artefact manifestation in the posterior circulation are explored. As a whole, this work delivers novel and unique insights into the intracranial vascular anatomy and haemodynamic physiology as well as into the prevalence of large vessel cerebrovascular disease as part of a multi-ethnic population-based investigation, presenting new evidence for morphological and pathophysiological differences between women and men, and between different ethnic populations.
Open Access
Acceleration of Subtractive Non-contrast-enhanced Magnetic Resonance Angiography
Li, Hao
Although contrast-enhanced magnetic resonance angiography (CE-MRA) is widely established as a clinical examination for the diagnosis of human vascular diseases, non-contrast-enhanced MRA (NCE-MRA) techniques have drawn increasing attention in recent years. NCE-MRA is based on the intrinsic physical properties of blood and does not require the injection of any exogenous contrast agents. Subtractive NCE-MRA is a class of techniques that acquires two image sets with different vascular signal intensity, which are later subtracted to generate angiograms. The long acquisition time is an important drawback of NCE-MRA techniques, which not only limits the clinical acceptance of these techniques but also renders them sensitive to artefacts from patient motion. Another problem for subtractive NCE-MRA is the unwanted residual background signal caused by different static background signal levels on the two raw image sets. This thesis aims at improving subtractive NCE-MRA techniques by addressing both these limitations, with a particular focus on three-dimensional (3D) femoral artery fresh blood imaging (FBI). The structure of the thesis is as follows: Chapter 1 describes the anatomy and physiology of the vascular system, including the characteristics of arteries and veins, and the MR properties and flow characteristics of blood. These characteristics are the foundation of NCE-MRA technique development. Chapter 2 introduces commonly used diagnostic angiographic methods, particularly CE-MRA and NCE-MRA. Current NCE-MRA techniques are reviewed and categorised into different types. Their principles, implementations and limitations are summarised. Chapter 3 describes imaging acceleration theories including compressed sensing (CS), parallel imaging (PI) and partial Fourier (PF). The Split Bregman algorithm is described as an efficient CS reconstruction method. The SPIRiT reconstruction for PI and homodyne detection for PF are also introduced and combined with Split Bregman to form the basis of the reconstruction strategy for undersampled MR datasets. Four image quality metrics are presented for evaluating the quality of reconstructed images. In Chapter 4, an intensity correction method is proposed to improve background suppression for subtractive NCE-MRA techniques. Residual signals of background tissues are removed by performing a weighted subtraction, in which the weighting factor is obtained by a robust regression method. Image sparsity can also be increased and thereby potentially benefit CS reconstruction in the following chapters. Chapter 5 investigates the optimal k-space sampling patterns for the 3D accelerated femoral artery FBI sequence. A variable density Poisson-disk with a fully sampled centre region and missing partial Fourier fractions is employed for k-space undersampling in the ky-kz plane. Several key parameters in sampling pattern design, such as partial Fourier sampling ratios, fully sampled centre region size and density decay factor, are evaluated and optimised. Chapter 6 introduces several reconstruction strategies for accelerated subtractive NCE-MRA. A new reconstruction method, k-space subtraction with phase and intensity correction (KSPIC), is developed. By performing subtraction in k-space, KSPIC can exploit the sparsity of subtracted angiogram data and potentially improve the reconstruction performance. A phase correction procedure is used to restore the polarity of negative signals caused by subtraction. The intensity correction method proposed in Chapter 4 is also incorporated in KSPIC as it improves background suppression and thereby sparsity. The highly accelerated technique can be used not only to reduce the acquisition time, but also to enable imaging with increased resolution with no time penalty. A time-efficient high-resolution FBI technique is proposed in Chapter 7. By employing KSPIC and modifying the flow-compensation/spoiled gradients, the image matrix size can be increased from 256×256 to up to 512×512 without prolonging the acquisition time. Chapter 8 summarises the overall achievements and limitations of this thesis, as well as outlines potential future research directions.
Open Access
Novel approaches to MRI of glioma
Zaccagna, Fulvio; Zaccagna, Fulvio [0000-0001-6838-9532]
Gliomas are extremely heterogeneous, both morphologically and biologically, which contributes to a very poor prognosis. Current imaging of glioma is insufficient for a thorough diagnosis, therapy assessment and prognosis prediction. Moreover, refined and more sophisticated imaging technique could help in furthering our knowledge of gliomas. In order to facilitate proliferation, cancer cells undergo a change in structure and an increase in metabolism that results in distortion and disruption of tissue architecture. Gliomas are characterised by an increase in cells of variable sizes, as well as changes in the tissue microstructure. Diffusion-Weighted Imaging (DWI) and the apparent diffusion coefficient (ADC), have been extensively studied as potential imaging biomarkers for cellularity and tissue architecture. However, several studies have shown partial overlap in the measured values between tumour subtypes. Moreover, ADC is influenced by several factors and does not provide detailed information on the tissue microstructure. The Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT) is a novel diffusion model that infers tissue microstructure compartment from conventional DWI measurements. This model derives metrics for the intracellular, intravascular and extracellular– extravascular spaces providing a more detailed interpretation of the tissue microstructure. To date, VERDICT has been applied to xenograft models of colorectal cancer, patient studies of prostate cancer and recently its feasibility in glioma has been shown. In this PhD I have applied a shortened version of the VERDICT method to image intratumoral and intertumoral heterogeneity in glioma. The results have also been validated with histology as part of a prospective study. Gliomas also exhibit a significant increase in mitotic activity within the tumour. The increased number of mitosis alters cell density which, in turn, affects the total concentration of tissue sodium as the concentration of tissue sodium is approximately ten-fold higher in the extracellular compared to the intracellular space. In addition, there is a decrease in Na+/K+-ATPase activity in tumours due to ATP depletion, which contributes to disturb sodium homeostasis. Non-invasive detection of 23Na with MRI has the potential to quantify sodium concentration and therefore could be an imaging probe of cell morphology and membrane function within the tumour microenvironment, as well as a method of probing tissue heterogeneity. During my PhD, a novel 23Na-MRI technique has been used to evaluate sodium distribution within glioma and in the surrounding tissue. Metabolic reprogramming is one of the major driving forces for determining glioma growth and invasion. Therefore, the non-invasive characterization of metabolic intratumoral, peritumoral and intertumoral heterogeneity in vivo could help to better stratify patients and to develop novel therapeutic strategies targeting cancer-specific metabolic pathways. 13C magnetic resonance imaging (MRI) using dynamic nuclear polarization (DNP) is a novel technique that allows non-invasive assessment of the metabolism of hyperpolarized (HP) 13C-labelled molecules in vivo, such as the exchange of [1-13C]pyruvate to [1-13C]lactate in tumours (Warburg effect). Part of my PhD has focused on developing and translating HP [1-13C]pyruvate MRI to explore metabolic reprogramming in glioma and the surrounding microenvironment. The overall aim of my PhD has been to develop novel approaches to imaging glioma with MRI to probe both the architectural and metabolic changes of Glioma. The preliminary evidence suggests that these tools can more deeply phenotype tumours than conventional imaging approaches. Although the main focus of this work has been gliomas, the techniques developed and presented here may be applied to study other pathological conditions within the brain, which raises the possibility of other potential clinical applications for this work.
Open Access
Advanced Magnetic Resonance Imaging of Osteoarthritis
(2020-01-25) MacKay, James; MacKay, James [0000-0001-7558-3800]
This thesis examines the potential utility of magnetic resonance (MR) quantitative imaging biomarkers (QIBs) of knee osteoarthritis (OA) for rapid assessment of treatment efficacy in experimental medicine studies. The development of treatments able to modify disease in OA is hampered by an inability to evaluate treatment response over a timeframe relevant to clinical trials. There are particular challenges in the experimental medicine setting due to the small numbers of participants and short follow-up duration relative to the expected time course of OA development and progression. Multiple MR QIBs of OA exist which may help address the problem of early evaluation of treatment response. However, their use in early phase studies has remained limited. Possible reasons for this include incomplete characterisation of the performance of QIBs in this setting and lack of head-to-head comparison of candidate QIBs to determine which would be optimal. This thesis aims to address these shortcomings and provide new information on the likely utility of MR QIBs in the setting of experimental medicine studies, as well as their potential for improving our general understanding of OA pathophysiology. I start by examining the reliability and ability to discriminate between OA and healthy knees of cartilage compositional MR imaging in a systematic review and meta-analysis. I then describe the development and validation of a novel semi-automatic surface-based method for analysing articular cartilage composition and morphology at the knee which may offer improved responsiveness and spatial localisation of change. Moving to QIBs of subchondral bone, I evaluate the association between measures of subchondral bone architecture derived from MR texture analysis and OA progression in the Osteoarthritis Initiative. The remainder of the thesis describes a prospective observational study where the utility of MR QIBs of synovium, subchondral bone and cartilage in experimental medicine studies is assessed. In summary, this thesis will inform decisions regarding the use of MR-based QIBs in future longitudinal and interventional studies. Their inclusion in experimental medicine studies may allow early assessment of treatment efficacy at a structural level and improve efficiency of treatment development pipelines.
Open Access
Magnetic Resonance imaging of tumour biomarkers in ovarian cancer
(2019-12-31) Deen, Surrin Shazam
This thesis explores the application of novel magnetic resonance imaging (MRI) techniques to the evaluation of ovarian cancer. Diffusion kurtosis imaging (DKI), sodium MRI, magnetization transfer (MT) imaging, hyperpolarized carbon-13 MRI and magnetic resonance fingerprinting (MRF) were employed to image ovarian tumours in human subjects. The results of the imaging were compared to semi-quantitative measurements of histology and immunohistochemistry staining of tissue samples. It was found that DKI may predict responders to cytotoxic drugs and that sodium MRI and MT measure cellularity. Effective techniques to perform hyperpolarized carbon-13 MRI and MRF were also shown in a clinical setting, where MRF may improve imaging speed and the reproducibility of proton imaging and hyperpolarized carbon-13 MRI could provide unique in vivo metabolic information that differs from FDG-PET.
Open Access
Imaging and Measuring Cerebral Metabolism in the Healthy Brain and Changes Following Inflammation
(2019-05-08) Grist, James Timothy; Grist, James Timothy [0000-0001-7223-4031]
Metabolism is a key process to the function and survival of all living organisms. The role of metabolism is key in many pathologies, and presents a prime opportunity to both understand and treat disease in new ways. In particular, lactate is a molecule which has been known and studied for many years by a broad spectrum of scientists from many research fields, with it appearing to have a number of roles in the routine operation and function of living organisms, as well as signaling pathological disturbance of normal physiology in many circumstances. This thesis aims to further the understanding of how measuring and quantifying both lactate and sodium with both NMR and spectral photometric techniques can be a powerful tool for the researcher in cell, pre-clinical, and clinical research. The research for my PhD has focused on basic biology, pre-clinical large animal imaging, clinical sodium imaging in Multiple Sclerosis, and a physiological first in man study of the healthy brain with hyperpolarised [1-13C] pyruvate.
Controlled Access
Magnetic Resonance Imaging of Atherosclerosis
(2019-07-19) Usman, Ammara
Stroke remains the most common cause of long-term disability with approximately two-thirds of ischaemic strokes resulting from underlying carotid atherosclerotic disease. The clinical management of carotid artery disease relies primarily on the evaluation of the severity of carotid artery luminal stenosis. However, there is growing evidence that morphological and functional information about carotid plaques may also be crucial for the assessment of the severity of atherosclerosis. High-resolution magnetic resonance (MR) imaging is an emerging imaging technique, which has shown great promise in providing detailed information about plaque pathobiology besides luminal stenosis. Using a special contrast medium called ultrasmall superparamagnetic particles of iron oxide (USPIO), MR imaging can also help in the assessment of carotid plaque inflammation. In this dissertation, I explore the different MR imaging modalities for the assessment of morphological, biomechanical and functional characteristics of the atherosclerotic plaques in different patient cohorts, to assess the efficacy of these techniques in identifying high-risk atherosclerotic plaques. It is important to identify these individuals with vulnerable plaques and are the risk of future cerebrovascular events so that they receive optimal medical therapy and timely surgical intervention. Overall the results of this dissertation provide strong support for the use of functional MR imaging techniques i.e. USPIO-enhanced and Dynamic contrast-enhanced MR imaging for detailed morphological and functional assessment of plaques. This may help refine risk stratification especially in subgroups of patients with asymptomatic carotid disease. This may assist in in improving our standing of the pathogenesis of cardiovascular disease in different patient cohorts and help to determine disease severity and prognosis, as well as providing a biomarker to assess the efficacy of established or novel therapeutic interventions
Open Access
Development of a novel uncovered stent system for the management of complex aortic aneurysms
(2019-01-31) Wang, Shuo
Endovascular aortic repair (EVAR) is a minimally invasive alternative to open surgery for the treatment of aortic aneurysms (AA). However, standard EVAR is not applicable to complex AA with involvement of vital branches, which could be occluded by the endograft. As an emerging technique, the concept of multiple overlapping uncovered stents (MOUS) have been proposed to manage complex lesions. MOUS was used to modulate the flow pattern inside the aneurysm sac, and promote the thrombus formation followed by the aneurysm shrinkage. In this dissertation, we sought to investigate the mechanism of MOUS-induced flow modulation and key factors associated with the success of this novel technique: - The mechanical behaviour of AA was characterised by uniaxial material tests (Chapter 4). A Bayesian framework was proposed for material constants identification. They were found correlated to the microstructure of tissue fibre network and were capable in differentiating tissue types. - Solid-to-solid interaction and one-way fluid-solid interaction (FSI) analysis was performed based on patient-specific computer tomography angiography (Chapters 5&6). Structural stress concentrations were observed within the landing zones, which increased with the number of stents deployed. In the parameter studies (Chapter 6), the overall porosity was identified as the dominant factor of the flow-diverting outcome, while cross-stent structures of MOUS had limited influence. - The pathological effect of structural stress concentration induced by an implanted device was further studied in rabbit models (Chapter 7). The wall structural stress and fluid shear stress were obtained from FSI analysis based on magnetic resonance imaging (MRI), and correlated to plaque characteristics. Both high structural stress and low fluid shear stress were found correlated to plaque initialisation and increased inflammation. Overall, MOUS modulates the blood flow with robust performance under different overlapping patterns. Image-based biomechanical analysis can optimise MOUS design and can contribute to personalised pre-surgery planning.