Potentials and caveats of AI in Hybrid Imaging

State-of-the-art patient management frequently mandates the investigation of both anatomy and physiology of the patients. Hybrid imaging modalities such as the PET/MRI, PET/CT and SPECT/CT have the ability to provide both structural and functional information of the investigated tissues in a single examination. With the introduction of such advanced hardware fusion, new problems arise such as the exceedingly large amount of multi-modality data that requires novel approaches of how to extract a maximum of clinical information from large sets of multi-dimensional imaging data. Artificial intelligence (AI) has emerged as one of the leading technologies that has shown promise in facilitating highly integrative analysis of multi-parametric data. Specifically, the usefulness of AI algorithms in the medical imaging field has been heavily investigated in the realms of (1) image acquisition and reconstruction, (2) post-processing and (3) data mining and modelling. Here, we aim to provide an overview of the challenges encountered in hybrid imaging and discuss how AI algorithms can facilitate potential solutions. In addition, we highlight the pitfalls and challenges in using advanced AI algorithms in the context of hybrid imaging and provide suggestions for building robust AI solutions that enable reproducible and transparent research

Single photon emission computed tomography: performance assessment, development and clinical applications

This is a general investigation of the SPECT imaging process. The primary aim is to determine the manner in which the SPECT studies should be performed in order to maximise the relevant clinical information given the characteristics and limitations of the particular gamma camera imaging system used. Thus the first part of this thesis is concerned with an assessment of the performance characteristics of the SPECT system itself. This involves the measurement of the fundamental planar imaging properties of the camera, their stability with rotation, the ability of the camera to rotate in a perfect circle and the accuracy of the transfer of the information from the camera to the computing system. Following this the performance of the SPECT system as a whole is optimised. This is achieved by examining the fundamental aspects of the SPECT imaging process and by optimising the selection of the parameters chosen for the acquisition and reconstruction of the data. As an aid to this a novel mathematical construct is introduced. By taking the logarithm of the power spectrum of the normalised projection profile data the relationship between the signal power and the noise power in the detected data can be visualised. From a theoretical consideration of the available options the Butterworth filter is chosen for use because it provides the best combination of spatial frequency transfer characteristics and flexibility. The flexibility of the Butterworth filter is an important feature because it means that the form of the actual function used in the reconstruction of a transaxial section can be chosen with regard to the relationship between the signal and the noise in the data. A novel method is developed to match the filter to the projection data. This consists of the construction of a mean angular power spectrum from the set of projection profiles required for the reconstruction of the particular transaxial section in question. From this the spatial frequency at which the the signal becomes dominated by the noise is identified. The value which the Butterworth filter should take at this point can then be determined with regard to the requirements of the particular clinical investigation to be performed. The filter matching procedure can be extended to two dimensions in a practical manner by operating on the projection data after it has been filtered in the y direction. The efficacy of several methods to correct for the effects of scatter, attenuation and camera non-uniformity are also investigated. Having developed the optimised methodology for the acquisition and reconstruction of the SPECT data the results which are obtained are applied in the investigation of some specific clinical problems. The assessment of intractable epilepsy using 99mTc-HMPAO is performed followed by the investigation of ischaemic heart disease using 99mTc-MIBI and finally, the diagnosis of avascular necrosis of the femoral head using 99mTc-MDP is studied. The SPECT studies described in this thesis make a significant contribution to patient management

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging

The clinical impact of multidetector SPET technology

Introduction: Single photon emission tomography (SPET) is an established technique in Nuclear Medicine. Recent advances in SPET technology have now permitted the development of multidetector gamma cameras. This thesis evaluates some of these new gamma cameras and their impact on clinical practice. Aim: (a) To assess four new multidetector SPET gamma cameras (IGE Neurocam, Toshiba GCA-9300A, IGE Optima and Sopha DST). (b) To establish appropriate acquisition and analytical clinical protocols. Methodology: For each instrument, the tomographic spatial resolution, contrast and sensitivity were measured. The capability of a new slant hole collimator (IGE Optima) to perform radionuclide ventriculography (RNV) was assessed. To evaluate the utility of these systems, a total of 1215 patient studies were performed (1007 cardiac, 85 skeletal, 73 renal and 50 brain studies). The effect of 8, 16 and 32 minutes data acquisition on image quality and clinical relevance was evaluated. In addition, a new cardiac SPET protocol for rest/stress myocardial perfusion scintigraphy (thallium-201/Tc-99m tetrofosmin) was tested. Results: Tomographic spatial resolution of the order of 10 mm FWHM was achieved by all four systems. System sensitivity was related to the number of detectors and ranged between 9.2–11.2 Kcps/(MBq/ml)/cm per detector. The slant hole collimator with cephalic tilt gave highly reproducible results (r=0.98,SEE=+2) for ejection fraction measurements in 75 patients. There was no significant difference in the clinical information obtained using 8 min, 16 min and 32 min acquisitions. Based on patient studies and experience with these multidetector SPET systems, optimum acquisition and analysis protocols for commonly performed SPET studies were documented for routine clinical use. Artefacts due to patient movement during Tl-201 myocardial SPET studies were less frequent on a dual-detector system compared with a single detector system (0.7% and 4% respectively); while artefacts due to poor positioning or shift in centre of rotation were more. The rest/stress thallium-201/Tc-99m tetrofosmin study protocol (acquisition and analysis) was completed in 90 min. This protocol gave a sensitivity of 80% and specificity of 70% for the detection of coronary artery disease. Conclusion: For the first time a comprehensive comparison of multidetector SPET systems has been documented. Optimum acquisition and analysis protocols have been identified. The study also shows that the new generation of multidetector SPET systems offer adequate resolution and sensitivity for routine clinical imaging. Increased sensitivity can be translated into an increased patient throughput. This can increase the cost-effectiveness of this new technology

The Estimation and Correction of Rigid Motion in Helical Computed Tomography

X-ray CT is a tomographic imaging tool used in medicine and industry. Although technological developments have significantly improved the performance of CT systems, the accuracy of images produced by state-of-the-art scanners is still often limited by artefacts due to object motion. To tackle this problem, a number of motion estimation and compensation methods have been proposed. However, no methods with the demonstrated ability to correct for rigid motion in helical CT scans appear to exist. The primary aims of this thesis were to develop and evaluate effective methods for the estimation and correction of arbitrary six degree-of-freedom rigid motion in helical CT. As a first step, a method was developed to accurately estimate object motion during CT scanning with an optical tracking system, which provided sub-millimetre positional accuracy. Subsequently a motion correction method, which is analogous to a method previously developed for SPECT, was adapted to CT. The principle is to restore projection consistency by modifying the source-detector orbit in response to the measured object motion and reconstruct from the modified orbit with an iterative reconstruction algorithm. The feasibility of this method was demonstrated with a rapidly moving brain phantom, and the efficacy of correcting for a range of human head motions acquired from healthy volunteers was evaluated in simulations. The methods developed were found to provide accurate and artefact-free motion corrected images with most types of head motion likely to be encountered in clinical CT imaging, provided that the motion was accurately known. The method was also applied to CT data acquired on a hybrid PET/CT scanner demonstrating its versatility. Its clinical value may be significant by reducing the need for repeat scans (and repeat radiation doses), anesthesia and sedation in patient groups prone to motion, including young children

Diagnostic value of nuclear cardiology in coronary artery disease

This thesis investigates the diagnostic value of cardiac positron emission tomography when compared to single photon emission computed tomography for detection of coronary artery disease. This prospective study involves comparison of myocardial perfusion single photon emission computed tomography with coronary calcium scores; optimization of nuclear cardiac protocols in cardiac phantom experiments; and determination of diagnostic performance of cardiac positron emission tomography in the evaluation of myocardial viability in patients with significant coronary disease

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

Flow pattern analysis for magnetic resonance velocity imaging

Blood flow in the heart is highly complex. Although blood flow patterns have been investigated by both computational modelling and invasive/non-invasive imaging techniques, their evolution and intrinsic connection with cardiovascular disease has yet to be explored. Magnetic resonance (MR) velocity imaging provides a comprehensive distribution of multi-directional in vivo flow distribution so that detailed quantitative analysis of flow patterns is now possible. However, direct visualisation or quantification of vector fields is of little clinical use, especially for inter-subject or serial comparison of changes in flow patterns due to the progression of the disease or in response to therapeutic measures. In order to achieve a comprehensive and integrated description of flow in health and disease, it is necessary to characterise and model both normal and abnormal flows and their effects. To accommodate the diversity of flow patterns in relation to morphological and functional changes, we have described in this thesis an approach of detecting salient topological features prior to analytical assessment of dynamical indices of the flow patterns. To improve the accuracy of quantitative analysis of the evolution of topological flow features, it is essential to restore the original flow fields so that critical points associated with salient flow features can be more reliably detected. We propose a novel framework for the restoration, abstraction, extraction and tracking of flow features such that their dynamic indices can be accurately tracked and quantified. The restoration method is formulated as a constrained optimisation problem to remove the effects of noise and to improve the consistency of the MR velocity data. A computational scheme is derived from the First Order Lagrangian Method for solving the optimisation problem. After restoration, flow abstraction is applied to partition the entire flow field into clusters, each of which is represented by a local linear expansion of its velocity components. This process not only greatly reduces the amount of data required to encode the velocity distribution but also permits an analytical representation of the flow field from which critical points associated with salient flow features can be accurately extracted. After the critical points are extracted, phase portrait theory can be applied to separate them into attracting/repelling focuses, attracting/repelling nodes, planar vortex, or saddle. In this thesis, we have focused on vortical flow features formed in diastole. To track the movement of the vortices within a cardiac cycle, a tracking algorithm based on relaxation labelling is employed. The constraints and parameters used in the tracking algorithm are designed using the characteristics of the vortices. The proposed framework is validated with both simulated and in vivo data acquired from patients with sequential MR examination following myocardial infarction. The main contribution of the thesis is in the new vector field restoration and flow feature abstraction method proposed. They allow the accurate tracking and quantification of dynamic indices associated with salient features so that inter- and intra-subject comparisons can be more easily made. This provides further insight into the evolution of blood flow patterns and permits the establishment of links between blood flow patterns and localised genesis and progression of cardiovascular disease.Open acces

Pharmacokinetic Analysis of Gd-DTPA Enhancement in dynamic three-dimensional MRI of breast lesions

The purpose of this study was to demonstrate that dynamic MRI covering both breasts can provide sensitivity for tumor detection as well as specificity and sensitivity for differentiation of tumor malignancy. Three-dimensional gradient echo scans were used covering both breasts. Before Gd-DTPA bolus injection, two scans were obtained with different flip angles, and after injection, a dynamic series followed. Thirty-two patients were scanned according to this protocol. From these scans, in addition to enhancement, the value of T1 before injection was obtained. This was used to estimate the concentration of Gd-DTPA as well as the pharmacokinetic parameters governing its time course. Signal enhancement in three-dimensional dynamic scanning was shown to be a sensitive basis for detection of tumors. In our series, all but two mam-mographically suspicious lesions did enhance, and in three cases, additional enhancing lesions were found, two of which were in the contralateral breast. The parameter most suited for classification of breast lesions into benign or malignant was shown to be the pharmacokinetically defined permeability k31, which, for that test, gave a sensitivity of 92% and a specificity of 70%. Our three-dimensional dynamic MRI data are sensitive for detection of mammographically occult breast tumors and specific for classification of these as benign or malignant

Localising epileptiform activity and eloquent cortex using magnetoencephalography

In patients with drug resistant epilepsy, the surgical resection of epileptogenic cortex allows the possibility for seizure freedom, provided that epileptogenic and eloquent brain tissue can be accurately identified prior to surgery. This is often achieved using various techniques including neuroimaging, electroencephalographic (EEG), neuropsychological and invasive measurements. Over the last 20 years, magnetoencephalography (MEG) has emerged as a non-invasive tool that can provide important clinical information to patients with suspected neocortical epilepsy being considered for surgery. The standard clinical MEG analyses to localise abnormalities are not always successful and therefore the development and evaluation of alternative methods are warranted. There is also a continuous need to develop MEG techniques to delineate eloquent cortex. Based on this rationale, this thesis is concerned with the presurgical evaluation of drug resistant epilepsy patients using MEG and consists of two themes: the first theme focuses on the refinement of techniques to functionally map the brain and the second focuses on evaluating alternative techniques to localise epileptiform activity. The first theme involved the development of an alternative beamformer pipeline to analyse Elekta Neuromag data and was subsequently applied to data acquired using a pre-existing and a novel language task. The findings of the second theme demonstrated how beamformer based measures can objectively localise epileptiform abnormalities. A novel measure, rank vector entropy, was introduced to facilitate the detection of multiple types of abnormal signals (e.g. spikes, slow waves, low amplitude transients). This thesis demonstrates the clinical capacity of MEG and its role in the presurgical evaluation of drug resistant epilepsy patients