Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

QUANTITATIVE NUCLEAR MEDICINE IMAGING USING ADVANCED IMAGE RECONSTRUCTION AND RADIOMICS

Our aim is to help put nuclear medicine at the forefront of quantitation on the path to the realization of personalized medicine. We propose and evaluate (Part I) advanced image reconstruction and (Part II) robust radiomics (large-scale data-oriented study of radiological images). The goal is to attain significantly improved diagnostic, prognostic and treatment-response assessment capabilities. Part I presents a new paradigm in point-spread function (PSF)-modeling, a partial volume correction method in PET imaging where resolution-degrading phenomena are modeled within the reconstruction framework. PSF-modeling improves resolution and enhances contrast, but significantly alters noise properties and induces edge-overshoots. Past efforts involve a dichotomy of PSF vs. no-PSF modeling; by contrast, we focus on a wide-spectrum of PSF models, including under- and over-estimation of the true PSF, for the potential of enhanced quantitation in standardized uptake values (SUVs). We show for the standard range of iterations employed in clinic (not excessive), edge enhancement due to overestimation actually lower SUV bias in small regions, while inter-voxel correlations suppress image roughness and enhance uniformity. An overestimated PSF yields improved contrast and limited edge-overshoot effects at lower iterations, enabling enhanced SUV quantitation. Overall, our framework provides an effective venue for quantitative task-based optimization. Part II proposes robust and reproducible radiomics methods. Radiomics workflows are complex, generating hundreds of features, which can lead to high variability and overfitting, and ultimately hampering performance. We developed and released a Standardized Environment for Radiomics Analysis (SERA) solution to enable robust radiomics analyses. We conduct studies on two unique imaging datasets – renal cell carcinoma SPECT and prostate cancer PET – identifying robust and reproducible radiomic features. In addition, we evaluate a novel hypothesis that radiomic features extracted from clinically normal (non-ischemic) myocardial perfusion SPECT (MPS) can predict coronary artery calcification (CAC; as extracted from CT). This has important implications, since CAC assessment is not commonly-performed nor reimbursed in wide community settings. SERA-derived radiomic features were utilized in a multi-step feature selection framework, followed by the application of machine learning to radiomic features. Our results show the potential to predict CAC from normal MPS, suggesting added usage and value for routine standard MPS

Towards standardisation in breathomics

Exhaled breath VOCs analysis is safe and non-invasive method of monitoring for human metabolic profiles and has the potential to become diagnostic tool in clinical practise. This thesis first describe in detail the different aspects of exhaled breath VOCs and its use as diagnostic tool in respiratory diseases. The current exhaled breath analysis work-flow including breath sampling, analysis and data processing is also described. A single exhaled breath sample can contain in excess of 500 different chemical species. There is a wide range of factors that can cause the variability to individual breath profiles. In order to detect small changes in breath profiles, a standardised and reproducible approach to exhaled breath analysis methodology is required. The long term storage of exhaled breath samples using multi-sorbent tubes is investigated, the optimum storage protocol and condition is discussed. A portable breath sampling system was also developed for remote sampling. The introduction of this new feature enables breath sampling to be carried out outside the designated laboratory with no location restriction. This feature combined with the easy to use and non-invasive original sampling unit designed for subjects with impaired lung function minimise participant stress level and discomfort. It also utilises the custom developed air supply filtration assembly to create a standardised purified breathable air that can minimise the method variability and improve standardisation to breath samples collected. This methodology is tested in an excise induced bronchoconstriction (EIB) study where two groups of participants: healthy and excise induced bronchoconstriction (EIB) positive undergo high intensity cardiopulmonary exercise testing (CPET). The data from two groups of participants is analysed and three markers which shown correlation with EIB positive participants are determined

Mapping Trabecular Bone Fabric Tensor by in Vivo Magnetic Resonance Imaging

The mechanical competence of bone depends upon its quantity, structural arrangement, and chemical composition. Assessment of these factors is important for the evaluation of bone integrity, particularly as the skeleton remodels according to external (e.g. mechanical loading) and internal (e.g. hormonal changes) stimuli. Micro magnetic resonance imaging (µMRI) has emerged as a non-invasive and non-ionizing method well-suited for the repeated measurements necessary for monitoring changes in bone integrity. However, in vivo image-based directional dependence of trabecular bone (TB) has not been linked to mechanical competence or fracture risk despite the existence of convincing ex vivo evidence. The objective of this dissertation research was to develop a means of capturing the directional dependence of TB by assessing a fabric tensor on the basis of in vivo µMRI. To accomplish this objective, a novel approach for calculating the TB fabric tensor based on the spatial autocorrelation function was developed and evaluated in the presence of common limitations to in vivo µMRI. Comparisons were made to the standard technique of mean-intercept-length (MIL). Relative to MIL, ACF was identified as computationally faster by over an order of magnitude and more robust within the range of the resolutions and SNRs achievable in vivo. The potential for improved sensitivity afforded by isotropic resolution was also investigated in an improved µMR imaging protocol at 3T. Measures of reproducibility and reliability indicate the potential of images with isotropic resolution to provide enhanced sensitivity to orientation-dependent measures of TB, however overall reproducibility suffered from the sacrifice in SNR. Finally, the image-derived TB fabric tensor was validated through its relationship with TB mechanical competence in specimen and in vivo µMR images. The inclusion of trabecular bone fabric measures significantly improved the bone volume fraction-based prediction of elastic constants calculated by micro-finite element analysis. This research established a method for detecting TB fabric tensor in vivo and identified the directional dependence of TB as an important determinant of TB mechanical competence

Quantification of atherosclerotic plaque in the elderly with positron emission tomography/computed tomography

L'athérosclérose est une maladie cardiovasculaire inflammatoire qui est devenue la première cause de morbidité et de mortalité dans les pays développés et parmi les principales causes d’invalidité au monde. Elle se caractérise par l’épaississement de la paroi vasculaire artérielle suite à l'accumulation de lipides et le dépôt d'autres substances au niveau de l’intima (endothélium) pour former la plaque d’athérome. Avec l'âge, cette plaque peut grossir, se calcifier et ainsi rétrécir le calibre de l'artère pour diminuer son débit et à un stade avancé de la maladie, elle peut se rompre et obstruer les petites artères dans n'importe quelle partie du corps causant des complications aigues, y compris la mort soudaine. L'objectif de cette thèse est de pouvoir détecter l'inflammation de la plaque athérosclérotique quantitativement avec la TEP/TDM dans le but de prévenir son détachement. Les mesures avec la TDM et la TEP avec le 18F-FDG ont été acquises chez des sujets humains âgés de 65 à 85 ans. Des analyses quantitatives ont été conduites sur les images de TDM en fonction de l'intensité et des étendues des calcifications, et sur les images de la TEP pour évaluer le métabolisme des plaques. L'effet des traitements par les statines a aussi été étudié. Au-delà la couverture de cette étude de façon détaillée au niveau physiologique en corrélant différents paramètres des plaques, et au niveau méthodologique en utilisant de nouvelles approches pour l'analyse pharmacocinétique, il en ressort principalement la suggestion de la détection de la vulnérabilité de la plaque artérielle par la TDM, plus disponible et moins coûteuse, en remplacement des analyses biochimiques, surtout la protéine C-réactive (CRP) considérée être la méthode standard.Abstract : Atherosclerosis is an inflammatory cardiovascular disease considered the leading cause of morbidity and mortality in developed countries and among the leading causes of disability worldwide. It is characterized by the thickening of the arterial vascular wall due to the accumulation of lipids and the deposition of other substances in the intima (endothelium) to form atheroma plaque. With age, this plaque can grow larger, calcify and thus narrow the size of the artery to decrease blood flow and at an advanced stage of the disease, it can rupture, be transported by blood and block the small arteries in any part of the body causing acute complications, including sudden death. The objective of this thesis was to be able to detect the inflammation of the atherosclerotic plaque quantitatively with PET/CT in order to prevent its detachment. Measurements with CT and PET with 18F-FDG were acquired in human subjects aged 65 to 85 years. Quantitative analyzes were performed on CT images based on the intensity and extent of calcifications, and on PET images to assess plaque metabolism. The effect of statin treatments has also been studied. Beyond the coverage of this study in a detailed manner at the physiological level by correlating different parameters of the plaques, and at the methodological level by using new approaches for pharmacokinetic analysis, it mainly emerges the suggestion for the detection of the vulnerability of the arterial plaque by CT alone, more available and less expensive, replacing biochemical analyzes, especially Creactive protein (CRP) considered to be the standard method

CaImAn an open source tool for scalable calcium imaging data analysis

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons

Analysis of first pass myocardial perfusion imaging with magnetic resonance

Early diagnosis and localisation of myocardial perfusion defects is an important step in the treatment of coronary artery disease. Thus far, coronary angiography is the conventional standard investigation for patients with known or suspected coronary artery disease and it provides information about the presence and location of coronary stenoses. In recent years, the development of myocardial perfusion CMR has extended the role of MR in the evaluation of ischaemic heart disease beyond the situations where there have already been gross myocardial changes such as acute infarction or scarring. The ability to non-invasively evaluate cardiac perfusion abnormalities before pathologic effects occur, or as follow-up to therapy, is important to the management of patients with coronary artery disease. Whilst limited multi-slice 2D CMR perfusion studies are gaining increased clinical usage for quantifying gross ischaemic burden, research is now directed towards complete 3D coverage of the myocardium for accurate localisation of the extent of possible defects. In 3D myocardial perfusion imaging, a complete volumetric data set has to be acquired for each cardiac cycle in order to study the first pass of the contrast bolus. This normally requires a relatively large acquisition window within each cardiac cycle to ensure a comprehensive coverage of the myocardium and reasonably high resolution of the images. With multi-slice imaging, long axis cardiac motion during this large acquisition window can cause the myocardium imaged in different cross- sections to be mis-registered, i.e., some part of the myocardium may be imaged more than twice whereas other parts may be missed out completely. This type of mis-registration is difficult to correct for by using post-processing techniques. The purpose of this thesis is to investigate techniques for tracking through plane motion during 3D myocardial perfusion imaging, and a novel technique for extracting intrinsic relationships between 3D cardiac deformation due to respiration and multiple ID real-time measurable surface intensity traces is developed. Despite the fact that these surface intensity traces can be strongly coupled with each other but poorly correlated with respiratory induced cardiac deformation, we demonstrate how they can be used to accurately predict cardiac motion through the extraction of latent variables of both the input and output of the model. The proposed method allows cross-modality reconstruction of patient specific models for dense motion field prediction, which after initial modelling can be use in real-time prospective motion tracking or correction. In CMR, new imaging sequences have significantly reduced the acquisition window whilst maintaining the desired spatial resolution. Further improvements in perfusion imaging will require the application of parallel imaging techniques or making full use of the information content of the ¿-space data. With this thesis, we have proposed RR-UNFOLD and RR-RIGR for significantly reducing the amount of data that is required to reconstruct the perfusion image series. The methods use prospective diaphragmatic navigator echoes to ensure UNFOLD and RIGR are carried out on a series of images that are spatially registered. An adaptive real-time re-binning algorithm is developed for the creation of static image sub-series related to different levels of respiratory motion. Issues concerning temporal smoothing of tracer kinetic signals and residual motion artefact are discussed, and we have provided a critical comparison of the relative merit and potential pitfalls of the two techniques. In addition to the technical and theoretical descriptions of the new methods developed, we have also provided in this thesis a detailed literature review of the current state-of-the-art in myocardial perfusion imaging and some of the key technical challenges involved. Issues concerning the basic background of myocardial ischaemia and its functional significance are discussed. Practical solutions to motion tracking during imaging, predictive motion modelling, tracer kinetic modelling, RR-UNFOLD and RR-RIGR are discussed, all with validation using patient and normal subject data to demonstrate both the strength and potential clinical value of the proposed techniques.Open acces

Quantitative PET-CT Perfusion Imaging of Prostate Cancer

Functional imaging of 18F-Fluorocholine PET holds promise in the detection of dominant prostatic lesions. Quantitative parameters from PET-CT Perfusion may be capable of measuring choline kinase activity, which could assist in identification of the dominant prostatic lesion for more accurate targeting of biopsies and radiation dose escalation. The objectives of this thesis are: 1) investigate the feasibility of using venous TACs in quantitative graphical analysis, and 2) develop and test a quantitative PET-CT Perfusion imaging technique that shows promise for identifying dominant prostatic lesions. Chapter 2 describes the effect of venous dispersion on distribution volume measurements with the Logan Plot. The dispersion of venous PET curves was simulated based on the arterio-venous transit time spectrum measured in a perfusion CT study of the human forearm. The analysis showed good agreement between distribution volume measurements produced by the arterial and venous TACs. Chapter 3 details the mathematical implementation of a linearized solution of the 3-Compartment kinetic model for hybrid PET-CT Perfusion imaging. A noise simulation determined the effect of incorporating CT perfusion parameters into the PET model on the accuracy and variability of measurements of the choline kinase activity. Results indicated that inclusion of CT perfusion parameters known a priori can significantly improve the accuracy and variability of imaging parameters measured with PET. Chapter 4 presents the implementation of PET-CT Perfusion imaging in a xenograft mouse model of human prostate cancer. Image-derived arterial TACs from the left ventricle were corrected for partial volume and spillover effects and validated by comparing to blood sampled curves. The PET-CT Perfusion imaging technique produced parametric maps of the choline kinase activity, k3. The results showed that the partial volume and spillover corrected arterial TACs agreed well with the blood sampled curves, and that k3max was significantly correlated with tumor volume, while SUV was not. In summary, this thesis establishes a solid foundation for future clinical research into 18F-fluorocholine PET imaging for the identification of dominant prostatic lesions. Quantitative PET-CT Perfusion imaging shows promise for assisting targeting of biopsy and radiation dose escalation of prostate cancer