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

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

Fast Objective Coupled Planar Illumination Microscopy

Among optical imaging techniques light sheet fluorescence microscopy stands out as one of the most attractive for capturing high-speed biological dynamics unfolding in three dimensions. The technique is potentially millions of times faster than point-scanning techniques such as two-photon microscopy. This potential is especially poignant for neuroscience applications due to the fact that interactions between neurons transpire over mere milliseconds within tissue volumes spanning hundreds of cubic microns. However current-generation light sheet microscopes are limited by volume scanning rate and/or camera frame rate. We begin by reviewing the optical principles underlying light sheet fluorescence microscopy and the origin of these rate bottlenecks. We present an analysis leading us to the conclusion that Objective Coupled Planar Illumination (OCPI) microscopy is a particularly promising technique for recording the activity of large populations of neurons at high sampling rate. We then present speed-optimized OCPI microscopy, the first fast light sheet technique to avoid compromising image quality or photon efficiency. We enact two strategies to develop the fast OCPI microscope. First, we devise a set of optimizations that increase the rate of the volume scanning system to 40 Hz for volumes up to 700 microns thick. Second, we introduce Multi-Camera Image Sharing (MCIS), a technique to scale imaging rate by incorporating additional cameras. MCIS can be applied not only to OCPI but to any widefield imaging technique, circumventing the limitations imposed by the camera. Detailed design drawings are included to aid in dissemination to other research groups. We also demonstrate fast calcium imaging of the larval zebrafish brain and find a heartbeat-induced motion artifact. We recommend a new preprocessing step to remove the artifact through filtering. This step requires a minimal sampling rate of 15 Hz, and we expect it to become a standard procedure in zebrafish imaging pipelines. In the last chapter we describe essential computational considerations for controlling a fast OCPI microscope and processing the data that it generates. We introduce a new image processing pipeline developed to maximize computational efficiency when analyzing these multi-terabyte datasets, including a novel calcium imaging deconvolution algorithm. Finally we provide a demonstration of how combined innovations in microscope hardware and software enable inference of predictive relationships between neurons, a promising complement to more conventional correlation-based analyses

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

Validation of first pass magnetic resonance myocardial perfusion imaging using fractional flow reserve

Background - Magnetic Resonance Myocardial Perfusion Imaging (MRMPI) has been used for the detection of reversible myocardial ischaemia in humans since the early 1990’s. This non-invasive method of diagnosing reversible myocardial ischaemia has a number of advantages over the other more commonly used non-invasive tests such as ETT, stress echocardiography and radionuclide single photon emission computerised tomography (SPECT). There is no need to perform physical exercise, no image orientation constraints, excellent spatial and temporal resolution, no photon scatter or attenuation artefacts and no exposure to ionising radiation. The use of MRMPI for the detection of reversible myocardial ischaemia has been extensively investigated in the past using other non-invasive tests as the gold standard namely PET and SPECT. Invasive comparisons have been made with visual coronary angiography and quantitative coronary angiography (QCA). This previous work has been summarised in a meta-analysis which estimated the sensitivity and specificity to be 84% and 85% respectively. The majority of previous studies have used QCA or visual estimation of stenosis severity to determine the diameter of stenosis (DS). This however has been shown to correlate poorly with the functional significance of disease within a coronary artery. Prior to the commencement of this study no comparison had been made with the invasive gold standard of FFR. This is measured using a coronary pressure wire at the time of coronary angiography and is regarded by many cardiologists to be the current invasive gold standard for determining if coronary artery disease (CAD) is physiologically significant. We therefore undertook the present study to determine the true accuracy of MRMPI for the diagnosis of physiologically significant CAD. We also assessed the ability of MRMPI to detect isolated microcirculatory disease as determined by thermodilution derived CFR. Our other aims included an analysis of troponin release following PCI and its relation to QCA, pressure wire data and the occurrence of new late gadolinium enhancement (LGE). New LGE post CABG was also quantified and compared with that encountered post-PCI. Methods - One hundred and three patients with chest pain were referred for coronary angiography and underwent MRMPI in the week prior to the angiogram. This was performed on a Siemens Sonata 1.5Tesla scanner (Erlangen, Germany). Scanning commenced with localisers and cine long and short axis scans (TrueFISP sequence) to provide left ventricular mass, volume and ejection fraction data. This was followed by perfusion imaging of 3 short axis slices using a turboFLASH sequence (TI 90ms, TE 0.99ms, TR 173ms, Flip Angle 8 degrees, Matrix 80 x 128). Thereafter long and short axis slices were acquired for the detection of LGE (turboFLASH). Maximal hyperaemia was achieved using intravenous adenosine (140µg/kg/min). The first pass bolus contained 0.1mmol/kg of gadolinium (Omniscan, Amersham Health, Oslo, Norway) power injected at 5ml/sec (Medrad, Pittsburgh, PA) followed by a 20ml saline bolus. Twenty minutes after the initial bolus of gadolinium a further bolus was administered to obtain rest perfusion images. During coronary angiography the FFR was recorded in all patent major epicardial coronary arteries using a coronary pressure wire (RADI Medical Systems Ltd, Uppsala, Sweden) with hyperaemia induced using intravenous adenosine as above. An FFR value of <0.75 was taken as the cut off for the diagnosis of significant CAD. CFR measurements were obtained at rest and during maximal hyperaemia by means of thermodilution using 3ml boluses of saline. Following coronary angiography those patients who underwent PCI returned for a repeat MRMPI scan at 24 hours and 4 weeks and CABG patients returned for a 4 week scan. PCI patients had a troponin I measurement performed at approximately 24 hours, just prior to their repeat MRMPI. Qualitative MRMPI analysis, left ventricular mass, volume and ejection fraction analysis and QCA were all performed by two blinded independent experienced observers. Results - Of the 103 enrolled patients, two were excluded from the final analysis. Seventy-six (74%) were male with a mean age of 60 years (SD = 9). 25 (24.8%) of 101 scans were normal, 40 (39.6%) had single-vessel disease, 26 (25.7%) had two-vessel disease and 10 (9.9%) had triple-vessel disease. 121 perfusion defects were reported in 300 coronary territories (3 patients had complete data for only 2 coronary territories) of which 110 had an FFR0.8 and a CFR<2.0 indicative of isolated microcirculatory disease with no physiologically significant epicardial disease. No coronary territories were found to have a perfusion defect on MRMPI suggesting that by visual analysis MRMPI is unable to detect isolated microvascular disease. The median post PCI troponin level was 0.57µg/L (SD=2, Range undetected - 13.1). The only parameters found to correlate with troponin I levels post-PCI were increasing lesion length (r=0.6, p<0.0001) and increasing total stent length (r=0.37, p=0.02). We compared the increase in mass of LGE between the post-PCI scans and the pre-PCI scan and compared this with the troponin measurement. No significant correlation was found to exist between these parameters at 24 hours (r=0.25, p=0.07) or at 4 weeks (r=-0.19, p=0.2). The change in mass of LGE was calculated for the PCI and CABG patients. The mean difference in the PCI group was -0.12g (Median=0, SD=0.8, Interquartile Range 0 – 0) and for the CABG group was 1.08g (Median=0.11, SD=2.3, Interquartile Range -0.11 – 1.38). There is a trend towards the development of more LGE following CABG than PCI however the difference between groups did not reach statistical significance (p=0.07). Conclusion - MRMPI can accurately detect significant CHD with excellent results using FFR as the gold standard. Interobserver agreement is also very good even when examining individual coronary artery territories. Qualitative analysis of MRMPI is unable to detect isolated microcirculatory disease as defined by an FFR>0.8 and a CFR<2.0. Small troponin releases are common post-PCI and are related to the length of the lesion being treated and the length of stent deployed to treat the lesion. These small troponin releases do not accurately correlate with the occurrence of new LGE. CABG did result in a trend towards more new LGE compared to PCI

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

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

On the importance of cellular composition in human brain transcriptomics

The human brain consists of billions of cells, classifiable into hundreds of distinct cell-types and -subtypes. However, as studying cells or cell-types in isolation has proven challenging, most functional genomic assays are performed at the bulk level, i.e., pool signal across a heterogenous mass of cells. Such bulk assays provide an aggregated measure: that of the signal within the bulk’s constituent cell-types, weighted by their relative abundances. In this thesis, I explore the role cellular composition plays in brain transcriptome studies, and argue that its quantification and control is critical for correctly interpreting results. I begin by evaluating in silico methods for estimating cellular composition from bulk RNA-seq output. Using a diverse range of samples with known composition, I show that accurate estimation is achieved by combining partial deconvolution algorithms with biologically-relevant signatures, and confirm these findings in real transcriptome data using the goodness-of-fit metric. Having established that composition can be estimated in brain transcriptomes, I next demonstrate the importance of doing so. Through simulation, I show that small composition differences across samples (~5%) can lead to hundreds of false positives in differential expression, but modelling composition as a covariate is sufficient to control it. I apply these findings to a recent bulk brain resource of Autism vs. Control RNA-seq, and propose that the majority of reported differentially-expressed genes are driven by composition rather than dysregulation. To extend up these findings, I use data from recent experimental methods to explore brain cell-type-specific gene expression. I characterise 9 adult human brain samples at the single-nucleus level, exploring the diversity in cell-types and their perturbation in autism. Rich time-course data spanning the prenatal period to adulthood are also evaluated to explore how dynamic, cell-type-specific regulation across development associates with autism and other brain traits. The work in this thesis thus represents a critical re-evaluation of past brain transcriptome data, whilst also looking forward towards new analytical approaches and experimental methods

Quantitative Cardiac Magnetic Resonance Imaging Biomarkers for the Characterisation of Ischaemic Cardiomyopathy

Our understanding of the processes that determine outcomes in patients with ischaemic cardiomyopathy is based on conventional physiological concepts such as ischaemia and viability. Qualitative methods for characterising these processes tend to be binary and often fail to capture the complexity of the underlying biology. Importantly, these are perhaps inadequate to evaluate treatment effects, including the impact of coronary revascularisation. The aim of this thesis was to deploy novel quantitative cardiac magnetic resonance (CMR) techniques to evaluate and distinguish between the pathophysiological processes that determine outcomes in patients with ischaemic cardiomyopathy, through integration of anatomical, functional, perfusion and tissue characterisation information. The work is centred around the use of coronary artery bypass graft (CABG) surgery as the method for revascularisation, and focuses on the impact of myocardial blood flow alterations on cardiac physiology and clinical outcomes. In this work, I first evaluate the impact of surgical revascularisation on myocardial structure and function in patients with impaired left ventricular (LV) systolic function, using paired assessments before and after CABG. I found that at 6 months following revascularisation, despite improvement in functional capacity, more than a third of total myocardial segments examined are no longer considered revascularised. As a result, the overall augmentation in global myocardial blood flow (MBF) following CABG surgery is significantly blunted. There are however technical concerns regarding the quantitative estimation of myocardial blood flow in patients with coronary artery grafts, particularly in relation to the impact of long coronary grafts on contrast kinetics. I therefore evaluated the impact of arterial contrast delay on myocardial blood flow estimation in patients with left internal mammary artery (LIMA) grafts. I showed that absolute MBF estimation is minimally affected by delayed contrast arrival in patients with LIMA grafts, and that irrespective of graft patency, residual native disease severity is a key determinant of myocardial blood flow. Following these findings, I then assessed the prognostic impact of myocardial blood flow in a large cohort of patients with prior CABG. The only imaging study to date examining the prognostic role of quantitative perfusion indices in this population, it demonstrated that both stress MBF and myocardial perfusion reserve (MPR) independently predict adverse cardiovascular outcomes and all cause-mortality. Finally, using the existing quantitative perfusion technique and its associated framework, I co-developed and implemented a non-invasive, in-line method of measuring pulmonary transit time (PTT) and pulmonary blood volume (PBV) during routine CMR scanning. I then found that both imaging parameters can be used as independent quantitative prognostic biomarkers in patients with known or suspected coronary artery disease