High-throughput transgenic mouse phenotyping using microscopic-MRI

With the completion of the human genome sequence in 2003, efforts have shifted towards elucidating gene function. Such phenotypic investigations are aided by advances in techniques for genetic modification of mice, with whom we share ~99% of genes. Mice are key models for both examination of basic gene function and translational study of human conditions. Furthering these efforts, ambitious programmes are underway to produce knockout mice for the ~25,000 mouse genes. In the coming years, methods to rapidly phenotype mouse morphology will be in great demand. This thesis demonstrates the development of non-invasive microscopic magnetic resonance imaging (\muMRI) methods for high-resolution ex-vivo phenotyping of mouse embryo and mouse brain morphology. It then goes on to show the application of computational atlasing techniques to these datasets, enabling automated analysis of phenotype. First, the issue of image quality in high-throughput embryo MRI was addressed. After investigating preparation and imaging parameters, substantial gains in signal- and contrast-to-noise were achieved. This protocol was applied to a study of Chd7+/- mice (a model of CHARGE syndrome), identifying cardiac defects. Combining this protocol with automated segmentation-propagation techniques, phenotypic differences were shown between three groups of mice in a volumetric analysis involving a number of organ systems. Focussing on the mouse brain, the optimal preparation and imaging parameters to maximise image quality and structural contrast were investigated, producing a high-resolution in-skull imaging protocol. Enhanced delineation of hippocampal and cerebellar structures was observed, correlating well to detailed histological comparisons. Subsequently this protocol was applied to a phenotypic investigation of the Tc1 model of Down syndrome. Using both visual inspection and automated, tensor based morphometry, novel phenotypic findings were identified in brain and inner ear structures. It is hoped that a combination of \muMRI with computational analysis techniques, as presented in this work, may help ease the burden of current phenotyping efforts

Development and application of a human cortical brain atlas on MRI considering phylogeny = Développement et emploi d’un atlas du cortex cérébral humain réalisé sur IRM et tenant compte de la phylogénie

Le cortex cérébral est une structure en couches complexe qui remplit différents types de fonctions. Au cours de l’histoire des neurosciences, plusieurs atlas corticaux ont été développés pour classifier différentes régions du cortex en tant que zones aux caractéristiques structurelles ou fonctionnelles communes, afin d'étudier et de quantifier les changements aux états sain et pathologique. Cependant, il n'existe pas d'atlas suivant une approche phylogénétique, c'est-à-dire, basée sur les critères d'évolution communs. Ce mémoire présente les étapes de création d'un nouvel atlas dans un modèle d’imagerie par résonance magnétique (IRM) en espace standard (pseudo-Talairach) : le PAN-Atlas, basé sur l'origine phylogénétique commune de chaque zone corticale, et son application sur des scans d’IRM de dix individus pour évaluer sa performance. D’abord, nous avons regroupé les différentes régions corticales en cinq régions d'intérêt (RdI) d'origine phylogénétique connue (archicortex, paléocortex, périarchicortex, proïsocortex, isocortex ou néocortex) sur la base de protocoles de segmentation validés histologiquement par d'autres groupes de chercheurs. Puis, nous avons segmenté ces régions manuellement sur le modèle d’IRM cérébrale moyen MNI-ICBM 2009c, en formant des masques. Par la suite, on a utilisé un pipeline multi-étapes de traitement des images pour réaliser le recalage des masques de notre atlas aux scans pondérés T1 de dix participants sains, en obtenant ainsi des masques automatiques pour chaque RdI. Les masques automatiques ont été évalués après une correction manuelle par le biais de l’indice Dice-kappa, qui quantifie la colocalisation des voxels de chaque masque automatique vs. le masque corrigé manuellement. L’indice a montré une très bonne à excellente performance de notre atlas. Cela a permis l’évaluation et comparaison des volumes corticales de chaque région et la quantification des valeurs de transfert de magnétisation (ITM), qui sont sensibles à la quantité de myéline présente dans le tissu. Ce travail montre que la division régionale du cortex en IRM avec une approche phylogénétique est réalisable à l'aide de notre PAN-Atlas en espace standard et que les masques peuvent être utilisés pour différents types de quantifications, comme les volumes corticaux, ou l’estimation des valeurs de ITM. Notre atlas pourrait éventuellement servir à évaluer les différences entre personnes saines et celles atteintes par des maladies neurodégénératives ou d’autres maladies neurologiques.The cerebral cortex is a complex layered structure that performs different types of functions. Throughout the history of neuroscience, several cortical atlases have been developed to classify/divide different regions of the cortex into areas with common structural or functional characteristics, to then study and quantify changes in healthy and pathological states. However, to date, there is no atlas following a phylogenetic approach, i.e. based on the common evolution criteria. This thesis presents the steps of creation of a new atlas corresponding to a standard MRI template: the PAN-Atlas, based on the common phylogenetic origin of each cortical zone, and its application on MRI scans of ten healthy participants to assess its performance. First, we grouped the different cortical regions into five regions of interest (ROI) of known phylogenetic origin (archicortex, paleocortex, periarchicortex, proisocortex, isocortex or neocortex) based on MRI protocols previously validated through histology by other groups of researchers. Then, we manually segmented these ROIs on the MNI-ICBM 2009c average brain MRI template, creating corresponding masks. We then used a multi-step image processing pipeline to register the atlas’ masks to T1 weighted images of ten healthy participants, generating automatic masks for each scan. The accuracy of these automatic atlas’ masks was assessed after manual correction using Dice-kappa similarity index, to quantify the colocalization of the automatic vs. the manually corrected masks. The Dice-kappa values showed a very good to excellent performance of the automatic atlas’ masks. This allowed the evaluation and comparison of cortical volumes of each ROI, as well as the quantification of magnetization transfer ratio (MTR) values, which are sensitive to myelin content. This work shows that the division of the cortex on MRI following a phylogenetic approach is feasible using our PAN Atlas, and that the masks of the atlas can be used to perform different types of quantifications, such as the ones presented here (cortical volume and MTR per ROI). Our atlas could similarly be used to assess differences between the cortex of healthy individuals and people affected by neurodegenerative diseases and other neurological disorders

Anthropometric and genetic determinants of cardiac morphology and function

Background Cardiac structure and function result from complex interactions between genetic and environmental factors. Population-based studies have relied on 2-dimensional cardiovascular magnetic resonance as the gold-standard for phenotyping. However, this technique provides limited global metrics and is insensitive to regional or asymmetric changes in left ventricular (LV) morphology. High-resolution 3-dimensional cardiac magnetic resonance (3D-CMR) with computational quantitative phenotyping, might improve on traditional CMR by enabling the creation of detailed 3D statistical models of the variation in cardiac phenotypes for use in studies of genetic and/or environmental effects on cardiac form or function. Purpose To determine whether 3D-CMR is applicable at scale, and provides methodological and statistical advantages over conventional imaging for large-scale population studies and to apply 3D-CMR to anthropometric and genetic studies of the heart. Methods 1530 volunteers (54.8% females, 74.7% Caucasian, mean age 41.3±13.0 years) without self-reported cardiovascular disease were recruited prospectively to the Digital Heart Project. Using a cardiac atlas-based software, these images were computationally processed and quantitatively analysed. Parameters such as myocardial shape, curvature, wall thickness, relative wall thickness, end-systolic wall stress, fractional wall thickening and ventricular volumes were extracted at over 46,000 points in the model. The relationships between these parameters and systolic blood pressure (SBP), fat mass, lean mass and genetic variationswere analysed using 3D regression models adjusted for body surface area, gender, race, age and multiple testing. Targeted resequencing of titin (TTN), the largest human gene and the commonest genetic cause of dilated cardiomyopathy, was performed in 928 subjects while common variants (~700.000) were genotyped in 1346 subjects. Results Automatically segmented 3D images were more accurate than 2D images at defining cardiac surfaces, resulting in fewer subjects being required to detect a statistically significant 1 mm difference in wall thickness. 3D-CMR enabled the detection of a strong and distinct regionality of the effects of SBP, body composition and genetic variation on the heart. It shows that the precursors of the hypertensive heart phenotype can be traced to healthy normotensives and that different ratios of body composition are associated with particular gender-specific patterns of cardiac remodelling. In 17 asymptomatic subjects with genetic variations associated with dilated cardiomyopathy, early stages of ventricular impairment and wall thinning were identified, which were not apparent by 2D imaging. Conclusions 3D-CMR combined with computational modelling provides high-resolution insight into the earliest stages of heart disease. These methods show promise for population-based studies of the anthropometric, environmental and genetic determinants of LV form and function in health and disease.Open Acces

Development and application of a human cortical brain atlas on MRI considering phylogeny = Développement et emploi d'un atlas du cortex cérébral humain réalisé sur IRM et tenant compte de la phylogénie

Le cortex cérébral est une structure en couches complexe qui remplit différents types de fonctions. Au cours de l’histoire des neurosciences, plusieurs atlas corticaux ont été développés pour classifier différentes régions du cortex en tant que zones aux caractéristiques structurelles ou fonctionnelles communes, afin d'étudier et de quantifier les changements aux états sain et pathologique. Cependant, il n'existe pas d'atlas suivant une approche phylogénétique, c'est-à-dire, basée sur les critères d'évolution communs. Ce mémoire présente les étapes de création d'un nouvel atlas dans un modèle d’imagerie par résonance magnétique (IRM) en espace standard (pseudo-Talairach) : le PAN-Atlas, basé sur l'origine phylogénétique commune de chaque zone corticale, et son application sur des scans d’IRM de dix individus pour évaluer sa performance. D’abord, nous avons regroupé les différentes régions corticales en cinq régions d'intérêt (RdI) d'origine phylogénétique connue (archicortex, paléocortex, périarchicortex, proïsocortex, isocortex ou néocortex) sur la base de protocoles de segmentation validés histologiquement par d'autres groupes de chercheurs. Puis, nous avons segmenté ces régions manuellement sur le modèle d’IRM cérébrale moyen MNI-ICBM 2009c, en formant des masques. Par la suite, on a utilisé un pipeline multi-étapes de traitement des images pour réaliser le recalage des masques de notre atlas aux scans pondérés T1 de dix participants sains, en obtenant ainsi des masques automatiques pour chaque RdI. Les masques automatiques ont été évalués après une correction manuelle par le biais de l’indice Dice-kappa, qui quantifie la colocalisation des voxels de chaque masque automatique vs. le masque corrigé manuellement. L’indice a montré une très bonne à excellente performance de notre atlas. Cela a permis l’évaluation et comparaison des volumes corticales de chaque région et la quantification des valeurs de transfert de magnétisation (ITM), qui sont sensibles à la quantité de myéline présente dans le tissu. Ce travail montre que la division régionale du cortex en IRM avec une approche phylogénétique est réalisable à l'aide de notre PAN-Atlas en espace standard et que les masques peuvent être utilisés pour différents types de quantifications, comme les volumes corticaux, ou l’estimation des valeurs de ITM. Notre atlas pourrait éventuellement servir à évaluer les différences entre personnes saines et celles atteintes par des maladies neurodégénératives ou d’autres maladies neurologiques.The cerebral cortex is a complex layered structure that performs different types of functions. Throughout the history of neuroscience, several cortical atlases have been developed to classify/divide different regions of the cortex into areas with common structural or functional characteristics, to then study and quantify changes in healthy and pathological states. However, to date, there is no atlas following a phylogenetic approach, i.e. based on the common evolution criteria. This thesis presents the steps of creation of a new atlas corresponding to a standard MRI template: the PAN-Atlas, based on the common phylogenetic origin of each cortical zone, and its application on MRI scans of ten healthy participants to assess its performance. First, we grouped the different cortical regions into five regions of interest (ROI) of known phylogenetic origin (archicortex, paleocortex, periarchicortex, proisocortex, isocortex or neocortex) based on MRI protocols previously validated through histology by other groups of researchers. Then, we manually segmented these ROIs on the MNI-ICBM 2009c average brain MRI template, creating corresponding masks. We then used a multi-step image processing pipeline to register the atlas’ masks to T1 weighted images of ten healthy participants, generating automatic masks for each scan. The accuracy of these automatic atlas’ masks was assessed after manual correction using Dice-kappa similarity index, to quantify the colocalization of the automatic vs. the manually corrected masks. The Dice-kappa values showed a very good to excellent performance of the automatic atlas’ masks. This allowed the evaluation and comparison of cortical volumes of each ROI, as well as the quantification of magnetization transfer ratio (MTR) values, which are sensitive to myelin content. This work shows that the division of the cortex on MRI following a phylogenetic approach is feasible using our PAN Atlas, and that the masks of the atlas can be used to perform different types of quantifications, such as the ones presented here (cortical volume and MTR per ROI). Our atlas could similarly be used to assess differences between the cortex of healthy individuals and people affected by neurodegenerative diseases and other neurological disorders

Automated deep phenotyping of the cardiovascular system using magnetic resonance imaging

Across a lifetime, the cardiovascular system must adapt to a great range of demands from the body. The individual changes in the cardiovascular system that occur in response to loading conditions are influenced by genetic susceptibility, and the pattern and extent of these changes have prognostic value. Brachial blood pressure (BP) and left ventricular ejection fraction (LVEF) are important biomarkers that capture this response, and their measurements are made at high resolution. Relatively, clinical analysis is crude, and may result in lost information and the introduction of noise. Digital information storage enables efficient extraction of information from a dataset, and this strategy may provide more precise and deeper measures to breakdown current phenotypes into their component parts. The aim of this thesis was to develop automated analysis of cardiovascular magnetic resonance (CMR) imaging for more detailed phenotyping, and apply these techniques for new biological insights into the cardiovascular response to different loading conditions. I therefore tested the feasibility and clinical utility of computational approaches for image and waveform analysis, recruiting and acquiring additional patient cohorts where necessary, and then applied these approaches prospectively to participants before and after six-months of exercise training for a first-time marathon. First, a multi-centre, multi-vendor, multi-field strength, multi-disease CMR resource of 110 patients undergoing repeat imaging in a short time-frame was assembled. The resource was used to assess whether automated analysis of LV structure and function is feasible on real-world data, and if it can improve upon human precision. This showed that clinicians can be confident in detecting a 9% change in EF or a 20g change in LV mass. This will be difficult to improve by clinicians because the greatest source of human error was attributable to the observer rather than modifiable factors. Having understood these errors, a convolutional neural network was trained on separate multi-centre data for automated analysis and was successfully generalizable to the real-world CMR data. Precision was similar to human analysis, and performance was 186 times faster. This real-world benchmarking resource has been made freely available (thevolumesresource.com). Precise automated segmentations were then used as a platform to delve further into the LV phenotype. Global LVEFs measured from CMR imaging in 116 patients with severe aortic stenosis were broken down into ~10 million regional measurements of structure and function, represented by computational three-dimensional LV models for each individual. A cardiac atlas approach was used to compile, label, segment and represent these data. Models were compared with healthy matched controls, and co-registered with follow-up one year after aortic valve replacement (AVR). This showed that there is a tendency to asymmetric septal hypertrophy in all patients with severe aortic stenosis (AS), rather than a characteristic specific to predisposed patients. This response to AS was more unfavourable in males than females (associated with higher NT-proBNP, and lower blood pressure), but was more modifiable with AVR. This was not detected using conventional analysis. Because cardiac function is coupled with the vasculature, a novel integrated assessment of the cardiovascular system was developed. Wave intensity theory was used to combine central blood pressure and CMR aortic blood flow-velocity waveforms to represent the interaction of the heart with the vessels in terms of traveling energy waves. This was performed and then validated in 206 individuals (the largest cohort to date), demonstrating inefficient ventriculo-arterial coupling in female sex and healthy ageing. CMR imaging was performed in 236 individuals before training for a first-time marathon and 138 individuals were followed-up after marathon completion. After training, systolic/diastolic blood pressure reduced by 4/3mmHg, descending aortic stiffness decreased by 16%, and ventriculo-arterial coupling improved by 14%. LV mass increased slightly, with a tendency to more symmetrical hypertrophy. The reduction in aortic stiffness was equivalent to a 4-year reduction in estimated biological aortic age, and the benefit was greater in older, male, and slower individuals. In conclusion, this thesis demonstrates that automating analysis of clinical cardiovascular phenotypes is precise with significant time-saving. Complex data that is usually discarded can be used efficiently to identify new biology. Deeper phenotypes developed in this work inform risk reduction behaviour in healthy individuals, and demonstrably deliver a more sensitive marker of LV remodelling, potentially enhancing risk prediction in severe aortic stenosis

Basal forebrain cholinergic system volume is associated with general cognitive ability in the elderly

OBJECTIVE: At the present, it is unclear whether association of basal forebrain cholinergic system (BFCS) volume with cognitive performance exists in healthy as well as in cognitively impaired elderly subjects. Whereas one small study reported an association of BFCS volume with general cognitive ability 'g' in healthy ageing, effects on specific cognitive domains have only been found in subjects with cognitive decline. Here we aim to clarify whether an association of BFCS volume and 'g' is present in a larger sample of elderly subjects without obvious symptoms of dementia and whether similar associations can also be observed in specific cognitive domains. METHODS: 282 pre-surgical patients from the BioCog study (aged 72.7±4.9 years with a range of 65-87 years, 110 women) with a median MMSE score of 29 points (range 24-30) were investigated. BFCS and brain volume as well as brain parenchymal fraction were assessed in T1-weighted MR images using SPM12 and a probabilistic map of the BFCS. Neuropsychological assessment comprised the CANTAB cognitive battery and paper-and-pencil based tests. For data analysis, generalised linear models and quantile regression were applied. RESULTS: Significant associations of BFCS volume with 'g' and several cognitive domains were found, with the strongest association found for 'g'. BFCS volume explained less variance in cognitive performance than brain volume. The association was not confounded by brain parenchymal fraction. Furthermore, the association of BFCS volume and 'g' was similar in high- and low-performers. CONCLUSION: Our results extend previous study findings on BFCS volume associations with cognition in elderly subjects. Despite the observed associations of BFCS volume and cognitive performance, this association seems to reflect a more general association of brain volume and cognition. Accordingly, a specific association of BFCS volume and cognition in non-demented elderly subjects is questionable

Development of MRI Techniques for Experimental Models of Cardiovascular Disease

Cardiovascular diseases (CVDs) – including stroke and heart failure – are the leading cause of death worldwide. More people die from CVDs each year than any other cause. Magnetic resonance imaging (MRI) is a powerful technique which is now routinely used for imaging these diseases as it offers high-resolution anatomical detail, exquisite soft-tissue contrast and assessment of function such as tissue water content, oxygenation, metabolism, vascular blood flow and microvascular perfusion. This thesis focuses on the development of MRI techniques for use in pre-clinical animal models of cardiovascular diseases, with a focus on stroke and heart disease. Firstly, in chapter 3, the continued development of an in-house MRI sequence known as extravascular convectography (EVAC) for measuring the flow of interstitial fluid is described. A series of phantom experiments were conducted to assess the sensitivity of the sequence to slow flowing fluid. Next, an in vivo repeatability and reproducibility study was conducted before finally the technique was applied to a rat model of stroke. In chapter 4, a pair of studies was carried out using recently established, advanced cardiac imaging techniques. In the first study, CINE and late gadolinium-enhanced inversion recovery (LGE IR) imaging were used to assess cardiac structure and function in a Prox1-deficient genetic mouse model of dilated cardiomyopathy. In the second part of the chapter, a multi-parametric MRI study – incorporating CINE, LGE IR, arterial spin labeling and T2-mapping – was conducted in a mouse model of reperfused myocardial infarction to assess the extent of area-at-risk and compare with gold-standard histological staining. Finally, in chapter 5, the development of a retrospective high-temporal resolution (HTR) CINE MRI sequence for assessing cardiac diastolic function is described and compared with pulsed wave Doppler ultrasound, which is the currently-accepted standard for measuring diastolic function. The HTR-CINE sequence was established, validated and optimised in phantoms and naïve mouse hearts. Repeatability studies were then carried out to ensure the robustness of the technique before application to a mouse model of myocardial infarction. The overall aim of the research in this thesis is the development of MRI techniques for application to experimental models of cardiovascular disease

Imaging mouse models of neurodegeneration using multi-parametric MRI

Alzheimer’s disease (AD) is a devastating condition characterised by significant cognitive impairment and memory loss. Transgenic mouse models are increasingly being used to further our knowledge of the cause and progression of AD, and identify new targets for therapeutic intervention. These mice permit the study of specific pathological hallmarks of the disease, including intracellular deposits of hyperphosphorylated tau protein and extracellular amyloid plaques. In order to characterise these transgenic mice, robust biomarkers are required to evaluate neurodegenerative changes and facilitate preclinical evaluation of emerging therapeutics. In this work, a platform for in vivo structural imaging of the rTg4510 mouse model of tauopathy was developed and optimised. This was combined with a range of other clinically relevant magnetic resonance imaging (MRI) biomarkers including: arterial spin labelling, diffusion tensor imaging and chemical exchange saturation transfer. These techniques were applied in a single time-point study of aged rTg4510 mice, as well as a longitudinal study to serially assess neurodegeneration in the same cohort of animals. Doxycycline was administered to a subset of rTg4510 mice to suppress the tau transgene; this novel intervention strategy permitted the evaluation of the sensitivity of MRI biomarkers to the accumulation and suppression of tau. Follow-up ex vivo scans were acquired in order to assess the sensitivity of in vivo structural MRI to the current preclinical gold standard. High resolution structural MRI, when used in conjunction with advanced computational analysis, yielded high sensitivity to pathological changes occurring in the rTg4510 mouse. Atrophy was reduced in animals treated with doxycycline. All other MRI biomarkers were able to discriminate between doxycycline-treated and untreated rTg4510 mice as well as wildtype controls, and provided insight into complimentary pathological mechanisms occurring within the disease process. In addition, this imaging protocol was applied to the J20 mouse model of familial AD. This mouse exhibits widespread plaque formation, enabling the study of amyloid-specific pathological changes. Atrophy and deficits in cerebral blood flow were observed; however, the changes occurring in this model were markedly less than those observed in the rTg4510 mouse. This study was expanded to investigate the early-onset AD observed in individuals with Down’s syndrome (DS) by breeding the J20 mouse with the Tc1 mouse model of DS, permitting the relationship between genetics and neurodegeneration to be dissected. This thesis demonstrates the application of in vivo multi-parametric MRI to mouse models of neurodegeneration. All techniques were sensitive to pathological changes occurring in the models, and may serve as important biomarkers in clinical studies of AD. In addition, in vivo multi-parametric MRI permits longitudinal studies of the same animal cohort. This experimental design produces more powerful results, whilst contributing to worldwide efforts to reduce animal usage with respect to the 3Rs principles