Affine Transformation Edited and Refined Deep Neural Network for Quantitative Susceptibility Mapping

Deep neural networks have demonstrated great potential in solving dipole inversion for Quantitative Susceptibility Mapping (QSM). However, the performances of most existing deep learning methods drastically degrade with mismatched sequence parameters such as acquisition orientation and spatial resolution. We propose an end-to-end AFfine Transformation Edited and Refined (AFTER) deep neural network for QSM, which is robust against arbitrary acquisition orientation and spatial resolution up to 0.6 mm isotropic at the finest. The AFTER-QSM neural network starts with a forward affine transformation layer, followed by an Unet for dipole inversion, then an inverse affine transformation layer, followed by a Residual Dense Network (RDN) for QSM refinement. Simulation and in-vivo experiments demonstrated that the proposed AFTER-QSM network architecture had excellent generalizability. It can successfully reconstruct susceptibility maps from highly oblique and anisotropic scans, leading to the best image quality assessments in simulation tests and suppressed streaking artifacts and noise levels for in-vivo experiments compared with other methods. Furthermore, ablation studies showed that the RDN refinement network significantly reduced image blurring and susceptibility underestimation due to affine transformations. In addition, the AFTER-QSM network substantially shortened the reconstruction time from minutes using conventional methods to only a few seconds

Motion robust acquisition and reconstruction of quantitative T2* maps in the developing brain

The goal of the research presented in this thesis was to develop methods for quantitative T2* mapping of the developing brain. Brain maturation in the early period of life involves complex structural and physiological changes caused by synaptogenesis, myelination and growth of cells. Molecular structures and biological processes give rise to varying levels of T2* relaxation time, which is an inherent contrast mechanism in magnetic resonance imaging. The knowledge of T2* relaxation times in the brain can thus help with evaluation of pathology by establishing its normative values in the key areas of the brain. T2* relaxation values are a valuable biomarker for myelin microstructure and iron concentration, as well as an important guide towards achievement of optimal fMRI contrast. However, fetal MR imaging is a significant step up from neonatal or adult MR imaging due to the complexity of the acquisition and reconstruction techniques that are required to provide high quality artifact-free images in the presence of maternal respiration and unpredictable fetal motion. The first contribution of this thesis, described in Chapter 4, presents a novel acquisition method for measurement of fetal brain T2* values. At the time of publication, this was the first study of fetal brain T2* values. Single shot multi-echo gradient echo EPI was proposed as a rapid method for measuring fetal T2* values by effectively freezing intra-slice motion. The study concluded that fetal T2* values are higher than those previously reported for pre-term neonates and decline with a consistent trend across gestational age. The data also suggested that longer than usual echo times or direct T2* measurement should be considered when performing fetal fMRI in order to reach optimal BOLD sensitivity. For the second contribution, described in Chapter 5, measurements were extended to a higher field strength of 3T and reported, for the first time, both for fetal and neonatal subjects at this field strength. The technical contribution of this work is a fully automatic segmentation framework that propagates brain tissue labels onto the acquired T2* maps without the need for manual intervention. The third contribution, described in Chapter 6, proposed a new method for performing 3D fetal brain reconstruction where the available data is sparse and is therefore limited in the use of current state of the art techniques for 3D brain reconstruction in the presence of motion. To enable a high resolution reconstruction, a generative adversarial network was trained to perform image to image translation between T2 weighted and T2* weighted data. Translated images could then be served as a prior for slice alignment and super resolution reconstruction of 3D brain image.Open Acces

Development of Deep Learning Methods for Magnetic Resonance Phase Imaging of Neurological Disease

Magnetic resonance imaging (MRI) is a high-resolution, non-invasive medical imaging modality that is widely used in human brain. In recent years, susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) have been proposed to utilize MR phase signal to generate contrast from tissue magnetic susceptibility and even quantify the property. On the other hand, deep learning, especially deep convolutional neural networks (DCNNs), have achieved state-of-the-art performances in numerous computer vision tasks and gained significant attention in the field of medical imaging in the recent years. This dissertation combined the idea of deep learning with the two MR phase imaging methods. To combined deep learning with SWI, we designed and trained a 3D deep residual network that can distinguish false positive detected candidates from cerebral microbleeds (CMBs) and built an automatic CMB detection pipeline with high performance. We further confirmed the generalizability of this deep learning-based pipeline using multiple dataset with different scan parameters and pathologies and provided lessons for application and generalization of generic deep learning based medical imaging methods.To combine deep learning with QSM, we developed a 3D U-Net based network that learns to perform dipole inversion from gold standard QSM acquired from data with multiple orientation. The model was further improved with adversarial training strategy and achieved significantly lower reconstruction error than traditional QSM algorithms. In addition, we also performed various background removal and dipole inversion algorithms on both brain tumor patients and healthy volunteers to study and compare their performances. The results could provide guidance on future application of QSM in different scenarios

Magnetic Resonance Characterization of Porous Media Using Diffusion through Internal Magnetic Fields

When a porous material is inserted into a uniform magnetic field, spatially varying fields typically arise inside the pore space due to susceptibility contrast between the solid matrix and the surrounding fluid. As a result, direct measurement of the field variation may provide a unique opportunity to characterize the pore geometry. The sensitivity of nuclear magnetic resonance (NMR) to inhomogeneous field variations through their dephasing effects on diffusing spins is unique and powerful. Recent theoretical and experimental research sheds new light on how to utilize susceptibility-induced internal field gradients to quantitatively probe the microstructure of porous materials. This article reviews ongoing developments based on the stimulated echo-pulse sequence to extend the characterization of porous media using both spatially resolved and unresolved susceptibility-induced internal gradients that operate on a diffusing-spin ensemble.open

Detecting Compaction Disequilibrium with Anisotropy of Magnetic Susceptibility

In clay-rich sediment, microstructures and macrostructures influence how sediments deform when under stress. When lithology is fairly constant, anisotropy of magnetic susceptibility (AMS) can be a simple technique for measuring the relative consolidation state of sediment, which reflects the sediment burial history. AMS can reveal areas of high water content and apparent overconsolidation associated with unconformities where sediment overburden has been removed. Many other methods for testing consolidation and water content are destructive and invasive, whereas AMS provides a nondestructive means to focus on areas for additional geotechnical study. In zones where the magnetic minerals are undergoing diagenesis, AMS should not be used for detecting compaction state. By utilizing AMS in the Santa Barbara Basin, we were able to identify one clear unconformity and eight zones of high water content in three cores. With the addition of susceptibility, anhysteretic remanent magnetization, and isothermal remanent magnetization rock magnetic techniques, we excluded 3 out of 11 zones from being compaction disequilibria. The AMS signals for these three zones are the result of diagenesis, coring deformation, and burrows. In addition, using AMS eigenvectors, we are able to accurately show the direction of maximum compression for the accumulation zone of the Gaviota Slide

Soil erosion in the Alps : causes and risk assessment

The issue of soil erosion in the Alps has long been neglected due to the low economic value of the agricultural land. However, soil stability is a key parameter which affects ecosystem services like slope stability, water budgets (drinking water reservoirs as well as flood prevention), vegetation productivity, ecosystem biodiversity and nutrient production. In alpine regions, spatial estimates on soil erosion are difficult to derive because the highly heterogeneous biogeophysical structure impedes measurement of soil erosion and the applicability of soil erosion models. However, remote sensing and geographic information system (GIS) methods allow for spatial estimation of soil erosion by direct detection of erosion features and supply of input data for soil erosion models. Thus, the main objective of this work is to address the problem of soil erosion risk assessment in the Alps on catchment scale with remote sensing and GIS tools. Regarding soil erosion processes the focus is on soil erosion by water (here sheet erosion) and gravity (here landslides). For these two processes we address i) the monitoring and mapping of the erosion features and related causal factors ii) soil erosion risk assessment with special emphasis on iii) the validation of existing models for alpine areas. All investigations were accomplished in the Urseren Valley (Central Swiss Alps) where the valley slopes are dramatically affected by sheet erosion and landslides. For landslides, a natural susceptibility of the catchment has been indicated by bivariate and multivariate statistical analysis. Geology, slope and stream density are the most significant static landslide causal factors. Static factors are here defined as factors that do not change their attributes during the considered time span of the study (45 years), e.g. geology, stream network. The occurrence of landslides might be significantly increased by the combined effects of global climate and land use change. Thus, our hypothesis is that more recent changes in land use and climate affected the spatial and temporal occurrence of landslides. The increase of the landslide area of 92% within 45 years in the study site confirmed our hypothesis. In order to identify the cause for the trend in landslide occurrence time-series of landslide causal factors were analysed. The analysis revealed increasing trends in the frequency and intensity of extreme rainfall events and stocking of pasture animals. These developments presumably enhanced landslide hazard. Moreover, changes in land-cover and land use were shown to have affected landslide occurrence. For instance, abandoned areas and areas with recently emerging shrub vegetation show very low landslide densities. Detailed spatial analysis of the land use with GIS and interviews with farmers confirmed the strong influence of the land use management practises on slope stability. The definite identification and quantification of the impact of these non-stationary landslide causal factors (dynamic factors) on the landslide trend was not possible due to the simultaneous change of several factors. The consideration of dynamic factors in statistical landslide susceptibility assessments is still unsolved. The latter may lead to erroneous model predictions, especially in times of dramatic environmental change. Thus, we evaluated the effect of dynamic landslide causal factors on the validity of landslide susceptibility maps for spatial and temporal predictions. For this purpose, a logistic regression model based on data of the year 2000 was set up. The resulting landslide susceptibility map was valid for spatial predictions. However, the model failed to predict the landslides that occurred in a subsequent event. In order to handle this weakness of statistic landslide modelling a multitemporal approach was developed. It is based on establishing logistic regression models for two points in time (here 1959 and 2000). Both models could correctly classify >70% of the independent spatial validation dataset. By subtracting the 1959 susceptibility map from the 2000 susceptibility map a deviation susceptibility map was obtained. Our interpretation was that these susceptibility deviations indicate the effect of dynamic causal factors on the landslide probability. The deviation map explained 85% of new independent landslides occurring after 2000. Thus, we believe it to be a suitable tool to add a time element to a susceptibility map pointing to areas with changing susceptibility due to recently changing environmental conditions or human interactions. In contrast to landslides that are a direct threat to buildings and infrastructure, sheet erosion attracts less attention because it is often an unseen process. Nonetheless, sheet erosion may account for a major proportion of soil loss. Soil loss by sheet erosion is related to high spatial variability, however, in contrast to arable fields for alpine grasslands erosion damages are long lasting and visible over longer time periods. A crucial erosion triggering parameter that can be derived from satellite imagery is fractional vegetation cover (FVC). Measurements of the radiogenic isotope Cs-137, which is a common tracer for soil erosion, confirm the importance of FVC for soil erosion yield in alpine areas. Linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and the spectral index NDVI are applied for estimating fractional abundance of vegetation and bare soil. To account for the small scale heterogeneity of the alpine landscape very high resolved multispectral QuickBird imagery is used. The performance of LSU and MTMF for estimating percent vegetation cover is good (r²=0.85, r²=0.71 respectively). A poorer performance is achieved for bare soil (r²=0.28, r²=0.39 respectively) because compared to vegetation, bare soil has a less characteristic spectral signature in the wavelength domain detected by the QuickBird sensor. Apart from monitoring erosion controlling factors, quantification of soil erosion by applying soil erosion risk models is done. The performance of the two established models Universal Soil Loss Equation (USLE) and Pan-European Soil Erosion Risk Assessment (PESERA) for their suitability to model erosion for mountain environments is tested. Cs-137 is used to verify the resulting erosion rates from USLE and PESERA. PESERA yields no correlation to measured Cs-137 long term erosion rates and shows lower sensitivity to FVC. Thus, USLE is used to model the entire study site. The LSU-derived FVC map is used to adapt the C factor of the USLE. Compared to the low erosion rates computed with the former available low resolution dataset (1:25000) the satellite supported USLE map shows “hotspots” of soil erosion of up to 16 t ha-1 a-1. In general, Cs-137 in combination with the USLE is a very suitable method to assess soil erosion for larger areas, as both give estimates on long-term soil erosion. Especially for inaccessible alpine areas, GIS and remote sensing proved to be powerful tools that can be used for repetitive measurements of erosion features and causal factors. In times of global change it is of crucial importance to account for temporal developments. However, the evaluation of the applied soil erosion risk models revealed that the implementation of temporal aspects, such as varying climate, land use and vegetation cover is still insufficient. Thus, the proposed validation strategies (spatial, temporal and via Cs-137) are essential. Further case studies in alpine regions are needed to test the methods elaborated for the Urseren Valley. However, the presented approaches are promising with respect to improve the monitoring and identification of soil erosion risk areas in alpine regions

APPLICATION-SPECIFIC OPTIMIZATION OF QUANTITATIVE SUSCEPTIBILITY MAPPING FOR CLINICAL IMAGING

Magnetic resonance imaging (MRI) is a noninvasive clinical imaging modality with very rich contrasts based on the physical properties of the imaged tissues. MRI can be used for quantification of volumetric distributions of various biomolecules and chemical elements - such as triglycerides, calcium and iron - that regarded as participants in normal tissue biochemistry, and whose dysregulations are often manifested in pathologic processes. This dissertation reports optimization steps undertaken to overcome technical challenges in quantitative susceptibility mapping (QSM) in different parts of human body. Often in QSM it is assumed that susceptibility is the only contributor to the observed field inhomogeneity, which may be a valid assumption for neuroimaging applications. However, multiple molecules found in biological tissues (e.g., triglycerides of fat) have a resonance frequency different from that of water, and this resonance frequency offset is referred to as chemical shift. This chemical shift affects the phase of the MRI signal. Although ways to estimate field inhomogeneity in the presence of chemical shift have been proposed, they often rely on the a priori knowledge of the chemical spectrum. Unfortunately, variability of chemical spectra have been reported. In this dissertation, an automated joint estimation of the chemical shift and the susceptibility from an MRI dataset is reported, where the chemical shift is also treated as an unknown variable subject to optimization. QSM may become a useful diagnostic tool for noninvasive assessment of bone health without the use of ionizing radiation, however this application has been a challenging task challenging because QSM requires complete measurements of phase everywhere within the region of interest, and cortical bone typically has very low or no signal at conventional echo times in gradient echo (GRE) imaging. An additional problem arises from intermingling of fat and water protons in the bone marrow, necessitating the application of water–fat separation techniques for field mapping. In this dissertation, a novel signal model is proposed, feasibility of using QSM for measuring bone MRI signal is investigated, and the inherent technical issues involved in this application are highlighted. QSM has been widely applied in neuroimaging. In particular, due to its ability to accurately map iron deposits in deep brain nuclei, QSM promises precise targeting of the subthalamic nucleus (STN) in deep brain stimulation surgery (DBS). This dissertation reports results of comparison between QSM and standard-of-care T2w imaging of the STN, and their performance in high-resolution presugrical anatomic imaging

Étude magnétique des particules en suspension dans l'air (PM) capturées dans des bio-capteurs et des filtres à air dans différents environnements urbains

Les particules en suspension dans l'air (PM) sont aujourd'hui considérées comme un risque majeur pour la santé. Les enfants constituent l'un des groupes les plus vulnérables aux PM et à la pollution atmosphérique. Comme la majorité de la population passe plus de temps à l'intérieur, il est très important de connaître les différentes sources de particules dans cet environnement et la contribution des sources extérieures. Malgré les progrès réalisés dans la compréhension de la qualité de l'air intérieur, de nombreuses lacunes subsistent en ce qui concerne le transfert des particules de l'extérieur vers l'intérieur. Le magnétisme environnemental offre une grande opportunité pour l'étude des PM, car il est suffisamment sensible pour étudier les fractions les plus fines des oxydes de fer présents dans les PM. Les méthodes magnétiques sont également particulièrement adaptées pour être utilisées avec des biocollecteurs, échantillons naturels capables de retenir les polluants. Les biocollecteurs constituent une excellente alternative aux capteurs à faible coût, car ils sont rentables et ont un faible impact sur l'environnement. Ici, nous avons combiné des méthodes magnétiques avec des biocollecteurs afin de mieux comprendre le problème des PM intérieur-extérieur dans différents contextes urbains. L'objectif principal de la thèse était de caractériser les émissions anthropiques de PM à l'intérieur et à l'extérieur et la relation entre elles. Les différentes sources d'émissions urbaines ont été caractérisées dans des filtres PM2.5, fournissant des informations sur les propriétés magnétiques de ces sources, qui ont ensuite été utilisées dans l'étude des biocollecteurs. Les biocollecteurs ont été utilisés dans le cadre de projets scientifiques citoyens, afin d'étudier les PM dans les environnements urbains. Dans cette thèse, des techniques magnétiques innovantes ont également été utilisées pour étudier la fraction ultrafine des PM magnétiques. La microscopie électronique à balayage a fourni des informations morphologiques complémentaires sur les oxydes de fer et les autres constituants des PM. Les résultats indiquent tout d'abord que les différentes sources d'émissions anthropiques présentaient une distribution granulométrique étroite. Pour la ville de Toulouse, les émissions dues au trafic routier ont dominé la fraction magnétique des PM qui sont transportées à l'intérieur des habitations. Des sphérules d'oxydes de fer ultrafines d'environ 50 nm (et plus) liées aux émissions du trafic, ont été détectées au MEB. L'environnement intérieur présente une concentration plus faible de PM magnétiques (avec des I/O moyens pour le SIRM compris entre 0,7 et 0,9 pour les écoles et de 0,5 pour les résidences). La fraction granulométrique est plus fine par rapport à l'extérieur (dans le SSD). La fraction ultrafine pour ce type de grain a un diamètre moyen calculé à 7.7nm. D'autres sources de particules, outre les émissions du trafic, sont également importantes à l'intérieur, notamment dans l'environnement scolaire, comme le montrent les I/O pour la concentration de carbone organique allant de 1,1 à 1,9. Avec l'hypothèse que certaines des particules PM émises en milieu urbain sont entraînées dans le cycle de l'eau, les sédiments de la Garonne ont été étudiés. Les résultats montrent des pics de susceptibilité magnétique (atteignant des valeurs de 2,95x10-6) et de métaux traces (tels que Cu et Pb atteignant des concentrations de 139,0 et 73,5 ppm) dans le centre-ville de Toulouse qui indiquent un apport anthropique. La présence de sphérules d'oxydes de fer de taille micrométrique (allant de 10 à 91 um) montre que les sources d'émission liée au trafic routier sont à l'origine des particules détectées. En conclusion, cette thèse a fourni de nouvelles informations sur les émissions anthropiques de particules et sur leur relation intérieur-extérieur, qui peuvent être utilisées pour caractériser la qualité de l'air dans les environnements urbaines.Airborne particulate matter (PM) is understood nowadays as a major health risk. The finer PM fraction is the most dangerous for human health. Children are one of the most vulnerable groups to PM and air pollution, due to their immature respiratory systems and higher respiration rates than adults. Since the majority of the population spends more time indoors, knowing the different sources of PM in this environment and the contribution of outdoor sources is of great importance. Despite advances in the comprehension of indoor air quality, many gaps still exist regarding PM transfer from outdoors to indoors environments. Environmental magnetism offers a great opportunity for PM investigation, being sensible enough to investigate the finer fractions (sub-micrometric) of iron oxides present in PM even when they occur in small concentrations. Magnetic methods are also particularly suited to be used together with biocollectors, which are natural samples able to retain pollutants, such as tree leaves and tree bark. Biocollectors are a great alternative to low cost sensors, being cost-effective and of low environmental impact. They also offer the opportunity for innovative experimental designs. Here we combined magnetic methods with biocollectors in order to better understand the indoor-outdoor PM problem in different urban contexts. The main goal of the thesis was to characterize anthropogenic emissions of PM indoors and outdoors and the relationship between them. The different urban emission sources were characterized in PM2.5 filters, providing information about the magnetic properties of those sources, which were later used in the study of biocollectors. Biocollectors were used in citizen science projects, to study PM indoors and outdoors in urban environments. In this thesis innovative magnetic techniques were also used to investigate the ultrafine fraction of magnetic PM, regarding grains on the superparamagnetic size range (i.e. below ~30 nm for magnetite). Scanning electronic microscopy provided complementary morphological information about iron oxides and other PM constituents. The results indicate firstly that different anthropogenic emission sources had a narrow grain size distribution. Traffic emissions dominated the magnetic fraction of PM that is carried indoors both in domestic environments and in schools.. Ultrafine iron oxides spherules of about 50 nm (and finer) are related to traffic emissions, as detected in the SEM. The indoor environment has a lower concentration of magnetic PM (with mean I/O for SIRM calculated at 0.7 and 0.9 on the schools and 0.5 on the residencies), although the size fraction is finer in comparison with outdoors (in the SSD). The ultrafine fraction (below the SP-SSD boundary) shows an I/O for concentration calculated at 0.4, evincing a higher concentration outdoors for this kind of grain with mean diameter calculated at 7.7nm. Other PM sources, besides traffic emissions, are also important indoors, especially in the school environment, as shown by I/O for organic carbon concentration ranging from 1.1 to 1.9. Lastly, we investigated the fate of PM emitted in the urban setting. With the hypothesis that PM particles emitted in urban settings are carried away in the water cycle, sediments of the Garonne river were studied. The results show peaks in magnetic susceptibility (reaching values of 2.95x10-6) and trace metals (such as Cu and Pb reaching concentrations of 139.0 and 73.5ppm) in the downtown region of Toulouse that point to anthropogenic input. Presence of iron oxides spherules with micrometric size (ranging from 10 to 91um) shows traffic emission sources as origin for the detected particles. Overall, this thesis provided new insights on the anthropogenic emission of PM, and their indoor-outdoor relationship which can be used in characterizing the domestic and school environment air quality