An Automatic Level Set Based Liver Segmentation from MRI Data Sets

A fast and accurate liver segmentation method is a challenging work in medical image analysis area. Liver segmentation is an important process for computer-assisted diagnosis, pre-evaluation of liver transplantation and therapy planning of liver tumors. There are several advantages of magnetic resonance imaging such as free form ionizing radiation and good contrast visualization of soft tissue. Also, innovations in recent technology and image acquisition techniques have made magnetic resonance imaging a major tool in modern medicine. However, the use of magnetic resonance images for liver segmentation has been slow when we compare applications with the central nervous systems and musculoskeletal. The reasons are irregular shape, size and position of the liver, contrast agent effects and similarities of the gray values of neighbor organs. Therefore, in this study, we present a fully automatic liver segmentation method by using an approximation of the level set based contour evolution from T2 weighted magnetic resonance data sets. The method avoids solving partial differential equations and applies only integer operations with a two-cycle segmentation algorithm. The efficiency of the proposed approach is achieved by applying the algorithm to all slices with a constant number of iteration and performing the contour evolution without any user defined initial contour. The obtained results are evaluated with four different similarity measures and they show that the automatic segmentation approach gives successful results

Fractional anisotropy shows differential reduction in frontal-subcortical fiber bundles - A longitudinal MRI study of 76 middle-aged and older adults

Motivated by the frontal- and white matter (WM) retrogenesis hypotheses and the assumptions that fronto-striatal circuits are especially vulnerable in normal aging, the goal of the present study was to identify fiber bundles connecting subcortical nuclei and frontal areas and obtain site-specific information about age related fractional anisotropy (FA) changes. Multimodal magnetic resonance image acquisitions [3D T1-weighted and diffusion weighted imaging (DWI)] were obtained from healthy older adults (N = 76, range 49–80 years at inclusion) at two time points, 3 years apart. A subset of the participants (N = 24) was included at a third time-point. In addition to the frontal-subcortical fibers, the anterior callosal fiber (ACF) and the corticospinal tract (CST) was investigated by its mean FA together with tract parameterization analysis. Our results demonstrated fronto-striatal structural connectivity decline (reduced FA) in normal aging with substantial inter-individual differences. The tract parameterization analysis showed that the along tract FA profiles were characterized by piece-wise differential changes along their extension rather than being uniformly affected. To the best of our knowledge, this is the first longitudinal study detecting age-related changes in frontal-subcortical WM connections in normal aging.publishedVersio

Epilepsy-related cytoarchitectonic abnormalities along white matter pathways

Objective Temporal lobe epilepsy (TLE) is one of the most common forms of epilepsy. Unfortunately, the clinical outcomes of TLE cannot be determined based only on current diagnostic modalities. A better understanding of white matter (WM) connectivity changes in TLE may aid the identification of network abnormalities associated with TLE and the phenotypic characterisation of the disease. Methods We implemented a novel approach for characterising microstructural changes along WM pathways using diffusional kurtosis imaging (DKI). Along-the-tract measures were compared for 32 subjects with left TLE and 36 age-matched and gender-matched controls along the left and right fimbria-fornix (FF), parahippocampal WM bundle (PWMB), arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF) and cingulum bundle (CB). Limbic pathways were investigated in relation to seizure burden and control with antiepileptic drugs. Results By evaluating measures along each tract, it was possible to identify abnormalities localised to specific tract subregions. Compared with healthy controls, subjects with TLE demonstrated pathological changes in circumscribed regions of the FF, PWMB, UF, AF and ILF. Several of these abnormalities were detected only by kurtosis-based and not by diffusivity-based measures. Structural WM changes correlated with seizure burden in the bilateral PWMB and cingulum. Conclusions DKI improves the characterisation of network abnormalities associated with TLE by revealing connectivity abnormalities that are not disclosed by other modalities. Since TLE is a neuronal network disorder, DKI may be well suited to fully assess structural network abnormalities related to epilepsy and thus serve as a tool for phenotypic characterisation of epilepsy

Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter

Diffusion-weighted magnetic resonance imaging (DWI) is undergoing constant evolution with the ambitious goal of developing in-vivo histology of the brain. A recent methodological advancement is Neurite Orientation Dispersion and Density Imaging (NODDI), a histologically validated multi-compartment model to yield microstructural features of brain tissue such as geometric complexity and neurite packing density, which are especially useful in imaging the white matter. Since NODDI is increasingly popular in clinical research and fields such as developmental neuroscience and neuroplasticity, it is of vast importance to characterize its reproducibility (or reliability). We acquired multi-shell DWI data in 29 healthy young subjects twice over a rescan interval of 4 weeks to assess the within-subject coefficient of variation (CVWS), between-subject coefficient of variation (CVBS) and the intraclass correlation coefficient (ICC), respectively. Using these metrics, we compared regional and voxel-by-voxel reproducibility of the most common image analysis approaches (tract-based spatial statistics [TBSS], voxel-based analysis with different extents of smoothing [“VBM-style”], ROI-based analysis). We observed high test–retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). Our findings also suggest that the choice of analysis approach might have significant consequences for the results of a study. Collectively, the voxel-based approach with Gaussian smoothing kernels of ≥4 mm FWHM and ROI-averaging yielded the highest reproducibility across NDI and ODI maps (CVWS mostly ≤3%, ICC mostly ≥0.8), respectively, whilst smaller kernels and TBSS performed consistently worse. Furthermore, we demonstrate that image quality (signal-to-noise ratio [SNR]) is an important determinant of NODDI metric reproducibility. We discuss the implications of these results for longitudinal and cross-sectional research designs commonly employed in the neuroimaging field

Aerobic Exercise for the Promotion of Healthy Aging: Changes in Brain Structure Assessed with New Methods

As the proportion of older individuals in the population increases, so does the scientific concern surrounding age-related deterioration of brain tissue and related cognitive decline. One modifiable lifestyle factor of interest in the pursuit to slow or even reverse age-related brain atrophy is aerobic exercise. A number of studies have already demonstrated that aerobic exercise in older age can induce maintenance (i.e., reduction of loss) of both gray and white matter volume, particularly in the frontal regions of the brain, which are vulnerable to shrinkage in older age. Other magnetic resonance imaging (MRI)-based techniques, such as quantitative MRI and diffusion-weighted MRI, have been used to measure age-related deterioration of gray and white matter integrity in both voxel-wise analyses as well as on the latent level, but whether these negative changes can be ameliorated through exercise has yet to be shown. The current dissertation includes three papers which used a number of both established and novel MRI-based metrics to quantify changes in brain tissue integrity resulting from aging, as well as to investigate whether these changes can be ameliorated through aerobic exercise. In Paper I (Wenger et al., 2022), we tested the reliability of quantitative MRI measures, namely longitudinal relaxation rate, effective transverse relaxation rate, proton density, and magnetization transfer saturation, by measuring them in a two-day, four-session design with repositioning in the scanner. Using the intra-class effect decomposition model, we found that magnetization transfer saturation could reliably detect individual differences, validating its use to investigate changes in brain structure longitudinally, as well as correlations with other variables of interest, such as change in cardiovascular fitness. In Paper II (Polk et al., 2022), we tested the effects of aerobic exercise on a latent factor of gray-matter structural integrity, comprising observed measures of gray-matter volume, magnetization transfer saturation, and mean diffusivity, in regions of interest that have previously shown volumetric effects of aerobic exercise. We found that gray-matter structural integrity was maintained in frontal and midline regions, and that change in gray-matter structural integrity in the right anterior cingulate cortex was positively correlated with change in cardiovascular fitness within exercising participants. These results suggest a causal relationship between aerobic exercise, cardiovascular fitness, and gray-matter structural integrity in this region. In Paper III (Polk et al., 2022), we tested the effects of aerobic exercise on white matter integrity, measured with both established and recently developed metrics. We were able to replicate findings from a previous study on the effects of aerobic exercise on white matter volume, and we also found change-change correlations between white matter volume and cardiovascular fitness as well as between white matter volume and performance on a test of perceptual speed. We also found unexpected exercise-induced changes in the diffusion weighted imaging-derived metrics of fractional anisotropy, mean diffusivity, fiber density, and fiber density and cross-section. Specifically, we found increases (or decreases in the case of mean diffusivity) within control participants and decreases (or increases in mean diffusivity) in exercisers. Furthermore, we found that percent change in fiber density and fiber density and cross-section correlated negatively with percent change in both cardiovascular fitness and cognitive performance. This casts doubt on the functional interpretation of these measures and suggests that the “more is better” principle may not be universally applicable when investigating age-related and exercise-induced changes in white matter integrity. In sum, this dissertation showed that regular at-home aerobic exercise, which may be more accessible for older individuals than supervised exercise, can be an effective tool to ameliorate age-related decreases in a latent measure of gray-matter structural integrity as well as white matter volume. It also illuminated potential limitations of other measures of white matter integrity in the context of aging and aerobic exercise, and calls for further research into these novel measures, especially when considering functional outcomes such as cognitive performance

Development of Advanced, Clinically Feasible Neuroimaging Methodology with Diffusional Kurtosis Imaging

Diffusion MRI (dMRI) is a powerful, non-invasive tool for probing the structural organization of the human brain. Quantitative dMRI analyses provide unique capabilities for the characterization of tissue microstructure as well as imaging contrast that is not available to other modalities. White matter tractography relies on dMRI and is currently the only non-invasive technique for mapping structural connections in the human brain. In this chapter, we will describe diffusional kurtosis imaging, an effective and versatile dMRI technique, and discuss a clinical problem in temporal lobe epilepsy (TLE) which is insurmountable with current diagnostic approaches. Subsequent chapters will further develop the capabilities of DKI and demonstrate how it may be particularly well suited to overcome current barriers to care in the clinical management of TLE