Publications

BACKGROUND: Exposure to cigarette smoke has been shown to lead to vascular remodelling. Computed tomography (CT) imaging measures of vascular pruning have been associated with pulmonary vascular disease, an important morbidity associated with smoking. In this study we compare CT-based measures of distal vessel loss to histological vascular and parenchymal changes.

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The back-and-forth debate on radiation risk, in the recent years, has unscientifically drifted away from proportionality and become increasingly antagonistic. A handful of authors have used exaggerated claims which are corroborated by their own previous work and presented using heated and superlative language. With unwarranted certainty, many have also referenced studies which report inconclusive findings and given undue weight to the results of laboratory animal and cellular studies, regardless of their exact positions on radiation risk. The passion and subjective interpretation with which the debate is now presented detracts from rational, scientific evaluation. A reform of the debate is needed to reach grounded consensus in the community and, if appropriate, begin the process of amending the legislation to reflect it. In this article we have analysed key research on the topic and discussed the fundamental limitations of science in providing satisfactory answers to our questions.

Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.

OBJECTIVE: Detecting brain abnormalities in clinical high-risk populations before the onset of psychosis is important for tracking pathological pathways and for identifying possible intervention strategies that may impede or prevent the onset of psychotic disorders. Co-occurring cellular and extracellular white matter alterations have previously been implicated after a first psychotic episode. The authors investigated whether or not cellular and extracellular alterations are already present in a predominantly medication-naive cohort of clinical high-risk individuals experiencing attenuated psychotic symptoms. METHODS: Fifty individuals at clinical high risk, of whom 40 were never medicated, were compared with 50 healthy control subjects, group-matched for age, gender, and parental socioeconomic status. 3-T multishell diffusion MRI data were obtained to estimate free-water imaging white matter measures, including fractional anisotropy of cellular tissue (FA) and the volume fraction of extracellular free water (FW). RESULTS: Significantly lower FA was observed in the clinical high-risk group compared with the healthy control group, but no statistically significant FW alterations were observed between groups. Lower FA in the clinical high-risk group was significantly associated with a decline in Global Assessment of Functioning Scale (GAF) score compared with highest GAF score in the previous 12 months. CONCLUSIONS: Cellular but not extracellular alterations characterized the clinical high-risk group, especially in those who experienced a decline in functioning. These cellular changes suggest an early deficit that possibly reflects a predisposition to develop attenuated psychotic symptoms. In contrast, extracellular alterations were not observed in this clinical high-risk sample, suggesting that previously reported extracellular abnormalities may reflect an acute response to psychosis, which plays a more prominent role closer to or at onset of psychosis.

Compartmental diffusion MRI models that account for intravoxel incoherent motion (IVIM) of blood perfusion allow for estimation of the fractional volume of the microvascular compartment. Conventional IVIM models are known to be biased by not accounting for partial volume effects caused by free water and cerebrospinal fluid (CSF), or for tissue-dependent relaxation effects. In this work, a three-compartment model (tissue, free water and blood) that includes relaxation terms is introduced. To estimate the model parameters, in vivo human data were collected with multiple echo times (TE), inversion times (TI) and b-values, which allowed a direct relaxation estimate alongside estimation of perfusion, diffusion and fractional volume parameters. Compared to conventional two-compartment models (with and without relaxation compensation), the three-compartment model showed less effects of CSF contamination. The proposed model yielded significantly different volume fractions of blood and tissue compared to the non-relaxation-compensated model, as well as to the conventional two-compartment model, suggesting that previously reported parameter ranges, using models that do not account for relaxation, should be reconsidered.

PURPOSE: To demonstrate the feasibility of multidimensional diffusion MRI to probe and quantify microscopic fractional anisotropy (µFA) in human kidneys in vivo. METHODS: Linear tensor encoded (LTE) and spherical tensor encoded (STE) renal diffusion MRI scans were performed in 10 healthy volunteers. Respiratory triggering and image registration were used to minimize motion artefacts during the acquisition. Kidney cortex-medulla were semi-automatically segmented based on fractional anisotropy (FA) values. A model-free analysis of LTE and STE signal dependence on b-value in the renal cortex and medulla was performed. Subsequently, µFA was estimated using a single-shell approach. Finally, a comparison of conventional FA and µFA is shown.

Computational methods are crucial for the analysis of diffusion magnetic resonance imaging (MRI) of the brain. Computational diffusion MRI can provide rich information at many size scales, including local microstructure measures such as diffusion anisotropies or apparent axon diameters, whole-brain connectivity information that describes the brain’s wiring diagram and population-based studies in health and disease. Many of the diffusion MRI analyses performed today were not possible five, ten or twenty years ago, due to the requirements for large amounts of computer memory or processor time. In addition, mathematical frameworks had to be developed or adapted from other fields to create new ways to analyze diffusion MRI data. The purpose of this review is to highlight recent computational and statistical advances in diffusion MRI and to put these advances into context by comparison with the more traditional computational methods that are in popular clinical and scientific use. We aim to provide a high-level overview of interest to diffusion MRI researchers, with a more in-depth treatment to illustrate selected computational advances.

Huntington’s disease (HD) is an inherited neurodegenerative disorder that causes progressive breakdown of striatal neurons. Standard white matter integrity measures like fractional anisotropy and mean diffusivity derived from diffusion tensor imaging were analyzed in prodromal-HD subjects; however, they studied either a whole brain or specific subcortical white matter structures with connections to cortical motor areas. In this work, we propose a novel analysis of a longitudinal cohort of 243 prodromal-HD individuals and 88 healthy controls who underwent two or more diffusion MRI scans as part of the PREDICT-HD study. We separately trace specific white matter fiber tracts connecting the striatum (caudate and putamen) with four cortical regions corresponding to the hand, face, trunk, and leg motor areas. A multi-tensor tractography algorithm with an isotropic volume fraction compartment allows estimating diffusion of fast-moving extra-cellular water in regions containing crossing fibers and provides quantification of a microstructural property related to tissue atrophy. The tissue atrophy rate is separately analyzed in eight cortico-striatal pathways as a function of CAG-repeats (genetic load) by statistically regressing out age effect from our cohort. The results demonstrate a statistically significant increase in isotropic volume fraction (atrophy) bilaterally in hand fiber connections to the putamen with increasing CAG-repeats, which connects the genetic abnormality (CAG-repeats) to an imaging-based microstructural marker of tissue integrity in specific white matter pathways in HD. Isotropic volume fraction measures in eight cortico-striatal pathways are also correlated significantly with total motor scores and diagnostic confidence levels, providing evidence of their relevance to HD clinical presentation.

Mild traumatic brain injuries (mTBIs) are often associated with posttraumatic stress disorder (PTSD). In cases of chronic mTBI, accurate diagnosis can be challenging due to the overlapping symptoms this condition shares with PTSD. Furthermore, mTBIs are heterogeneous and not easily observed using conventional neuroimaging tools, despite the fact that diffuse axonal injuries are the most common injury. Diffusion tensor imaging (DTI) is sensitive to diffuse axonal injuries and is thus more likely to detect mTBIs, especially when analyses account for the inter-individual variability of these injuries. Using a subject-specific approach, we compared fractional anisotropy (FA) abnormalities between groups with a history of mTBI (n = 35), comorbid mTBI and PTSD (mTBI + PTSD; n = 22), and healthy controls (n = 37). We compared all three groups on the number of abnormal FA clusters derived from subject-specific injury profiles (i.e., individual z-score maps) along a common white matter skeleton. The mTBI + PTSD group evinced a greater number of abnormally low FA clusters relative to both the healthy controls and the mTBI group without PTSD (p