Thijs Dhollander

Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data

Constrained spherical deconvolution (CSD) has become one of the most widely used methods to extract white matter (WM) fibre orientation information from diffusion-weighted MRI (DW-MRI) data, overcoming the crossing fibre limitations inherent in the diffusion tensor model. It is routinely used to obtain high quality fibre orientation distribution function (fODF) estimates and fibre tractograms and is increasingly used to obtain apparent fibre density (AFD) measures. Unfortunately, CSD typically only supports data acquired on a single shell in q-space. With multi-shell data becoming more and more prevalent, there is a growing need for CSD to fully support such data. Furthermore, CSD can only provide high quality fODF estimates in voxels containing WM only. In voxels containing other tissue types such as grey matter (GM) and cerebrospinal fluid (CSF), the WM response function may no longer be appropriate and spherical deconvolution produces unreliable, noisy fODF estimates. The aim of this study is to incorporate support for multi-shell data into the CSD approach as well as to exploit the unique b-value dependencies of the different tissue types to estimate a multi-tissue ODF. The resulting approach is dubbed multi-shell, multi-tissue CSD (MSMT-CSD) and is compared to the state-of-the-art single-shell, single-tissue CSD (SSST-CSD) approach. Using both simulations and real data, we show that MSMT-CSD can produce reliable WM/GM/CSF volume fraction maps, directly from the DW data, whereas SSST-CSD has a tendency to overestimate the WM volume in voxels containing GM and/or CSF. In addition, compared to SSST-CSD, MSMT-CSD can substantially increase the precision of the fODF fibre orientations and reduce the presence of spurious fODF peaks in voxels containing GM and/or CSF. Both effects translate into more reliable AFD measures and tractography results with MSMT-CSD compared to SSST-CSD.

Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury

Patients with traumatic brain injury show clear impairments in behavioural flexibility and inhibition that often persist beyond the time of injury, affecting independent living and psychosocial functioning. Functional magnetic resonance imaging studies have shown that patients with traumatic brain injury typically show increased and more broadly dispersed frontal and parietal activity during performance of cognitive control tasks. We constructed binary and weighted functional networks and calculated their topological properties using a graph theoretical approach. Twenty-three adults with traumatic brain injury and 26 age-matched controls were instructed to switch between coordination modes while making spatially and temporally coupled circular motions with joysticks during event-related functional magnetic resonance imaging. Results demonstrated that switching performance was significantly lower in patients with traumatic brain injury compared with control subjects. Furthermore, although brain networks of both groups exhibited economical small-world topology, altered functional connectivity was demonstrated in patients with traumatic brain injury. In particular, compared with controls, patients with traumatic brain injury showed increased connectivity degree and strength, and higher values of local efficiency, suggesting adaptive mechanisms in this group. Finally, the degree of increased connectivity was significantly correlated with poorer switching task performance and more severe brain injury. We conclude that analysing the functional brain network connectivity provides new insights into understanding cognitive control changes following brain injury.

Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model.

Diffusion-weighted imaging and tractography provide a unique, non-invasive technique to study the macroscopic structure and connectivity of brain white matter in vivo. Global tractography methods aim at reconstructing the full-brain fiber configuration that best explains the measured data, based on a generative signal model. In this work, we incorporate a multi-shell multi-tissue model based on spherical convolution, into a global tractography framework, which allows to deal with partial volume effects. The required tissue response functions can be estimated from and hence calibrated to the data. The resulting track reconstruction is quantitatively related to the apparent fiber density in the data. In addition, the fiber orientation distribution for white matter and the volume fractions of gray matter and cerebrospinal fluid are produced as ancillary results. Validation results on simulated data demonstrate that this data-driven approach improves over state-of-the-art streamline and global tracking methods, particularly in the valid connection rate. Results in human brain data correspond to known white matter anatomy and show improved modeling of partial voluming. This work is an important step toward detecting and quantifying white matter changes and connectivity in healthy subjects and patients.

The associative-semantic network for words and pictures: Effective connectivity and graph analysis

Explicit associative-semantic processing of words and pictures activates a distributed set of brain areas that has been replicated across a wide range of studies. We applied graph analysis to examine the structure of this network. We determined how the left ventral occipitotemporal transition zone (vOT) was connected to word-specific areas. A modularity analysis discerned four communities: one corresponded to the classical perisylvian language system, including superior temporal sulcus (STS), middle temporal gyrus (GTm) and pars triangularis of the inferior frontal gyrus (GFi), among other nodes. A second subsystem consisted of vOT and anterior fusiform gyrus along with hippocampus and intraparietal sulcus. The two subsystems were linked through a unique connection between vOT and GTm, which were hubs with a high betweenness centrality compared to STS and GFi which had a high local clustering coefficient. Graph analysis reveals novel insights into the structure of the network for associative-semantic processing.

Bimanual Motor Coordination in Older Adults Is Associated with Increased Functional Brain Connectivity – A Graph-Theoretical Analysis

In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA) to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had “small world” character. The present findings indicate (a) that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b) that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions.

Track Orientation Density Imaging (TODI) and Track Orientation Distribution (TOD) based tractography

Ever since the introduction of the concept of fiber tractography, methods to generate better and more plausible tractograms have become available. Many modern methods can handle complex fiber architecture and take on a probabilistic approach to account for different sources of uncertainty. The resulting tractogram from any such method typically represents a finite random sample from a complex distribution of possible tracks. Generating a higher amount of tracks allows for a more accurate depiction of the underlying distribution. The recently proposed method of track-density imaging (TDI) allows to capture the spatial distribution of a tractogram. In this work, we propose an extension of TDI towards the 5D spatio-angular domain, which we name track orientation density imaging (TODI). The proposed method aims to capture the full track orientation distribution (TOD). Just as the TDI map, the TOD is amenable to spatial super-resolution (or even sub-resolution), but in addition also to angular super-resolution. Through experiments on in vivo human subject data, an in silico numerical phantom and a challenging tractography phantom, we found that the TOD presents an increased amount of regional spatio-angular consistency, as compared to the fiber orientation distribution (FOD) from constrained spherical deconvolution (CSD). Furthermore, we explain how the amplitude of the TOD of a short-tracks distribution (i.e. where the track length is limited) can be interpreted as a measure of track-like local support (TLS). This in turn motivated us to explore the idea of TOD-based fiber tractography. In such a setting, the short-tracks TOD is able to guide a track along directions that are more likely to correspond to continuous structure over a longer distance. This powerful concept is shown to greatly robustify targeted as well as whole-brain tractography. We conclude that the TOD is a versatile tool that can be cast in many different roles and scenarios in the expanding domain of fiber tractography based methods and their applications.

Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space

In the field of diffusion weighted imaging (DWI), it is common to fit one of many available models to the acquired data. A hybrid diffusion imaging (HYDI) approach even allows to reconstruct different models and measures from a single dataset. Methods for DWI atlas construction (and registration) are as plenty as the number of available models. Therefore, it would be nice if we were able to perform atlas building before model reconstruction. In this work, we present a method for atlas construction of DWI data in q-space: we developed a new multi-subject multi-channel diffeomorphic matching algorithm, which is combined with a recently proposed DWI retransformation method in q-space. We applied our method to HYDI data of 10 healthy subjects. From the resulting atlas, we also reconstructed some advanced models. We hereby demonstrate the feasibility of q-space atlas building, as well as the quality, advantages and possibilities of such an atlas.

Groupwise Deformable Registration of Fiber Track Sets Using Track Orientation Distributions

Diffusion-weighted imaging (DWI) and tractography allow to study the macroscopic structure of white matter in vivo. We present a novel method for deformable registration of unsegmented full-brain fiber track sets extracted from DWI data. Our method attempts to align the track orientation distributions (TODs) of multiple subjects, rather than individual tracks. As such, it can handle complex track configurations and allows for multi-resolution registration. We validated the registration method on synthetically deformed DWI data and on data of 15 healthy subjects, and achieved sub-voxel accuracy in dense white matter structures. This work is, to the best of our knowledge, the first demonstration of direct registration of probabilistic tractography data.

Atlas-Guided Global Tractography: Imposing a Prior on the Local Track Orientation

Since its introduction over a decade ago, diffusion tractography has come a long way from local, deterministic methods, over probabilistic approaches, towards global tractography. Yet, the development of tractography methods has been largely focused on single subject data, and very little on cross-population analysis and inter-subject variability. In this work, we extend global tractography with a prior on the local track orientation distribution (TOD), derived from 20 normal subjects. The proposed method is evaluated in five independent subjects. Results show that adding such prior regularizes the reconstructed track distribution, although registration errors can induce local artefacts. We conclude that atlas-guided global tractography can improve the fibre reconstruction and ultimately detect and quantify inter-subject differences in tractography.

FIXEL-BASED ANALYSIS OF FIBRE TRACT DEGENERATION IN MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DISEASE

characteristics in preclinical models. [11C]BU99008 is selective for I2-imidazoline binding sites (I2BS) expressed on the mitochondrial membranes of astrocytes. These I2 imidazoline binding sites (I2BS) increase with astroglial activation in the brain. Methods: The primary objective is to assess the uptake of [11C]BU99008 in mild to moderate AD compared to healthy volunteers (HV). We also are exploring the relationship between increased uptake, brain amyloid load and glucose metabolism. Thus far, in two separate cohorts, we have completed analysis of a total of 18 HVs. Nonlinear registration of the CIC atlas into native space for each subject’s dynamic PET data and generation of regional time-activity data, time-activity curves for frontal, temporal, parietal occipital and hippocampus are being modelled using two-tissue (2TCM) compartmental models using MIAKAT. Results:Cohort 1 consists of 13 subjects age (5467yr; mean6SD), data previously presented (Tyacke et al, NRM 2016). The new Cohort 2 consists of a significantly more elderly group of 5 subjects (7067yr). They showed uptake (VT, ml.cm ) highest in: nucleus accumbens (152624), globus pallidus (141645) and striatum (119633); intermediate in the insular cortex (87610), and cingulate cortex (76612); and lowest in the occipital cortex (6365) and cerebellum (5763). These data are in good agreement with those in Cohort 1. However, in cohort 2 there was significantly greater (Student t-test; P<0.05) increase in the regions showing lowest binding in both cohorts. A correlation using all 18 subjects for whole brain binding showed a trend towards a significant increase with age (P1⁄40.06; Spearmans). Conclusions: The [11C]BU99008 PET tracer has demonstrated that the tracer has good brain uptake in humans. More AD, MCI and healthy control subjects are being scanned to evaluate its possible use as a marker of pathology progression in AD. The Medical Research Council Dementias Platform UK (DPUK) is a multi-million pound public-private partnership developed by the MRC. This study was conducted as a component of a developing DPUK Imaging Network experimental medicine programme.