Showing papers by "Alexander Leemans published in 2017"

The challenge of mapping the human connectome based on diffusion tractography

Abstract: Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

The importance of correcting for signal drift in diffusion MRI.

Abstract: Purpose To investigate previously unreported effects of signal drift as a result of temporal scanner instability on diffusion MRI data analysis and to propose a method to correct this signal drift. Methods We investigated the signal magnitude of non-diffusion-weighted EPI volumes in a series of diffusion-weighted imaging experiments to determine whether signal magnitude changes over time. Different scan protocols and scanners from multiple vendors were used to verify this on phantom data, and the effects on diffusion kurtosis tensor estimation in phantom and in vivo data were quantified. Scalar metrics (eigenvalues, fractional anisotropy, mean diffusivity, mean kurtosis) and directional information (first eigenvectors and tractography) were investigated. Results Signal drift, a global signal decrease with subsequently acquired images in the scan, was observed in phantom data on all three scanners, with varying magnitudes up to 5% in a 15-min scan. The signal drift has a noticeable effect on the estimation of diffusion parameters. All investigated quantitative parameters as well as tractography were affected by this artifactual signal decrease during the scan. Conclusion By interspersing the non-diffusion-weighted images throughout the session, the signal decrease can be estimated and compensated for before data analysis; minimizing the detrimental effects on subsequent MRI analyses. Magn Reson Med 77:285–299, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

"MASSIVE" Brain Dataset : Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation

Abstract: Purpose In this work, we present the MASSIVE (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation) brain dataset of a single healthy subject, which is intended to facilitate diffusion MRI (dMRI) modeling and methodology development. Methods MRI data of one healthy subject (female, 25 years) were acquired on a clinical 3 Tesla system (Philips Achieva) with an eight-channel head coil. In total, the subject was scanned on 18 different occasions with a total acquisition time of 22.5 h. The dMRI data were acquired with an isotropic resolution of 2.5 mm3 and distributed over five shells with b-values up to 4000 s/mm2 and two Cartesian grids with b-values up to 9000 s/mm2 . Results The final dataset consists of 8000 dMRI volumes, corresponding B0 field maps and noise maps for subsets of the dMRI scans, and ten three-dimensional FLAIR, T1 -, and T2 -weighted scans. The average signal-to-noise-ratio of the non-diffusion-weighted images was roughly 35. Conclusion This unique set of in vivo MRI data will provide a robust framework to evaluate novel diffusion processing techniques and to reliably compare different approaches for diffusion modeling. The MASSIVE dataset is made publically available (both unprocessed and processed) on www.massive-data.org. Magn Reson Med 77:1797-1809, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Changes in Brain Structural Networks and Cognitive Functions in Testicular Cancer Patients Receiving Cisplatin-Based Chemotherapy

Abstract: Background Cisplatin-based chemotherapy may have neurotoxic effects within the central nervous system. The aims of this study were 1) to longitudinally investigate the impact of cisplatin-based chemotherapy on whole-brain networks in testicular cancer patients undergoing treatment and 2) to explore whether possible changes are related to decline in cognitive functioning. Methods Sixty-four newly orchiectomized TC patients underwent structural magnetic resonance imaging (T1-weighted and diffusion-weighted imaging) and cognitive testing at baseline prior to further treatment and again at a six-month follow-up. At follow-up, 22 participants had received cisplatin-based chemotherapy (CT) while 42 were in active surveillance (S). Brain structural networks were constructed for each participant, and network properties were investigated using graph theory and longitudinally compared across groups. Cognitive functioning was evaluated using standardized neuropsychological tests. All statistical tests were two-sided. Results Compared with the S group, the CT group demonstrated altered global and local brain network properties from baseline to follow-up as evidenced by decreases in important brain network properties such as small-worldness (P = .04), network clustering (P = .04), and local efficiency (P = .02). In the CT group, poorer overall cognitive performance was associated with decreased small-worldness (r = -0.46, P = .04) and local efficiency (r = -0.51, P = .02), and verbal fluency was associated with decreased local efficiency (r = -0.55, P = .008). Conclusions Brain structural networks may be disrupted following treatment with cisplatin-based chemotherapy. Impaired brain networks may underlie poorer performance over time on both specific and nonspecific cognitive functions in patients undergoing chemotherapy. To the best of our knowledge, this is the first study to longitudinally investigate changes in structural brain networks in a cancer population, providing novel insights regarding the neurobiological mechanisms of cancer-related cognitive impairment.

Transcallosal connectivity of the human cortical motor network

Abstract: The organisational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualise white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has, therefore, remained elusive. We employed constrained spherical deconvolution (CSD) tractography-an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity-exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasised. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity.

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

Abstract: Purpose To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue. Materials and Methods Ten healthy volunteers were examined at 3T, with T2-weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono-, bi-, and triexponential fit parameters (D1, D2, D3, ffast2, ffast3, and finterm) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R2 ( Radj2) and the Shapiro-Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared. Results Fitting the diffusion signal was feasible for all models. The three-component model was best able to describe fast signal decay at low b values (b 0.05) between the diffusion constant of the medulla and cortex, whereas the ffast component of the two and three-component models were significantly different (P < 0.001). Conclusion Triexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information. Level of Evidence: 2 J. Magn. Reson. Imaging 2016

Anatomical integration and rich-club connectivity in euthymic bipolar disorder.

Abstract: Background Although repeatedly associated with white matter microstructural alterations, bipolar disorder (BD) has been relatively unexplored using complex network analysis. This method combines structural and diffusion magnetic resonance imaging (MRI) to model the brain as a network and evaluate its topological properties. A group of highly interconnected high-density structures, termed the ‘rich-club’, represents an important network for integration of brain functioning. This study aimed to assess structural and rich-club connectivity properties in BD through graph theory analyses. Method We obtained structural and diffusion MRI scans from 42 euthymic patients with BD type I and 43 age- and gender-matched healthy volunteers. Weighted fractional anisotropy connections mapped between cortical and subcortical structures defined the neuroanatomical networks. Next, we examined between-group differences in features of graph properties and sub-networks. Results Patients exhibited significantly reduced clustering coefficient and global efficiency, compared with controls globally and regionally in frontal and occipital regions. Additionally, patients displayed weaker sub-network connectivity in distributed regions. Rich-club analysis revealed subtly reduced density in patients, which did not withstand multiple comparison correction. However, hub identification in most participants indicated differentially affected rich-club membership in the BD group, with two hubs absent when compared with controls, namely the superior frontal gyrus and thalamus. Conclusions This graph theory analysis presents a thorough investigation of topological features of connectivity in euthymic BD. Abnormalities of global and local measures and network components provide further neuroanatomically specific evidence for distributed dysconnectivity as a trait feature of BD.

Structural and functional cortical connectivity mediating cross education of motor function

Abstract: Cross-education (CE) is the process whereby training with one limb leads to subsequent improvement in performance by the opposite untrained limb. We used multimodal neuroimaging in humans to investigate the mediating neural mechanisms by relating quantitative estimates of functional and structural cortical connectivity to individual levels of interlimb transfer. Resting-state (rs)-fMRI and diffusion weighted imaging (DWI) scans were undertaken before unilateral ballistic wrist flexion training. The rs-fMRI sequence was repeated immediately afterward. The increase in performance of the untrained limb was 83.6% of that observed for the trained limb and significantly greater than that of a control group who undertook no training. Functional connectivity in the resting motor network between right and left supplementary motor areas (SMA) was elevated after training. These changes were not, however, correlated with individual levels of transfer. Analysis of the DWI data using constrained spherical deconvolution-based tractography indicated that fractional anisotropy and apparent fiber density in tracts connecting bilateral SMA were negatively correlated with and predictive of transfer. The findings suggest that interhemispheric interactions between bilateral SMA play an instrumental role in CE and that the structural integrity of the connecting white matter pathways influences the level of transfer.SIGNIFICANCE STATEMENT Strength or skill training with one limb also brings about improvements in the performance of the opposite, untrained limb. This phenomenon, termed cross-education (CE), has obvious potential for the rehabilitation of functional capacity that has been lost through brain insult or musculoskeletal injury. The neural mechanisms that give rise to CE are, however, poorly understood. We used a combination of neuroimaging methods to investigate the pathways in the human brain that mediate CE. We determined that the supplementary motor area (SMA) plays an important role in the interlimb transfer of performance gains and demonstrate that the quality of the white matter fibers connecting right and left SMA predicts the benefit that an individual derives from CE.

White matter maturation in the neonatal brain is predictive of school age cognitive capacities in children born very preterm

Abstract: Aim To investigate the association between white matter organization in the neonatal brain and cognitive capacities at early school age in children born very preterm. Method Thirty children born very preterm (gestational age median 27.5wks, interquartile range [IQR] 25.5–29.5; 18 males, 12 females) were included in this retrospective observational cohort study. Diffusion-weighted imaging (DWI) had been performed on a 3T system in the neonatal period (median 41.3 [IQR 40.0–42.6]wks) and cognitive functioning was formally assessed at age 5 years and 7 months (IQR 5.4–5.9y) using the Wechsler Preschool and Primary Scale of Intelligence. Structural connectivity maps were reconstructed from the DWI data using deterministic streamline tractography. Network metrics of global and local communication and mean fractional anisotropy of white matter pathways were related to IQ and processing speed at age 5 years using linear regression analyses. Results Mean fractional anisotropy was significantly related to Performance IQ at age 5 years (F=8.48, p=0.007). Findings persisted after adjustment for maternal education level. Interpretation Our findings provide evidence that the blueprint of later cognitive achievement is already present at term-equivalent age and suggest that white matter connectivity strength may be a valuable predictor for long-term cognitive functioning.

MRI shows thickening and altered diffusion in the median and ulnar nerves in multifocal motor neuropathy.

Abstract: To study disease mechanisms in multifocal motor neuropathy (MMN) with magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) of the median and ulnar nerves. We enrolled ten MMN patients, ten patients with amyotrophic lateral sclerosis (ALS) and ten healthy controls (HCs). Patients underwent MRI (in a prone position) and nerve conduction studies. DTI and fat-suppressed T2-weighted scans of the forearms were performed on a 3.0T MRI scanner. Fibre tractography of the median and ulnar nerves was performed to extract diffusion parameters: fractional anisotropy (FA), mean (MD), axial (AD) and radial (RD) diffusivity. Cross-sectional areas (CSA) were measured on T2-weighted scans. Forty-five out of 60 arms were included in the analysis. AD was significantly lower in MMN patients (2.20 ± 0.12 × 10-3 mm2/s) compared to ALS patients (2.31 ± 0.17 × 10-3 mm2/s; p < 0.05) and HCs (2.31± 0.17 × 10-3 mm2/s; p < 0.05). Segmental analysis showed significant restriction of AD, RD and MD (p < 0.005) in the proximal third of the nerves. CSA was significantly larger in MMN patients compared to ALS patients and HCs (p < 0.01). Thickening of nerves is compatible with changes in the myelin sheath structure, whereas lowered AD values suggest axonal dysfunction. These findings suggest that myelin and axons are diffusely involved in MMN pathogenesis. • Diffusion magnetic resonance imaging provides quantitative information about multifocal motor neuropathy (MMN). • Diffusion tensor imaging allows non-invasive evaluation of the forearm nerves in MMN. • Nerve thickening and lowered diffusion parameters suggests myelin and axonal changes. • This study can help to provide insight into pathological mechanisms of MMN.

Altered wiring of the human structural connectome in adults with mild traumatic brain injury.

Abstract: In this study, structural connectivity after mild traumatic brain injury (mTBI) was examined from a network perspective, with a particular focus on post-traumatic complaints. Fifty-three patients with and without self-reported complaints at 2 weeks after uncomplicated mTBI were included, in addition to 20 matched healthy controls. Diffusion weighted imaging was performed at 4 weeks post-injury, and neuropsychological tests measuring processing speed and verbal memory were administered at 3 months post-injury to determine cognitive outcome. Structural connectivity was investigated using whole brain tractography and subsequent graph theory analysis. In patients with mTBI, eigenvector centrality within the left temporal pole was lower than in healthy controls. In patients without complaints, global and mean local efficiency were lower than in patients with complaints, although no differences were found between either subgroup and the group of healthy controls. Neuropsychological test scores were similar for patients with mTBI and healthy controls. However, patients with complaints showed higher processing speed than patients without complaints. Within the total mTBI group, a trend was found toward a correlation between lower network clustering and higher processing speed. Additionally, significant correlations were found between higher betweenness centrality values of language areas and lower verbal memory scores in patients with mTBI. In conclusion, our findings may indicate that global graph measures of the structural connectome are associated with pre- and/or non-injury-related factors that determine the susceptibility to developing (persistent) complaints after mTBI. Further, correlations between graph measures and neuropsychological test scores could suggest early compensatory mechanisms to maintain adequate cognitive performance.

Microstructure of Strategic White Matter Tracts and Cognition in Memory Clinic Patients with Vascular Brain Injury.

Abstract: BACKGROUND White matter injury is an important factor for cognitive impairment in memory clinic patients. We determined the added value of diffusion tensor imaging (DTI) of strategic white matter tracts in explaining variance in cognition in memory clinic patients with vascular brain injury. METHODS We included 159 patients. Conventional MRI markers (white matter hyperintensity volume, lacunes, nonlacunar infarcts, brain atrophy, and microbleeds), and fractional anisotropy and mean diffusivity (MD) of the whole brain white matter and of 18 white matter tracts were related to cognition using linear regression and Bayesian network analysis. RESULTS On top of all conventional MRI markers combined, MD of the whole brain white matter explained an additional 3.4% (p = 0.014), 7.8% (p < 0.001), and 1.2% (p = 0.119) variance in executive functioning, speed, and memory, respectively. The Bayesian analyses of regional DTI measures identified strategic tracts for executive functioning (right superior longitudinal fasciculus), speed (left corticospinal tract), and memory (left uncinate fasciculus). MD within these tracts explained an additional 3.4% (p = 0.012), 3.8% (p = 0.007), and 2.1% (p = 0.041) variance in executive functioning, speed, and memory, respectively, on top of all conventional MRI and global DTI markers combined. CONCLUSION In memory clinic patients with vascular brain injury, DTI of strategic white matter tracts has a significant added value in explaining variance in cognitive functioning.

Antibody-Induced Internalization of the Human Respiratory Syncytial Virus Fusion Protein.

Abstract: Respiratory syncytial virus (RSV) infections remain a major cause of respiratory disease and hospitalizations among infants. Infection recurs frequently and establishes a weak and short-lived immunity. To date, RSV immunoprophylaxis and vaccine research is mainly focused on the RSV fusion (F) protein, but a vaccine remains elusive. The RSV F protein is a highly conserved surface glycoprotein and is the main target of neutralizing antibodies induced by natural infection. Here, we analyzed an internalization process of antigen-antibody complexes after binding of RSV-specific antibodies to RSV antigens expressed on the surface of infected cells. The RSV F protein and attachment (G) protein were found to be internalized in both infected and transfected cells after the addition of either RSV-specific polyclonal antibodies (PAbs) or RSV glycoprotein-specific monoclonal antibodies (MAbs), as determined by indirect immunofluorescence staining and flow-cytometric analysis. Internalization experiments with different cell lines, well-differentiated primary bronchial epithelial cells (WD-PBECs), and RSV isolates suggest that antibody internalization can be considered a general feature of RSV. More specifically for RSV F, the mechanism of internalization was shown to be clathrin dependent. All RSV F-targeted MAbs tested, regardless of their epitopes, induced internalization of RSV F. No differences could be observed between the different MAbs, indicating that RSV F internalization was epitope independent. Since this process can be either antiviral, by affecting virus assembly and production, or beneficial for the virus, by limiting the efficacy of antibodies and effector mechanism, further research is required to determine the extent to which this occurs in vivo and how this might impact RSV replication.IMPORTANCE Current research into the development of new immunoprophylaxis and vaccines is mainly focused on the RSV F protein since, among others, RSV F-specific antibodies are able to protect infants from severe disease, if administered prophylactically. However, antibody responses established after natural RSV infections are poorly protective against reinfection, and high levels of antibodies do not always correlate with protection. Therefore, RSV might be capable of interfering, at least partially, with antibody-induced neutralization. In this study, a process through which surface-expressed RSV F proteins are internalized after interaction with RSV-specific antibodies is described. One the one hand, this antigen-antibody complex internalization could result in an antiviral effect, since it may interfere with virus particle formation and virus production. On the other hand, this mechanism may also reduce the efficacy of antibody-mediated effector mechanisms toward infected cells.

Learning Morse Code Alters Microstructural Properties in the Inferior Longitudinal Fasciculus : A DTI Study

Abstract: Learning relies on neuroplasticity, which has mainly been studied in gray matter (GM). However, there is mounting evidence indicating a critical role of white matter changes involved in learning processes. One of the most important learning processes in human development is language acquisition. However, due to the length of this learning process, it has been notoriously difficult to investigate the underlying neuroplastic changes. Here, we report a novel learning paradigm to assess the role of white matter plasticity for language acquisition. By acoustically presenting Morse Code (MC) using an in house developed audio book as a model for language-type learning, we generated a well-controlled learning environment that allows for the detection of subtle white matter changes related to language type learning in a much shorter time frame than usual language acquisition. In total 12 letters of the MC alphabet were learned within six learning session, which allowed study participants to perform a word recognition MC decoding task. In this study, we found that learning MC was associated with significant microstructural changes in the left inferior longitudinal fasciculus (ILF). The fractional anisotropy (FA) of this associative fiber bundle connecting the occipital and posterior temporal cortex with the temporal pole as well as the hippocampus and amygdala was increased. Furthermore, white matter plasticity was associated with task performance of MC decoding, indicating that the structural changes were related to learning efficiency. In conclusion, our findings demonstrate an important role of white matter neuroplasticity for acquiring a new language skill.

The Arcuate Fasciculus Network and Verbal Deficits in Psychosis.

Abstract: Background Verbal learning (VL) and fluency (VF) are prominent cognitive deficits in psychosis, of which the precise neuroanatomical contributions are not fully understood. We investigated the arcuate fasciculus (AF) and its associated cortical regions to identify structural abnormalities contributing to these verbal impairments in early stages of psychotic illness. Methods Twenty-six individuals with recent-onset psychosis and 27 healthy controls underwent cognitive testing (MATRICS Consensus Cognitive Battery) and structural/diffusion-weighted MRI. Bilaterally, AF anisotropy and cortical thickness, surface area and volume of seven cortical regions were investigated in relation to VL and VF performance in both groups. Results Reduced right superior temporal gyrus surface area and volume related to better VF in controls. In psychosis, greater right pars opercularis volume and reduced left lateralization of this region related to better VL, while greater right long AF fractional anisotropy and right pars orbitalis volume related to better VF, these findings not present in controls. Psychosis had reduced right pars orbitalis thickness compared to controls. Conclusion Anatomical substrates for normal processing of VL and VF appear altered in recent-onset psychosis. A possible aberrant role of the right hemisphere arcuate fasciculus and fronto-temporal cortical regions in psychosis may contribute to deficits in VL and VF.

Sampling Stability And Processing Parameter-Dependent Characteristics Of The 3D Fractal Dimension As A Marker Of Structural Brain Complexity In Magnetic Resonance Images

Abstract: Fractal analysis, ie the estimation of an object's fractal dimension (FD) as a marker of its morphometric complexity, has attracted increasing interest as a versatile tool for the analysis of structural neuroimaging data in both health and disease However, a number of important methodological questions regarding fractal analysis in magnetic resonance images have so far remained unaddressed This includes the stability of the FD over repeated within-subject measurements, ie the susceptibility of fractal analysis to noise, a formal assessment of its sampling distribution, and the impact of image acquisition and processing parameters Importantly, fractal analysis has not yet been explored in detail in T2 contrast images To address these issues, we analyzed structural images from the recently published MASSIVE data set (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation) We conduct a fine-grained stratification of image parameters, leading to 32 distinct analysis groups as a combination of image contrast, spatial resolution, segmentation procedures, tissue type, and image complexity We estimate 3D tissue models based on the thus obtained input volumes and compute the FDs as the box-counting regression on these models Furthermore, we present a detailed deviation analysis including resampling methods, composite normality assessment, outlier detection, and multivariate comparisons to establish the susceptibility of the FD to noise We find that in both T1 and T2 contrasts, the FD of gray matter (GM) segmentations was generally higher than in white matter volumes (WM) FDs in both image contrasts were sampled in comparable range and showed similar responses to processing parameters, eg as regards the effects of binary vs partial volume segmentation and a decrease in FD by image skeletization Lower spatial resolution invariably resulted in decreased FDs in unskeletized images, while the response depended on the segmentation procedure in image skeletons Furthermore, in multiple measurements, the FD can be assumed to be sampled from an underlying normal distribution We tested different options for a sensible within-group deviation criterion and found that outlier detection by Grubbs testing and a 2 standard-deviation interval around the sample mean performed very well in this regard Even with the more conservative threshold, the overall robustness of the FD to noise was well above 90 % Most deviations were found in T1-weighted images, and binarized image skeletons were most susceptible to deviations Importantly, our analysis was able to detect sample-wise deviation clusters, and we identify image registration as a source of noise in fractal analysis Interestingly, registration-induced deviations were limited to T1-weighted images, lending even further support for the usefulness of T2 contrast in fractal analysis In conclusion, we provide detailed evidence for the stability of the FD as a marker of structural brain complexity and its parameter-dependent characteristics in magnetic resonance images and thus contribute to the development of fractal analysis as a scientifically and clinically useful neuroimaging tool