REKINDLE: Robust extraction of kurtosis INDices with linear estimation

Patent Ductus Arteriosus and Brain Volume

BACKGROUND AND OBJECTIVES

A hemodynamically significant patent ductus arteriosus (PDA) can compromise perfusion and oxygenation of the preterm brain. Reports suggest that PDA is associated with increased mortality and morbidity. We hypothesize that long-standing low cerebral oxygenation due to PDA might affect brain volume at term equivalent age.

METHODS

Observational study in 140 infants investigating the relationship between near-infrared spectroscopy-monitored cerebral oxygen saturation (rSco2) and MRI-assessed regional brain volume and maturation of the posterior limb of the internal capsule at term-equivalent age in 3 groups: those whose PDA closed with indomethacin, those who needed additional surgical closure, and matched controls.

RESULTS

The surgery group had the lowest rSco2 values before closure (n = 35), 48% ± 9.7% (mean ± SD) as compared with the indomethacin (n = 35), 59% ± 10.4 (P < .001), and control groups (n = 70), 66% ± 6.9 (P < .001); the highest postnatal age before effective treatment; and the lowest volumes of most brain regions at term-equivalent age. Multiple linear regression analysis showed a significant effect of preductal closure rSco2 on cerebellar volume in this group. No differences were found in maturation of the posterior limb of the internal capsule.

CONCLUSIONS

Long-standing suboptimal cerebral oxygenation due to a PDA may negatively influence brain growth, affecting neurodevelopmental outcome.

D-BRAIN: Anatomically Accurate Simulated Diffusion MRI Brain Data

Diffusion Weighted (DW) MRI allows for the non-invasive study of water diffusion inside living tissues. As such, it is useful for the investigation of human brain white matter (WM) connectivity in vivo through fiber tractography (FT) algorithms. Many DW-MRI tailored restoration techniques and FT algorithms have been developed. However, it is not clear how accurately these methods reproduce the WM bundle characteristics in real-world conditions, such as in the presence of noise, partial volume effect, and a limited spatial and angular resolution. The difficulty lies in the lack of a realistic brain phantom on the one hand, and a sufficiently accurate way of modeling the acquisition-related degradation on the other. This paper proposes a software phantom that approximates a human brain to a high degree of realism and that can incorporate complex brain-like structural features. We refer to it as a Diffusion BRAIN (D-BRAIN) phantom. Also, we propose an accurate model of a (DW) MRI acquisition protocol to allow for validation of methods in realistic conditions with data imperfections. The phantom model simulates anatomical and diffusion properties for multiple brain tissue components, and can serve as a ground-truth to evaluate FT algorithms, among others. The simulation of the acquisition process allows one to include noise, partial volume effects, and limited spatial and angular resolution in the images. In this way, the effect of image artifacts on, for instance, fiber tractography can be investigated with great detail. The proposed framework enables reliable and quantitative evaluation of DW-MR image processing and FT algorithms at the level of large-scale WM structures. The effect of noise levels and other data characteristics on cortico-cortical connectivity and tractography-based grey matter parcellation can be investigated as well.

Neonatal DTI early after birth predicts motor outcome in preterm infants with periventricular hemorrhagic infarction

BACKGROUND

To determine the association between early neonatal diffusion tensor imaging (DTI) and the development of unilateral spastic cerebral palsy (USCP) in preterm infants with periventricular hemorrhagic infarction (PVHI).

METHODS

Preterm infants with PVHI were assessed with early (≤4 wk after birth) and term-equivalent age MRI-DTI. Involvement of corticospinal tracts was assessed by visual assessment of the posterior limb of the internal capsule (PLIC) on DTI (classified asymmetrical, equivocal, or symmetrical) and by an atlas-based approach calculating fractional anisotropy asymmetry index in the PLIC. Motor outcome was assessed at ≥15 mo corrected age.

RESULTS

Seven out of 23 infants with PVHI developed USCP. Their PLIC was visually scored as asymmetrical in 6 and equivocal in 1 on the early DTI. Thirteen out of 16 infants with a symmetrical motor development had a symmetrical PLIC on early DTI, the remaining 3 were equivocal. All infants with USCP had a fractional anisotropy asymmetry index of >0.05 (optimal cut-off value) on early DTI. In infants with a symmetrical motor development (n = 16), 14 had an asymmetry index ≤0.05 while 2 had an index >0.05.

CONCLUSION

DTI in preterm infants with PVHI within a few weeks after birth is associated with later motor development.

Dynamics of the connectome in Huntington's disease: A longitudinal diffusion MRI study

Objectives

To longitudinally investigate the connectome in different stages of Huntington's disease (HD) by applying graph theoretical analysis to diffusion MRI data.

Experimental design

We constructed weighted structural networks and calculated their topological properties. Twenty-two premanifest (preHD), 10 early manifest HD and 24 healthy controls completed baseline and 2 year follow-up scans. We stratified the preHD group based on their predicted years to disease onset into a far (preHD-A) and near (preHD-B) to disease onset group. We collected clinical and behavioural measures per assessment time point.

Principle observations

We found a significant reduction over time in nodal betweenness centrality both in the early manifest HD and preHD-B groups as compared to the preHD-A and control groups, suggesting a decrease of importance of specific nodes to overall network organization in these groups (FDR adjusted ps < 0.05). Additionally, we found a significant longitudinal decrease of the clustering coefficient in preHD when compared to healthy controls (FDR adjusted p < 0.05), which can be interpreted as a reduced capacity for internodal information processing at the local level. Furthermore, we demonstrated dynamic changes to hub-status loss and gain both in preHD and early manifest HD. Finally, we found significant cross-sectional as well as longitudinal relationships between graph metrics and clinical and neurocognitive measures.

Conclusions

This study demonstrates divergent longitudinal changes to the connectome in (pre) HD compared to healthy controls. This provides novel insights into structural correlates associated with clinical and cognitive functions in HD and possible compensatory mechanisms at play in preHD.

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Investigates characteristics of the connectome in Huntington's disease (HD).

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HD patients showed longitudinal changes in their structural connectome.

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Connectome dynamics correlated with changes in clinical and cognitive measures.

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Connectomics provides novel insights into compensatory strategies of the diseased brain.

The effect of Gibbs ringing artifacts on measures derived from diffusion MRI

Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a unique method to investigate microstructural tissue properties noninvasively and is one of the most popular methods for studying the brain white matter in vivo. To obtain reliable statistical inferences with diffusion MRI, however, there are still many challenges, such as acquiring high-quality DW-MRI data (e.g., high SNR and high resolution), careful data preprocessing (e.g., correcting for subject motion and eddy current induced geometric distortions), choosing the appropriate diffusion approach (e.g., diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), or diffusion spectrum MRI), and applying a robust analysis strategy (e.g., tractography based or voxel based analysis). Notwithstanding the numerous efforts to optimize many steps in this complex and lengthy diffusion analysis pipeline, to date, a well-known artifact in MRI--i.e., Gibbs ringing (GR)--has largely gone unnoticed or deemed insignificant as a potential confound in quantitative DW-MRI analysis. Considering the recent explosion of diffusion MRI applications in biomedical and clinical applications, a systematic and comprehensive investigation is necessary to understand the influence of GR on the estimation of diffusion measures. In this work, we demonstrate with simulations and experimental DW-MRI data that diffusion estimates are significantly affected by GR artifacts and we show that an off-the-shelf GR correction procedure based on total variation already can alleviate this issue substantially.

Diffusion Tensor Imaging and Fiber Tractography in Children with Craniosynostosis Syndromes

BACKGROUND AND PURPOSE

Patients with craniosynostosis syndromes caused by mutations in FGFR-2, FGFR-3, and TWIST1 genes are characterized by having prematurely fused skull sutures and skull base synchondroses, which result in a skull deformity and are accompanied by brain anomalies, including altered white matter microarchitecture. In this study, the reliability and reproducibility of DTI fiber tractography was investigated in these patients. The outcomes were compared with those of controls.

MATERIALS AND METHODS

DTI datasets were acquired with a 1.5T MR imaging system with 25 diffusion gradient orientations (voxel size = 1.8 × 1.8 × 3.0 mm(3), b-value = 1000 s/mm(2)). White matter tracts studied included the following: corpus callosum, cingulate gyrus, fornix, corticospinal tracts, and medial cerebellar peduncle. Tract pathways were reconstructed with ExploreDTI in 58 surgically treated patients with craniosynostosis syndromes and 7 controls (age range, 6-18 years).

RESULTS

Because of the brain deformity and abnormal ventricular shape and size, DTI fiber tractography was challenging to perform in patients with craniosynostosis syndromes. To provide reliable tracts, we adapted standard tracking protocols. Fractional anisotropy was equal to that in controls (0.44 versus 0.45 ± 0.02, P = .536), whereas mean, axial, and radial diffusivity parameters of the mean white matter were increased in patients with craniosynostosis syndromes (P < .001). No craniosynostosis syndrome-specific difference in DTI properties was seen for any of the fiber tracts studied in this work.

CONCLUSIONS

Performing DTI fiber tractography in patients with craniosynostosis syndromes was difficult due to partial volume effects caused by an anisotropic voxel size and deformed brain structures. Although these patients have a normal fiber organization, increased diffusivity parameters suggest abnormal microstructural tissue properties of the investigated white matter tracts.

Microstructural brain abnormalities in Huntington's disease: A two-year follow-up

OBJECTIVES

To investigate both cross-sectional and time-related changes of striatal and whole-brain microstructural properties in different stages of Huntington's disease (HD) using diffusion tensor imaging.

EXPERIMENTAL DESIGN

From the TRACK-HD study, premanifest gene carriers (preHD), early manifest HD and controls were scanned at baseline and 2-year follow-up. Stratification of the preHD group into a far (preHD-A) and near (preHD-B) to predicted disease onset was performed. Age-corrected histograms of whole-brain white matter (WM), gray matter (GM) and striatal diffusion measures were computed and normalised by the number of voxels in each subject's data set.

PRINCIPLE OBSERVATIONS

Higher cross-sectional mean, axial and radial diffusivities were found in both WM (P ≤ 0.001) and GM (P ≤ 0.001) of the manifest HD compared to the preHD and control groups. In preHD, only WM axial diffusivity (AD) was higher than in controls (P ≤ 0.01). This finding remained valid only in preHD-B (P ≤ 0.001). AD was also higher in the striatum of preHD-B compared to controls and preHD-A (P ≤ 0.01). Fractional anisotropy (FA) lacked sensitivity in differentiating between the groups. Histogram peak heights were generally lower in manifest HD compared to the preHD and control groups. No longitudinal differences were found in the degree of diffusivity change between the groups in the two year follow-up. There was a significant relationship between diffusivity and neurocognitive measures.

CONCLUSIONS

Alterations in cross-sectional diffusion profiles between manifest HD subjects and controls were evident, both in whole-brain and striatum. In the preHD stage, only AD alterations were found, a finding suggesting that this metric is a sensitive marker for early change in HD prior to disease manifestation. The individual diffusivities were superior to FA in revealing pathologic microstructural brain alterations. Diffusion measures were well related to clinical functioning and disease stage.

Recent advancements in diffusion MRI for investigating cortical development after preterm birth-potential and pitfalls

Preterm infants are born during a critical period of brain maturation, in which even subtle events can result in substantial behavioral, motor and cognitive deficits, as well as psychiatric diseases. Recent evidence shows that the main source for these devastating disabilities is not necessarily white matter (WM) damage but could also be disruptions of cortical microstructure. Animal studies showed how moderate hypoxic-ischemic conditions did not result in significant neuronal loss in the developing brain, but did cause significantly impaired dendritic growth and synapse formation alongside a disturbed development of neuronal connectivity as measured using diffusion magnetic resonance imaging (dMRI). When using more advanced acquisition settings such as high-angular resolution diffusion imaging (HARDI), more advanced reconstruction methods can be applied to investigate the cortical microstructure with higher levels of detail. Recent advances in dMRI acquisition and analysis have great potential to contribute to a better understanding of neuronal connectivity impairment in preterm birth. We will review the current understanding of abnormal preterm cortical development, novel approaches in dMRI, and the pitfalls in scanning vulnerable preterm infants.

High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing

Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g., intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2–3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1 mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view (rFoV) imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e., produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.

Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS

In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron's local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract's position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values.

Kurtosis analysis of neural diffusion organization

A computational framework is presented for relating the kurtosis tensor for water diffusion in brain to tissue models of brain microstructure. The tissue models are assumed to be comprised of non-exchanging compartments that may be associated with various microstructural spaces separated by cell membranes. Within each compartment the water diffusion is regarded as Gaussian, although the diffusion for the full system would typically be non-Gaussian. The model parameters are determined so as to minimize the Frobenius norm of the difference between the measured kurtosis tensor and the model kurtosis tensor. This framework, referred to as kurtosis analysis of neural diffusion organization (KANDO), may be used to help provide a biophysical interpretation to the information provided by the kurtosis tensor. In addition, KANDO combined with diffusional kurtosis imaging can furnish a practical approach for developing candidate biomarkers for neuropathologies that involve alterations in tissue microstructure. KANDO is illustrated for simple tissue models of white and gray matter using data obtained from healthy human subjects.