Introduction. Local microstructural pathology in multiple sclerosis patients might influence their clinical performance. This study applied multicontrast MRI to quantify inflammation and ...neurodegeneration in MS lesions. We explored the impact of MRI-based lesion pathology in cognition and disability. Methods. 36 relapsing-remitting MS subjects and 18 healthy controls underwent neurological, cognitive, behavioural examinations and 3 T MRI including (i) fluid attenuated inversion recovery, double inversion recovery, and magnetization-prepared gradient echo for lesion count; (ii) T1, T2, and T2* relaxometry and magnetisation transfer imaging for lesion tissue characterization. Lesions were classified according to the extent of inflammation/neurodegeneration. A generalized linear model assessed the contribution of lesion groups to clinical performances. Results. Four lesion groups were identified and characterized by (1) absence of significant alterations, (2) prevalent inflammation, (3) concomitant inflammation and microdegeneration, and (4) prevalent tissue loss. Groups 1, 3, 4 correlated with general disability (Adj-R2=0.6; P=0.0005), executive function (Adj-R2=0.5; P=0.004), verbal memory (Adj-R2=0.4; P=0.02), and attention (Adj-R2=0.5; P=0.002). Conclusion. Multicontrast MRI provides a new approach to infer in vivo histopathology of plaques. Our results support evidence that neurodegeneration is the major determinant of patients’ disability and cognitive dysfunction.
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.
Spherical deconvolution methods are widely used to estimate the brain's white-matter fiber orientations from diffusion MRI data. In this study, eight spherical deconvolution algorithms were ...implemented and evaluated. These included two model selection techniques based on the extended Bayesian information criterion (i.e., best subset selection and the least absolute shrinkage and selection operator), iteratively reweighted l2- and l1-norm approaches to approximate the l0-norm, sparse Bayesian learning, Cauchy deconvolution, and two accelerated Richardson-Lucy algorithms. Results from our exhaustive evaluation show that there is no single optimal method for all different fiber configurations, suggesting that further studies should be conducted to find the optimal way of combining solutions from different methods. We found l0-norm regularization algorithms to resolve more accurately fiber crossings with small inter-fiber angles. However, in voxels with very dominant fibers, algorithms promoting more sparsity are less accurate in detecting smaller fibers. In most cases, the best algorithm to reconstruct fiber crossings with two fibers did not perform optimally in voxels with one or three fibers. Therefore, simplified validation systems as employed in a number of previous studies, where only two fibers with similar volume fractions were tested, should be avoided as they provide incomplete information. Future studies proposing new reconstruction methods based on high angular resolution diffusion imaging data should validate their results by considering, at least, voxels with one, two, and three fibers, as well as voxels with dominant fibers and different diffusion anisotropies.
•There is no single optimal SD method for all the different fiber configurations.•Sparse algorithms to resolve fiber crossings with small inter-fiber angles were found.•Algorithms promoting more sparsity are less accurate in detecting smaller fibers.•Future studies should validate their results by considering many fiber configurations.
Despite the high prevalence of sensory processing difficulties in children with autism spectrum disorder (ASD), little research has focused on the sex differences in sensory processing. Furthermore, ...there is a lack of knowledge on the female‐specific symptoms of ASD, contributing to later referral, diagnosis and intervention. In this study, we examined the sex differences in sensory processing symptoms in large cohorts of ASD children (N = 168; 26 females, 142 males) and typically developing (TD) children (N = 439; 209 females, 230 males). For this, we translated the sensory processing measure (SPM) and SPM – Preschool (SPM‐P) Home Forms to French. The SPM/SPM‐P are parent/caregiver questionnaires that assess typical behavioral responses to sensory stimuli. Overall, our results showed that the magnitude of the differences in sensory processing between males and females is larger in ASD children relative to TD children, with females showing more severe symptoms in Hearing, as well as Balance and Motion subscales. Additionally, linear discriminant analysis showed that the SPM/SPM‐P are good at discriminating TD children from ASD, children with higher accuracy rates for females than for males. These findings are discussed in light of the heterogeneity of sensory processing difficulties present in ASD. Overall, our results suggest that there seem to be female‐specific profiles in sensory processing difficulties in ASD. Implications of findings concerning sex differences in sensory processing and their potential for improving identification and diagnosis of ASD females are discussed.
Lay Summary
The present study examined sex differences in behavioral responses to sensory stimuli in children with autism spectrum disorder (ASD), and typically developing (TD) children. While there is a small trend for TD males to show more sensory processing atypicalities, female ASD children show significantly more atypical responses compared to their male counterparts. This has important implications for characterizing female autism profiles, and ultimately improving the chance for earlier detection, diagnosis and treatment.
Non-invasive axon diameter distribution (ADD) mapping using diffusion MRI is an ill-posed problem. Current ADD mapping methods require knowledge of axon orientation before performing the acquisition. ...Instead, ActiveAx uses a 3D sampling scheme to estimate the orientation from the signal, providing orientationally invariant estimates. The mean diameter is estimated instead of the distribution for the solution to be tractable. Here, we propose an extension (ActiveAx
) that provides non-parametric and orientationally invariant estimates of the whole distribution.
The accelerated microstructure imaging with convex optimization (AMICO) framework accelerates mean diameter estimation using a linear formulation combined with Tikhonov regularization to stabilize the solution. Here, we implement a new formulation (ActiveAx
) that uses Laplacian regularization to provide robust estimates of the whole ADD.
The performance of ActiveAx
was evaluated using Monte Carlo simulations on synthetic white matter samples mimicking axon distributions reported in histological studies.
ActiveAx
provided robust ADD reconstructions when considering the isolated intra-axonal signal. However, our formulation inherited some common microstructure imaging limitations. When accounting for the extra axonal compartment, estimated ADDs showed spurious peaks and increased variability because of the difficulty of disentangling intra and extra axonal contributions.
Laplacian regularization solves the ill-posedness regarding the intra axonal compartment. ActiveAx
can potentially provide non-parametric and orientationally invariant ADDs from isolated intra-axonal signals. However, further work is required before ActiveAx
can be applied to real data containing extra-axonal contributions, as disentangling the 2 compartment appears to be an overlooked challenge that affects microstructure imaging methods in general.
Brain hemispheres develop rather symmetrically, except in the case of pathology or intense training. As school experience is a form of training, the current study tested the influence of pedagogy on ...morphological development through the cortical thickness (CTh) asymmetry index (AI). First, we compared the CTh AI of 111 students aged 4 to 18 with 77 adults aged > 20. Second, we investigated the CTh AI of the students as a function of schooling background (Montessori or traditional). At the whole-brain level, CTh AI was not different between the adult and student groups, even when controlling for age. However, pedagogical experience was found to impact CTh AI in the temporal lobe, within the parahippocampal (PHC) region. The PHC region has a functional lateralization, with the right PHC region having a stronger involvement in spatiotemporal context encoding, while the left PHC region is involved in semantic encoding. We observed CTh asymmetry toward the left PHC region for participants enrolled in Montessori schools and toward the right for participants enrolled in traditional schools. As these participants were matched on age, intelligence, home-life and socioeconomic conditions, we interpret this effect found in memory-related brain regions to reflect differences in learning strategies. Pedagogy modulates how new concepts are encoded, with possible long-term effects on knowledge transfer.
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