Diffusion MRI fiber tractography is widely used to probe the structural connectivity of the brain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, ...tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the 3-D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge at the ISBI 2018 conference. We made available three unique independent tractography validation datasets – a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractography's inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.
•Organized international tractography challenge utilizing three validation datasets.•Anatomical accuracy of modern diffusion tractography techniques is limited.•Advancements are needed to overcome limited sensitivity/specificity of reconstructions.
Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called “virtual dissection.” Human errors ...and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC‐ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real‐life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and “virtual dissection” across various laboratories and hospitals. Intra‐rater agreement (Dice score) was approximately 0.77, while inter‐rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.
•Normative modelling for AD based on DL + DiReCT is equivalent to Freesurfer.•Both tools are equivalent regarding clinical-grade scans.•DL + DiReCT processes scans 15 times faster, while providing ...equivalent scores.•Atrophy patterns match published literature regarding Alzheimer disease.
Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of “ScanOMetrics”, an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer’s disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.
In the central nervous system of primates, several pathways are characterized by different spectra of axon diameters.
In vivo
methods, based on diffusion-weighted magnetic resonance imaging, can ...provide axon diameter index estimates non-invasively. However, such methods report voxel-wise estimates, which vary from voxel-to-voxel for the same white matter bundle due to partial volume contributions from other pathways having different microstructure properties. Here, we propose a novel microstructure-informed tractography approach, COMMIT
AxSize
, to resolve axon diameter index estimates at the streamline level, thus making the estimates invariant along trajectories. Compared to previously proposed voxel-wise methods, our formulation allows the estimation of a distinct axon diameter index value for each streamline, directly, furnishing a complementary measure to the existing calculation of the mean value along the bundle. We demonstrate the favourable performance of our approach comparing our estimates with existing histologically-derived measurements performed in the corpus callosum and the posterior limb of the internal capsule. Overall, our method provides a more robust estimation of the axon diameter index of pathways by jointly estimating the microstructure properties of the tissue and the macroscopic organisation of the white matter connectivity.
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.
SNAP(c) is one of a few basal transcription factors used by both RNA polymerase (pol) II and pol III. To define the set of active SNAP(c)-dependent promoters in human cells, we have localized ...genome-wide four SNAP(c) subunits, GTF2B (TFIIB), BRF2, pol II, and pol III. Among some seventy loci occupied by SNAP(c) and other factors, including pol II snRNA genes, pol III genes with type 3 promoters, and a few un-annotated loci, most are primarily occupied by either pol II and GTF2B, or pol III and BRF2. A notable exception is the RPPH1 gene, which is occupied by significant amounts of both polymerases. We show that the large majority of SNAP(c)-dependent promoters recruit POU2F1 and/or ZNF143 on their enhancer region, and a subset also recruits GABP, a factor newly implicated in SNAP(c)-dependent transcription. These activators associate with pol II and III promoters in G1 slightly before the polymerase, and ZNF143 is required for efficient transcription initiation complex assembly. The results characterize a set of genes with unique properties and establish that polymerase specificity is not absolute in vivo.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodological pitfalls in ...the design of the biomimicking geometrical configurations and the simulation parameters can lead to approximation biases. Such pitfalls affect the reliability of the estimated signal, as well as its validity and reproducibility as ground truth data. In this work, we first present a set of experiments in order to study three critical pitfalls encountered in the design of MCDS in the literature, namely, the number of simulated particles and time steps, simplifications in the intra-axonal substrate representation, and the impact of the substrate's size on the signal stemming from the extra-axonal space. The results obtained show important changes in the simulated signals and the recovered microstructure features when changes in those parameters are introduced. Thereupon, driven by our findings from the first studies, we outline a general framework able to generate complex substrates. We show the framework's capability to overcome the aforementioned simplifications by generating a complex crossing substrate, which preserves the volume in the crossing area and achieves a high packing density. The results presented in this work, along with the simulator developed, pave the way toward more realistic and reproducible Monte-Carlo simulations for Diffusion-Weighted MRI.
While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article ...is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care.
Sensory processing atypicalities are frequent in Autism Spectrum Disorder (ASD) and neurodevelopmental disorders (NDD). Different domains of sensory processing appear to be differentially altered in ...these disorders. In this study, we explored the sensory profile of two clinical cohorts, in comparison with a sample of typically developing children.
Behavioral responses to sensory stimuli were assessed using the Sensory Processing Measure (parent-report questionnaire). We included 121 ASD children, 17 carriers of the 16p11.2 deletion (Del 16p11.2) and 45 typically developing (TD) children. All participants were aged between 2 and 12 years. Additional measures included the Tactile Defensiveness and Discrimination Test-Revised, Wechsler Intelligence Scales and Autism Diagnostic Observation Schedule (ADOS-2). Statistical analyses included MANCOVA and regression analyses.
ASD children score significantly higher on all SPM subscales compared to TD. Del16p11.2 also scored higher than TD on all subscales except for tactile and olfactory/taste processing, in which they score similarly to TD. When assessing sensory modulation patterns (hyper-, hypo-responsiveness and seeking), ASD did not significantly differ from del16p11.2. Both groups had significantly higher scores across all patterns than the TD group. There was no significant association between the SPM Touch subscale and the TDDT-R.
Sensory processing was assessed using a parent-report questionnaire. Even though it captures observable behavior, a questionnaire does not assess sensory processing in all its complexity. The sample size of the genetic cohort and the small subset of ASD children with TDDT-R data render some of our results exploratory. Divergence between SPM Touch and TDDT-R raises important questions about the nature of the process that is assessed.
Touch and olfaction/taste seem to be particularly affected in ASD children compared to del16p11.2. These results indicate that parent report measures can provide a useful perspective on behavioral expression. Sensory phenotyping, when combined with neurobiological and psychophysical methods, might have the potential to provide a better understanding of the sensory processing in ASD and in other NDD.
Introduction
In patients with multiple sclerosis (MS), conventional magnetic resonance imaging (MRI) provides only limited insights into the nature of brain damage with modest clinic‐radiological ...correlation. In this study, we applied recent advances in MRI techniques to study brain microstructural alterations in early relapsing‐remitting MS (RRMS) patients with minor deficits. Further, we investigated the potential use of advanced MRI to predict functional performances in these patients.
Methods
Brain relaxometry (T1, T2, T2*) and magnetization transfer MRI were performed at 3T in 36 RRMS patients and 18 healthy controls (HC). Multicontrast analysis was used to assess for microstructural alterations in normal‐appearing (NA) tissue and lesions. A generalized linear model was computed to predict clinical performance in patients using multicontrast MRI data, conventional MRI measures as well as demographic and behavioral data as covariates.
Results
Quantitative T2 and T2* relaxometry were significantly increased in temporal normal‐appearing white matter (NAWM) of patients compared to HC, indicating subtle microedema (P = 0.03 and 0.004). Furthermore, significant T1 and magnetization transfer ratio (MTR) variations in lesions (mean T1 z‐score: 4.42 and mean MTR z‐score: −4.09) suggested substantial tissue loss. Combinations of multicontrast and conventional MRI data significantly predicted cognitive fatigue (P = 0.01, Adj‐R2 = 0.4), attention (P = 0.0005, Adj‐R2 = 0.6), and disability (P = 0.03, Adj‐R2 = 0.4).
Conclusion
Advanced MRI techniques at 3T, unraveled the nature of brain tissue damage in early MS and substantially improved clinical–radiological correlations in patients with minor deficits, as compared to conventional measures of disease.
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