David Romascano

The challenge of mapping the human connectome based on diffusion tractography

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.Though tractography is widely used, it has not been systematically validated. Here, authors report results from 20 groups showing that many tractography algorithms produce both valid and invalid bundles.

Structural abnormalities in the thalamus of migraineurs with aura: A multiparametric study at 3 T

Background and objectives: The thalamus exerts a pivotal role in pain processing and cortical excitability control, and migraine is characterized by repeated pain attacks and abnormal cortical habituation to excitatory stimuli. This work aimed at studying the microstructure of the thalamus in migraine patients using an innovative multiparametric approach at high‐field magnetic resonance imaging (MRI). Design: We examined 37 migraineurs (22 without aura, MWoA, and 15 with aura, MWA) as well as 20 healthy controls (HC) in a 3‐T MRI equipped with a 32‐channel coil. We acquired whole‐brain T1 relaxation maps and computed magnetization transfer ratio (MTR), generalized fractional anisotropy, and T2* maps to probe microstructural and connectivity integrity and to assess iron deposition. We also correlated the obtained parametric values with the average monthly frequency of migraine attacks and disease duration. Results: T1 relaxation time was significantly shorter in the thalamus of MWA patients compared with MWoA (P < 0.001) and HC (P ≤ 0.01); in addition, MTR was higher and T2* relaxation time was shorter in MWA than in MWoA patients (P < 0.05, respectively). These data reveal broad microstructural alterations in the thalamus of MWA patients compared with MWoA and HC, suggesting increased iron deposition and myelin content/cellularity. However, MWA and MWoA patients did not show any differences in the thalamic nucleus involved in pain processing in migraine. Conclusions: There are broad microstructural alterations in the thalamus of MWA patients that may underlie abnormal cortical excitability control leading to cortical spreading depression and visual aura. Hum Brain Mapp 35:1461–1468, 2014.

Advanced MRI unravels the nature of tissue alterations in early multiple sclerosis

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.

Multicontrast connectometry: A new tool to assess cerebellum alterations in early relapsing-remitting multiple sclerosis.

Background: Cerebellar pathology occurs in late multiple sclerosis (MS) but little is known about cerebellar changes during early disease stages. In this study, we propose a new multicontrast “connectometry” approach to assess the structural and functional integrity of cerebellar networks and connectivity in early MS. Methods: We used diffusion spectrum and resting‐state functional MRI (rs‐fMRI) to establish the structural and functional cerebellar connectomes in 28 early relapsing‐remitting MS patients and 16 healthy controls (HC). We performed multicontrast “connectometry” by quantifying multiple MRI parameters along the structural tracts (generalized fractional anisotropy‐GFA, T1/T2 relaxation times and magnetization transfer ratio) and functional connectivity measures. Subsequently, we assessed multivariate differences in local connections and network properties between MS and HC subjects; finally, we correlated detected alterations with lesion load, disease duration, and clinical scores. Results: In MS patients, a subset of structural connections showed quantitative MRI changes suggesting loss of axonal microstructure and integrity (increased T1 and decreased GFA, P < 0.05). These alterations highly correlated with motor, memory and attention in patients, but were independent of cerebellar lesion load and disease duration. Neither network organization nor rs‐fMRI abnormalities were observed at this early stage. Conclusion: Multicontrast cerebellar connectometry revealed subtle cerebellar alterations in MS patients, which were independent of conventional disease markers and highly correlated with patient function. Future work should assess the prognostic value of the observed damage. Hum Brain Mapp 36:1609–1619, 2015.

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.

A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment

Objectives The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI). Methods Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects. Results Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics. Conclusion Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.

Accelerated Microstructure Imaging via Convex Optimisation for regions with multiple fibres (AMICOx)

This paper reviews and extends our previous work to enable fast axonal diameter mapping from diffusion MRI data in the presence of multiple fibre populations within a voxel. Most of the existing mi-crostructure imaging techniques use non-linear algorithms to fit their data models and consequently, they are computationally expensive and usually slow. Moreover, most of them assume a single axon orientation while numerous regions of the brain actually present more complex configurations, e.g. fiber crossing. We present a flexible framework, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented. We show through numerical simulations the ability of our method to correctly estimate the microstructure features (mean axon diameter and intra-cellular volume fraction) in crossing regions.

Sparse wars: A survey and comparative study of spherical deconvolution algorithms for diffusion MRI

&NA; Spherical deconvolution methods are widely used to estimate the brains 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. HighlightsThere 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.

Limits to anatomical accuracy of diffusion tractography using modern approaches

&NA; 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 tractographys 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. HighlightsOrganized 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.

Central nervous system microbleeds in the acute phase are associated with structural integrity by DTI one year after mild traumatic brain injury: A longitudinal study

INTRODUCTION Several imaging modalities are under investigation to unravel the pathophysiological mystery of delayed performance deficits in patients after mild traumatic brain injury (mTBI). Although both imaging and neuropsychological studies have been conducted, only few data on longitudinal correlations of diffusion tensor imaging (DTI), susceptibility weighted imaging (SWI) and extensive neuropsychological testing exist. METHODS MRI with T1- and T2-weighted, SWI and DTI sequences at baseline and 12 months of 30 mTBI patients were compared with 20 healthy controls. Multiparametric assessment included neuropsychological testing of cognitive performance and post-concussion syndrome (PCS) at baseline, 3 and 12 months post-injury. Data analysis encompassed assessment of cerebral microbleeds (Mb) in SWI, tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM) of DTI (VBM-DTI). Imaging markers were correlated with neuropsychological testing to evaluate sensitivity to cognitive performance and post-concussive symptoms. RESULTS Patients with Mb in SWI in the acute phase showed worse performance in several cognitive tests at baseline and in the follow-ups during the chronic phase and higher symptom severity in the post concussion symptom scale (PCSS) at twelve months post-injury. In the acute phase there was no statistical difference in structural integrity as measured with DTI between mTBI patients and healthy controls. At twelve months post-injury, loss of structural integrity in mTBI patients was found in nearly all DTI indices compared to healthy controls. CONCLUSIONS Presence of Mb detected by SWI was associated with worse cognitive outcome and persistent PCS in mTBI patients, while DTI did not prove to predict neuropsychological outcome in the acute phase.