White matter microstructure, traumatic brain injury, and disruptive behavior disorders in girls and boys.

Introduction: Girls and boys presenting disruptive behavior disorders (DBDs) display differences in white matter microstructure (WMM) relative to typically developing (TD) sex-matched peers. Boys with DBDs are at increased risk for traumatic brain injuries (TBIs), which are also known to impact WMM. This study aimed to disentangle associations of WMM with DBDs and TBIs. Methods: The sample included 673 children with DBDs and 836 TD children, aged 9-10, from the Adolescent Brain Cognitive Development Study. Thirteen white matter bundles previously associated with DBDs were the focus of study. Analyses were undertaken separately by sex, adjusting for callous-unemotional traits (CU), attention-deficit hyperactivity disorder (ADHD), age, pubertal stage, IQ, ethnicity, and family income. Results: Among children without TBIs, those with DBDs showed sex-specific differences in WMM of several tracts relative to TD. Most differences were associated with ADHD, CU, or both. Greater proportions of girls and boys with DBDs than sex-matched TD children had sustained TBIs. Among girls and boys with DBDs, those who had sustained TBIs compared to those not injured, displayed WMM alterations that were robust to adjustment for all covariates. Across most DBD/TD comparisons, axonal density scores were higher among children presenting DBDs. Discussion: In conclusion, in this community sample of children, those with DBDs were more likely to have sustained TBIs that were associated with additional, sex-specific, alterations of WMM. These additional alterations further compromise the future development of children with DBDs.

Progressive remodeling of structural networks following surgery for operculo-insular epilepsy.

Introduction: Operculo-insular epilepsy (OIE) is a rare condition amenable to surgery in well-selected cases. Despite the high rate of neurological complications associated with OIE surgery, most postoperative deficits recover fully and rapidly. We provide insights into this peculiar pattern of functional recovery by investigating the longitudinal reorganization of structural networks after surgery for OIE in 10 patients. Methods: Structural T1 and diffusion-weighted MRIs were performed before surgery (t0) and at 6 months (t1) and 12 months (t2) postoperatively. These images were processed with an original, comprehensive structural connectivity pipeline. Using our method, we performed comparisons between the t0 and t1 timepoints and between the t1 and t2 timepoints to characterize the progressive structural remodeling. Results: We found a widespread pattern of postoperative changes primarily in the surgical hemisphere, most of which consisted of reductions in connectivity strength (CS) and regional graph theoretic measures (rGTM) that reflect local connectivity. We also observed increases in CS and rGTMs predominantly in regions located near the resection cavity and in the contralateral healthy hemisphere. Finally, most structural changes arose in the first six months following surgery (i.e., between t0 and t1). Discussion: To our knowledge, this study provides the first description of postoperative structural connectivity changes following surgery for OIE. The ipsilateral reductions in connectivity unveiled by our analysis may result from the reversal of seizure-related structural alterations following postoperative seizure control. Moreover, the strengthening of connections in peri-resection areas and in the contralateral hemisphere may be compatible with compensatory structural plasticity, a process that could contribute to the recovery of functions seen following operculo-insular resections for focal epilepsy.

Characterization of the orientation dependence of magnetization transfer measures in single and crossing-fiber white matter.

PURPOSE: To fully characterize the orientation dependence of magnetization transfer (MT) and inhomogeneous MT (ihMT) measures in the whole white matter (WM), for both single-fiber and crossing-fiber voxels. METHODS: A characterization method was developed using the fiber orientation obtained from diffusion MRI (dMRI) with diffusion tensor imaging (DTI) and constrained spherical deconvolution. This allowed for characterization of the orientation dependence of measures in all of WM, regardless of the number of fiber orientation in a voxel. Furthermore, the orientation dependence inside 31 different WM bundles was characterized to evaluate the homogeneity of the effect. Variation of the results within and between-subject was assessed from a 12-subject dataset. RESULTS: Previous results for single-fiber voxels were reproduced and a novel characterization was produced in voxels of crossing fibers, which seems to follow trends consistent with single-fiber results. Heterogeneity of the orientation dependence across bundles was observed, but homogeneity within similar bundles was also highlighted. Differences in behavior between MT and ihMT measures, as well as the ratio and saturation versions of these, were noted. CONCLUSION: Orientation dependence characterization was proven possible over the entirety of WM. The vast range of effects and subtleties of the orientation dependence on MT measures showed the need for, but also the challenges of, a correction method.

Altered fornix integrity is associated with sleep apnea-related hypoxemia in mild cognitive impairment.

INTRODUCTION: The limbic system is critical for memory function and degenerates early in the Alzheimer's disease continuum. Whether obstructive sleep apnea (OSA) is associated with alterations in the limbic white matter tracts remains understudied. METHODS: Polysomnography, neurocognitive assessment, and brain magnetic resonance imaging (MRI) were performed in 126 individuals aged 55-86 years, including 70 cognitively unimpaired participants and 56 participants with mild cognitive impairment (MCI). OSA measures of interest were the apnea-hypopnea index and composite variables of sleep fragmentation and hypoxemia. Microstructural properties of the cingulum, fornix, and uncinate fasciculus were estimated using free water-corrected diffusion tensor imaging. RESULTS: Higher levels of OSA-related hypoxemia were associated with higher left fornix diffusivities only in participants with MCI. Microstructure of the other white matter tracts was not associated with OSA measures. Higher left fornix diffusivities correlated with poorer episodic verbal memory. DISCUSSION: OSA may contribute to fornix damage and memory dysfunction in MCI. HIGHLIGHTS: Sleep apnea-related hypoxemia was associated with altered fornix integrity in MCI. Altered fornix integrity correlated with poorer memory function. Sleep apnea may contribute to fornix damage and memory dysfunction in MCI.

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study.

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Structural white matter properties and cognitive resilience to tau pathology.

INTRODUCTION: We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. METHODS: We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-ß/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. RESULTS: Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. DISCUSSION: White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. HIGHLIGHTS: Aß and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.

White Matter Microstructural Underpinnings of Mild Behavioral Impairment in Parkinson's Disease.

BACKGROUND: Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood. OBJECTIVE: The aim was to explore the changes in white matter microstructure linked to MBI and mild cognitive impairment (MCI) in early- to mid-stage PD using diffusion magnetic resonance imaging (dMRI). METHODS: A total of 91 PD patients and 36 healthy participants were recruited and underwent anatomical MRI and dMRI, a comprehensive neuropsychological battery, and the completion of the Mild Behavioral Impairment-Checklist. Metrics of white matter integrity included tissue fractional anisotropy (FAt) and radial diffusivity (RDt), free water (FW), and fixel-based apparent fiber density (AFD). RESULTS: The connection between the left amygdala and the putamen was disrupted when comparing PD patients with MBI (PD-MBI) to PD-non-MBI, as evidenced by increased RDt (η2 = 0.09, P = 0.004) and both decreased AFD (η2 = 0.05, P = 0.048) and FAt (η2 = 0.12, P = 0.014). Compared to controls, PD patients with both MBI and MCI demonstrated increased FW for the connection between the left orbitofrontal gyrus (OrG) and the hippocampus (η2 = 0.22, P = 0.008), augmented RDt between the right OrG and the amygdala (η2 = 0.14, P = 0.008), and increased RDt (η2 = 0.25, P = 0.028) with decreased AFD (η2 = 0.10, P = 0.046) between the right OrG and the caudate nucleus. CONCLUSION: MBI is associated with abnormal microstructure of connections involving the orbitofrontal cortex, putamen, and amygdala. To our knowledge, this is the first assessment of the white matter microstructure in PD-MBI using dMRI. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study.

Introduction: Multi-shell diffusion Magnetic Resonance Imaging (dMRI) data has been widely used to characterise white matter microstructure in several neurodegenerative diseases. The lack of standardised dMRI protocols often implies the acquisition of redundant measurements, resulting in prolonged acquisition times. In this study, we investigate the impact of the number of gradient directions on Diffusion Tensor Imaging (DTI) and on Neurite Orientation Dispersion and Density Imaging (NODDI) metrics. Methods: Data from 124 healthy controls collected in three different longitudinal studies were included. Using an in-house algorithm, we reduced the number of gradient directions in each data shell. We estimated DTI and NODDI measures on six white matter bundles clinically relevant for neurodegenerative diseases. Results: Fractional Anisotropy (FA) measures on bundles where data were sampled at the 30% rate, showed a median L1 distance of up to 3.92% and a 95% CI of (1.74, 8.97)% when compared to those obtained at reference sampling. Mean Diffusivity (MD) reached up to 4.31% and a 95% CI of (1.60, 16.98)% on the same premises. At a sampling rate of 50%, we obtained a median of 3.90% and a 95% CI of (1.99, 16.65)% in FA, and 5.49% with a 95% CI of (2.14, 21.68)% in MD. The Intra-Cellular volume fraction (ICvf) median L1 distance was up to 2.83% with a 95% CI of (1.98, 4.82)% at a 30% sampling rate and 3.95% with a 95% CI of (2.39, 7.81)% at a 50% sampling rate. The volume difference of the reconstructed white matter at reference and 50% sampling reached a maximum of (2.09 ± 0.81)%. Discussion: In conclusion, DTI and NODDI measures reported at reference sampling were comparable to those obtained when the number of dMRI volumes was reduced by up to 30%. Close to reference DTI and NODDI metrics were estimated with a significant reduction in acquisition time using three shells, respectively with: 4 directions at a b value of 700 s/mm2, 14 at 1000 s/mm2, and 32 at 2000 s/mm2. The study revealed aspects that can be important for large-scale clinical studies on bundle-specific diffusion MRI.

Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning.

Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters. In vivo and synthetic brain 5D-Diffusion-T1-T2∗-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cramér-Rao lower bound optimisation. The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value. The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.

Visual evoked potentials in multiple sclerosis: P100 latency and visual pathway damage including the lateral geniculate nucleus.

OBJECTIVE: To explore associations of the main component (P100) of visual evoked potentials (VEP) to pre- and postchiasmatic damage in multiple sclerosis (MS). METHODS: 31 patients (median EDSS: 2.5), 13 with previous optic neuritis (ON), and 31 healthy controls had VEP, optical coherence tomography and magnetic resonance imaging. We tested associations of P100-latency to the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell/inner plexiform layers (GCIPL), lateral geniculate nucleus volume (LGN), white matter lesions of the optic radiations (OR-WML), fractional anisotropy of non-lesional optic radiations (NAOR-FA), and to the mean thickness of primary visual cortex (V1). Effect sizes are given as marginal R2 (mR2). RESULTS: P100-latency, pRNFL, GCIPL and LGN in patients differed from controls. Within patients, P100-latency was significantly associated with GCIPL (mR2 = 0.26), and less strongly with OR-WML (mR2 = 0.17), NAOR-FA (mR2 = 0.13) and pRNFL (mR2 = 0.08). In multivariate analysis, GCIPL and NAOR-FA remained significantly associated with P100-latency (mR2 = 0.41). In ON-patients, P100-latency was significantly associated with LGN volume (mR2 = -0.56). CONCLUSIONS: P100-latency is affected by anterior and posterior visual pathway damage. In ON-patients, damage at the synapse-level (LGN) may additionally contribute to latency delay. SIGNIFICANCE: Our findings corroborate post-chiasmatic contributions to the VEP-signal, which may relate to distinct pathophysiological mechanisms in MS.

Multimodal study of multilevel pulvino-temporal connections: a new piece in the puzzle of lexical retrieval networks.

Advanced methods of imaging and mapping the healthy and lesioned brain have allowed for the identification of the cortical nodes and white matter tracts supporting the dual neurofunctional organization of language networks in a dorsal phonological and a ventral semantic stream. Much less understood are the anatomical correlates of the interaction between the two streams; one hypothesis being that of a subcortically mediated interaction, through crossed cortico-striato-thalamo-cortical and cortico-thalamo-cortical loops. In this regard, the pulvinar is the thalamic subdivision that has most regularly appeared as implicated in the processing of lexical retrieval. However, descriptions of its connections with temporal (language) areas remain scarce. Here we assess this pulvino-temporal connectivity using a combination of state-of-the-art techniques: white matter stimulation in awake surgery and postoperative diffusion MRI (n = 4), virtual dissection from the Human Connectome Project 3 and 7 T datasets (n = 172) and operative microscope-assisted post-mortem fibre dissection (n = 12). We demonstrate the presence of four fundamental fibre contingents: (i) the anterior component (Arnold's bundle proper) initially described by Arnold in the 19th century and destined to the anterior temporal lobe; (ii) the optic radiations-like component, which leaves the pulvinar accompanying the optical radiations and reaches the posterior basal temporal cortices; (iii) the lateral component, which crosses the temporal stem orthogonally and reaches the middle temporal gyrus; and (iv) the auditory radiations-like component, which leaves the pulvinar accompanying the auditory radiations to the superomedial aspect of the temporal operculum, just posteriorly to Heschl's gyrus. Each of those components might correspond to a different level of information processing involved in the lexical retrieval process of picture naming.

A unified filtering method for estimating asymmetric orientation distribution functions.

Numerous filtering methods have been proposed for estimating asymmetric orientation distribution functions (ODFs) for diffusion magnetic resonance imaging (dMRI). It can be hard to make sense of all these different methods, which share similar features and result in similar outputs. In this work, we disentangle these many filtering methods proposed in the past and combine them into a novel, unified filtering equation. We also propose a self-supervised data-driven approach for calibrating the filtering parameter values. Our equation is implemented in an open-source GPU-accelerated python software to facilitate its integration into any existing dMRI processing pipeline. Our method is applied on multi-shell multi-tissue fiber ODFs from the Human Connectome Project dataset (1.25 mm3 native resolution) and on single-shell single-tissue fiber ODFs from the Bilingualism and the Brain dataset (2.0 mm3 isotropic resolution) to evaluate the occurrence of asymmetric patterns on different spatial resolutions, representing cutting-edge and "clinical" research data. Asymmetry measures such as the asymmetric index (ASI) and our novel number of fiber directions (NuFiD) are then used to explain the behaviour of our method in these images. The contributions of this work are: (i) the disentanglement and unification of filtering methods for estimating asymmetric ODFs; (ii) a calibration method for automatically fixing the parameters governing the filtering; (iii) an open-source, efficient implementation of our unified filtering method for estimating asymmetric ODFs; (iv) a novel number of fiber directions (NuFiD) index for explaining asymmetric fiber configurations; and (v) a novel template of asymmetries, revealing that our filtering method estimates asymmetric configurations in at least 50% of the brain voxels (∼31% of the white matter and ∼63% of the gray matter).

What matters in reinforcement learning for tractography.

Recently, deep reinforcement learning (RL) has been proposed to learn the tractography procedure and train agents to reconstruct the structure of the white matter without manually curated reference streamlines. While the performances reported were competitive, the proposed framework is complex, and little is still known about the role and impact of its multiple parts. In this work, we thoroughly explore the different components of the proposed framework, such as the choice of the RL algorithm, seeding strategy, the input signal and reward function, and shed light on their impact. Approximately 7,400 models were trained for this work, totalling nearly 41,000 h of GPU time. Our goal is to guide researchers eager to explore the possibilities of deep RL for tractography by exposing what works and what does not work with the category of approach. As such, we ultimately propose a series of recommendations concerning the choice of RL algorithm, the input to the agents, the reward function and more to help future work using reinforcement learning for tractography. We also release the open source codebase, trained models, and datasets for users and researchers wanting to explore reinforcement learning for tractography.

Electrostimulation of the white matter of the posterior insula and medial operculum: perception of vibrations, heat, and pain.

ABSTRACT: This study aimed to characterize the sensory responses observed when electrically stimulating the white matter surrounding the posterior insula and medial operculum (PIMO). We reviewed patients operated on under awake conditions for a glioma located in the temporoparietal junction. Patients' perceptions were retrieved from operative reports. Stimulation points were registered in the Montreal Neurological Institute template. A total of 12 stimulation points in 8 patients were analyzed. Painful sensations in the contralateral leg were reported (5 sites in 5 patients) when stimulating the white matter close to the parcel OP2/3 of the Glasser atlas. Pain had diverse qualities: burning, tingling, crushing, or electric shock. More laterally, in the white matter of OP1, pain and heat sensations in the upper part of the body were described (5 sites in 2 patients). Intermingled with these sites, vibration sensations were also reported (3 sites in 2 patients). Based on the tractograms of 44 subjects from the Human Connectome Project data set, we built a template of the pathways linking the thalamus to OP2/3 and OP1. Pain sites were located in the thalamo-OP2/3 and thalamo-OP1 tracts. Heat sites were located in the thalamo-OP1 tract. In the 227 awake surgeries performed for a tumor located outside of the PIMO region, no patients ever reported pain or heat sensations when stimulating the white matter. Thus, we propose that the thalamo-PIMO connections constitute the main cortical inputs for nociception and thermoception and emphasize that preserving these fibers is of utmost importance to prevent the postoperative onset of a debilitating insulo-opercular pain syndrome.

Longitudinal evolution of diffusion metrics after left hemisphere ischaemic stroke.

White matter is often severely affected after human ischaemic stroke. While animal studies have suggested that various factors may contribute to white matter structural damage after ischaemic stroke, the characterization of damaging processes to the affected hemisphere after human stroke remains poorly understood. Thus, the present study aims to thoroughly describe the longitudinal pattern of evolution of diffusion magnetic resonance imaging metrics in different parts of the ipsilesional white matter after stroke. We acquired diffusion and anatomical images in 17 patients who had suffered from a single left hemisphere ischaemic stroke, at 24-72 h, 8-14 days and 6 months post-stroke. For each patient, we created three regions of interest: (i) the white matter lesion; (ii) the perilesional white matter; and (iii) the remaining white matter of the left hemisphere. We extracted diffusion metrics (fractional anisotropy, mean, axial and radial diffusivities) for each region and conducted two-way repeated measures ANOVAs with stage post-stroke (acute, subacute and chronic) × regions of interest (white matter lesion, perilesional white matter and remaining white matter). Fractional anisotropy values stayed consistent across time-points, with significantly lower values in the white matter lesion compared to the perilesional white matter and remaining white matter tissue. Fractional anisotropy values of the perilesional white matter were also significantly lower than that of the remaining white matter. Mean, axial and radial diffusivities in the white matter lesion were all decreased in the acute stage compared to perilesional white matter and remaining white matter, but significantly increased in both the subacute and chronic stages. Significant increases in mean and radial diffusivities in the perilesional white matter were seen in the later stages of stroke. Our findings suggest that various physiological processes are at play in the acute, subacute and chronic stages following ischaemic stroke, with the infarct territory and perilesional white matter affected by ischaemia at different rates and to different extents throughout the stroke recovery stages. The examination of multiple diffusivity metrics may inform us about the mechanisms occurring at different time-points, i.e. focal swelling, axonal damage or myelin loss.

Exploratory analysis of cortical thickness in low- and high-fit young adults.

OBJECTIVE: Studies have shown changes in the human brain associated with physical activity and cardiorespiratory fitness (CRF). The effects of CRF on cortical thickness have been well-described in older adults, where a positive association between CRF and cortical thickness has been reported, but the impact of sustained aerobic activity in young adults remains poorly described. Here, exploratory analysis was performed on cortical thickness data that was collected in groups of fit and sedentary young adults. METHODS: Twenty healthy sedentary individuals (<2 h/week physical activity) were compared to 20 active individuals (>6 h/week physical activity) and cortical thickness was measured in 34 cortical areas. Cortical thickness values were compared between groups, and correlations between cortical thickness and VO2 max were tested. RESULTS: Cardiorespiratory fitness was significantly higher in active individuals compared to sedentary individuals. Cortical thickness was lower in regions of the left (lateral and medial orbitofrontal cortex, pars orbitalis, pars triangularis, rostral anterior cingulate cortex, superior temporal cortex and frontal pole) and right (lateral and medial orbitofrontal cortex and pars opercularis) hemispheres. Only the left frontal pole and right lateral orbitofrontal cortical thickness remained significant after false discovery rate correction. Negative correlations were observed between VO2 max and cortical thickness in the left (frontal pole) and right (caudal anterior cingulate and medial orbitofrontal cortex) hemispheres. CONCLUSION: The present exploratory analysis supports previous findings suggesting that neuroplastic effects of cardiorespiratory fitness may be attenuated in young compared with older individuals, underscoring a moderating effect of age on the relationship between fitness and cortical thickness.

White matter microstructure is differently associated with executive functioning in youth born with congenital heart disease and youth born preterm.

INTRODUCTION: Executive function deficits and adverse psychological outcomes are common in youth with congenital heart disease (CHD) or born preterm. Association white matter bundles play a critical role in higher order cognitive and emotional functions and alterations to their microstructural organization may result in adverse neuropsychological functioning. This study aimed to examine the relationship of myelination and axon density and orientation alterations within association bundles with executive functioning, psychosocial well-being, and resilience in youth with CHD or born preterm. METHODS: Youth aged 16 to 26 years born with complex CHD or preterm at ≤33 weeks of gestational age and healthy controls completed a brain MRI and self-report assessments of executive functioning, psychosocial well-being, and resilience. Multicomponent driven equilibrium single-pulse observation of T1 and T2 and neurite orientation dispersion and density imaging were used to calculate average myelin water fraction (MWF), neurite density index (NDI), and orientation dispersion index values for eight bilateral association bundles. The relationships of bundle-average metrics with neuropsychological outcomes were explored with linear regression and mediation analyses. RESULTS: In the CHD group, lower MWF in several bundles was associated with poorer working memory and behavioral self-monitoring and mediated self-monitoring deficits relative to controls. In the preterm group, lower NDI in several bundles was associated with poorer emotional control and lower MWF in the left superior longitudinal fasciculus III mediated planning/organizing deficits relative to controls. No significant relationships were observed for psychosocial well-being or resilience. CONCLUSION: The findings of this study suggest that microstructural alterations to association bundles, including lower myelination and axon density, have different relationships with executive functioning in youth with CHD and youth born preterm. Future studies should aim to characterize other neurobiological, social, and environmental influences that may interact with white matter microstructure and neuropsychological functioning in these at-risk individuals.

The Challenge of Diffusion Magnetic Resonance Imaging in Cerebral Palsy: A Proposed Method to Identify White Matter Pathways.

Cerebral palsy (CP), a neuromotor disorder characterized by prenatal brain lesions, leads to white matter alterations and sensorimotor deficits. However, the CP-related diffusion neuroimaging literature lacks rigorous and consensual methodology for preprocessing and analyzing data due to methodological challenges caused by the lesion extent. Advanced methods are available to reconstruct diffusion signals and can update current advances in CP. Our study demonstrates the feasibility of analyzing diffusion CP data using a standardized and open-source pipeline. Eight children with CP (8-12 years old) underwent a single diffusion magnetic resonance imaging (MRI) session on a 3T scanner (Achieva 3.0T (TX), Philips Healthcare Medical Systems, Best, The Netherlands). Exclusion criteria were contraindication to MRI and claustrophobia. Anatomical and diffusion images were acquired. Data were corrected and analyzed using Tractoflow 2.3.0 version, an open-source and robust tool. The tracts were extracted with customized procedures based on existing atlases and freely accessed standardized libraries (ANTs, Scilpy). DTI, CSD, and NODDI metrics were computed for each tract. Despite lesion heterogeneity and size, we successfully reconstructed major pathways, except for a participant with a larger lesion. Our results highlight the feasibility of identifying and quantifying subtle white matter pathways. Ultimately, this will increase our understanding of the clinical symptoms to provide precision medicine and optimize rehabilitation.

Impact of follow ups, time interval and study duration in diffusion & myelin MRI clinical study in MS.

It is currently unknown how quantitative diffusion and myelin MRI designs affect the results of a longitudinal study. We used two independent datasets containing 6 monthly MRI measurements from 20 healthy controls and 20 relapsing-remitting multiple sclerosis (RR-MS) patients. Six designs were tested, including 3 MRI acquisitions, either over 6 months or over a shorter study duration, with balanced (same interval) or unbalanced (different interval) time intervals between MRI acquisitions. First, we show that in RR-MS patients, the brain changes over time obtained with 3 MRI acquisitions were similar to those observed with 5 MRI acquisitions and that designs with an unbalanced time interval showed the highest similarity, regardless of study duration. No significant brain changes were found in the healthy controls over the same periods. Second, the study duration affects the sample size in the RR-MS dataset; a longer study requires more subjects and vice versa. Third, the number of follow-up acquisitions and study duration affect the sensitivity and specificity of the associations with clinical parameters, and these depend on the white matter bundle and MRI measure considered. Together, this suggests that the optimal design depends on the assumption of the dynamics of change in the target population and the accuracy required to capture these dynamics. Thus, this work provides a better understanding of key factors to consider in a longitudinal study and provides clues for better strategies in clinical trial design.

Improved Functionnectome by dissociating the contributions of white matter fiber classes to functional activation.

Integrating the underlying brain circuit's structural and functional architecture is required to explore the functional organization of cognitive networks. In that regard, we recently introduced the Functionnectome. This structural-functional method combines an fMRI acquisition with tractography-derived white matter connectivity data to map cognitive processes onto the white matter. However, this multimodal integration faces three significant challenges: (1) the necessarily limited overlap between tractography streamlines and the grey matter, which may reduce the amount of functional signal associated with the related structural connectivity; (2) the scrambling effect of crossing fibers on functional signal, as a single voxel in such regions can be structurally connected to several cognitive networks with heterogeneous functional signals; and (3) the difficulty of interpretation of the resulting cognitive maps, as crossing and overlapping white matter tracts can obscure the organization of the studied network. In the present study, we tackled these problems by developing a streamline-extension procedure and dividing the white matter anatomical priors between association, commissural, and projection fibers. This approach significantly improved the characterization of the white matter involvement in the studied cognitive processes. The new Functionnectome priors produced are now readily available, and the analysis workflow highlighted here should also be generalizable to other structural-functional approaches. We improved the Functionnectome approach to better study the involvement of white matter in brain function by separating the analysis of the three classes of white matter fibers (association, commissural, and projection fibers). This step successfully clarified the activation maps and increased their statistical significance.