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We aimed to compare the ability of diffusion tensor imaging and multi‐compartment spherical mean technique to detect focal tissue damage and in distinguishing between different connectivity patterns associated with varying clinical outcomes in multiple sclerosis (MS). Seventy‐six people diagnosed with MS were scanned using a SIEMENS Prisma Fit 3T magnetic resonance imaging (MRI), employing both conventional (T1w and fluid‐attenuated inversion recovery) and advanced diffusion MRI sequences from which fractional anisotropy (FA) and microscopic FA (μFA) maps were generated. Using automated fiber quantification (AFQ), we assessed diffusion profiles across multiple white matter (WM) pathways to measure the sensitivity of anisotropy diffusion metrics in detecting localized tissue damage. In parallel, we analyzed structural brain connectivity in a specific patient cohort to fully grasp its relationships with cognitive and physical clinical outcomes. This evaluation comprehensively considered different patient categories, including cognitively preserved (CP), mild cognitive deficits (MCD), and cognitively impaired (CI) for cognitive assessment, as well as groups distinguished by physical impact: those with mild disability (Expanded Disability Status Scale [EDSS] <=3) and those with moderate–severe disability (EDSS >3). In our initial objective, we employed Ridge regression to forecast the presence of focal MS lesions, comparing the performance of μFA and FA. μFA exhibited a stronger association with tissue damage and a higher predictive precision for focal MS lesions across the tracts, achieving an R‐squared value of.57, significantly outperforming the R‐squared value of.24 for FA (p‐value <.001). In structural connectivity, μFA exhibited more pronounced differences than FA in response to alteration in both cognitive and physical clinical scores in terms of effect size and number of connections. Regarding cognitive groups, FA differences between CP and MCD groups were limited to 0.5% of connections, mainly around the thalamus, while μFA revealed changes in 2.5% of connections. In the CP and CI group comparison, which have noticeable cognitive differences, the disparity was 5.6% for FA values and 32.5% for μFA. Similarly, μFA outperformed FA in detecting WM changes between the MCD and CI groups, with 5% versus 0.3% of connections, respectively. When analyzing structural connectivity between physical disability groups, μFA still demonstrated superior performance over FA, disclosing a 2.1% difference in connectivity between regions closely associated with physical disability in MS. In contrast, FA spotted a few regions, comprising only 0.6% of total connections. In summary, μFA emerged as a more effective tool than FA in predicting MS lesions and identifying structural changes across patients with different degrees of cognitive and global disability, offering deeper insights into the complexities of MS‐related impairments. [ABSTRACT FROM AUTHOR]

Objective: Juvenile fibromyalgia (JFM) is a chronic pain syndrome predominantly affecting adolescent girls. Resilience may be a protective factor in coping with pain, reducing affective burden, and promoting positive outlooks. Brain regions affected in JFM overlap with those linked to resilience, particularly in the default-mode network (DMN). We investigate the role of resilience on core somatic and affective symptoms in JFM and assess the neurophysiological substrates for the first time., Methods: Forty-one girls with JFM and 40 pain-free adolescents completed a resting-state fMRI assessment and self-report questionnaires. We used clustering analyses to group JFM participants based on resilience, and principal component analyses to summarize core somatic and affective symptoms. We estimated whole-brain and within-DMN connectivity and assessed differences between higher and lower resilience JFM groups and compared their connectivity patterns to pain-free participants., Results: The higher resilience JFM group had less affective (T=4.03; p<.001) but similar core somatic symptoms (T=1.05; p=.302) than the lower resilience JFM group. They had increased whole-brain (T's>3.90, pFDR's<.03) and within-DMN (T=2.20, p=.03) connectivity strength, and higher connectivity between DMN nodes and self-referential, regulatory, and reward-processing regions. Conversely, higher DMN-premotor connectivity was observed in the lower resilience group., Conclusion: JFM participants with higher resilience were protected affectively but not in core somatic symptoms. Greater resilience was accompanied by higher signal integration within the DMN, a network central to internally oriented attention and flexible attention shifting. Crucially, the connectivity pattern in highly resilient patients resembled that of pain-free adolescents, which was not the case for the lower resilience group., Competing Interests: Conflict of Interest Statement The authors have no conflict of interest to declare.

Objective: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group., Methods: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in (1) all epilepsies, (2) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), (3) nonlesional temporal lobe epilepsy, (4) genetic generalized epilepsy, and (5) extratemporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness., Results: Across all epilepsies, reduced total cerebellar volume was observed (d = .42). Maximum volume loss was observed in the corpus medullare (d max  = .49) and posterior lobe gray matter regions, including bilateral lobules VIIB (d max  = .47), crus I/II (d max  = .39), VIIIA (d max  = .45), and VIIIB (d max  = .40). Earlier age at seizure onset ( η ρ max 2  = .05) and longer epilepsy duration ( η ρ max 2  = .06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE, with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls., Significance: We provide robust evidence of deep cerebellar and posterior lobe subregional gray matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in nonmotor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellar subregional damage into neurobiological models of epilepsy., (© 2024 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Introduction: Regional gray matter (GM) alterations have been reported in early-onset psychosis (EOP, onset before age 18), but previous studies have yielded conflicting results, likely due to small sample sizes and the different brain regions examined. In this study, we conducted a whole brain voxel-based morphometry (VBM) analysis in a large sample of individuals with EOP, using the newly developed ENIGMA-VBM tool., Methods: 15 independent cohorts from the ENIGMA-EOP working group participated in the study. The overall sample comprised T1-weighted MRI data from 482 individuals with EOP and 469 healthy controls. Each site performed the VBM analysis locally using the standardized ENIGMA-VBM tool. Statistical parametric T-maps were generated from each cohort and meta-analyzed to reveal voxel-wise differences between EOP and healthy controls as well as the individual-based association between GM volume and age of onset, chlorpromazine (CPZ) equivalent dose, and other clinical variables., Results: Compared with healthy controls, individuals with EOP showed widespread lower GM volume encompassing most of the cortex, with the most marked effect in the left median cingulate (Hedges' g = 0.55, p = 0.001 corrected), as well as small clusters of lower white matter (WM), whereas no regional GM or WM volumes were higher in EOP. Lower GM volume in the cerebellum, thalamus and left inferior parietal gyrus was associated with older age of onset. Deficits in GM in the left inferior frontal gyrus, right insula, right precentral gyrus and right superior frontal gyrus were also associated with higher CPZ equivalent doses., Conclusion: EOP is associated with widespread reductions in cortical GM volume, while WM is affected to a smaller extent. GM volume alterations are associated with age of onset and CPZ equivalent dose but these effects are small compared to case-control differences. Mapping anatomical abnormalities in EOP may lead to a better understanding of the role of psychosis in brain development during childhood and adolescence., (© 2023. The Author(s).)

Emerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset <18 years). However, as neuroimaging methods vary and sample sizes are modest, results remain inconclusive. Using harmonized data processing protocols and a mega-analytic approach, we compared white matter microstructure in EOP and healthy controls using diffusion tensor imaging (DTI). Our sample included 321 adolescents with EOP (median age = 16.6 years, interquartile range (IQR) = 2.14, 46.4% females) and 265 adolescent healthy controls (median age = 16.2 years, IQR = 2.43, 57.7% females) pooled from nine sites. All sites extracted mean fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) for 25 white matter regions of interest per participant. ComBat harmonization was performed for all DTI measures to adjust for scanner differences. Multiple linear regression models were fitted to investigate case-control differences and associations with clinical variables in regional DTI measures. We found widespread lower FA in EOP compared to healthy controls, with the largest effect sizes in the superior longitudinal fasciculus (Cohen's d = 0.37), posterior corona radiata (d = 0.32), and superior fronto-occipital fasciculus (d = 0.31). We also found widespread higher RD and more localized higher MD and AD. We detected significant effects of diagnostic subgroup, sex, and duration of illness, but not medication status. Using the largest EOP DTI sample to date, our findings suggest a profile of widespread white matter microstructure alterations in adolescents with EOP, most prominently in male individuals with early-onset schizophrenia and individuals with a shorter duration of illness., (© 2022. The Author(s).)

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome., Methods: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom., Results: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%., Significance: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy., (© 2021 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Glutamic acid decarboxylase 65 antibodies (anti-GAD65) have been found in patients with late-onset chronic temporal lobe epilepsy (TLE). No prior neuroimaging studies have addressed how they affect hippocampal volume and shape and how they relate to cognitive abnormalities. We aimed to investigate both brain structure and function in patients with isolated TLE and high anti-GAD65 levels (RIA ≥ 2000 U/ml) compared to 8 non-immune mesial TLE (niTLE) and 8 healthy controls (HC). Hippocampal subfield volume properties were correlated with the duration of the disease and cognitive test scores. The affected hippocampus of GAD-TLE patients showed no volume changes to matched HC whereas niTLE volumes were significantly smaller. Epilepsy duration in GAD-TLE patients correlated negatively with volumes in the presubiculum, subiculum, CA1, CA2-3, CA4, molecular layer and granule cell-molecular layer of the dentate nucleus. We found differences by advanced vertex-wise shape analysis in the anterior hippocampus of the left GAD-TLE compared to HC whereas left niTLE showed bilateral posterior hippocampus deformation. Verbal deficits were similar in GAD-TLE and niTLE but did not correlate to volume changes. These data might suggest a distinct expression of hippocampal structural and functional abnormalities based on the immune response.

The Extended Frontal Aslant Tract (exFAT) is a recently described tractography-based extension of the Frontal Aslant Tract connecting Broca's territory to both supplementary and pre-supplementary motor areas, and more anterior prefrontal regions. In this study, we aim to characterize the microstructural properties of the exFAT trajectories as a means to perform a laterality analysis to detect interhemispheric structural differences along the tracts using the Human Connectome Project (HCP) dataset. To that end, the bilateral exFAT was reconstructed for 3T and 7T HCP acquisitions in 120 randomly selected subjects. As a complementary exploration of the exFAT anatomy, we performed a white matter dissection of the exFAT trajectory of two ex-vivo left hemispheres that provide a qualitative assessment of the tract profiles. We assessed the lateralization structural differences in the exFAT by performing: (i) a laterality comparison between the mean microstructural diffusion-derived parameters for the exFAT trajectories, (ii) a laterality comparison between the tract profiles obtained by applying the Automated Fiber Quantification (AFQ) algorithm, and (iii) a cross-validated Machine Learning (ML) classifier analysis using single and combined tract profiles parameters for single-subject classification. The mean microstructural diffusion-derived parameter comparison showed statistically significant differences in mean FA values between left and right exFATs in the 3T sample. The diffusion parameters studied with the AFQ technique suggest that the inferiormost half of the exFAT trajectory has a hemispheric-dependent fingerprint of microstructural properties, with an increased measure of tissue hindrance in the orthogonal plane and a decreased measure of orientational dispersion along the main tract direction in the left exFAT compared to the right exFAT. The classification accuracy of the ML models showed a high agreement with the magnitude of those differences., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

The extended frontal aslant tract (exFAT) is a tractography-based extension of the frontal aslant tract (FAT) which has been shown to be related with language and working memory performance in healthy human adults, but whether those functional implications map to structurally separate regions along its trajectory is still an open question. We present a tractography-informed Voxel-Based Morphometry procedure capable of detecting local tract-specific structural differences in white matter regions and apply it in two maximum variation sampling studies by comparing local differences in diffusion-derived microstructural parameters and fiber density along the exFAT territory between top performers and bottom performers in language and working memory tasks. In the right hemisphere we were able to detect, without prior constraints, a vertical frontal aslant component approximating the original FAT trajectory whose fiber density was significantly correlated with language (but not working memory) performance and an anterior cluster component corresponding to a distinct anterior frontal aslant component whose fiber density was significantly correlated with working memory (but not language) performance. The reported sub-division of the exFAT territory describes a set of frontal connections that are compatible with previously reported results on the Broca's territory and frontal cortex hierarchical organization along an anterior-posterior gradient, suggesting that the exFAT could be part of a common neuroanatomical scaffold where language and working memory functions are integrated in the healthy human brain., (Copyright © 2020 Varriano, Pascual-Diaz and Prats-Galino.)

The Kocher-Monro trajectory to the cerebral ventricular system represents one of the most common surgical procedures in the field of neurosurgery. Several studies have analyzed the specific white matter disruption produced during this intervention, which has no reported adverse neurological outcomes. In this study, a graph-theoretical approach was applied to quantify the structural alterations in whole-brain level connectivity. To this end, 132 subjects were randomly selected from the Human Connectome Project dataset and used to create 3 independent 44 subjects groups. Two of the groups underwent a simulated left/right Kocher-Monro trajectory and the third was kept as a control group. For the right Kocher-Monro approach, the nodal analysis revealed decreased strength in the anterior cingulate gyrus of the transected hemisphere. The network-based statistic analysis revealed a set of right lateralized subnetworks with decreased connectivity strength that is consistent with a subset of the Default Mode Network, Salience Network, and Cingulo-Opercular Network. These findings could allow for a better understanding of structural alterations caused by Kocher-Monro approaches that could reveal previously undetected clinical alterations and inform the process of designing safer and less invasive cerebral ventricular approaches., Competing Interests: The authors have declared that no competing interests exist.

The Frontal Aslant Tract (FAT) is a tract recently described as having implications on language function. The originally proposed anatomical FAT definition characterizes a connection between Broca's territory and anterior supplementary and pre-supplementary motor areas in the Superior Frontal Gyrus (SFG). Here we propose an extended definition of the FAT (the exFAT) that propagates more anteriorly into the SFG. A sample of 834 subjects from the WU-Minn HCP 900 subjects data release (S900) was selected. The bilateral exFATs were reconstructed for the whole sample using an automated pipeline and thresholded adjusted tract volumes were calculated. A laterality test was performed on the whole sample. The frontal cortex has known implications on superior cognitive functions, so here we evaluate the implications of exFAT volume on performance in a language task and on a set of working memory tasks. Two sub-samples of 70 subjects each were drawn from the S900 sample by selecting the 35 top-performers and 35 bottom-performers for both language and working memory tasks. Additional laterality tests were performed on each subsample. We did not find the exFAT to be lateralized in any of the samples. We found statistically significant differences in left adjusted exFAT volume between top-performers and bottom-performers in the language task. We also found statistically significant differences in right adjusted exFAT volume between top-performers and bottom-performers for 2-back working memory tasks. To check for the predictive power of the exFAT volumes as correlates for performance, we ran a repeated random sub-sampling cross-validation procedure based on a Support Vector Machine (SVM) classifier that was capable of correctly classifying holdout subjects to their corresponding group (top-performer vs bottom-performer) with an average accuracy of 74.5% for language task performance based on left exFAT volume and an accuracy of 64.2% for Working Memory performance based on right exFAT volume., Competing Interests: The authors have declared that no competing interests exist.