Subcortical brain segmentation of two dimensional T1-weighted data sets with FMRIB's Integrated Registration and Segmentation Tool (FIRST)

Exploring changes in brain function in IBD patients using SPCCA: a study of simultaneous EEG-fMRI

Research on functional changes in the brain of inflammatory bowel disease (IBD) patients is emerging around the world, which brings new perspectives to medical research. In this paper, the methods of canonical correlation analysis (CCA), kernel canonical correlation analysis (KCCA), and sparsity preserving canonical correlation analysis (SPCCA) were applied to the fusion of simultaneous EEG-fMRI data from 25 IBD patients and 15 healthy individuals. The CCA, KCCA and SPCCA fusion methods were used for data processing to compare the results obtained by the three methods. The results clearly show that there is a significant difference in the activation intensity between IBD and healthy control (HC), not only in the frontal lobe (p < 0.01) and temporal lobe (p < 0.01) regions, but also in the posterior cingulate gyrus (p < 0.01), gyrus rectus (p < 0.01), and amygdala (p < 0.01) regions, which are usually neglected. The mean difference in the SPCCA activation intensity was 60.1. However, the mean difference in activation intensity was only 36.9 and 49.8 by using CCA and KCCA. In addition, the correlation of the relevant components selected during the SPCCA calculation was high, with correlation components of up to 0.955; alternatively, the correlations obtained from CCA and KCCA calculations were only 0.917 and 0.926, respectively. It can be seen that SPCCA is indeed superior to CCA and KCCA in processing high-dimensional multimodal data. This work reveals the process of analyzing the brain activation state in IBD disease, provides a further perspective for the study of brain function, and opens up a new avenue for studying the SPCCA method and the change in the intensity of brain activation in IBD disease.

Exploring Successful Cognitive Aging: Insights Regarding Brain Structure, Function, and Demographics

In the realm of cognitive science, the phenomenon of "successful cognitive aging" stands as a hallmark of individuals who exhibit cognitive abilities surpassing those of their age-matched counterparts. However, it is paramount to underscore a significant gap in the current research, which is marked by a paucity of comprehensive inquiries that deploy substantial sample sizes to methodically investigate the cerebral biomarkers and contributory elements underpinning this cognitive success. It is within this context that our present study emerges, harnessing data derived from the UK Biobank. In this study, a highly selective cohort of 1060 individuals aged 65 and above was meticulously curated from a larger pool of 17,072 subjects. The selection process was guided by their striking cognitive resilience, ascertained via rigorous evaluation encompassing both generic and specific cognitive assessments, compared to their peers within the same age stratum. Notably, the cognitive abilities of the chosen participants closely aligned with the cognitive acumen commonly observed in middle-aged individuals. Our study leveraged a comprehensive array of neuroimaging-derived metrics, obtained from three Tesla MRI scans (T1-weighted images, dMRI, and resting-state fMRI). The metrics included image-derived phenotypes (IDPs) that addressed grey matter morphology, the strength of brain network connectivity, and the microstructural attributes of white matter. Statistical analyses were performed employing ANOVA, Mann-Whitney U tests, and chi-square tests to evaluate the distinctive aspects of IDPs pertinent to the domain of successful cognitive aging. Furthermore, these analyses aimed to elucidate lifestyle practices that potentially underpin the maintenance of cognitive acumen throughout the aging process. Our findings unveiled a robust and compelling association between heightened cognitive aptitude and the integrity of white matter structures within the brain. Furthermore, individuals who exhibited successful cognitive aging demonstrated markedly enhanced activity in the cerebral regions responsible for auditory perception, voluntary motor control, memory retention, and emotional regulation. These advantageous cognitive attributes were mirrored in the health-related lifestyle choices of the surveyed cohort, characterized by elevated educational attainment, a lower incidence of smoking, and a penchant for moderate alcohol consumption. Moreover, they displayed superior grip strength and enhanced walking speeds. Collectively, these findings furnish valuable insights into the multifaceted determinants of successful cognitive aging, encompassing both neurobiological constituents and lifestyle practices. Such comprehensive comprehension significantly contributes to the broader discourse on aging, thereby establishing a solid foundation for the formulation of targeted interventions aimed at fostering cognitive well-being among aging populations.

Protocol for an observational cohort study investigating biomarkers predicting seizure recurrence following a first unprovoked seizure in adults

INTRODUCTION

A first unprovoked seizure is a common presentation, reliably identifying those that will have recurrent seizures is a challenge. This study will be the first to explore the combined utility of serum biomarkers, quantitative electroencephalogram (EEG) and quantitative MRI to predict seizure recurrence. This will inform patient stratification for counselling and the inclusion of high-risk patients in clinical trials of disease-modifying agents in early epilepsy.

METHODS AND ANALYSIS

100 patients with first unprovoked seizure will be recruited from a tertiary neuroscience centre and baseline assessments will include structural MRI, EEG and a blood sample. As part of a nested pilot study, a subset of 40 patients will have advanced MRI sequences performed that are usually reserved for patients with refractory chronic epilepsy. The remaining 60 patients will have standard clinical MRI sequences. Patients will be followed up every 6 months for a 24-month period to assess seizure recurrence. Connectivity and network-based analyses of EEG and MRI data will be carried out and examined in relation to seizure recurrence. Patient outcomes will also be investigated with respect to analysis of high-mobility group box-1 from blood serum samples.

ETHICS AND DISSEMINATION

This study was approved by North East-Tyne & Wear South Research Ethics Committee (20/NE/0078) and funded by an Association of British Neurologists and Guarantors of Brain clinical research training fellowship. Findings will be presented at national and international meetings published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NIHR Clinical Research Network's (CRN) Central Portfolio Management System (CPMS)-44976.

MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

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Sharing data from cooperative studies is essential to develop new biomarkers in MS.

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Differences in MRI acquisition, analysis, storage represent a substantial constraint.

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We review the state of the art and developments in the harmonization of MRI.

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We provide recommendations to harmonize large MRI datasets in the MS field.

There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.

Hippocampus-Based Dynamic Functional Connectivity Mapping in the Early Stages of Alzheimer's Disease

BACKGROUND

The hippocampus with varying degrees of atrophy was a crucial neuroimaging feature resulting in the declining memory and cognitive function in Alzheimer's disease (AD). However, the abnormal dynamic functional connectivity (DFC) in both white matter (WM) and gray matter (GM) from the left and right hippocampus remains unclear.

OBJECTIVE

To explore the abnormal DFC within WM and GM from the left and right hippocampus across the different stages of AD.

METHODS

Current study employed the OASIS-3 dataset including 43 mild cognitive impairment (MCI), 71 pre-mild cognitive impairment (pre-MCI), and matched 87 normal cognitive (NC). Adopting the FMRIB's Integrated Registration and Segmentation Tool, we obtained the left and right hippocampus mask. Based on above hippocampus mask as seed point, we calculated the DFC between left/right hippocampus and all voxel time series within whole brain. One-way ANOVA analysis was performed to estimate the abnormal DFC among MCI, pre-MCI, and NC groups.

RESULTS

We found that MCI and pre-MCI groups showed the common abnormalities of DFC in the Temporal_Mid_L, Cingulum_Mid_L, and Thalamus_L. Specific abnormalities were found in the Cerebelum_9_L and Precuneus of MCI group and Vermis_8 and Caudate_L of pre-MCI group. In addition, we found that DFC within WM regions also showed the common low DFC for the Cerebellum anterior lobe-WM, Corpus callosum, and Frontal lobe-WM in MCI and pre-MCI group.

CONCLUSION

Our findings provided a novel information for discover the pathophysiological mechanisms of AD and indicate WM lesions were also an important cause of cognitive decline in AD.

Morphological analysis of the brain subcortical gray structures in restless legs syndrome

BACKGROUND

Although several studies have shown the involvement of specific structures of the central nervous system, the dopaminergic system, and iron metabolism in restless legs syndrome (RLS), the exact location and extent of its anatomical substrate is not yet known. The scope of this new study was to investigate the brain subcortical gray structures, by means of structural magnetic resonance imaging (MRI) studies, in RLS patients in order to assess the presence of any volume or shape abnormalities involving these structures.

METHODS

Thirty-three normal controls (24 females and nine males) and 45 RLS patients (34 females and 11 males) were retrospectively recruited and underwent a 1.5 Tesla MRI study with two-dimensional T1 sequences in the sagittal plane. Post-processing was performed by means of the Functional Magnetic Resonance Imaging of the Brain Analysis Group Integrated Registration and Segmentation Tool (FIRST) software, and both volumetric and morphological analyses of the thalamus, caudate, putamen, globus pallidus, brainstem, hippocampus, and amygdala, bilaterally, were carried out.

RESULTS

A statistically significant volumetric reduction in the left amygdala and left globus pallidus was found in subjects with RLS, as well as large surface morphological alterations affecting the amygdala bilaterally and other less widespread surface changes in both hippocampi, the right caudate, the left globus pallidus, and the left putamen.

CONCLUSIONS

These findings seem to indicate that the basic mechanisms of RLS might include a pathway involving not only the hypothalamus-spinal dopaminergic circuit (nucleus A11), but also pathways including the basal ganglia and structures that are part of the limbic system; moreover, structural alterations in RLS seem to concern the morphology as well as the volume of the above structures. The role of basal ganglia in the complex neurophysiological and neurochemical mechanism of RLS needs to carefully reconsidered.

Automated subcortical volume estimation from 2D MRI in epilepsy and implications for clinical trials

Purpose

Most techniques used for automatic segmentation of subcortical brain regions are developed for three-dimensional (3D) MR images. MRIs obtained in non-specialist hospitals may be non-isotropic and two-dimensional (2D). Automatic segmentation of 2D images may be challenging and represents a lost opportunity to perform quantitative image analysis. We determine the performance of a modified subcortical segmentation technique applied to 2D images in patients with idiopathic generalised epilepsy (IGE).

Methods

Volume estimates were derived from 2D (0.4 × 0.4 × 3 mm) and 3D (1 × 1x1mm) T1-weighted acquisitions in 31 patients with IGE and 39 healthy controls. 2D image segmentation was performed using a modified FSL FIRST (FMRIB Integrated Registration and Segmentation Tool) pipeline requiring additional image reorientation, cropping, interpolation and brain extraction prior to conventional FIRST segmentation. Consistency between segmentations was assessed using Dice coefficients and volumes across both approaches were compared between patients and controls. The influence of slice thickness on consistency was further assessed using 2D images with slice thickness increased to 6 mm.

Results

All average Dice coefficients showed excellent agreement between 2 and 3D images across subcortical structures (0.86–0.96). Most 2D volumes were consistently slightly lower compared to 3D volumes. 2D images with increased slice thickness showed lower agreement with 3D images with lower Dice coefficients (0.55–0.83). Significant volume reduction of the left and right thalamus and putamen was observed in patients relative to controls across 2D and 3D images.

Conclusion

Automated subcortical volume estimation of 2D images with a resolution of 0.4 × 0.4x3mm using a modified FIRST pipeline is consistent with volumes derived from 3D images, although this consistency decreases with an increased slice thickness. Thalamic and putamen atrophy has previously been reported in patients with IGE. Automated subcortical volume estimation from 2D images is feasible and most reliable at using in-plane acquisitions greater than 1 mm x 1 mm and provides an opportunity to perform quantitative image analysis studies in clinical trials.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-021-02811-x.

Multimodal Investigations of Reward Circuitry and Anhedonia in Adolescent Depression

Depression is a highly prevalent condition with devastating personal and public health consequences that often first manifests during adolescence. Though extensively studied, the pathogenesis of depression remains poorly understood, and efforts to stratify risks and identify optimal interventions have proceeded slowly. A major impediment has been the reliance on an all-or-nothing categorical diagnostic scheme based solely on whether a patient endorses an arbitrary number of common symptoms for a sufficiently long period. This approach masks the well-documented heterogeneity of depression, a disorder that is highly variable in presentation, severity, and course between individuals and is frequently comorbid with other psychiatric conditions. In this targeted review, we outline the limitations of traditional diagnosis-based research and instead advocate an alternative approach centered around symptoms as unique dimensions of clinical dysfunction that span across disorders and more closely reflect underlying neurobiological abnormalities. In particular, we highlight anhedonia-the reduced ability to anticipate and experience pleasure-as a specific, quantifiable index of reward dysfunction and an ideal candidate for dimensional investigation. Anhedonia is a core symptom of depression but also a salient feature of numerous other conditions, and its severity varies widely within clinical and even healthy populations. Similarly, reward dysfunction is a hallmark of depression but is evident across many psychiatric conditions. Reward function is especially relevant in adolescence, a period characterized by exaggerated reward-seeking behaviors and rapid maturation of neural reward circuitry. We detail extensive work by our research group and others to investigate the neural and systemic factors contributing to reward dysfunction in youth, including our cumulative findings using multiple neuroimaging and immunological measures to study depressed adolescents but also trans-diagnostic cohorts with diverse psychiatric symptoms. We describe convergent evidence that reward dysfunction: (a) predicts worse clinical outcomes, (b) is associated with functional and chemical abnormalities within and beyond the neural reward circuitry, (c) is linked to elevated peripheral levels of inflammatory biomarkers, and (d) manifests early in the course of illness. Emphasis is placed on high-resolution neuroimaging techniques, comprehensive immunological assays, and data-driven analyses to fully capture and characterize the complex, interconnected nature of these systems and their contributions to adolescent reward dysfunction.

A Robust and Accurate Deep-learning-based Method for the Segmentation of Subcortical Brain: Cross-dataset Evaluation of Generalization Performance

Purpose:

To analyze subcortical brain volume more reliably, we propose a deep learning segmentation method of subcortical brain based on magnetic resonance imaging (MRI) having high generalization performance, accuracy, and robustness.

Methods:

First, local images of three-dimensional (3D) bounding boxes were extracted for seven subcortical structures (thalamus, putamen, caudate, pallidum, hippocampus, amygdala, and accumbens) from a whole brain MR image as inputs to the neural network. Second, dilated convolution layers, which input information of variable scope, were introduced to the blocks that make up the neural network. These blocks were connected in parallel to simultaneously process global and local information obtained by the dilated convolution layers. To evaluate generalization performance, different datasets were used for training and testing sessions (cross-dataset evaluation) because subcortical brain segmentation in clinical analysis is assumed to be applied to unknown datasets.

Results:

The proposed method showed better generalization performance that can obtain stable accuracy for all structures, whereas the state-of-the-art deep learning method obtained extremely low accuracy for some structures. The proposed method performed segmentation for all samples without failing with significantly higher accuracy (P < 0.005) than conventional methods such as 3D U-Net, FreeSurfer, and Functional Magnetic Resonance Imaging of the Brain’s (FMRIB’s) Integrated Registration and Segmentation Tool in the FMRIB Software Library (FSL-FIRST). Moreover, when applying this proposed method to larger datasets, segmentation was robustly performed for all samples without producing segmentation results on the areas that were apparently different from anatomically relevant areas. On the other hand, FSL-FIRST produced segmentation results on the area that were apparently and largely different from the anatomically relevant area for about one-third to one-fourth of the datasets.

Conclusion:

The cross-dataset evaluation showed that the proposed method is superior to existing methods in terms of generalization performance, accuracy, and robustness.

Whole Brain Adiabatic T1rho and Relaxation Along a Fictitious Field Imaging in Healthy Volunteers and Patients With Multiple Sclerosis: Initial Findings

BACKGROUND

In preclinical models of multiple sclerosis (MS), both adiabatic T_1rho (T_1ρadiab ) and relaxation along a fictitious field (RAFF) imaging have demonstrated potential to noninvasively characterize MS.

PURPOSE

To evaluate the feasibility of whole brain T_1ρadiab and RAFF imaging in healthy volunteers and patients with MS.

STUDY TYPE

Single institutional clinical trial.

SUBJECTS

38 healthy volunteers (24-69 years) and 21 patients (26-59 years) with MS. Five healthy volunteers underwent a second MR examination performed within 8 days. Clinical disease severity (The Expanded Disability Status Scale [EDSS] and The Multiple Sclerosis Severity Score [MSSS]) was evaluated at baseline and 1-year follow-up (FU).

FIELD STRENGTH/SEQUENCE

RAFF in second rotating frame of reference (RAFF2) was performed at 3 T using 3D-fast-field echo with magnetization preparation, RF amplitude of 11.74 μT while the corresponding value for T_1ρadiab was 13.50 μT. T₁ -, T₂ -, and FLAIR-weighted images were acquired with reconstruction voxel size 1.0 × 1.0 × 1.0 mm³ .

ASSESSMENT

The parametric maps of T_1ρadiab and RAFF2 (T_RAFF2 ) were calculated using a monoexponential model. Semi-automatic segmentation of MS lesions, white matter (WM), and gray matter (GM), and WM tracks was performed using T₁ -, T₂ -, and FLAIR-weighted images.

STATISTICAL TESTS

Regression analysis was used to evaluate correlation of T_1ρadiab and T_RAFF2 with age and disease severity while a Friedman test followed by Wilcoxon Signed Rank test for differences between tissue types. Short-term repeatability was evaluated on voxel level.

RESULTS

Both T_1ρadiab and T_RAFF2 demonstrated good short-term repeatability with relative differences on voxel level in the range of 6.1%-11.9%. Differences in T_1ρadiab and T_RAFF2 between the tissue types in MS patients were significant (P < 0.05). T_1ρadiab and T_RAFF2 correlated (P < 0.001) with baseline EDSS/MSSM and disease progression at FU (P < 0.001).

DATA CONCLUSION

Whole brain T_1ρadiab and T_RAFF2 at 3 T was feasible with significant differences in T_1ρadiab and T_RAFF2 values between tissues types and correlation with disease severity.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Fingolimod in children with Rett syndrome: the FINGORETT study

Background

Rett syndrome (RS) is a severe neurodevelopmental disorder for which there is no approved therapy. This study aimed to assess safety and efficacy of oral fingolimod in children with RS using a pre-post and case–control design.

Methods

At the University of Basel Children’s Hospital, Basel, Switzerland, children with RS were included if they were older than 6 years and met the established diagnostic criteria of RS, including a positive MeCP2 mutation. Participants were observed 6 months before and after treatment and received 12 months of fingolimod treatment. Serum samples of 50 children without RS served as reference for brain-derived neurotrophic factor (BDNF) measurements. Primary outcome measures were safety and efficacy, the latter measured by change in levels of BDNF in serum/CSF (cerebrospinal fluid) and change in deep gray matter volumes measured by magnetic resonance imaging (MRI). Secondary outcome measure was efficacy measured by change in clinical scores [Vineland Adaptive Behaviour Scale (VABS), Rett Severity Scale (RSSS) and Hand Apraxia Scale (HAS)].

Results

Six children with RS (all girls, mean and SD age 11.3 ± 3.1 years) were included. Serum samples of 50 children without RS (25 females, mean and SD age 13.5 ± 3.9 years) served as reference for BDNF measurements. No serious adverse events occurred. Primary and secondary outcome measures were not met. CSF BDNF levels were associated with all clinical scores: RSSS (estimate − 0.04, mult.effect 0.96, CI [0.94; 0.98], p = 0.03), HAS (estimate − 0.09, mult.effect 0.91, CI [0.89; 0.94], p <  0.01) and VABS (communication: estimate 0.03, mult.effect 1.03, CI [1.02; 1.04], p < 0.01/daily living: estimate 0.03, mult.effect 1.03, CI [1.02; 1.04], p < 0.01/social skills: estimate 0.07, mult.effect 1.08, CI [1.05; 1.11], p < 0.01/motoric skills: estimate 0.04, mult.effect 1.04, CI [1.03; 1.06], p = 0.02).

Conclusions

In children with RS, treatment with fingolimod was safe. The study did not provide supportive evidence for an effect of fingolimod on clinical, laboratory, and imaging measures. CSF BDNF levels were associated with clinical scores, indicating a need to further evaluate its potential as a biomarker for RS. This finding should be further validated in independent patient groups.

Trial Registration

Clinical Trials.gov NCT02061137, registered on August 27th 2013, https://clinicaltrials.gov/ct2/show/study/NCT02061137.

Lesion Induced Error on Automated Measures of Brain Volume: Data From a Pediatric Traumatic Brain Injury Cohort

Structural segmentation of T1-weighted (T1w) MRI has shown morphometric differences, both compared to controls and longitudinally, following a traumatic brain injury (TBI). While many patients with TBI present with abnormalities on structural MRI images, most neuroimaging software packages have not been systematically evaluated for accuracy in the presence of these pathology-related MRI abnormalities. The current study aimed to assess whether acute MRI lesions (MRI acquired 7–71 days post-injury) cause error in the estimates of brain volume produced by the semi-automated segmentation tool, Freesurfer. More specifically, to investigate whether this error was global, the presence of lesion-induced error in the contralesional hemisphere, where no abnormal signal was present, was measured. A dataset of 176 simulated lesion cases was generated using actual lesions from 16 pediatric TBI (pTBI) cases recruited from the emergency department and 11 typically-developing controls. Simulated lesion cases were compared to the “ground truth” of the non-lesion control-case T1w images. Using linear mixed-effects models, results showed that hemispheric measures of cortex volume were significantly lower in the contralesional-hemisphere compared to the ground truth. Interestingly, however, cortex volume (and cerebral white matter volume) were not significantly different in the lesioned hemisphere. However, percent volume difference (PVD) between the simulated lesion and ground truth showed that the magnitude of difference of cortex volume in the contralesional-hemisphere (mean PVD = 0.37%) was significantly smaller than that in the lesioned hemisphere (mean PVD = 0.47%), suggesting a small, but systematic lesion-induced error. Lesion characteristics that could explain variance in the PVD for each hemisphere were investigated. Taken together, these results suggest that the lesion-induced error caused by simulated lesions was not focal, but globally distributed. Previous post-processing approaches to adjust for lesions in structural analyses address the focal region where the lesion was located however, our results suggest that focal correction approaches are insufficient for the global error in morphometric measures of the injured brain.

The fitness versus body fat hypothesis in relation to hippocampal structure

The Fitness Versus Body Fat Hypothesis argues that cardiorespiratory fitness (CRF) plays a more important role in cardiovascular health than adiposity. It remains poorly understood whether CRF or adiposity accounts for a greater amount of variation in measures of brain health. We examined the contribution of CRF, adiposity, and their interaction with hippocampal structure. This study included 124 sedentary adults (M = 44.34) with overweight/obesity (Body Mass Index mean = 32.43). FMRIB's Integrated Registration and Segmentation Tool was used to segment the hippocampus. Using hierarchical regression, we examined whether CRF, assessed via a submaximal graded exercise test, or adiposity, assessed as percent body fat using dual-energy x-ray absorptiometry (DXA) was associated with left and right hippocampal volume. Vertex-wise shape analysis was performed to examine regional shape differences associated with CRF and adiposity. Higher CRF was significantly associated with greater left hippocampal volume (p = .031), with outward shape differences along the surface of the subiculum and CA1 regions. Adiposity was not associated with left or right hippocampal volume or shape. The interaction between adiposity and CRF was not significant. Neither CRF nor adiposity were associated with thalamus or caudate nucleus volumes or shapes, two control regions. Higher CRF, but not adiposity, was related to greater left hippocampal volume, with outward shape differences along the surface of the subiculum and CA1 regions in a midlife sample with overweight/obesity. These findings indicate that, within the context of obesity, CRF is an important contributor to hippocampal structure, highlighting the importance of interventions targeting CRF.

Early putamen hypertrophy and ongoing hippocampus atrophy predict cognitive performance in the first ten years of relapsing-remitting multiple sclerosis

BACKGROUND

The first years of relapsing-remitting multiple sclerosis (RRMS) constitute the most vulnerable phase for the progression of cognitive impairment (CImp), due to a gradual decrease of compensatory mechanisms. In the first 10 years of RRMS, the temporal volumetric changes of deep gray matter structures must be clarified, since they could constitute reliable cognitive biomarkers for diagnostic, prognostic, and therapeutic purposes.

METHODS

Forty-five cognitively asymptomatic patients with RRMS lasting ≤ 10 years, and with a brain MRI performed in a year from the neuropsychological evaluation (Te-MRI), were included. They performed the Brief International Cognitive Assessment battery for MS. Thirty-one brain MRIs performed in the year of diagnosis (Td-MRI) and 13 brain MRIs of age- and sex-matched healthy controls (HCs) were also included in the study. The relationships between clinical features, cognitive performances, and Te- and Td-MRI volumes were statistically analyzed.

RESULTS

Cognitively preserved (CP) patients had significantly increased Td-L-putamen (P = 0.035) and Td-R-putamen volume (P = 0.027) with respect to cognitively impaired (CI) ones. CI patients had significantly reduced Te-L-hippocampus (P = 0.019) and Te-R-hippocampus volume (P = 0.042) compared, respectively, with Td-L-hippocampus and Td-R-hippocampus volume. Td-L-putamen volume (P = 0.011) and Te-L-hippocampus volume (P = 0.023) were independent predictors of the Symbol Digit Modalities Test score in all patients (r2 = 0.31, F = 6.175, P = 0.001).

CONCLUSION

In the first years of RRMS, putamen hypertrophy and hippocampus atrophy could represent promising indices of cognitive performance and reserve, and become potentially useful tools for diagnostic, prognostic, and therapeutic purposes.

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Brain volume is related to neurological impairment and to copper overload in Wilson's disease

Introduction

To determine whether brain volume was associated with functional and neurological impairments and with copper overload markers in patients with Wilson’s disease.

Methods

In 48 treatment-naïve patients, we assessed functional and neurological impairments with the Unified Wilson’s Disease Rating Scale, measured normalized brain volumes based on magnetic resonance images, and assessed concentration of non-ceruloplasmin-bound copper. We correlated brain volume measures with functional and neurological impairment scores and copper overload indices.

Results

Functional and neurological impairments correlated with all brain volume measures, including the total brain volume and the volumes of white matter and gray matter (both peripheral gray matter and deep brain nuclei). Higher non-ceruloplasmin-bound copper concentrations were associated with greater functional and neurological impairments and lower brain volumes.

Conclusions

Our findings provided the first in vivo evidence that the severity of brain atrophy is a correlate of functional and neurological impairments in patients with Wilson’s disease and that brain volume could serve as a marker of neurodegeneration induced by copper.

Electronic supplementary material

The online version of this article (10.1007/s10072-019-03942-z) contains supplementary material, which is available to authorized users.

Subcortical Volume Changes in Migraine with Aura

Background and Purpose

Various features of the cerebral cortex and white matter have been extensively investigated in migraine with aura (MwA), but the morphological characteristics of subcortical structures have been largely neglected. The aim of this study was to identify possible differences in subcortical structures between MwA patients and healthy subjects (HS), and also to determine the correlations between the characteristics of migraine aura and the volumes of subcortical structures.

Methods

Thirty-two MwA patients and 32 HS matched by sex and age were analyzed in this study. Regional subcortical brain volumes were automatically calculated using the FSL/FMRIB Image Registration and Segmentation Tool software (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Glossary). A general linear model analysis was used to investigate differences in the volume of subcortical structures between the MwA patients and HS. A partial correlation test was used to assess correlations between the volume of subcortical structures and characteristics of MwA.

Results

The volumes of the right globus pallidus, left globus pallidus, and left putamen were significantly smaller in MwA patients than in HS (mean±SD): 1,427±135 mm³ vs. 1,557±136 mm³ (p<0.001), 1,436±126 mm³ vs. 1,550±139 mm³ (p=0.001), and 4,235±437 mm³ vs. 4,522±412 mm³ (p=0.006), respectively. There were no significant relationships between subcortical structures and clinical parameters.

Conclusions

These findings suggest that both the globus pallidi and left putamen play significant roles in the pathophysiology of the MwA. Future studies should determine the cause-and-effect relationships, since these could not be discriminated in this study due to its cross-sectional design.

Changes of deep gray matter magnetic susceptibility over 2 years in multiple sclerosis and healthy control brain

In multiple sclerosis, pathological changes of both tissue iron and myelin occur, yet these factors have not been characterized in a longitudinal fashion using the novel iron- and myelin-sensitive quantitative susceptibility mapping (QSM) MRI technique. We investigated disease-relevant tissue changes associated with myelin loss and iron accumulation in multiple sclerosis deep gray matter (DGM) over two years. One-hundred twenty (120) multiple sclerosis patients and 40 age- and sex-matched healthy controls were included in this prospective study. Written informed consent and local IRB approval were obtained from all participants. Clinical testing and QSM were performed both at baseline and at follow-up. Brain magnetic susceptibility was measured in major DGM structures. Temporal (baseline vs. follow-up) and cross-sectional (multiple sclerosis vs. controls) differences were studied using mixed factorial ANOVA analysis and appropriate t-tests. At either time-point, multiple sclerosis patients had significantly higher susceptibility in the caudate and globus pallidus and lower susceptibility in the thalamus. Over two years, susceptibility increased significantly in the caudate of both controls and multiple sclerosis patients. Inverse thalamic findings among MS patients suggest a multi-phase pathology explained by simultaneous myelin loss and/or iron accumulation followed by iron depletion and/or calcium deposition at later stages.

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM)

Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T₁-weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images. Consequently, such deviations from the average brain anatomy may introduce analysis bias in clinical studies, which may not always be obvious and potentially remain unidentified. To improve the segmentation of subcortical nuclei, we propose to use FIRST in combination with a special Hybrid image Contrast (HC) and Non-Linear (nl) registration module (HC-nlFIRST), where the hybrid image contrast is derived from T1w images and magnetic susceptibility maps to create subcortical contrast that is similar to that in the Montreal Neurological Institute (MNI) template. In our approach, a nonlinear registration replaces FIRST's default linear registration, yielding a more accurate alignment of the input data to the MNI template. We evaluated our method on 82 subjects with particularly abnormal brain anatomy, selected from a database of >2000 clinical cases. Qualitative and quantitative analyses revealed that HC-nlFIRST provides improved segmentation compared to the default FIRST method.

Measurement of Cortical Thickness and Volume of Subcortical Structures in Multiple Sclerosis: Agreement between 2D Spin-Echo and 3D MPRAGE T1-Weighted Images

BACKGROUND AND PURPOSE

Gray matter pathology is known to occur in multiple sclerosis and is related to disease outcomes. FreeSurfer and the FMRIB Integrated Registration and Segmentation Tool (FIRST) have been developed for measuring cortical and subcortical gray matter in 3D-gradient-echo T1-weighted images. Unfortunately, most historical MS cohorts do not have 3D-gradient-echo, but 2D-spin-echo images instead. We aimed to evaluate whether cortical thickness and the volume of subcortical structures measured with FreeSurfer and FIRST could be reliably measured in 2D-spin-echo images and to investigate the strength and direction of clinicoradiologic correlations.

MATERIALS AND METHODS

Thirty-eight patients with MS and 2D-spin-echo and 3D-gradient-echo T1-weighted images obtained at the same time were analyzed by using FreeSurfer and FIRST. The intraclass correlation coefficient between the estimates was obtained. Correlation coefficients were used to investigate clinicoradiologic associations.

RESULTS

Subcortical volumes obtained with both FreeSurfer and FIRST showed good agreement between 2D-spin-echo and 3D-gradient-echo images, with 68.8%-76.2% of the structures having either a substantial or almost perfect agreement. Nevertheless, with FIRST with 2D-spin-echo, 18% of patients had mis-segmentation. Cortical thickness had the lowest intraclass correlation coefficient values, with only 1 structure (1.4%) having substantial agreement. Disease duration and the Expanded Disability Status Scale showed a moderate correlation with most of the subcortical structures measured with 3D-gradient-echo images, but some correlations lost significance with 2D-spin-echo images, especially with FIRST.

CONCLUSIONS

Cortical thickness estimates with FreeSurfer on 2D-spin-echo images are inaccurate. Subcortical volume estimates obtained with FreeSurfer and FIRST on 2D-spin-echo images seem to be reliable, with acceptable clinicoradiologic correlations for FreeSurfer.

Localized atrophy of the thalamus and slowed cognitive processing speed in MS patients

BACKGROUND

Deep gray matter (DGM) atrophy is common in multiple sclerosis (MS), but no studies have investigated surface-based structure changes over time with respect to healthy controls (HCs). Moreover, the relationship between cognition and the spatio-temporal evolution of DGM atrophy is poorly understood.

OBJECTIVES

To explore DGM structural differences between MS and HCs over time in relation to neuropsychological (NP) outcomes.

METHODS

The participants were 44 relapsing-remitting and 20 secondary progressive MS patients and 22 HCs. All were scanned using 3T magnetic resonance imaging (MRI) at baseline and 3-year follow-up. NP examination emphasized consensus standard tests of processing speed and memory. We performed both volumetric and shape analysis of DGM structures and assessed their relationships with cognition.

RESULTS

Compared to HCs, MS patients presented with significantly smaller DGM volumes. For the thalamus and caudate, differences in shape were mostly localized along the lateral ventricles. NP outcomes were related to both volume and shape of the DGM structures. Over 3 years, decreased cognitive processing speed was related to localized atrophy on the anterior and superior surface of the left thalamus.

CONCLUSIONS

These findings highlight the role of atrophy in the anterior nucleus of the thalamus and its relation to cognitive decline in MS.