Regional morphometric abnormalities and clinical relevance in Wilson's disease

Correlation between neuroimaging, neurological phenotype, and functional outcomes in Wilson's disease

INTRODUCTION

Wilson's disease (WD) is associated with a variety of movement disorders and progressive neurological dysfunction. The aim of this study was to correlate baseline brain magnetic resonance imaging (MRI) features with clinical phenotype and long-term outcomes in chronically treated WD patients.

METHODS

Patients were retrospectively selected from an institutional database. Two experienced neuroradiologists reviewed baseline brain MRI. Functional assessment was performed using the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) scale, and disease severity was classified using the Global Assessment Scale for Wilson's Disease (GASWD).

RESULTS

Of 27 patients selected, 14 were female (51.9%), with a mean (standard deviation [SD]) age at onset of 19.5 (7.1) years. Neurological symptoms developed in 22 patients (81.5%), with hyperkinetic symptoms being the most common (70.4%). Baseline brain MRI showed abnormal findings in 18 cases (66.7%), including T2 hyperintensities in 59.3% and atrophy in 29.6%. After a mean (SD) follow-up of 20.9 (11.0) years, WD patients had a mean score of 19.2 (10.2) on WHODAS 2.0 and 6.4 (5.7) on GASWD. The presence of hyperkinetic symptoms correlated with putaminal T2 hyperintensities (p = 0.003), putaminal T2 hypointensities (p = 0.009), and mesencephalic T2 hyperintensities (p = 0.009). Increased functional disability was associated with brain atrophy (p = 0.007), diffusion abnormalities (p = 0.013), and burden of T2 hyperintensities (p = 0.002). A stepwise regression model identified atrophy as a predictor of increased WHODAS 2.0 (p = 0.023) and GASWD (p = 0.007) scores.

CONCLUSIONS

Atrophy and, to a lesser extent, deep T2 hyperintensity are associated with functional disability and disease severity in long-term follow-up of WD patients.

Abnormalities in subcortical function and their treatment response in Wilson's disease

Extensive neuroimaging abnormalities in subcortical regions build the pathophysiological basis of Wilson's disease (WD). Yet, subcortical topographic organization fails to articulate, leaving a huge gap in understanding the neural mechanism of WD. Thus, how functional abnormalities of WD subcortical regions influence complex clinical symptoms and response to treatment remain unknown. Using resting-state functional MRI data from 232 participants (including 130 WD patients and 102 healthy controls), we applied a connectivity-based parcellation technique to develop a subcortical atlas for WD. The atlas was further used to investigate abnormalities in subcortical function (ASF) by exploring intrasubcortical functional connectivity (FC) and topographic organization of cortico-subcortical FC. We further used support vector machine (SVM) to integrate these functional abnormalities into the ASF score, which serves as a biomarker for characterizing individual subcortical dysfunction for WD. Finally, the baseline ASF score and one-year treatment data of the follow-up WD patients were used to assess treatment response. A group set of subcortical parcellations was evaluated, in which 26 bilateral regions well recapitulated the anatomical nuclei of the subcortical areas of WD. The results of cortico-subcortical FC and intrasubcortical FC reveal that dysfunction of the somatomotor networks-lenticular nucleus-thalamic pathways is involved in complex symptoms of WD. The ASF score was able to characterize disease progression and was significantly associated with treatment response of WD. Our findings provide a comprehensive elaboration of functional abnormalities of WD subcortical regions and reveal their association with clinical presentations, improving our understanding of the functional neural underpinnings in WD. Furthermore, abnormalities in subcortical function could serve as a potential biomarker for understanding the disease progression and evaluating treatment response of WD.

The volume and structural covariance network of thalamic nuclei in patients with Wilson's disease: an investigation of the association with neurological impairment

OBJECTIVE

This study aimed to examine the volumes of thalamic nuclei and the intrinsic thalamic network in patients with Wilson's disease (WDs), and to explore the correlation between these volumes and the severity of neurological symptoms.

METHODS

A total of 61 WDs and 33 healthy controls (HCs) were included in the study. The volumes of 25 bilateral thalamic nuclei were measured using structural imaging analysis with Freesurfer, and the intrinsic thalamic network was evaluated through structural covariance network (SCN) analysis.

RESULTS

The results indicated that multiple thalamic nuclei were smaller in WDs compared to HCs, including mediodorsal medial magnocellular (MDm), anterior ventral (AV), central median (CeM), centromedian (CM), lateral geniculate (LGN), limitans-suprageniculate (L-Sg), reuniens-medial ventral (MV), paracentral (Pc), parafascicular (Pf), paratenial (Pt), pulvinar anterior (PuA), pulvinar inferior (PuI), pulvinar medial (PuM), ventral anterior (VA), ventral anterior magnocellular (VAmc), ventral lateral anterior (VLa), ventral lateral posterior (VLp), ventromedial (VM), ventral posterolateral (VPL), and right middle dorsal intralaminar (MDI). The study also found a negative correlation between the UWDRS scores and the volume of the right MDm. The intrinsic thalamic network analysis showed abnormal topological properties in WDs, including increased mean local efficiency, modularity, normalized clustering coefficient, small-world index, and characteristic path length, and a corresponding decrease in mean node betweenness centrality. WDs with cerebral involvement had a lower modularity compared to HCs.

CONCLUSIONS

The findings suggest that the majority of thalamic nuclei in WDs exhibit significant volume reduction, and the atrophy of the right MDm is closely related to the severity of neurological symptoms. The intrinsic thalamic network in WDs demonstrated abnormal topological properties, indicating a close relationship with neurological impairment.

ProbaStem, a pipeline towards the first high-resolution probabilistic atlas of the whole human brainstem

The brainstem plays an essential role in many vital functions, such as autonomic control, consciousness and sleep, motricity, somatic afferent function, and cognition. Its involvement in several neurological diseases and the definition of brainstem targets for deep brain stimulation (DBS) explain the need for brainstem atlases describing its structural organization and connectivity from several modalities, from histology to ultrahigh field ex vivo MRI. Nonetheless, these atlases are often limited to a subpart of the brainstem or only include a single subject, the brainstem variability being considered low. This paper proposes a pipeline to create a high-resolution multisubject probabilistic atlas of the whole human brainstem based on four ultrahigh field ex vivo MRI datasets. The variability of the brainstem structures appears higher than usually considered, both for the volume and position of the central gray matter structures of the brainstem. This justifies the creation of atlases that capture the anatomical variability across subjects. The one we present here only included four specimens, but can easily be incremented due to its highly flexible design.

Treating the Neurologic Manifestations of Wilson's Disease With Liver Transplantation

Wilson's Disease (WD) manifests with systemic and neuropsychiatric symptoms, caused by an ATP7B genetic mutation, leading to an accumulation of copper. Presentations are diverse and the diagnosis should be considered in anyone under 50 with a new onset movement disorder. Early recognition and treatment can limit morbidity. While liver transplantation (LT) is recommended in WD patients with hepatic failure, its use for pure neurologic indication remains controversial. We present a patient who failed medical management and underwent LT for pure neurologic indications. Subsequent neurologic symptom improvement supports the use of LT for patients with pure neurologic manifestations of WD.

Large-scale networks changes in Wilson's disease associated with neuropsychiatric impairments: a resting-state functional magnetic resonance imaging study

BACKGROUND

In Wilson's disease (WD) patients, network connections across the brain are disrupted, affecting multidomain function. However, the details of this neuropathophysiological mechanism remain unclear due to the rarity of WD. In this study, we aimed to investigate alterations in brain network connectivity at the whole-brain level (both intra- and inter-network) in WD patients through independent component analysis (ICA) and the relationship between alterations in these brain network functional connections (FCs) and clinical neuropsychiatric features to understand the underlying pathophysiological and central compensatory mechanisms.

METHODS

Eighty-five patients with WD and age- and sex-matched 85 healthy control (HC) were recruited for resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We extracted the resting-state networks (RSNs) using the ICA method, analyzed the changes of FC in these networks and the correlation between alterations in FCs and clinical neuropsychiatric features.

RESULTS

Compared with HC, WD showed widespread lower connectivity within RSNs, involving default mode network (DMN), frontoparietal network (FPN), somatomotor network (SMN), dorsal attention network (DAN), especially in patients with abnormal UWDRS scores. Furthermore, the decreased FCs in the left medial prefrontal cortex (L_ MPFC), left anterior cingulate gyrus (L_ACC), precuneus (PCUN)within DMN were negatively correlated with the Unified Wilson's Disease Rating Scale-neurological characteristic examination (UWDRS-N), and the decreased FCs in the L_MPFC, PCUN within DMN were negatively correlated with the Unified Wilson's Disease Rating Scale-psychiatric symptoms examination (UWDRS-P). We additionally discovered that the patients with WD exhibited significantly stronger FC between the FPN and DMN, between the DAN and DMN, and between the FPN and DAN compared to HC.

CONCLUSIONS

We have provided evidence that WD is a disease with widespread dysfunctional connectivity in resting networks in brain, leading to neurological features and psychiatric symptoms (e.g. higher-order cognitive control and motor control impairments). The alter intra- and inter-network in the brain may be the neural underpinnings for the neuropathological symptoms and the process of injury compensation in WD patients.

Lesions in White Matter in Wilson's Disease and Correlation with Clinical Characteristics

BACKGROUND

Neuroimaging studies in Wilson's disease (WD) have identified various alterations in white matter (WM) microstructural organization. However, it remains unclear whether these alterations are localized to specific regions of fiber tracts, and what diagnostic value they might have. The purpose of this study is to explore the spatial profile of WM abnormalities along defined fiber tracts in WD and its clinical relevance.

METHODS

Ninety-nine patients with WD (62 men and 37 women) and 91 age- and sex-matched controls (59 men and 32 women) were recruited to take part in experiments of diffusion-weighted imaging with 64 gradient vectors. The data were calculated by FMRIB Software Library (FSL) software and Automated Fiber Quantification (AFQ) software. After registration, patient groups and normal groups were compared by Mann-Whitney U test analysis.

RESULTS

Compared with the controls, the patients with WD showed widespread fractional anisotropy reduction and mean diffusivity, radial diffusivity elevation of identified fiber tracts. Significant correlations between diffusion tensor imaging (DTI) parameters and the neurological Unified Wilson's Disease Rating Scale (UWDRS-N), serum ceruloplasmin, and 24-h urinary copper excretion were found.

CONCLUSIONS

The present study has provided evidence that the metrics of DTI could be utilized as a potential biomarker of neuropathological symptoms in WD. Damage to the microstructure of callosum forceps and corticospinal tract may be involved in the pathophysiological process of neurological symptoms in WD patients, such as gait and balance disturbances, involuntary movements, dysphagia, and autonomic dysfunction.

Machine learning for detecting Wilson's disease by amplitude of low-frequency fluctuation

Wilson's disease (WD) is a genetic disorder with the A7P7B gene mutations. It is difficult to diagnose in clinic. The purpose of this study was to confirm whether amplitude of low-frequency fluctuations (ALFF) is one of the potential biomarkers for the diagnosis of WD. The study enrolled 30 healthy controls (HCs) and 37 WD patients (WDs) to obtain their resting-state functional magnetic resonance imaging (rs-fMRI) data. ALFF was obtained through preprocessing of the rs-fMRI data. To distinguish between patients with WDs and HCs, four clusters with abnormal ALFF-z values were identified through between-group comparisons. Based on these clusters, three machine learning models were developed, including Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). Abnormal ALFF z-values were also combined with volume information, clinical variables, and imaging features to develop machine learning models. There were 4 clusters where the ALFF z-values of the WDs were significantly higher than that of the HCs. Cluster1 was in the cerebellar region, Cluster2 was in the left caudate nucleus, Cluster3 was in the bilateral thalamus, and Cluster4 was in the right caudate nucleus. In the training set and test set, the models trained with Cluster2, Cluster3, and Cluster4 achieved area of curve (AUC) greater than 0.80. In the Delong test, only the AUC values of models trained with Cluster4 exhibited statistical significance. The AUC values of the Logit model (P = 0.04) and RF model (P = 0.04) were significantly higher than those of the SVM model. In the test set, the LR model and RF model trained with Cluster3 had high specificity, sensitivity, and accuracy. By conducting the Delong test, we discovered that there was no statistically significant inter-group difference in AUC values between the model that integrates multi-modal information and the model before fusion. The LR models trained with multimodal information and Cluster 4, as well as the LR and RF models trained with multimodal information and Cluster 3, have demonstrated high accuracy, specificity, and sensitivity. Overall, these findings suggest that using ALFF based on the thalamus or caudate nucleus as markers can effectively differentiate between WDs and HCs. The fusion of multimodal information did not significantly improve the classification performance of the models before fusion.

Metal deposits associated with brain atrophy in the deep gray matter nucleus in Wilson's disease

Regional atrophy and metal deposition are typical manifestations in Wilson's disease, but their relationship has not been systematically investigated. We aim to investigate the association of regional brain atrophy and metal deposition in the deep gray matter nucleus at MRI in Wilson's disease. We acquired the structural and susceptibility mapping and performed a cross-sectional comparison of volume and susceptibility in deep gray matter nucleus. The most extensive and severe atrophy was detected in brain regions in neuro-Wilson's disease, as well as the most widespread and heaviest metal deposits. Metal deposits were significantly negatively correlated with volume in the bilateral thalamus, caudate, and putamen. None of correlation was found between the clinical score with volume or susceptibility in the focused regions. In the 1-year follow-up analysis, the volume of right thalamus, globus pallidus, and brainstem and the susceptibility of the left caudate have decreased significantly as the symptom improvement. In Wilson's disease, phenotypes have varied scope and extend of volumetric atrophy and metal deposits. This study is expected to take the lead in revealing that in neuro-Wilson's disease, greater regional atrophy associated with heavier metal deposits in Wilson's disease. Moreover, after 1-year treatment, the imaging data have changed as the patient's condition improvement.

Microstructural and functional impairment of the basal ganglia in Wilson's disease: a multimodal neuroimaging study

Objectives

Magnetic susceptibility changes in brain MRI of Wilson's disease (WD) patients have been described in subcortical nuclei especially the basal ganglia. The objectives of this study were to investigate its relationship with other microstructural and functional alterations of the subcortical nuclei and the diagnostic utility of these MRI-related metrics.

Methods

A total of 22 WD patients and 20 healthy controls (HCs) underwent 3.0T multimodal MRI scanning. Susceptibility, volume, diffusion microstructural indices and whole-brain functional connectivity of the putamen (PU), globus pallidus (GP), caudate nucleus (CN), and thalamus (TH) were analyzed. Receiver operating curve (ROC) was applied to evaluate the diagnostic value of the imaging data. Correlation analysis was performed to explore the connection between susceptibility change and microstructure and functional impairment of WD and screen for neuroimaging biomarkers of disease severity.

Results

Wilson's disease patients demonstrated increased susceptibility in the PU, GP, and TH, and widespread atrophy and microstructural impairments in the PU, GP, CN, and TH. Functional connectivity decreased within the basal ganglia and increased between the PU and cortex. The ROC model showed higher diagnostic value of isotropic volume fraction (ISOVF, in the neurite orientation dispersion and density imaging model) compared with susceptibility. Severity of neurological symptoms was correlated with volume and ISOVF. Susceptibility was positively correlated with ISOVF in GP.

Conclusion

Microstructural impairment of the basal ganglia is related to excessive metal accumulation in WD. Brain atrophy and microstructural impairments are useful neuroimaging biomarkers for the neurological impairment of WD.

Dysfunction of the Lenticular Nucleus Is Associated with Dystonia in Wilson's Disease

Dysfunction of the lenticular nucleus is thought to contribute to neurological symptoms in Wilson's disease (WD). However, very little is known about whether and how the lenticular nucleus influences dystonia by interacting with the cerebral cortex and cerebellum. To solve this problem, we recruited 37 WD patients (20 men; age, 23.95 ± 6.95 years; age range, 12-37 years) and 37 age- and sex-matched healthy controls (HCs) (25 men; age, 25.19 ± 1.88 years; age range, 20-30 years), and each subject underwent resting-state functional magnetic resonance imaging (RS-fMRI) scans. The muscle biomechanical parameters and Unified Wilson Disease Rating Scale (UWDRS) were used to evaluate the level of dystonia and clinical representations, respectively. The lenticular nucleus, including the putamen and globus pallidus, was divided into 12 subregions according to dorsal, ventral, anterior and posterior localization and seed-based functional connectivity (FC) was calculated for each subregion. The relationships between FC changes in the lenticular nucleus with muscle tension levels and clinical representations were further investigated by correlation analysis. Dystonia was diagnosed by comparing all WD muscle biomechanical parameters with healthy controls (HCs). Compared with HCs, FC decreased from all subregions in the putamen except the right ventral posterior part to the middle cingulate cortex (MCC) and decreased FC of all subregions in the putamen except the left ventral anterior part to the cerebellum was observed in patients with WD. Patients with WD also showed decreased FC of the left globus pallidus primarily distributed in the MCC and cerebellum and illustrated decreased FC from the right globus pallidus to the cerebellum. FC from the putamen to the MCC was significantly correlated with psychiatric symptoms. FC from the putamen to the cerebellum was significantly correlated with muscle tension and neurological symptoms. Additionally, the FC from the globus pallidus to the cerebellum was also associated with muscle tension. Together, these findings highlight that lenticular nucleus-cerebellum circuits may serve as neural biomarkers of dystonia and provide implications for the neural mechanisms underlying dystonia in WD.

Utilizing average symmetrical surface distance in active shape modeling for subcortical surface generation with slow-fast learning

In this paper, we propose and validate an automatic pipeline for subcortical surface generation by making use of the average symmetrical surface distance (ASSD) loss in active shape modeling (ASM). A group of template surfaces are first generated via large deformation diffeomorphic metric mapping based surface deformation. ASM is then employed to obtain the mean shape and shape variation parameters of the template surfaces. To obtain the optimal shape variation parameters which best fit the target structure after acting upon the mean shape, a recently proposed derivative-free optimization method (the slow-fast learning method) is adopted. The ASSD loss, in addition to the typically utilized Dice similarity coefficient loss, is employed during the learning process to help enhance the boundary accuracy. We successfully validate the importance of the ASSD loss through ablation analysis. In addition, we show the effectiveness of the slow-fast learning method by comparing it with other state-of-the-art derivative-free optimization algorithms. Our proposed pipeline is found to be capable of yielding subcortical surfaces with high accuracy, correct anatomical topology, and sufficient smoothness. Clinical Relevance- This work provides a useful tool for generating subcortical surfaces which are important biomarkers for a variety of brain disorders.

Increased Magnetic Susceptibility in the Deep Gray Matter Nuclei of Wilson's Disease: Have We Been Ignoring Atrophy?

Background

Histopathological studies in Wilson's disease (WD) have revealed increased copper and iron concentrations in the deep gray matter nuclei. However, the commonly used mean bulk susceptibility only reflects the regional metal concentration rather than the total metal content, and regional atrophy may affect the assessment of mean bulk susceptibility. Our study aimed to quantitatively assess the changes of metal concentration and total metal content in deep gray matter nuclei by quantitative susceptibility mapping to distinguish patients with neurological and hepatic WD from healthy controls.

Methods

Quantitative susceptibility maps were obtained from 20 patients with neurological WD, 10 patients with hepatic WD, and 25 healthy controls on a 3T magnetic resonance imaging system. Mean bulk susceptibility, volumes, and total susceptibility of deep gray matter nuclei in different groups were compared using a linear regression model. The area under the curve (AUC) was calculated by receiver characteristic curve to analyze the diagnostic capability of mean bulk susceptibility and total susceptibility.

Results

Mean bulk susceptibility and total susceptibility of multiple deep gray matter nuclei in patients with WD were higher than those in healthy controls. Compared with patients with hepatic WD, patients with neurological WD had higher mean bulk susceptibility but similar total susceptibility in the head of the caudate nuclei, globus pallidus, and putamen. Mean bulk susceptibility of putamen demonstrated the best diagnostic capability for patients with neurological WD, the AUC was 1, and the sensitivity and specificity were all equal to 1. Total susceptibility of pontine tegmentum was most significant for the diagnosis of patients with hepatic WD, the AUC was 0.848, and the sensitivity and specificity were 0.7 and 0.96, respectively.

Conclusion

Brain atrophy may affect the assessment of mean bulk susceptibility in the deep gray matter nuclei of patients with WD, and total susceptibility should be an additional metric for total metal content assessment. Mean bulk susceptibility and total susceptibility of deep gray matter nuclei may be helpful for the early diagnosis of WD.

Neuroimaging correlates of brain injury in Wilson's disease: a multimodal, whole-brain MRI study

Wilson's disease is an autosomal-recessive disorder of copper metabolism with neurological and hepatic presentations. Chelation therapy is used to 'de-copper' patients but neurological outcomes remain unpredictable. A range of neuroimaging abnormalities have been described and may provide insights into disease mechanisms, in addition to prognostic and monitoring biomarkers. Previous quantitative MRI analyses have focused on specific sequences or regions of interest, often stratifying chronically treated patients according to persisting symptoms as opposed to initial presentation. In this cross-sectional study, we performed a combination of unbiased, whole-brain analyses on T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and susceptibility-weighted imaging data from 40 prospectively recruited patients with Wilson's disease (age range 16-68). We compared patients with neurological (n = 23) and hepatic (n = 17) presentations to determine the neuroradiological sequelae of the initial brain injury. We also subcategorized patients according to recent neurological status, classifying those with neurological presentations or deterioration in the preceding 6 months as having 'active' disease. This allowed us to compare patients with active (n = 5) and stable (n = 35) disease and identify imaging correlates for persistent neurological deficits and copper indices in chronically treated, stable patients. Using a combination of voxel-based morphometry and region-of-interest volumetric analyses, we demonstrate that grey matter volumes are lower in the basal ganglia, thalamus, brainstem, cerebellum, anterior insula and orbitofrontal cortex when comparing patients with neurological and hepatic presentations. In chronically treated, stable patients, the severity of neurological deficits correlated with grey matter volumes in similar, predominantly subcortical regions. In contrast, the severity of neurological deficits did not correlate with the volume of white matter hyperintensities, calculated using an automated lesion segmentation algorithm. Using tract-based spatial statistics, increasing neurological severity in chronically treated patients was associated with decreasing axial diffusivity in white matter tracts whereas increasing serum non-caeruloplasmin-bound ('free') copper and active disease were associated with distinct patterns of increasing mean, axial and radial diffusivity. Whole-brain quantitative susceptibility mapping identified increased iron deposition in the putamen, cingulate and medial frontal cortices of patients with neurological presentations relative to those with hepatic presentations and neurological severity was associated with iron deposition in widespread cortical regions in chronically treated patients. Our data indicate that composite measures of subcortical atrophy provide useful prognostic biomarkers, whereas abnormal mean, axial and radial diffusivity are promising monitoring biomarkers. Finally, deposition of brain iron in response to copper accumulation may directly contribute to neurodegeneration in Wilson's disease.

Plasma neurofilament light chain as a biomarker in Wilson's disease

INTRODUCTION

Neurofilament light chain (NfL) was recently proposed as a promising blood biomarker for nervous system diseases, including Wilson's disease (WD). In this study, we investigated plasma NfL concentrations in patients with different types of WD and their correlations with clinical manifestations and brain atrophy.

METHODS

Seventy-five WD cases (54 neurological type, 21 hepatic type) and 27 age-matched healthy controls were included in this study. We compared plasma NfL concentrations between the different types and correlated them with Unified Wilson's Disease Rating Scale (UWDRS) scores. Patients were allocated to stable and unstable groups according to changes in UWDRS scores and clinical assessment. We compared the differences in plasma NfL concentrations between groups. Voxel-based morphometry (VBM) and FreeSurfer software were used to analyze MRI images. We investigated the correlation between plasma NfL concentrations and volume of gray matter, white matter, and several areas of interest in the brain MRI of 24 patients.

RESULTS

Plasma NfL concentrations were significantly higher in neurological type WD than in hepatic type WD (8.16 vs. 3.19 pg/mL, p < 0.001). Plasma NfL concentrations were positively correlated with UWDRS scores (r = 0.291, p = 0.035) in patients with neurological type WD. Plasma NfL was significantly higher in unstable patients than in stable patients (10.74 vs. 7.23 pg/mL, p = 0.004). Significant negative associations were found between plasma NfL level and the volumes of total gray matter, bilateral caudate nucleus, putamen, and nucleus accumbens.

CONCLUSION

Plasma NfL is valuable as a biomarker for neurological damage in patients with WD.

A Hybrid Learning Pipeline for Automated Diagnosis of First-Episode Schizophrenia Utilizing T1-weighted Images

In this work, we proposed and validated a hybrid learning pipeline for automated diagnosis of first-episode schizophrenia (FES) utilizing T1-weighted images. Amygdalar and hippocampal shape abnormalities in FES have been observed in previous studies. In this work, we jointly made use of two types of features, together with advanced machine learning techniques, for an automated discrimination of FES and healthy control (96 versus 102). Specifically, we first employed a ResNet34 model to extract convolutional neural network (CNN) features. We then combined these CNN features with shape features of the bilateral hippocampi and the bilateral amygdalas, before being inputted to advanced classification algorithms such as the Gradient Boosting Decision Tree (GBDT) for classifying between FES and healthy control. Shape features were represented using log Jacobian determinants, through a well-established statistical shape analysis pipeline. When combining CNN with hippocampal shape, the best results came from utilizing GBDT as the classifier, with an overall accuracy of 75.15%, a sensitivity of 69.35%, a specificity of 80.19%, an F1 of 72.16%, and an AUC of 79.68%. When combing CNN and amygdalar shape, the best results came from utilizing Bagging as the classifier, with an overall accuracy of 74.39%, a sensitivity of 67.93%, a specificity of 80%, an F1 of 71.11%, and an AUC of 80.98%. Compared with using each single set of features, either CNN or shape, significant improvements have been observed, in terms of FES discrimination. To the best of our knowledge, this is the first work that has tried to combine CNN features and hippocampal/amygdalar shape features for automated FES identification.

Automatic hippocampal surface generation via 3D U-net and active shape modeling with hybrid particle swarm optimization

In this paper, we proposed and validated a fully automatic pipeline for hippocampal surface generation via 3D U-net coupled with active shape modeling (ASM). Principally, the proposed pipeline consisted of three steps. In the beginning, for each magnetic resonance image, a 3D U-net was employed to obtain the automatic hippocampus segmentation at each hemisphere. Secondly, ASM was performed on a group of pre-obtained template surfaces to generate mean shape and shape variation parameters through principal component analysis. Ultimately, hybrid particle swarm optimization was utilized to search for the optimal shape variation parameters that best match the segmentation. The hippocampal surface was then generated from the mean shape and the shape variation parameters. The proposed pipeline was observed to provide hippocampal surfaces at both hemispheres with high accuracy, correct anatomical topology, and sufficient smoothness.Clinical relevance-This work provides a useful tool for generating hippocampal surfaces which are important biomarkers for a variety of brain disorders.

Basal ganglia-orbitofrontal circuits are associated with prospective memory deficits in Wilson's disease

Degenerative changes in the basal ganglia (BG) are thought to contribute to neurological symptoms in Wilson's disease (WD). However, very little is known about whether and how the BG have an influence on prospective memory (PM) by interacting with the cerebral cortex. Here, we employed structural magnetic resonance imaging to systematically examine the effect of volume atrophy of BG on cortical thickness and to evaluate the relationships between cortical thickness of regions associated with BG atrophy and PM performance in WD. Cortical thickness atrophy in the left temporal pole and medial frontal gyrus are not related to degenerative changes in BG. Cortical thickness in the left superior frontal gyrus and right orbitofrontal gyrus (ORB) have stronger correlations with volume atrophy of the left accumbens, pallidum, and putamen in WD when compared with healthy controls. Furthermore, the cortical thickness of the right ORB is not only significantly correlated with PM performance but can also distinguish the severity of PM impairment in WD. Additionally, the middle cingulate cortex was related to volume atrophy of the accumbens, and its cortical thickness has a significant positive correlation with event-based PM. Together, these findings highlight that BG-orbitofrontal circuits may serve as neural biomarkers of PM and provide implications for the neural mechanisms underlying cognitive impairment in WD.

WIKIBrainStem: An online atlas to manually segment the human brainstem at the mesoscopic scale from ultrahigh field MRI

The brainstem is one of the most densely packed areas of the central nervous system in terms of gray, but also white, matter structures and, therefore, is a highly functional hub. It has mainly been studied by the means of histological techniques, which requires several hundreds of slices with a loss of the 3D coherence of the whole specimen. Access to the inner structure of the brainstem is possible using Magnetic Resonance Imaging (MRI), but this method has a limited spatial resolution and contrast in vivo. Here, we scanned an ex vivo specimen using an ultra-high field (11.7T) preclinical MRI scanner providing data at a mesoscopic scale for anatomical T2-weighted (100 µm and 185 µm isotropic) and diffusion-weighted imaging (300 µm isotropic). We then proposed a hierarchical segmentation of the inner gray matter of the brainstem and defined a set of rules for each segmented anatomical class. These rules were gathered in a freely accessible web-based application, WIKIBrainStem (https://fibratlas.univ-tours.fr/brainstems/index.html), for 99 structures, from which 13 were subdivided into 29 substructures. This segmentation is, to date, the most detailed one developed from ex vivo MRI of the brainstem. This should be regarded as a tool that will be complemented by future results of alternative methods, such as Optical Coherence Tomography, Polarized Light Imaging or histology… This is a mandatory step prior to segmenting multiple specimens, which will be used to create a probabilistic automated segmentation method of ex vivo, but also in vivo, brainstem and may be used for targeting anatomical structures of interest in managing some degenerative or psychiatric disorders.

Associations of Brain Atrophy and Cerebral Iron Accumulation at MRI with Clinical Severity in Wilson Disease

Background Abnormal findings at brain MRI in patients with neurologic Wilson disease (WD) are characterized by signal intensity changes and cerebral atrophy. T2 signal hypointensities and atrophy are largely irreversible with treatment; their relationship with permanent disability has not been systematically investigated. Purpose To investigate associations of regional brain atrophy and iron accumulation at MRI with clinical severity in participants with neurologic WD who are undergoing long-term anti-copper treatment. Materials and Methods Participants with WD and controls were compared in a prospective study performed from 2015 to 2019. MRI at 3.0 T included three-dimensional T1-weighted and six-echo multigradient-echo pulse sequences for morphometry and quantitative susceptibility mapping, respectively. Neurologic severity was assessed with the Unified WD Rating Scale (UWDRS). Automated multi-atlas segmentation pipeline with dual contrast (susceptibility and T1) was used for the calculation of volumes and mean susceptibilities in deep gray matter nuclei. Additionally, whole-brain analysis using deformation and surface-based morphometry was performed. Least absolute shrinkage and selection operator regression was used to assess the association of regional volumes and susceptibilities with the UWDRS score. Results Twenty-nine participants with WD (mean age, 47 years ± 9 [standard deviation]; 15 women) and 26 controls (mean age, 45 years ± 12; 14 women) were evaluated. Whole-brain analysis demonstrated atrophy of the deep gray matter nuclei, brainstem, internal capsule, motor cortex and corticospinal pathway, and visual cortex and optic radiation in participants with WD (P < .05 at voxel level, corrected for family-wise error). The UWDRS score was negatively correlated with volumes of putamen (r = -0.63, P < .001), red nucleus (r = -0.58, P = .001), globus pallidus (r = -0.53, P = .003), and substantia nigra (r = -0.50, P = .006) but not with susceptibilities. Only the putaminal volume was identified as a stable factor associated with the UWDRS score (R² = 0.38, P < .001) using least absolute shrinkage and selection operator regression. Conclusion Individuals with Wilson disease (WD) had widespread brain atrophy most pronounced in the central structures. The putaminal volume was associated with the Unified WD Rating Scale score and can be used as a surrogate imaging marker of clinical severity. © RSNA, 2021 Supplemental material is available for this article. See also the editorial by Du and Bydder in this issue.

Hippocampal and Amygdalar Morphological Abnormalities in Alzheimer's Disease Based on Three Chinese MRI Datasets

BACKGROUND

Early detection of Alzheimer's disease (AD) and its early stage, the mild cognitive impairment (MCI), has important scientific, clinical and social significance. Magnetic resonance imaging (MRI) based statistical shape analysis provides an opportunity to detect regional structural abnormalities of brain structures caused by AD and MCI.

OBJECTIVE

In this work, we aimed to employ a well-established statistical shape analysis pipeline, in the framework of large deformation diffeomorphic metric mapping, to identify and quantify the regional shape abnormalities of the bilateral hippocampus and amygdala at different prodromal stages of AD, using three Chinese MRI datasets collected from different domestic hospitals.

METHODS

We analyzed the region-specific shape abnormalities at different stages of the neuropathology of AD by comparing the localized shape characteristics of the bilateral hippocampi and amygdalas between healthy controls and two disease groups (MCI and AD). In addition to group comparison analyses, we also investigated the association between the shape characteristics and the Mini Mental State Examination (MMSE) of each structure of interest in the disease group (MCI and AD combined) as well as the discriminative power of different morphometric biomarkers.

RESULTS

We found the strongest disease pathology (regional atrophy) at the subiculum and CA1 subregions of the hippocampus and the basolateral, basomedial as well as centromedial subregions of the amygdala. Furthermore, the shape characteristics of the hippocampal and amygdalar subregions exhibiting the strongest AD related atrophy were found to have the most significant positive associations with the MMSE. Employing the shape deformation marker of the hippocampus or the amygdala for automated MCI or AD detection yielded a significant accuracy boost over the corresponding volume measurement.

CONCLUSION

Our results suggested that the amygdalar and hippocampal morphometrics, especially those of shape morphometrics, can be used as auxiliary indicators for monitoring the disease status of an AD patient.

Structural and Functional Changes Are Related to Cognitive Status in Wilson's Disease

Patients with Wilson’s disease (WD) suffer from prospective memory (PM) impairment, and some of patients develop cognitive impairment. However, very little is known about how brain structure and function changes effect PM in WD. Here, we employed multimodal neuroimaging data acquired from 22 WD patients and 26 healthy controls (HC) who underwent three-dimensional T1-weighted, diffusion tensor imaging (DTI), and resting state functional magnetic resonance imaging (RS-fMRI). We investigated gray matter (GM) volumes with voxel-based morphometry, DTI metrics using the fiber tractography method, and RS-fMRI using the seed-based functional connectivity method. Compared with HC, WD patients showed GM volume reductions in the basal ganglia (BG) and occipital fusiform gyrus, as well as volume increase in the visual association cortex. Moreover, whiter matter (WM) tracks of WD were widely impaired in association and limbic fibers. WM tracks in association fibers are significant related to PM in WD patients. Relative to HC, WD patients showed that the visual association cortex functionally connects to the thalamus and hippocampus, which is associated with global cognitive function in patients with WD. Together, these findings suggested that PM impairment in WD may be modulated by aberrant WM in association fibers, and that GM volume changes in the association cortex has no direct effect on cognitive status, but indirectly affect global cognitive function by its aberrant functional connectivity (FC) in patients with WD. Our findings may provide a new window to further study how WD develops into cognitive impairment, and deepen our understanding of the cognitive status and neuropathology of WD.

Thalamic atrophy in patients with pure hereditary spastic paraplegia type 4

SPG4 is an autosomal dominant pure form of hereditary spastic paraplegia (HSP) caused by mutations in the SPAST gene. HSP is considered an upper motor neuron disorder characterized by progressive spasticity and weakness of the lower limbs caused by degeneration of the corticospinal tract. In other neurodegenerative motor disorders, the thalamus and basal ganglia are affected, with a considerable impact on disease progression. However, only a few works have studied these brain structures in HSP, mainly in complex forms of this disease. Our research aims to detect potential alterations in the volume and shape of the thalamus and various basal ganglia structures by comparing 12 patients with pure HSP and 18 healthy controls. We used two neuroimaging procedures: automated segmentation of the subcortical structures (thalamus, hippocampus, caudate nucleus, globus pallidus, and putamen) in native space and shape analysis of the structures. We found a significant reduction in thalamic volume bilaterally, as well as an inward deformation, mainly in the sensory-motor thalamic regions in patients with pure HSP and a mutation in SPG4. We also observed a significant negative correlation between the shape of the thalamus and clinical scores (the Spastic Paraplegia Rating Scale score and disease duration). Moreover, we found a 'Group × Age' interaction that was closely related to the severity of the disease. No differences in volume or in shape were found in the remaining subcortical structures studied. Our results suggest that changes in structure of the thalamus could be an imaging biomarker of disease progression in pHSP.

Structural and functional brain changes in hepatic and neurological Wilson disease

Wilson disease (WD) can manifest with hepatic or neuropsychiatric symptoms. Our understanding of the in vivo brain changes in WD, particularly in the hepatic phenotype, is limited. Thirty subjects with WD and 30 age- and gender-matched controls participated. WD group underwent neuropsychiatric assessment. Unified WD Rating Scale neurological exam scores were used to determine neurological (WDN, score > 0) and hepatic-only (WDH, score 0) subgroups. All subjects underwent 3 Tesla anatomical and resting-state functional MRI. Diffusion tensor imaging (DTI) and susceptibility-weighted imaging (SWI) were performed only in the WD group. Volumetric, DTI, and functional connectivity analyses were performed to determine between-group differences. WDN and WDH groups were matched in demographic and psychiatric profiles. The entire WD group compared to controls showed significant thinning in the bilateral superior frontal cortex. The WDN group compared to control and WDH groups showed prominent structural brain changes including significant striatal and thalamic atrophy, more subcortical hypointense lesions on SWI, and diminished white matter integrity in the bilateral anterior corona radiata and corpus callosum. However, the WDH group also showed significant white matter volume loss compared to controls. The functional connectivity between the frontostriatal nodes was significantly reduced in the WDN group, whereas that of the hippocampus was significantly increased in the WDH group compared to controls. In summary, structural and functional brain changes were present even in neurologically non-manifesting WD patients in this cross-sectional study. Longitudinal brain MRI scans may be useful as biomarkers for prognostication and optimization of treatment strategies in WD.

Whole brain volume and cortical thickness abnormalities in Wilson's disease: a clinical correlation study

Wilson's disease (WD) is an inherited autosomal recessive disorder of copper metabolism, and its neurological and neuropsychiatric manifestations are associated with copper accumulation in brain. A few neuroimaging studies have shown that gray matter atrophy in WD affects both subcortical structures and cortex. This study aims to quantitatively evaluate the morphometric brain abnormalities in patients with WD in terms of whole brain volume and cortical thickness and their associations with clinical severity of WD. Thirty patients clinically diagnosed as WD with neurological manifestations and 25 healthy controls (HC) were recruited. 3D T1-weighted images were segmented into 276 whole-brain regions of interest (ROIs) and 68 cortical ROIs. WD-vs-HC group comparisons were then conducted for each ROI. The associations between those morphometric measurements and the Global Assessment Scale (GAS) score for WD were analyzed. Compared with HC, significant WD-related volumetric decreases were found in the bilateral subcortical nuclei (putamen, globus pallidus, caudate nucleus, substantia nigra, red nucleus and thalamus), diffuse white matter and several gray matter regions. WD patients showed reduced cortical thickness in the left precentral gyrus and the left insula. Further, the volumes of the right globus pallidus, bilateral putamen, right external capsule and left superior longitudinal fasciculus were negatively correlated with GAS. Our results indicated that significant WD-related morphometric abnormalities were quantified in terms of whole-brain volumes and cortical thicknesses, some of which correlated significantly to the clinical severity of WD. Those morphometrics may provide a potentially effective biomarker of WD.

Paramagnetic Metal Accumulation in the Deep Gray Matter Nuclei Is Associated With Neurodegeneration in Wilson's Disease

Background

Neuropathological studies have revealed copper and iron accumulation in the deep gray matter (DGM) nuclei of patients with Wilson’s disease (WD). However, the association between metal accumulation and neurodegeneration in WD has not been well studied in vivo. The study was aimed to investigate whether metal accumulation in the DGM was associated with the structural and functional changes of DGM in neurological WD patients.

Methods

Seventeen neurological WD patients and 20 healthy controls were recruited for the study. Mean bulk susceptibility values and volumes of DGM were obtained from quantitative susceptibility mapping (QSM). Regions of interest including the head of the caudate nucleus, globus pallidus, putamen, thalamus, substantia nigra, red nucleus, and dentate nucleus were manually segmented. The susceptibility values and volumes of DGM in different groups were compared using a linear regression model. Correlations between susceptibility values and volumes of DGM and Unified Wilson’s Disease Rating Scale (UWDRS) neurological subscores were investigated.

Results

The susceptibility values of all examined DGM in WD patients were higher than those in healthy controls (P < 0.05). Volume reductions were observed in the head of the caudate nucleus, globus pallidus, putamen, thalamus, and substantia nigra of WD patients (P < 0.001). Susceptibility values were negatively correlated with the volumes of the head of the caudate nucleus (r_p = −0.657, P = 0.037), putamen (r_p = −0.667, P = 0.037), and thalamus (r_p = −0.613, P = 0.046) in WD patients. UWDRS neurological subscores were positively correlated with the susceptibility values of all examined DGM. The susceptibility values of putamen, head of the caudate nucleus, and dentate nucleus could well predict UWDRS neurological subscores.

Conclusion

Our study provided in vivo evidence that paramagnetic metal accumulation in the DGM was associated with DGM atrophy and neurological impairment. The susceptibility of DGM could be used as a biomarker to assess the severity of neurodegeneration in WD.

Amygdalar and Hippocampal Morphometry Abnormalities in First-Episode Schizophrenia Using Deformation-Based Shape Analysis

In this study, we investigated and quantified the amygdalar and hippocampal morphometry abnormalities exerted by first-episode schizophrenia using a total of 92 patients and 106 healthy control participants. Magnetic resonance imaging (MRI) based automated segmentation was conducted to obtain the amygdalar and hippocampal segmentations. Disease-versus-control volume differences of the bilateral amygdalas and hippocampi were quantified. In addition, deformation-based statistical shape analysis was employed to quantify the region-specific shape abnormalities of each structure of interest. To better identify the key relevant areas in the pathology of first-episode schizophrenia, each structure was divided into four subregions; CA1, CA2, CA3 combined with dentate gyrus for the hippocampus in each hemisphere and basolateral, basomedial, centromedial, and lateral nucleus for the amygdala in each hemisphere. We observed significant global volume reduction and localized shape atrophy in each of the four structures of interest. The amygdalar shape abnormalities mainly occurred at the basolateral and centromedial subregions, whereas the hippocampal shape abnormalities mainly concentrated on the CA1 and CA2 subregions. For the same structure, the one on the right hemisphere was affected more by the disease pathology than that on the left hemisphere. To conclude, we have successfully quantified the global and local morphometric abnormalities of the bilateral amygdalas and hippocampi using a sophisticated statistical analysis pipeline and high-field subregion segmentations, with MRI data of a considerable sample size. This study is one of the very first of such kind in first-episode schizophrenia analyses.