Voxel-based morphometry in individual patients: a pilot study in early Huntington disease

Voxel-based morphometry in single subjects without a scanner-specific normal database using a convolutional neural network

OBJECTIVES

Reliable detection of disease-specific atrophy in individual T1w-MRI by voxel-based morphometry (VBM) requires scanner-specific normal databases (NDB), which often are not available. The aim of this retrospective study was to design, train, and test a deep convolutional neural network (CNN) for single-subject VBM without the need for a NDB (CNN-VBM).

MATERIALS AND METHODS

The training dataset comprised 8945 T1w scans from 65 different scanners. The gold standard VBM maps were obtained by conventional VBM with a scanner-specific NDB for each of the 65 scanners. CNN-VBM was tested in an independent dataset comprising healthy controls (n = 37) and subjects with Alzheimer's disease (AD, n = 51) or frontotemporal lobar degeneration (FTLD, n = 30). A scanner-specific NDB for the generation of the gold standard VBM maps was available also for the test set. The technical performance of CNN-VBM was characterized by the Dice coefficient of CNN-VBM maps relative to VBM maps from scanner-specific VBM. For clinical testing, VBM maps were categorized visually according to the clinical diagnoses in the test set by two independent readers, separately for both VBM methods.

RESULTS

The VBM maps from CNN-VBM were similar to the scanner-specific VBM maps (median Dice coefficient 0.85, interquartile range [0.81, 0.90]). Overall accuracy of the visual categorization of the VBM maps for the detection of AD or FTLD was 89.8% for CNN-VBM and 89.0% for scanner-specific VBM.

CONCLUSION

CNN-VBM without NDB provides a similar performance in the detection of AD- and FTLD-specific atrophy as conventional VBM.

CLINICAL RELEVANCE STATEMENT

A deep convolutional neural network for voxel-based morphometry eliminates the need of scanner-specific normal databases without relevant performance loss and, therefore, could pave the way for the widespread clinical use of voxel-based morphometry to support the diagnosis of neurodegenerative diseases.

KEY POINTS

• The need of normal databases is a barrier for widespread use of voxel-based brain morphometry. • A convolutional neural network achieved a similar performance for detection of atrophy than conventional voxel-based morphometry. • Convolutional neural networks can pave the way for widespread clinical use of voxel-based morphometry.

Removing outliers from the normative database improves regional atrophy detection in single-subject voxel-based morphometry

PURPOSE

Single-subject voxel-based morphometry (VBM) compares an individual T1-weighted MRI to a sample of normal MRI in a normative database (NDB) to detect regional atrophy. Outliers in the NDB might result in reduced sensitivity of VBM. The primary aim of the current study was to propose a method for outlier removal ("NDB cleaning") and to test its impact on the performance of VBM for detection of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD).

METHODS

T1-weighted MRI of 81 patients with biomarker-confirmed AD (n = 51) or FTLD (n = 30) and 37 healthy subjects with simultaneous FDG-PET/MRI were included as test dataset. Two different NDBs were used: a scanner-specific NDB (37 healthy controls from the test dataset) and a non-scanner-specific NDB comprising 164 normal T1-weighted MRI from 164 different MRI scanners. Three different quality metrics based on leave-one-out testing of the scans in the NDB were implemented. A scan was removed if it was an outlier with respect to one or more quality metrics. VBM maps generated with and without NDB cleaning were assessed visually for the presence of AD or FTLD.

RESULTS

Specificity of visual interpretation of the VBM maps for detection of AD or FTLD was 100% in all settings. Sensitivity was increased by NDB cleaning with both NDBs. The effect was statistically significant for the multiple-scanner NDB (from 0.47 [95%-CI 0.36-0.58] to 0.61 [0.49-0.71]).

CONCLUSION

NDB cleaning has the potential to improve the sensitivity of VBM for the detection of AD or FTLD without increasing the risk of false positive findings.

Optical coherence tomography with voxel-based morphometry: a new tool to unveil focal retinal neurodegeneration in multiple sclerosis

Neurodegeneration is the main contributor to disability accumulation in multiple sclerosis. Previous studies in neuro-ophthalmology have revealed that neurodegeneration in multiple sclerosis also affects the neuro-retina. Optical coherence tomography has been used to measure thinning of retinal layers, which correlates with several other markers for axonal/neuronal loss in multiple sclerosis. However, the existing analytical tools have limitations in terms of sensitivity and do not provide topographical information. In this study, we aim to evaluate whether voxel-based morphometry can increase sensitivity in detecting neuroaxonal degeneration in the retina and offer topographical information. A total of 131 people with multiple sclerosis (41 clinically isolated syndrome, 53 relapsing-remitting and 37 progressive multiple sclerosis) and 50 healthy subjects were included. Only eyes with normal global peripapillary retinal nerve fibre layer thickness and no history of optic neuritis were considered. Voxel-based morphometry and voxel-wise statistical comparisons were performed on the following: (i) patients at different disease stages and 2) patients who experienced the first demyelination attack without subclinical optic neuritis, assessed by visual evoked potentials. Standard parameters failed to discern any differences; however, voxel-based morphometry-optical coherence tomography successfully detected focal macular atrophy of retinal nerve fibre layer and ganglion cell/inner plexiform layer, along with thickening of inner nuclear layer in patients who experienced the first demyelination attack (disease duration = 4.2 months). Notably, the atrophy pattern of the ganglion cell/inner plexiform layer was comparable across disease phenotypes. In contrast, the retinal nerve fibre layer atrophy spread from the optic nerve head to the fovea as the disease evolved towards the progressive phase. Furthermore, for patients who experienced the first neurological episode, the severity of retinal nerve fibre layer atrophy at entry could predict a second attack. Our results demonstrate that voxel-based morphometry-optical coherence tomography exhibits greater sensitivity than standard parameters in detecting focal retinal atrophy, even at clinical presentation, in eyes with no history of optic neuritis and with normal latency of visual evoked potentials. Thinning of the ganglion cell/inner plexiform layer primarily concentrated in nasal perifovea in all disease phenotypes, indicating selective vulnerability of retinal ganglion cells and their perifoveal axons. Conversely, the degree of retinal nerve fibre layer thinning seems to be related to the clinical course of multiple sclerosis. The findings suggest bidirectional neurodegeneration in the visual pathway. Voxel-based morphometry-optical coherence tomography shows potential as a valuable tool for monitoring neurodegeneration on a patient level and evaluating the efficacy of novel neuroprotective treatments.

Fine-grained age-matching improves atrophy-based detection of mild cognitive impairment more than amyloid-negative reference subjects

INTRODUCTION

In clinical practice, differentiating between age-related gray matter (GM) atrophy and neurodegeneration-related atrophy at early disease stages, such as mild cognitive impairment (MCI), remains challenging. We hypothesized that fined-grained adjustment for age effects and using amyloid-negative reference subjects could increase classification accuracy.

METHODS

T1-weighted magnetic resonance imaging (MRI) data of 131 cognitively normal (CN) individuals and 91 patients with MCI from the Alzheimer's disease neuroimaging initiative (ADNI) characterized concerning amyloid status, as well as 19 CN individuals and 19 MCI patients from an independent validation sample were segmented, spatially normalized and analyzed in the framework of voxel-based morphometry (VBM). For each participant, statistical maps of GM atrophy were computed as the deviation from the GM of CN reference groups at the voxel level. CN reference groups composed with different degrees of age-matching, and mixed and strictly amyloid-negative CN reference groups were examined regarding their effect on the accuracy in distinguishing between CN and MCI. Furthermore, the effects of spatial smoothing and atrophy threshold were assessed.

RESULTS

Approaches with a specific reference group for each age significantly outperformed all other age-adjustment strategies with a maximum area under the curve of 1.0 in the ADNI sample and 0.985 in the validation sample. Accounting for age in a regression-based approach improved classification accuracy over that of a single CN reference group in the age range of the patient sample. Using strictly amyloid-negative reference groups improved classification accuracy only when age was not considered.

CONCLUSION

Our results demonstrate that VBM can differentiate between age-related and MCI-associated atrophy with high accuracy. Crucially, age-specific reference groups significantly increased accuracy, more so than regression-based approaches and using amyloid-negative reference groups.

Ex vivo 100 μm isotropic diffusion MRI-based tractography of connectivity changes in the end-stage R6/2 mouse model of Huntington's disease

Background

Huntington's disease is a progressive neurodegenerative disorder. Brain atrophy, as measured by volumetric magnetic resonance imaging (MRI), is a downstream consequence of neurodegeneration, but microstructural changes within brain tissue are expected to precede this volumetric decline. The tissue microstructure can be assayed non-invasively using diffusion MRI, which also allows a tractographic analysis of brain connectivity.

Methods

We here used ex vivo diffusion MRI (11.7 T) to measure microstructural changes in different brain regions of end-stage (14 weeks of age) wild type and R6/2 mice (male and female) modeling Huntington's disease. To probe the microstructure of different brain regions, reduce partial volume effects and measure connectivity between different regions, a 100 μm isotropic voxel resolution was acquired.

Results

Although fractional anisotropy did not reveal any difference between wild-type controls and R6/2 mice, mean, axial, and radial diffusivity were increased in female R6/2 mice and decreased in male R6/2 mice. Whole brain streamlines were only reduced in male R6/2 mice, but streamline density was increased. Region-to-region tractography indicated reductions in connectivity between the cortex, hippocampus, and thalamus with the striatum, as well as within the basal ganglia (striatum-globus pallidus-subthalamic nucleus-substantia nigra-thalamus).

Conclusions

Biological sex and left/right hemisphere affected tractographic results, potentially reflecting different stages of disease progression. This proof-of-principle study indicates that diffusion MRI and tractography potentially provide novel biomarkers that connect volumetric changes across different brain regions. In a translation setting, these measurements constitute a novel tool to assess the therapeutic impact of interventions such as neuroprotective agents in transgenic models, as well as patients with Huntington's disease.

Impact of normative brain volume reports on the diagnosis of neurodegenerative dementia disorders in neuroradiology: A real-world, clinical practice study

Background: Normative brain volume reports (NBVR) are becoming more available in the work-up of patients with suspected dementia disorders, potentially leveraging the value of structural MRI in clinical settings. The present study aims to investigate the impact of NBVRs on the diagnosis of neurodegenerative dementia disorders in real-world clinical practice.

Methods: We retrospectively analyzed data of 112 memory clinic patients, who were consecutively referred for MRI and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) during a 12-month period. Structural MRI was assessed by two residents with 2 and 3 years of neuroimaging experience. Statements and diagnostic confidence regarding the presence of a neurodegenerative disorder in general (first level) and Alzheimer’s disease (AD) pattern in particular (second level) were recorded without and with NBVR information. FDG-PET served as the reference standard.

Results: Overall, despite a trend towards increased accuracy, the impact of NBVRs on diagnostic accuracy was low and non-significant. We found a significant drop of sensitivity (0.75–0.58; p < 0.001) and increase of specificity (0.62–0.85; p < 0.001) for rater 1 at identifying patients with neurodegenerative dementia disorders. Diagnostic confidence increased for rater 2 (p < 0.001).

Conclusions: Overall, NBVRs had a limited impact on diagnostic accuracy in real-world clinical practice. Potentially, NBVR might increase diagnostic specificity and confidence of neuroradiology residents. To this end, a well-defined framework for integration of NBVR in the diagnostic process and improved algorithms of NBVR generation are essential.

Hyper-Adaptation in the Human Brain: Functional and Structural Changes in the Foot Section of the Primary Motor Cortex in a Top Wheelchair Racing Paralympian

The human brain has the capacity to drastically alter its somatotopic representations in response to congenital or acquired limb deficiencies and dysfunctions. The main purpose of the present study was to elucidate such extreme adaptability in the brain of an active top wheelchair racing Paralympian (participant P1) who has congenital paraplegia (dysfunction of bilateral lower limbs). Participant P1 has undergone long-term wheelchair racing training using bilateral upper limbs and has won a total of 19 medals in six consecutive summer Paralympic games as of 2021. We examined the functional and structural changes in the foot section of the primary motor cortex (M1) in participant P1 as compared to able-bodied control participants. We also examined the functional and structural changes in three other individuals (participants P2, P3, and P4) with acquired paraplegia, who also had long-term non-use period of the lower limbs and had undergone long-term training for wheelchair sports (but not top athletes at the level of participant P1). We measured brain activity in all the participants using functional magnetic resonance imaging (MRI) when bimanual wrist extension-flexion movement was performed, and the structural MRI images were collected. Compared to 37 control participants, participant P1 showed significantly greater activity in the M1 foot section during the bimanual task, and significant local GM expansion in this section. Significantly greater activity in the M1 foot section was also observed in participant P4, but not in P2 and P3, and the significant local GM expansion was observed in participant P2, but not in P3 and P4. Thus, functional or structural change was observed in an acquired paraplegic participant, but was not observed in all the paraplegic participants. The functional and structural changes typically observed in participant P1 may represent extreme adaptability of the human brain. We discuss the results in terms of a new idea of hyper-adaptation.

Altered large-scale functional brain networks in neurological Wilson's disease

Wilson's disease patients with neurological symptoms have motor symptoms and cognitive deficits, including frontal executive, visuospatial processing, and memory impairments. Although the brain structural abnormalities associated with Wilson's disease have been documented, it remains largely unknown how Wilson's disease affects large-scale functional brain networks. In this study, we investigated functional brain networks in Wilson's disease. Particularly, we analyzed resting state functional magnetic resonance images of 30 Wilson's disease patients and 26 healthy controls. First, functional brain networks for each participant were extracted using an independent component analysis method. Then, a computationally efficient pattern classification method was developed to identify discriminative brain functional networks associated with Wilson's disease. Experimental results indicated that Wilson's disease patients, compared with healthy controls, had altered large-scale functional brain networks, including the dorsal anterior cingulate cortex and basal ganglia network, the middle frontal gyrus, the dorsal striatum, the inferior parietal lobule, the precuneus, the temporal pole, and the posterior lobe of cerebellum. Classification models built upon these networks distinguished between neurological WD patients and HCs with accuracy up to 86.9% (specificity: 86.7%, sensitivity: 89.7%). The classification scores were correlated with the United Wilson's Disease Rating Scale measures and durations of disease of the patients. These results suggest that Wilson's disease patients have multiple aberrant brain functional networks, and classification scores derived from these networks are associated with severity of clinical symptoms.

Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging

Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand-alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR-negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel-wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion-weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR-negative epilepsy patients.

Assisted Reproductive Techniques and Genetic Manipulation in the Common Marmoset

Genetic modification of nonhuman primate (NHP) zygotes is a useful method for the development of NHP models of human diseases. This review summarizes the recent advances in the development of assisted reproductive and genetic manipulation techniques in NHP, providing the basis for the generation of genetically modified NHP disease models. In this study, we review assisted reproductive techniques, including ovarian stimulation, in vitro maturation of oocytes, in vitro fertilization, embryo culture, embryo transfer, and intracytoplasmic sperm injection protocols in marmosets. Furthermore, we review genetic manipulation techniques, including transgenic strategies, target gene knock-out and knock-in using gene editing protocols, and newly developed gene-editing approaches that may potentially impact the production of genetically manipulated NHP models. We further discuss the progress of assisted reproductive and genetic manipulation techniques in NHP; future prospects on genetically modified NHP models for biomedical research are also highlighted.

Machine learning for filtering out false positive grey matter atrophies in single subject voxel based morphometry: A simulation based study

Single subject VBM (SS-VBM), has been used as an alternative tool to standard VBM for single case studies. However, it has the disadvantage of producing an excessively large number of false positive detections. In this study we propose a machine learning technique widely used for automated data classification, namely Support Vector Machine (SVM), to refine the findings produced by SS-VBM. A controlled set of experiments was conducted to evaluate the proposed approach using three-dimensional T1 MRI scans from control subjects collected from the publicly available IXI dataset. The scans were artificially atrophied at different locations and with different sizes to mimic the behavior of neurological disorders. Results empirically demonstrated that the proposed method is able to significantly reduce the amount of false positive clusters (p < 0.05), with no statistical differences in the true positive findings (p > 0.05). This evidence was observed to be consistent for different atrophied areas and sizes of atrophies. This approach could be potentially be applied to alleviate the intensive manual analysis that radiologists and clinicians have to perform to filter out miss-detections of SS-VBM, increasing its usability for image reading.

The pathoconnectivity network analysis of the insular cortex: A morphometric fingerprinting

Brain disorders tend to impact on many different regions in a typical way: alterations do not spread randomly; rather, they seem to follow specific patterns of propagation that show a strong overlap between different pathologies. The insular cortex is one of the brain areas more involved in this phenomenon, as it seems to be altered by a wide range of brain diseases. On these grounds we thoroughly investigated the impact of brain disorders on the insular cortices analyzing the patterns of their structural co-alteration. We therefore investigated, applying a network analysis approach to meta-analytic data, 1) what pattern of gray matter alteration is associated with each of the insular cortex parcels; 2) whether or not this pattern correlates and overlaps with its functional meta-analytic connectivity; and, 3) the behavioral profile related to each insular co-alteration pattern. All the analyses were repeated considering two solutions: one with two clusters and another with three. Our study confirmed that the insular cortex is one of the most altered cerebral regions among the cortical areas, and exhibits a dense network of co-alteration including a prevalence of cortical rather than sub-cortical brain regions. Regions of the frontal lobe are the most involved, while occipital lobe is the less affected. Furthermore, the co-alteration and co-activation patterns greatly overlap each other. These findings provide significant evidence that alterations caused by brain disorders are likely to be distributed according to the logic of network architecture, in which brain hubs lie at the center of networks composed of co-altered areas. For the first time, we shed light on existing differences between insula sub-regions even in the pathoconnectivity domain.

Descriptive neuroradiology: beyond the hummingbird

Radiology signs have long been described in ways that communicate the imagery around us to enhance our cognitive perception. Here, we describe the use and limitations of 10 such signs in neuroradiology, divided into three groups. The first are signs that are reliable for a specific diagnosis, such as the Medusa head sign indicating a developmental venous anomaly, or a racing car sign in agenesis of corpus callosum. The second group of signs helps us to diagnose rare conditions, such as the onion skin sign in Balo's concentric sclerosis. The third group is of unreliable signs that may lead clinicians astray. For example, the absence of a swallow-tail sign in Parkinson's disease or the presence of a hummingbird sign and Mickey Mouse sign in progressive supranuclear palsy. The appropriate use of these signs in clinical practice is essential.

Normative brain volume reports may improve differential diagnosis of dementing neurodegenerative diseases in clinical practice

OBJECTIVES

Normative brain volume reports (NBVRs) are becoming more and more available for the workup of dementia patients in clinical routine. However, it is yet unknown how this information can be used in the radiological decision-making process. The present study investigates the diagnostic value of NBVRs for detection and differential diagnosis of distinct regional brain atrophy in several dementing neurodegenerative disorders.

METHODS

NBVRs were obtained for 81 consecutive patients with distinct dementing neurodegenerative diseases and 13 healthy controls (HC). Forty Alzheimer's disease (AD; 18 with dementia, 22 with mild cognitive impairment (MCI), 11 posterior cortical atrophy (PCA)), 20 frontotemporal dementia (FTD), and ten semantic dementia (SD) cases were analyzed, and reports were tested qualitatively for the representation of atrophy patterns. Gold standard diagnoses were based on the patients' clinical course, FDG-PET imaging, and/or cerebrospinal fluid (CSF) biomarkers following established diagnostic criteria. Diagnostic accuracy of pattern representations was calculated.

RESULTS

NBVRs improved the correct identification of patients vs. healthy controls based on structural MRI for rater 1 (p < 0.001) whereas the amount of correct classifications was rather unchanged for rater 2. Correct differential diagnosis of dementing neurodegenerative disorders was significantly improved for both rater 1 (p = 0.001) and rater 2 (p = 0.022). Furthermore, interrater reliability was improved from moderate to excellent for both detection and differential diagnosis of neurodegenerative diseases (κ = 0.556/0.894 and κ = 0.403/0.850, respectively).

CONCLUSION

NBVRs deliver valuable and observer-independent information, which can improve differential diagnosis of neurodegenerative diseases.

KEY POINTS

• Normative brain volume reports increase detection of neurodegenerative atrophy patterns compared to visual reading alone. • Differential diagnosis of regionally distinct atrophy patterns is improved. • Agreement between radiologists is significantly improved from moderate to excellent when using normative brain volume reports.

Tracking the brain in myotonic dystrophies: A 5-year longitudinal follow-up study

Objectives

The aim of this study was to examine the natural history of brain involvement in adult-onset myotonic dystrophies type 1 and 2 (DM1, DM2).

Methods

We conducted a longitudinal observational study to examine functional and structural cerebral changes in myotonic dystrophies. We enrolled 16 adult-onset DM1 patients, 16 DM2 patients, and 17 controls. At baseline and after 5.5 ± 0.4 years participants underwent neurological, neuropsychological, and 3T-brain MRI examinations using identical study protocols that included voxel-based morphometry and diffusion tensor imaging. Data were analyzed by (i) group comparisons between patients and controls at baseline and follow-up, and (ii) group comparisons using difference maps (baseline–follow-up in each participant) to focus on disease-related effects over time.

Results

We found minor neuropsychological deficits with mild progression in DM1 more than DM2. Daytime sleepiness was restricted to DM1, whereas fatigue was present in both disease entities and stable over time. Comparing results of cross-sectional neuroimaging analyses at baseline and follow-up revealed an unchanged pattern of pronounced white matter alterations in DM1. There was mild additional gray matter reduction in DM1 at follow-up. In DM2, white matter reduction was of lesser extent, but there were some additional alterations at follow-up. Gray matter seemed unaffected in DM2. Intriguingly, longitudinal analyses using difference maps and comparing them between patients and controls did not reveal any significant differences of cerebral changes over time between patients and controls.

Conclusion

The lack of significant disease-related progression of gray and white matter involvement over a period of five years in our cohort of DM1 and DM2 patients suggests either a rather slowly progressive process or even a stable course of cerebral changes in middle-aged adult-onset patients. Being the first longitudinal neuroimaging trial in DM1 and DM2, this study provides useful additional information regarding the natural history of brain involvement.

Personalized pathology maps to quantify diffuse and focal brain damage

Background and objectives

Quantitative MRI (qMRI) permits the quantification of brain changes compatible with inflammation, degeneration and repair in multiple sclerosis (MS) patients. In this study, we propose a new method to provide personalized maps of tissue alterations and longitudinal brain changes based on different qMRI metrics, which provide complementary information about brain pathology.

Methods

We performed baseline and two-years follow-up on (i) 13 relapsing-remitting MS patients and (ii) four healthy controls. A group consisting of up to 65 healthy controls was used to compute the reference distribution of qMRI metrics in healthy tissue. All subjects underwent 3T MRI examinations including T1, T2, T2* relaxation and Magnetization Transfer Ratio (MTR) imaging. We used a recent partial volume estimation algorithm to estimate the concentration of different brain tissue types on T1 maps; then, we computed a deviation map (z-score map) for each contrast at both time-points. Finally, we subtracted those deviation maps only for voxels showing a significant difference with healthy tissue in one of the time points, to obtain a difference map for each subject.

Results and conclusion

Control subjects did not show any significant z-score deviations or longitudinal z-score changes. On the other hand, MS patients showed brain regions with cross-sectional and longitudinal concomitant increase in T1, T2, T2* z-scores and decrease of MTR z-scores, suggesting brain tissue degeneration/loss. In the lesion periphery, we observed areas with cross-sectional and longitudinal decreased T1/T2 and slight decrease in T2* most likely related to iron accumulation. Moreover, we measured longitudinal decrease in T1, T2 - and to a lesser extent in T2* - as well as a concomitant increase in MTR, suggesting remyelination/repair.

In summary, we have developed a method that provides whole-brain personalized maps of cross-sectional and longitudinal changes in MS patients, which are computed in patient space. These maps may open new perspectives to complement and support radiological evaluation of brain damage for a given patient.

Statistical Structural Analysis of Familial Spontaneous Epileptic Cats Using Voxel-Based Morphometry

Voxel-based morphometry (VBM) based on high resolution three-dimensional data of magnetic resonance imaging has been developed as a statistical morphometric imaging analysis method to locate brain abnormalities in humans. Recently, VBM has been used for human patients with psychological or neurological disorders such as Alzheimer's disease, Parkinson's disease, and epilepsy. Traditional volumetry using region of interest (ROI) is performed manually and the observer needs detailed knowledge of the neuroanatomy having to trace objects of interest on many slices which can cause artificial errors. In contrast, VBM is an automatic technique that has less observer biases compared to the ROI method. In humans, VBM analysis is performed in patients with epilepsy to detect accurately structural abnormalities. Familial spontaneous epileptic cats (FSECs) have been developed as an animal model of mesial temporal lobe epilepsy. In FSECs, hippocampal asymmetry had been detected using three-dimensional magnetic resonance (MR) volumetry based on the ROI method. In this study, we produced a standard template of the feline brain and compared FSECs and healthy cats using standard VBM analysis. The feline standard template and tissue probability maps were created using 38 scans from 14 healthy cats. Subsequently, the gray matter was compared between FSECs (n = 25) and healthy controls (n = 12) as group analysis and between each FSEC and controls as individual analysis. The feline standard template and tissue probability maps could be created using the VBM tools for humans. There was no significant reduction of GM in the FSEC group compared to the control group. However, 5/25 (20%) FSECs showed significant decreases in the hippocampal and/or amygdaloid regions in individual analysis. Here, we established the feline standard templates of the brain that can be used to determine accurately abnormal zones. Furthermore, like MR volumetry, VBM identified morphometric changes in the hippocampus and/or amygdala in some FSECs.

Estimates of age-dependent cutoffs for pathological brain volume loss using SIENA/FSL-a longitudinal brain volumetry study in healthy adults

Brain volume loss (BVL) has gained increasing interest for monitoring tissue damage in neurodegenerative diseases including multiple sclerosis (MS). In this longitudinal study, 117 healthy participants (age range 37.3-82.6 years) received at least 2 magnetic resonance imaging examinations. BVL (in %) was determined with the Structural Image Evaluation using Normalisation of Atrophy/FMRIB Software Library and annualized. Mean BVL per year was 0.15%, 0.30%, 0.46%, and 0.61% at ages 45, 55, 65, and 75 years, respectively. The corresponding BVL per year values of the age-dependent 95th percentiles were 0.52%, 0.77%, 1.05% and 1.45%. Pathological BVL can be assumed if an individual BVL per year exceeds these thresholds for a given age. The mean BVL per year determined in this longitudinal study was consistent with results from a cross-sectional study that was published recently. The cut-off for a pathological BVL per year at the age of 45 years (0.52%) was consistent with the cut-off suggested previously to distinguish between physiological and pathological BVL in MS patients. Different cut-off values, however, need to be considered when interpreting BVL assessed in cohorts of higher ages.

Logopenic Aphasia due to a Strategic Stroke: New Evidence from a Single Case

Among primary progressive aphasias (PPAs), logopenic variant PPA (lv-PPA) is usually related to Alzheimer's disease. Although it has been widely clinically and pathologically evaluated, the topography in LPA is still controversial. We report a patient presenting with a logopenic syndrome due to a strategic lesion located in the superior and middle temporal gyrus and compare our findings with those of a PiB-PET positive lv-PPA patient matched by age, gender, and education. We consider that our study provides new anatomical clues to better understand the cognitive mechanisms underlying the logopenic syndrome.

Optimization of Statistical Single Subject Analysis of Brain FDG PET for the Prognosis of Mild Cognitive Impairment-to-Alzheimer's Disease Conversion

BACKGROUND

Positron emission tomography (PET) with the glucose analog F-18-fluorodeoxyglucose (FDG) is widely used in the diagnosis of neurodegenerative diseases. Guidelines recommend voxel-based statistical testing to support visual evaluation of the PET images. However, the performance of voxel-based testing strongly depends on each single preprocessing step involved.

OBJECTIVE

To optimize the processing pipeline of voxel-based testing for the prognosis of dementia in subjects with amnestic mild cognitive impairment (MCI).

METHODS

The study included 108 ADNI MCI subjects grouped as 'stable MCI' (n = 77) or 'MCI-to-AD converter' according to their diagnostic trajectory over 3 years. Thirty-two ADNI normals served as controls. Voxel-based testing was performed with the statistical parametric mapping software (SPM8) starting with default settings. The following modifications were added step-by-step: (i) motion correction, (ii) custom-made FDG template, (iii) different reference regions for intensity scaling, and (iv) smoothing was varied between 8 and 18 mm. The t-sum score for hypometabolism within a predefined AD mask was compared between the different settings using receiver operating characteristic (ROC) analysis with respect to differentiation between 'stable MCI' and 'MCI-to-AD converter'. The area (AUC) under the ROC curve was used as performance measure.

RESULTS

The default setting provided an AUC of 0.728. The modifications of the processing pipeline improved the AUC up to 0.832 (p = 0.046). Improvement of the AUC was confirmed in an independent validation sample of 241 ADNI MCI subjects (p = 0.048).

CONCLUSION

The prognostic value of voxel-based single subject analysis of brain FDG PET in MCI subjects can be improved considerably by optimizing the processing pipeline.

Early neuroimaging markers of FOXP2 intragenic deletion

FOXP2 is the major gene associated with severe, persistent, developmental speech and language disorders. While studies in the original family in which a FOXP2 mutation was found showed volume reduction and reduced activation in core language and speech networks, there have been no imaging studies of different FOXP2 mutations. We conducted a multimodal MRI study in an eight-year-old boy (A-II) with a de novo FOXP2 intragenic deletion. A-II showed marked bilateral volume reductions in the hippocampus, thalamus, globus pallidus, and caudate nucleus compared with 26 control males (effect sizes from −1 to −3). He showed no detectable functional MRI activity when repeating nonsense words. The hippocampus is implicated for the first time in FOXP2 diseases. We conclude that FOXP2 anomaly is either directly or indirectly associated with atypical development of widespread subcortical networks early in life.

Diagnostic Potential of Pulsed Arterial Spin Labeling in Alzheimer's Disease

Alzheimers disease (AD) is the most common cause of dementia. Although the underlying pathology is still not completely understood, several diagnostic methods are available. Frequently, the most accurate methods are also the most invasive. The present work investigates the diagnostic potential of Pulsed Arterial Spin Labeling (PASL) for AD: a non-invasive, MRI-based technique for the quantification of regional cerebral blood flow (rCBF). In particular, we propose a pilot computer aided diagnostic (CAD) procedure able to discriminate between healthy and diseased subjects, and at the same time, providing visual informative results. This method encompasses the creation of a healthy model, the computation of a voxel-wise likelihood function as comparison between the healthy model and the subject under examination, and the correction of the likelihood function via prior distributions. The discriminant analysis is carried out to maximize the accuracy of the classification. The algorithm has been trained on a dataset of 81 subjects and achieved a sensitivity of 0.750 and a specificity of 0.875. Moreover, in accordance with the current pathological knowledge, the parietal lobe, and limbic system are shown to be the main discriminant factors.

When the Single Matters more than the Group (II): Addressing the Problem of High False Positive Rates in Single Case Voxel Based Morphometry Using Non-parametric Statistics

In recent years, an increasing number of studies have used Voxel Based Morphometry (VBM) to compare a single patient with a psychiatric or neurological condition of interest against a group of healthy controls. However, the validity of this approach critically relies on the assumption that the single patient is drawn from a hypothetical population with a normal distribution and variance equal to that of the control group. In a previous investigation, we demonstrated that family-wise false positive error rate (i.e., the proportion of statistical comparisons yielding at least one false positive) in single case VBM are much higher than expected (Scarpazza et al., 2013). Here, we examine whether the use of non-parametric statistics, which does not rely on the assumptions of normal distribution and equal variance, would enable the investigation of single subjects with good control of false positive risk. We empirically estimated false positive rates (FPRs) in single case non-parametric VBM, by performing 400 statistical comparisons between a single disease-free individual and a group of 100 disease-free controls. The impact of smoothing (4, 8, and 12 mm) and type of pre-processing (Modulated, Unmodulated) was also examined, as these factors have been found to influence FPRs in previous investigations using parametric statistics. The 400 statistical comparisons were repeated using two independent, freely available data sets in order to maximize the generalizability of the results. We found that the family-wise error rate was 5% for increases and 3.6% for decreases in one data set; and 5.6% for increases and 6.3% for decreases in the other data set (5% nominal). Further, these results were not dependent on the level of smoothing and modulation. Therefore, the present study provides empirical evidence that single case VBM studies with non-parametric statistics are not susceptible to high false positive rates. The critical implication of this finding is that VBM can be used to characterize neuroanatomical alterations in individual subjects as long as non-parametric statistics are employed.

Investigating Neuroanatomical Features in Top Athletes at the Single Subject Level

In sport events like Olympic Games or World Championships competitive athletes keep pushing the boundaries of human performance. Compared to team sports, high achievements in many athletic disciplines depend solely on the individual's performance. Contrasting previous research looking for expertise-related differences in brain anatomy at the group level, we aim to demonstrate changes in individual top athlete's brain, which would be averaged out in a group analysis. We compared structural magnetic resonance images (MRI) of three professional track-and-field athletes to age-, gender- and education-matched control subjects. To determine brain features specific to these top athletes, we tested for significant deviations in structural grey matter density between each of the three top athletes and a carefully matched control sample. While total brain volumes were comparable between athletes and controls, we show regional grey matter differences in striatum and thalamus. The demonstrated brain anatomy patterns remained stable and were detected after 2 years with Olympic Games in between. We also found differences in the fusiform gyrus in two top long jumpers. We interpret our findings in reward-related areas as correlates of top athletes' persistency to reach top-level skill performance over years.

Patient-specific detection of cerebral blood flow alterations as assessed by arterial spin labeling in drug-resistant epileptic patients

Electrophysiological and hemodynamic data can be integrated to accurately and precisely identify the generators of abnormal electrical activity in drug-resistant focal epilepsy. Arterial Spin Labeling (ASL), a magnetic resonance imaging (MRI) technique for quantitative noninvasive measurement of cerebral blood flow (CBF), can provide a direct measure of variations in cerebral perfusion associated with the epileptic focus. In this study, we aimed to confirm the ASL diagnostic value in the identification of the epileptogenic zone, as compared to electrical source imaging (ESI) results, and to apply a template-based approach to depict statistically significant CBF alterations. Standard video-electroencephalography (EEG), high-density EEG, and ASL were performed to identify clinical seizure semiology and noninvasively localize the epileptic focus in 12 drug-resistant focal epilepsy patients. The same ASL protocol was applied to a control group of 17 healthy volunteers from which a normal perfusion template was constructed using a mixed-effect approach. CBF maps of each patient were then statistically compared to the reference template to identify perfusion alterations. Significant hypo- and hyperperfused areas were identified in all cases, showing good agreement between ASL and ESI results. Interictal hypoperfusion was observed at the site of the seizure in 10/12 patients and early postictal hyperperfusion in 2/12. The epileptic focus was correctly identified within the surgical resection margins in the 5 patients who underwent lobectomy, all of which had good postsurgical outcomes. The combined use of ESI and ASL can aid in the noninvasive evaluation of drug-resistant epileptic patients.

MEG-based detection and localization of perilesional dysfunction in chronic stroke

Post-stroke impairment is associated not only with structural lesions, but also with dysfunction in surviving perilesional tissue. Previous studies using equivalent current dipole source localization of MEG/EEG signals have demonstrated a preponderance of slow-wave activity localized to perilesional areas. Recent studies have also demonstrated the utility of nonlinear analyses such as multiscale entropy (MSE) for quantifying neuronal dysfunction in a wide range of pathologies. The current study utilized beamformer-based reconstruction of signals in source space to compare spectral and nonlinear measures of electrical activity in perilesional and healthy cortices. Data were collected from chronic stroke patients and healthy controls, both young and elderly. We assessed relative power in the delta (1–4 Hz), theta (4–7 Hz), alpha (8–12 Hz) and beta (15–30 Hz) frequency bands, and also measured the nonlinear complexity of electrical activity using MSE. Perilesional tissue exhibited a general slowing of the power spectrum (increased delta/theta, decreased beta) as well as a reduction in MSE. All measures tested were similarly sensitive to changes in the posterior perilesional regions, but anterior perilesional dysfunction was detected better by MSE and beta power. The findings also suggest that MSE is specifically sensitive to electrophysiological dysfunction in perilesional tissue, while spectral measures were additionally affected by an increase in rolandic beta power with advanced age. Furthermore, perilesional electrophysiological abnormalities in the left hemisphere were correlated with the degree of language task-induced activation in the right hemisphere. Finally, we demonstrate that single subject spectral and nonlinear analyses can identify dysfunctional perilesional regions within individual patients that may be ideal targets for interventions with noninvasive brain stimulation.

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We assessed the spontaneous MEG activity of perilesional tissue in stroke.

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We observed perilesional spectral slowing and reduced signal complexity.

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We demonstrate a method to identify dysfunctional tissue within a single subject.

Visual imagery and functional connectivity in blindness: a single-case study

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input.

The effect of multidisciplinary rehabilitation on brain structure and cognition in Huntington's disease: an exploratory study

BACKGROUND

There is a wealth of evidence detailing gray matter degeneration and loss of cognitive function over time in individuals with Huntington's disease (HD). Efforts to attenuate disease-related brain and cognitive changes have been unsuccessful to date. Multidisciplinary rehabilitation, comprising motor and cognitive intervention, has been shown to positively impact on functional capacity, depression, quality of life and some aspects of cognition in individuals with HD. This exploratory study aimed to evaluate, for the first time, whether multidisciplinary rehabilitation can slow further deterioration of disease-related brain changes and related cognitive deficits in individuals with manifest HD.

METHODS

Fifteen participants who manifest HD undertook a multidisciplinary rehabilitation intervention spanning 9 months. The intervention consisted of once-weekly supervised clinical exercise, thrice-weekly self-directed home based exercise and fortnightly occupational therapy. Participants were assessed using MR imaging and validated cognitive measures at baseline and after 9 months.

RESULTS

Participants displayed significantly increased gray matter volume in the right caudate and bilaterally in the dorsolateral prefrontal cortex after 9 months of multidisciplinary rehabilitation. Volumetric increases in gray matter were accompanied by significant improvements in verbal learning and memory (Hopkins Verbal Learning-Test). A significant association was found between gray matter volume increases in the dorsolateral prefrontal cortex and performance on verbal learning and memory.

CONCLUSIONS

This study provides preliminary evidence that multidisciplinary rehabilitation positively impacts on gray matter changes and cognitive functions relating to verbal learning and memory in individuals with manifest HD. Larger controlled trials are required to confirm these preliminary findings.

The importance of premotor cortex for supporting speech production after left capsular-putaminal damage

The left putamen is known to be important for speech production, but some patients with left putamen damage can produce speech remarkably well. We investigated the neural mechanisms that support this recovery by using a combination of techniques to identify the neural regions and pathways that compensate for loss of the left putamen during speech production. First, we used fMRI to identify the brain regions that were activated during reading aloud and picture naming in a patient with left putamen damage. This revealed that the patient had abnormally high activity in the left premotor cortex. Second, we used dynamic causal modeling of the patient's fMRI data to understand how this premotor activity influenced other speech production regions and whether the same neural pathway was used by our 24 neurologically normal control subjects. Third, we validated the compensatory relationship between putamen and premotor cortex by showing, in the control subjects, that lower connectivity through the putamen increased connectivity through premotor cortex. Finally, in a lesion-deficit analysis, we demonstrate the explanatory power of our fMRI results in new patients who had damage to the left putamen, left premotor cortex, or both. Those with damage to both had worse reading and naming scores. The results of our four-pronged approach therefore have clinical implications for predicting which patients are more or less likely to recover their speech after left putaminal damage.

Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects

Structural imaging based on MRI is an integral component of the clinical assessment of patients with potential dementia. We here propose an individualized Gaussian process-based inference scheme for clinical decision support in healthy and pathological aging elderly subjects using MRI. The approach aims at quantitative and transparent support for clinicians who aim to detect structural abnormalities in patients at risk of Alzheimer's disease or other types of dementia. Firstly, we introduce a generative model incorporating our knowledge about normative decline of local and global gray matter volume across the brain in elderly. By supposing smooth structural trajectories the models account for the general course of age-related structural decline as well as late-life accelerated loss. Considering healthy subjects' demography and global brain parameters as informative about normal brain aging variability affords individualized predictions in single cases. Using Gaussian process models as a normative reference, we predict new subjects' brain scans and quantify the local gray matter abnormalities in terms of Normative Probability Maps (NPM) and global z-scores. By integrating the observed expectation error and the predictive uncertainty, the local maps and global scores exploit the advantages of Bayesian inference for clinical decisions and provide a valuable extension of diagnostic information about pathological aging. We validate the approach in simulated data and real MRI data. We train the GP framework using 1238 healthy subjects with ages 18–94 years, and predict in 415 independent test subjects diagnosed as healthy controls, Mild Cognitive Impairment and Alzheimer's disease.

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We propose an approach to support individualized clinical decisions in elderlies.

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Gaussian process models are used to build a normative generative model of aging.

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It affords probabilistic predictions of local gray matter volume in subjects.

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We validate the model using simulated and large real MRI data samples.

The effects of immunologic brainstem encephalopathy on cognitive function following awakening from a progressive autoimmune coma

We describe a unique patient who experienced a progressive autoimmune coma from age 14 to 17. The patient awoke after treatment with immunosuppressant medication. Although alertness, verbalization, and mobilization markedly improved, the patient reported persistent cognitive difficulties. Neuropsychological assessment from age 21 showed impairments in selective attention, distractibility, and memory. Conversely, higher-order executive functions were preserved. Electrophysiological analysis also identified abnormal neural signatures of selective attention. Eighteen months after the neuropsychological assessment, voxel-based morphometry revealed reduced white matter in the medulla compared to controls. The findings are discussed in terms of the impact of brainstem encephalopathy on cognitive mechanisms.

Fully automatic detection of deep white matter T1 hypointense lesions in multiple sclerosis

A novel method is presented for fully automatic detection of candidate white matter (WM) T1 hypointense lesions in three-dimensional high-resolution T1-weighted magnetic resonance (MR) images. By definition, T1 hypointense lesions have similar intensity as gray matter (GM) and thus appear darker than surrounding normal WM in T1-weighted images. The novel method uses a standard classification algorithm to partition T1-weighted images into GM, WM and cerebrospinal fluid (CSF). As a consequence, T1 hypointense lesions are assigned an increased GM probability by the standard classification algorithm. The GM component image of a patient is then tested voxel-by-voxel against GM component images of a normative database of healthy individuals. Clusters (≥0.1 ml) of significantly increased GM density within a predefined mask of deep WM are defined as lesions. The performance of the algorithm was assessed on voxel level by a simulation study. A maximum dice similarity coefficient of 60% was found for a typical T1 lesion pattern with contrasts ranging from WM to cortical GM, indicating substantial agreement between ground truth and automatic detection. Retrospective application to 10 patients with multiple sclerosis demonstrated that 93 out of 96 T1 hypointense lesions were detected. On average 3.6 false positive T1 hypointense lesions per patient were found. The novel method is promising to support the detection of hypointense lesions in T1-weighted images which warrants further evaluation in larger patient samples.

Towards automated detection of depression from brain structural magnetic resonance images

INTRODUCTION

Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).

METHODS

Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.

RESULTS

The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.

CONCLUSION

Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

When the single matters more than the group: very high false positive rates in single case Voxel Based Morphometry

Voxel Based Morphometry (VBM) studies typically involve a comparison between groups of individuals; this approach however does not allow inferences to be made at the level of the individual. In recent years, an increasing number of research groups have attempted to overcome this issue by performing single case studies, which involve the comparison between a single subject and a control group. However, the interpretation of the results is problematic; for instance, any significant difference might be driven by individual variability in neuroanatomy rather than the neuropathology of the disease under investigation, or might represent a false positive due to the data being sampled from non-normally distributed populations. The aim of the present investigation was to empirically estimate the likelihood of detecting significant differences in gray matter volume in individuals free from neurological or psychiatric diagnosis. We compared a total of 200 single subjects against a group of 16 controls matched for age and gender, using two independent datasets from the Neuroimaging Informatics Tools and Resources Clearinghouse. We report that the chance of detecting a significant difference in a disease-free individual is much higher than previously expected; for instance, using a standard voxel-wise threshold of p<0.05 (corrected) and an extent threshold of 10 voxels, the likelihood of a single subject showing at least one significant difference is as high as 93.5% for increases and 71% for decreases. We also report that the chance of detecting significant differences was greatest in frontal and temporal cortices and lowest in subcortical regions. The chance of detecting significant differences was inversely related to the degree of smoothing applied to the data, and was higher for unmodulated than modulated data. These results were replicated in the two independent datasets. By providing an empirical estimation of the number of significant increases and decreases to be expected in each cortical and subcortical region in disease-free individuals, the present investigation could inform the interpretation of future single case VBM studies.

Movement disorders: role of imaging in diagnosis

Magnetic resonance imaging (MRI and single-photon emission computed tomography (SPECT) have a considerable role in the diagnosis of the single patient with movement disorders. Conventional MRI demonstrates symptomatic causes of parkinsonism but does not show any specific finding in Parkinson's disease (PD). However, SPECT using tracers of the dopamine transporter (DAT) demonstrates an asymmetric decrease of the uptake in the putamen and caudate from the earliest clinical stages. In other degenerative forms of parkinsonism, including progressive supranuclear palsy (PSP), multisystem atrophy (MSA), and corticobasal degeneration (CBD), MRI reveals characteristic patterns of regional atrophy combined with signal changes or microstructural changes in the basal ganglia, pons, middle and superior cerebellar peduncles, and cerebral subcortical white matter. SPECT demonstrates a decreased uptake of tracers of the dopamine D2 receptors in the striata of patients with PSP and MSA, which is not observed in early PD. MRI also significantly contributes to the diagnosis of some inherited hyperkinetic conditions including neurodegeneration with brain iron accumulation and fragile-X tremor/ataxia syndrome by revealing characteristic symmetric signal changes in the basal ganglia and middle cerebellar peduncles, respectively. A combination of the clinical features with MRI and SPECT is recommended for optimization of the diagnostic algorithm in movement disorders.

Altered ventral striatal activation during reward and punishment processing in premanifest Huntington's disease: a functional magnetic resonance study

Recent research using various neuroimaging methods revealed the crucial role of the striatum concerning the neuropathology of Huntington's disease. Degenerative changes located in the basal ganglia are already observable in premanifest stages of Huntington's disease (pre-HD), i.e., before the onset of manifest motor symptoms. Although the impact of the striatum on reward and punishment processing is well-established in healthy subjects, these processes have not been investigated in manifest and premanifest HD subjects using functional magnetic resonance imaging (fMRI) so far. We used the Monetary Incentive Delay Task to investigate valence discrimination in terms of rewarding and punishing cues in 30 pre-HD and 15 healthy subjects. According to the probability of disease onset within the next 5 years, pre-HD subjects were categorized as either near to motor symptom onset (pre-HD(near); 9.9 [±2.91] years to onset) or far from manifest disease onset (pre-HD(far); 23.49 [±5.99] years to onset). Compared to pre-HD(far) and healthy subjects, pre-HD(near) subjects showed a disturbed neuronal differentiation between reward and control anticipation located in the left ventral striatum. In contrast to pre-HD(far) and healthy subjects, no significant ventral striatal discrimination between punishing and control cues was detected in pre-HD(near) subjects. In the present study, we demonstrated for the first time significant differences in valence discrimination in pre-HD(near) subjects compared to pre-HD(far) subjects and healthy controls. Altered reward and punishment processing could therefore reflect a motivational deficit that may contribute to the pathogenesis of Huntington's disease.

Alexithymia in healthy young men: a voxel-based morphometric study

BACKGROUND

Alexithymia is a personality construct predominately associated with an impaired ability to identify and communicate emotions. Functional imaging studies showed that an altered function of the anterior cingulate cortex (ACC) may be relevant in alexithymia. In this study we investigated if the altered functional anatomy is related to structural changes (A) in the whole brain and (B) specifically in the ACC by applying a region-of-interest analysis.

METHODS

33 high- and 31 low-alexithymic right-handed young male subjects (selected by the 20-item Toronto Alexithymia Scale, TAS-20) were investigated using voxel-based morphometry (VBM) on high-resolution 3D magnetic resonance images. The group differences were analyzed by applying voxel-wise comparisons using two-sample t-tests. Moreover regression analyses with regard to the individual TAS-20 sum scores were calculated.

RESULTS

Neither the subtraction analyses nor the correlation analyses revealed significant differences between high- and low-alexithymic subjects. Thus, according to our results, the null hypothesis of no structural difference between the groups could not be rejected.

LIMITATIONS

The findings cannot be generalized to female subjects.

CONCLUSIONS

Our results did not reveal morphological differences between high- and low-alexithymic subjects. The functional differences known from imaging studies could not be attributed to underlying anatomical changes. Thus, the personality trait of alexithymia might be associated with fewer morphological abnormalities than previously assumed.

Sinais em neurorradiologia: parte 2

O uso de sinais na interpretação de imagens na neurorradiologia é extremamente útil. Muitos sinais são bastante específicos e em alguns casos, patognomônicos. Nesta segunda parte os autores descreverão 15 sinais neurorradiológicos adicionais. Serão novamente abordadas as principais características de imagem de cada um e sua importância na prática clínica.

Clinical functional MRI of the language domain in children with epilepsy

Functional MRI (fMRI) for the assessment of language functions is increasingly used in the diagnostic workup of patients with epilepsy. Termed "clinical fMRI," such an approach is also feasible in children who may display specific patterns of language reorganization. This study was aimed at assessing language reorganization in pediatric epilepsy patients, using fMRI. We studied 26 pediatric epilepsy patients (median age, 13.05 years; range, 5.6-18.7 years) and 23 healthy control children (median age, 9.37 years; range, 6.2-15.4 years), using two child-friendly fMRI tasks and adapted data-processing streams. Overall, 81 functional series could be analyzed. Reorganization seemed to occur primarily in homotopic regions in the contralateral hemisphere, but lateralization in the frontal as well as in the temporal lobes was significantly different between patients and controls. The likelihood to find atypical language organization was significantly higher in patients. Additionally, we found significantly stronger activation in the healthy controls in a primarily passive task, suggesting a systematic confounding influence of antiepileptic medication. The presence of a focal cortical dysplasia was significantly associated with atypical language lateralization. We conclude that important confounds need to be considered and that the pattern of language reorganization may be distinct from the patterns seen in later-onset epilepsy.

How neuroscience and behavioral genetics improve psychiatric assessment: report on a violent murder case

Despite the advances in the understanding of neural and genetic foundations of violence, the investigation of the biological bases of a mental disorder is rarely included in psychiatric evaluation of mental insanity. Here we report on a case in which cognitive neuroscience and behavioral genetics methods were applied to a psychiatric forensic evaluation conducted on a young woman, J.F., tried for a violent and impulsive murder. The defendant had a history of multidrug and alcohol abuse and non-forensic clinical evaluation concluded for a diagnosis of borderline personality disorder. We analyzed the defendant's brain structure in order to underlie possible brain structural abnormalities associated with pathological impulsivity. Voxel-based morphometry indexed a reduced gray matter volume in the left prefrontal cortex, in a region specifically associated with response inhibition. Furthermore, J.F.'s DNA was genotyped in order to identify genetic polymorphisms associated with various forms of violence and impulsive behavior. Five polymorphisms that are known to be associated with impulsivity, violence, and other severe psychiatric illnesses were identified in J.F.'s DNA. Taken together, these data provided evidence for the biological correlates of a mental disorder characterized by high impulsivity and aggressive tendencies. Our claim is that the use of neuroscience and behavioral genetics do not change the rationale underlying the determination of criminal liability, which must be based on a causal link between the mental disorder and the crime. Rather, their use is crucial in providing objective data on the biological bases of a defendant's mental disorder.

Early Detection of Huntington Disease

Huntington disease (HD) is a devastating illness, although its autosomal dominant genetic transmission allows a unique opportunity to study apparently healthy individuals before manifest disease. Attempts to study early disease are not unique in neurology (e.g., Mild Cognitive Impairment, Vascular Cognitive Impairment), but studying otherwise-healthy appearing individuals who will go on with nearly 99% certainty to manifest the symptoms of brain disease does provide distinct but valuable information about the true natural history of the disease. The field has witnessed an explosion of research examining possible early indicators of HD during what is now referred to as the "prodrome" of HD. A NIH study in its ninth year (PREDICT-HD) has offered a glimpse into the transition from an apparently healthy state to an obviously diseased state, and can serve as a model for many other genetic diseases, both neurological and non-neurological.