Do preprocessing algorithms and statistical models influence voxel-based morphometry (VBM) results in amyotrophic lateral sclerosis patients? A systematic comparison of popular VBM analytical methods

Common and distinct fronto-striatal volumetric changes in heroin and cocaine use disorders

Different drugs of abuse impact the morphology of fronto-striatal dopaminergic targets in both common and unique ways. While dorsal striatal volume tracks with addiction severity across drug classes, opiates impact ventromedial prefrontal cortex (vmPFC) and nucleus accumbens (NAcc) neuroplasticity in preclinical models, and psychostimulants alter inhibitory control, rooted in cortical regions such as the inferior frontal gyrus (IFG). We hypothesized parallel grey matter volume changes associated with human heroin or cocaine use disorder: lower grey matter volume of vmPFC/NAcc in heroin use disorder and IFG in cocaine use disorder, and putamen grey matter volume to be associated with addiction severity measures (including craving) across both. In this cross-sectional study, we quantified grey matter volume (P < 0.05-corrected) in age/sex/IQ-matched individuals with heroin use disorder (n = 32, seven females), cocaine use disorder (n = 32, six females) and healthy controls (n = 32, six females) and compared fronto-striatal volume between groups using voxel-wise general linear models and non-parametric permutation-based tests. Overall, individuals with heroin use disorder had smaller vmPFC and NAcc/putamen volumes than healthy controls. Bilateral lower IFG grey matter volume patterns were specifically evident in cocaine versus heroin use disorders. Correlations between addiction severity measures and putamen grey matter volume did not reach nominal significance level in this sample. These results indicate alterations in dopamine-innervated regions (in the vmPFC and NAcc) in heroin addiction. For the first time we demonstrate lower IFG grey matter volume specifically in cocaine compared with heroin use disorder, suggesting a signature of reduced inhibitory control, which remains to be tested directly using select behavioural measures. Overall, results suggest substance-specific volumetric changes in human psychostimulant or opiate addiction, with implications for fine-tuning biomarker and treatment identification by primary drug of abuse.

An analysis of the influence of transfer learning when measuring the tortuosity of blood vessels

BACKGROUND AND OBJECTIVE

Convolutional Neural Networks (CNNs) can provide excellent results regarding the segmentation of blood vessels. One important aspect of CNNs is that they can be trained on large amounts of data and then be made available, for instance, in image processing software. The pre-trained CNNs can then be easily applied in downstream blood vessel characterization tasks, such as the calculation of the length, tortuosity, or caliber of the blood vessels. Yet, it is still unclear if pre-trained CNNs can provide robust, unbiased, results in downstream tasks involving the morphological analysis of blood vessels. Here, we focus on measuring the tortuosity of blood vessels and investigate to which extent CNNs may provide biased tortuosity values even after fine-tuning the network to a new dataset under study.

METHODS

We develop a procedure for quantifying the influence of CNN pre-training in downstream analyses involving the measurement of morphological properties of blood vessels. Using the methodology, we compare the performance of CNNs that were trained on images containing blood vessels having high tortuosity with CNNs that were trained on blood vessels with low tortuosity and fine-tuned on blood vessels with high tortuosity. The opposite situation is also investigated.

RESULTS

We show that the tortuosity values obtained by a CNN trained from scratch on a dataset may not agree with those obtained by a fine-tuned network that was pre-trained on a dataset having different tortuosity statistics. In addition, we show that improving the segmentation accuracy does not necessarily lead to better tortuosity estimation. To mitigate the aforementioned issues, we propose the application of data augmentation techniques even in situations where they do not improve segmentation performance. For instance, we found that the application of elastic transformations was enough to prevent an underestimation of 8% of blood vessel tortuosity when applying CNNs to different datasets.

CONCLUSIONS

The results highlight the importance of developing new methodologies for training CNNs with the specific goal of reducing the error of morphological measurements, as opposed to the traditional approach of using segmentation accuracy as a proxy metric for performance evaluation.

Cerebral mechanism of Tuina analgesia in management of knee osteoarthritis using multimodal MRI: study protocol for a randomised controlled trial

Background

The chronic pain of patients with knee osteoarthritis (KOA) seriously affects their quality of life and leads to heavy social and economic burden. As a nondrug therapy in Traditional Chinese Medicine (TCM), Tuina is generally recognised as safe and effective for reducing the chronic pain of KOA. However, the underlying central mechanisms of Tuina for improving the pain of KOA are not fully understood.

Methods/design

This study will be a randomised controlled trial with a parallel-group design. A total of 60 eligible participants will be assigned to the Tuina group or healthcare education group (Education group) at 1:1 ratio using stratified randomisation with gender and age as factors. The interventions of both groups will last for 30 min per session and be conducted twice each week for 12 weeks. This study will primarily focus on pain evaluation assessed by detecting the changes in brain grey matter (GM) structure, white matter (WM) structure, and the cerebral functional connectivity (FC) elicited by Tuina treatment, e.g., thalamus, hippocampus, anterior cingulate gyrus, S1, insula, and periaqueductal grey subregions (PAG). The two groups of patients will be evaluated by clinical assessments and multimodal magnetic resonance imaging (MRI) to observe the alterations in the GM, WM, and FC of participants at the baseline and the end of 6 and 12 weeks’ treatment and still be evaluated by clinical assessments but not MRI for 48 weeks of follow-up. The visual analogue scale of current pain is the primary outcome. The Short-Form McGill Pain Questionnaire, Western Ontario and McMaster Universities Osteoarthritis Index, 36-Item Short Form Health Survey, Hamilton Depression Scale, and Hamilton Anxiety Scale will be used to evaluate the pain intensity, pain feeling, pain emotion, clinical symptoms, and quality of life, respectively. MRI assessments, clinical data evaluators, data managers, and statisticians will be blinded to the group allocation in the outcome evaluation procedure and data analysis to reduce the risk of bias. The repeated measures analysis of variance (2 groups × 6 time points ANOVA) will be used to analyse numerical variables of the clinical and neuroimaging data obtained in the study. P<0.05 will be the statistical significance level.

Discussion

The results of this randomised controlled trial with clinical assessments and multimodal MRI will help reveal the influence of Tuina treatment on the potential morphological changes in cortical and subcortical brain structures, the white matter integrity, and the functional activities and connectivity of brain regions of patients with KOA, which may provide scientific evidence for the clinical application of Tuina in the management of KOA.

Trial registration

Chinese Clinical Trial Registry ChiCTR2000037966. Registered on Sep. 8, 2020.

Dissemination

The results will be published in peer-reviewed journals and disseminated through the study’s website, and conferences.

Theory of Mind and Its Elusive Structural Substrate

Is brain structure related to function? Can one predict the other? These are questions that are still waiting to be answered definitively. In this paper we seek to investigate these questions, in particular, we are interested in the relation between brain structure and theory of mind (ToM). ToM is defined as the ability to attribute mental states to others. Previous studies have observed correlations between performance on ToM tasks, and gray-matter size/volume in dorsomedial prefrontal cortex (dmPFC), temporoparietal junction (TPJ) and precuneus (PCu). Despite these findings, there are concerns about false positive results and replicability issues. In this study we used two different tasks to evaluate ToM, Reading the Mind in the Eyes Test (RMET), and the Short Story Task (SST). Performance in these tasks was correlated to brain anatomy measures including voxel-based morphometry (VBM) and cortical thickness (CT) analysis, from ninety-one neurotypical participants. High-resolution structural brain images were acquired, and whole-brain and region of interest (ROI) analyses were implemented. The analyses did not show statistically significant associations between ToM performance and brain structural measures after correction. Significant associations between performance on ToM tests and a widespread array of regions loosely associated with ToM were observed only for whole brain uncorrected analysis (p < 0.001). These results do not replicate a previous study with neurotypical participants. We tested two different ToM tests, two different softwares for VBM and CT, and we used two samples, one with 91 and a sub-sample with 69 participants. Neither of these conditions made a difference in the results obtained. Consequently, these results suggest that if the population is neurotypical and homogenous, it is unlikely that a reliable association between brain anatomy measures and ToM performance, as measured with these tasks, may be found.

Grey matter alterations in restless legs syndrome: A coordinate-based meta-analysis

Brain structural abnormalities in idiopathic restless legs syndrome have long been debated. Voxel-based morphometry is an objective structural magnetic resonance imaging technique to investigate regional grey matter volume or density differences between groups. In the last decade, voxel-based morphometry studies have exhibited inconsistent and conflicting findings regarding the presence and localization of brain grey matter alterations in restless legs syndrome. We therefore conducted a coordinate-based meta-analysis to quantitatively examine whether there were consistent grey matter findings in restless legs syndrome using the latest algorithms, seed-based d mapping with permutation of subject images. We included 12 voxel-based morphometry studies (13 datasets, 375 patients and 385 healthy controls). Our coordinate-based meta-analysis did not identify evidence of consistent grey matter alterations in restless legs syndrome. Grey matter alterations via voxel-based morphometry analysis are not therefore recommended to be used as a reliable surrogate neuroimaging marker for restless legs syndrome. This lack of consistency may be attributed to differences in sample size, genetics, gender distribution and age at onset, clinical heterogeneity (clinical course, anatomical distribution of symptoms, disease severity, disease duration, abnormal sensory profiles and comorbidity), and variations in imaging acquisition, data processing and statistical strategies. Longitudinal studies with multimodal neuroimaging techniques are needed to determine whether structural changes are dynamic and secondary to functional abnormalities.

Comparing VBM and ROI analyses for detection of gray matter abnormalities in patients with bipolar disorder using MRI

Background

With the increasing efforts to a better understanding of psychiatric diseases, detection of brain morphological alterations is necessary. This study compared two methods—voxel-based morphometry (VBM) and region of interest (ROI) analyses—to identify significant gray matter changes of patients with bipolar disorder type I (BP I).

Results

The VBM findings suggested gray matter reductions in the left precentral gyrus and right precuneus of the patients compared to healthy subjects (α = 0.0005, uncorrected). However, no regions reached the level of significance in ROI analysis using the three atlases, i.e., hammers, lpba40, and neuromorphometrics atlases (α = 0.0005).

Conclusion

It can be concluded that VBM analysis seems to be more sensitive to partial changes in this study. If ROI analysis is employed in studies to detect structural brain alterations between groups, it is highly recommended to use VBM analysis besides.

A Meta-Analysis of Gray Matter Differences Between Bilinguals and Monolinguals

Bilingualism is of great interest to the neuroscience of language, and understanding the anatomical changes associated with second language learning help inform theories of bilingual advantage across the lifespan. While the literature on structural differences between bilinguals and monolinguals is robust, relatively few studies of gray matter (GM) have directly compared bilinguals with monolinguals in a whole-brain analysis. Overall, this and heterogeneity of study samples and methodology have led to a lack of clear anatomical support for major theories. Here, we engage in an activation likelihood estimate (ALE) meta-analysis of voxel-based morphometry (VBM) studies of GM for cases that directly compare bilingual and monolingual subjects in a whole-brain analysis. The analysis (sixteen foci, from ten contrasts across eight studies) resulted in one cluster located primarily within the anterior lobe of the right cerebellum. However, when the one pediatric study was removed, the analysis revealed no consistent results across the studies included in this meta-analysis. This suggests that for VBM studies of bilingual and monolingual adults there is considerable heterogeneity of results that complicate the understanding of the bilingual brain. Future studies will need to include larger, more well-defined samples and interrogate more fine-grained anatomical features such as cortical thickness and surface area in order to more fully examine the anatomical changes associated with bilingualism across the lifespan.

Localizing Age-Related Changes in Brain Structure Using Voxel-Based Morphometry

Aim. We report the dynamic anatomical sequence of human cortical gray matter development from late childhood to young adults using VBM and ROI-based methods. Method. The structural MRI of 91 normal individuals ranging in age from 6 to 26 years was obtained and the GMV for each region was measured. Results. Our results showed that the earliest loss of GMV occurred in left olfactory, right precuneus, caudate, left putamen, pallidum, and left middle temporal gyrus. In addition, the trajectory of maturational and aging showed a linear decline in GMV on both cortical lobes and subcortical regions. The most loss of gray matter was observed in the parietal lobe and basal ganglia, whereas the less loss occurred in the temporal lobe and hippocampus, especially in the left middle temporal pole, which showed no decline until 26 years old. Moreover, the volumes of GM, WM, and CSF were also assessed for linear age effects, showing a significant linear decline in GM with age and a significant linear increase in both WM and CSF with age. Interpretation. Overall, our findings lend support to previous findings of the normal brain development of regional cortex, and they may help in understanding of neurodevelopmental disorders.

Structural explanation of poor prognosis of amyotrophic lateral sclerosis in the non-demented state

BACKGROUND AND PURPOSE

Amyotrophic lateral sclerosis (ALS), a motor neuron disease, is associated with various cortical symptoms including mild cognitive decline with behavior changes, suggesting the involvement of extra-motor areas in ALS. Our aim was to investigate the specific patterns of brain atrophy in sporadic, impaired ALS patients without commonly known genetic mutations using voxel-based morphometry.

MATERIALS AND METHODS

Forty-seven patients with sporadic ALS and 28 age-matched healthy controls were recruited. ALS participants were divided into three groups according to comprehensive neuropsychological testing: pure (ALS-pure), cognitive impairment (ALSci) and behavioral impairment (ALSbi). Quantitative comparison of brain atrophy patterns was performed amongst these three groups using voxel-based analysis. All analyses were adjusted for total intracranial volume, age, sex, disease duration and functional disability score.

RESULTS

The ALSci group exhibited decreased volume in the left cerebellum, fusiform gyrus, optic radiations and corticospinal tracts compared to healthy controls. ALSci patient imaging showed decreased brain volume in the bilateral cerebellum, right putamen gray matter and bilateral superior longitudinal fasciculi white matter compared to pure ALS patients (P < 0.001 uncorrected, corrected for the entire volume). Compared to healthy controls, ALS-pure and ALSbi groups did not show any significant volume changes in gray and white matter.

CONCLUSIONS

These findings also support the hypothesis that ALS pathogenesis has a dual focality of onset (cortex and anterior horn) with contiguous spread outwards. Additionally, neuropsychological features may be an important predictor of progression and survival rates in ALS.

Inter-Method Discrepancies in Brain Volume Estimation May Drive Inconsistent Findings in Autism

Previous studies applying automatic preprocessing methods on Structural Magnetic Resonance Imaging (sMRI) report inconsistent neuroanatomical abnormalities in Autism Spectrum Disorder (ASD). In this study we investigate inter-method differences as a possible cause behind these inconsistent findings. In particular, we focus on the estimation of the following brain volumes: gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and total intra cranial volume (TIV). T1-weighted sMRIs of 417 ASD subjects and 459 typically developing controls (TDC) from the ABIDE dataset were estimated using three popular preprocessing methods: SPM, FSL, and FreeSurfer (FS). Brain volumes estimated by the three methods were correlated but had significant inter-method differences; except TIVSPM vs. TIVFS, all inter-method differences were significant. ASD vs. TDC group differences in all brain volume estimates were dependent on the method used. SPM showed that TIV, GM, and CSF volumes of ASD were larger than TDC with statistical significance, whereas FS and FSL did not show significant differences in any of the volumes; in some cases, the direction of the differences were opposite to SPM. When methods were compared with each other, they showed differential biases for autism, and several biases were larger than ASD vs. TDC differences of the respective methods. After manual inspection, we found inter-method segmentation mismatches in the cerebellum, sub-cortical structures, and inter-sulcal CSF. In addition, to validate automated TIV estimates we performed manual segmentation on a subset of subjects. Results indicate that SPM estimates are closest to manual segmentation, followed by FS while FSL estimates were significantly lower. In summary, we show that ASD vs. TDC brain volume differences are method dependent and that these inter-method discrepancies can contribute to inconsistent neuroimaging findings in general. We suggest cross-validation across methods and emphasize the need to develop better methods to increase the robustness of neuroimaging findings.

Widespread Focal Cortical Alterations in Autism Spectrum Disorder with Intellectual Disability Detected by Threshold-Free Cluster Enhancement

BACKGROUND AND PURPOSE

In the past decades, a large body of work aimed at investigating brain structural anomalies accrued in autism spectrum disorder. Autism spectrum disorder is associated with intellectual disability in up to 50% of cases. However, only a few neuroimaging studies were conducted in autism spectrum disorder with intellectual disability, and none of them benefited from a nonsyndromic intellectual disability control group.

MATERIALS AND METHODS

We performed a voxelwise investigation of the structural alterations in 25 children with autism spectrum disorder with intellectual disability by comparing them with 25 typically developing children and 25 nonsyndromic children with an intellectual disability. Besides a classic voxel-based morphometry statistical approach, the threshold-free cluster enhancement statistical approach was adopted.

RESULTS

Classic voxel-based morphometry results did not survive family-wise error correction. The threshold-free cluster enhancement-based analysis corrected for family-wise error highlighted the following: 1) widespread focal cortical anomalies and corpus callosum alteration detected in autism spectrum disorder with intellectual disability; 2) basal ganglia and basal forebrain alteration detected both in autism spectrum disorder with intellectual disability and in nonsyndromic intellectual disability; and 3) differences in the frontocingulate-parietal cortex between autism spectrum disorder with intellectual disability and nonsyndromic intellectual disability.

CONCLUSIONS

The present study suggests that the frontocingulate-parietal cortex may be the eligible key region for further investigations aiming at detecting imaging biomarkers in autism spectrum disorder with intellectual disability. The detection of structural alterations in neurodevelopmental disorders may be dramatically improved by using a threshold-free cluster enhancement statistical approach.

Brain Anatomy in Latino Farmworkers Exposed to Pesticides and Nicotine

OBJECTIVE

Migrant tobacco farmworkers experience regular occupational exposure to pesticides and nicotine. The present study was designed to determine whether there are differences in brain anatomy between Latino farmworkers and non-farmworkers.

METHODS

Magnetic resonance brain images were compared between farmworkers and non-farmworkers. In addition, blood cholinesterase activity and urinary cotinine levels were also used to identify associations with pesticide and nicotine exposure.

RESULTS

Farmworkers had greater gray matter signal in putamen and cerebellum, and lower gray matter signal in frontal and temporal lobes. Urinary cotinine was associated with the observed differences in brain anatomy, but blood cholinesterase activity was not.

CONCLUSIONS

Nicotine exposure was associated with neuroanatomical differences between Latino farmworkers and non-farmworkers. Future studies are needed to differentiate iron deposition from brain atrophy and to further assess the potential role of nicotine and pesticide exposure.

Structural and diffusion imaging versus clinical assessment to monitor amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a progressive neurodegenerative disease that affects upper and lower motor neurons. Observational and intervention studies can be tracked using clinical measures such as the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) but for a complete understanding of disease progression, objective in vivo biomarkers of both central and peripheral motor pathway pathology are highly desirable. The aim of this study was to determine the utility of structural and diffusion imaging as central nervous system biomarkers compared to the standard clinical measure, ALSFRS-R, to track longitudinal evolution using three time-point measurements. N = 34 patients with ALS were scanned and clinically assessed three times at a mean of three month time intervals. The MRI biomarkers were structural T1-weighted volumes for cortical thickness measurement as well as deep grey matter volumetry, voxel-based morphometry and diffusion tensor imaging (DTI). Cortical thickness focused specifically on the precentral gyrus while quantitative DTI biomarkers focused on the corticospinal tracts. The evolution of imaging biomarkers and ALSFRS-R scores over time were analysed using a mixed effects model that accounted for the scanning interval as a fixed effect variable, and, the initial measurements and time from onset as random variables. The mixed effects model showed a significant decrease in the ALSFRS-R score, (p < 0.0001, and an annual rate of change (AROC) of − 7.3 points). Similarly, fractional anisotropy of the corticospinal tract showed a significant decrease (p = 0.009, AROC = − 0.0066) that, in turn, was driven by a significant increase in radial diffusivity combined with a trend to decrease in axial diffusivity. No significant change in cortical thickness of the precentral gyrus was found (p > 0.5). In addition, deep grey matter volumetry and voxel-based morphometry also identified no significant changes. Furthermore, the availability of three time points was able to indicate that there was a linear progression in both clinical and fractional anisotropy measures adding to the validity of these results. The results indicate that DTI is clearly a superior imaging marker compared to atrophy for tracking the evolution of the disease and can act as a central nervous biomarker in longitudinal studies. It remains, however, less sensitive than the ALSFRS-R score for monitoring decline over time.

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Three time points were used for the first time to assess imaging biomarkers in ALS.

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Fractional anisotropy of the corticospinal tract showed linear decline.

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No atrophy measure was useful to track change.

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The ALSFRS-R clinical scale remains more sensitive than imaging biomarkers.

Motor and extra-motor gray matter atrophy in amyotrophic lateral sclerosis: quantitative meta-analyses of voxel-based morphometry studies

Considerable evidence from previous voxel-based morphometry studies indicates widespread but heterogeneous gray matter (GM) deficits in amyotrophic lateral sclerosis (ALS). Here, we aimed to investigate the concurrence across voxel-based morphometry studies to help clarify the spatial pattern of GM abnormalities that underlie this condition. Comprehensive meta-analyses to assess regional GM anomalies in ALS were conducted with the Anisotropic Effect Size version of Signed Differential Mapping software package. Twenty studies, which reported 22 comparisons and were composed of 454 ALS patients and 426 healthy controls, were included in the meta-analyses. Regional GM atrophy in ALS was consistently found in the frontal, temporal, and somatosensory areas. Meta-regression demonstrated that the disease duration, disease severity, and age were significantly related to GM deficits in ALS patients. The present meta-analysis provides convergent evidence that ALS is a multisystem degenerative disorder that is accompanied by a unique and widespread pattern of robust cortical GM atrophy. Future studies should investigate whether this atrophy pattern is a diagnostic and prognostic marker.

What does imaging reveal about the pathology of amyotrophic lateral sclerosis?

Amyotrophic lateral sclerosis (ALS) is now recognised to be a heterogeneous neurodegenerative syndrome of the motor system and its frontotemporal cortical connections. The development and application of structural and functional imaging over the last three decades, in particular magnetic resonance imaging (MRI), has allowed traditional post mortem histopathological and emerging molecular findings in ALS to be placed in a clinical context. Cerebral grey and white matter structural MRI changes are increasingly being understood in terms of brain connectivity, providing insights into the advancing degenerative process and producing candidate biomarkers. Such markers may refine the prognostic stratification of patients and the diagnostic pathway, as well as providing an objective assessment of changes in disease activity in response to future therapeutic agents. Studies are being extended to the spinal cord, and the application of neuroimaging to unaffected carriers of highly penetrant genetic mutations linked to the development of ALS offers a unique window to the pre-symptomatic landscape.

Neuroimaging as a New Diagnostic Modality in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is characterized by progressive degeneration of upper and lower motor neurons, with variable involvement of extramotor brain regions. Currently, there are no established objective markers of upper motor neuron and extramotor involvement in ALS. Here, we review the potential diagnostic value of advanced neuroimaging techniques that are increasingly being used to study the brain in ALS. First, we discuss the role of different imaging modalities in our increasing understanding of ALS pathogenesis, and their potential to contribute to objective upper motor neuron biomarkers for the disease. Second, we discuss the challenges to be overcome and the required phases of diagnostic test development to translate imaging technology to clinical care. We also present examples of multidimensional imaging approaches to achieve high levels of diagnostic accuracy. Last, we address the role of neuroimaging in clinical therapeutic trials. Advanced neuroimaging techniques will continue to develop and offer significant opportunities to facilitate the development of new effective treatments for ALS.

Gray matter atrophy in narcolepsy: An activation likelihood estimation meta-analysis

The authors reviewed the literature on the use of voxel-based morphometry (VBM) in narcolepsy magnetic resonance imaging (MRI) studies via the use of a meta-analysis of neuroimaging to identify concordant and specific structural deficits in patients with narcolepsy as compared with healthy subjects. We used PubMed to retrieve articles published between January 2000 and March 2014. The authors included all VBM research on narcolepsy and compared the findings of the studies by using gray matter volume (GMV) or gray matter concentration (GMC) to index differences in gray matter. Stereotactic data were extracted from 8 VBM studies of 149 narcoleptic patients and 162 control subjects. We applied activation likelihood estimation (ALE) technique and found significant regional gray matter reduction in the bilateral hypothalamus, thalamus, globus pallidus, extending to nucleus accumbens (NAcc) and anterior cingulate cortex (ACC), left mid orbital and rectal gyri (BAs 10 and 11), right inferior frontal gyrus (BA 47), and the right superior temporal gyrus (BA 41) in patients with narcolepsy. The significant gray matter deficits in narcoleptic patients occurred in the bilateral hypothalamus and frontotemporal regions, which may be related to the emotional processing abnormalities and orexin/hypocretin pathway common among populations of patients with narcolepsy.

Disparate voxel based morphometry (VBM) results between SPM and FSL softwares in ALS patients with frontotemporal dementia: which VBM results to consider?

Background

Because our previous study showed disparate voxel based morphometry (VBM) results between SPM and FSL softwares in the brain of amyotrophic lateral sclerosis patients with frontotemporal dementia (ALS-FTD), we investigated which VBM results may more represent atrophy by comparing with Freesurfer’s cortical volume and thickness measures.

Methods

MRI at 1.5 T was obtained during routine clinical imaging of ALS-FTD patients (n = 18) and in unaffected neurologic controls (n = 15). Gray matter (GM) VBM analysis was carried out using FSL and SPM. Cortical thickness and volume analysis was performed using Freesurfer.

Results

GM volume was significantly (p < 0.05) reduced in both motor and extra motor regions in ALS- FTD when compared to unaffected neurologic controls in FSL and Freesurfer but not in SPM. Dice similarity index for cortical GM volume changes between FSL and Freesurfer was 0.30 for motor and 0.31 for non-motor regions as opposed to 0 (motor) and 0.02 (non-motor) between SPM and Freesurfer.

Conclusion

GM volume changes using FSL showed similar pattern with Freesurfer cortical volume and thickness changes in contrast to SPM results. Our results suggest that, at least for our dataset, VBM results obtained using FSL software should be considered as more representative of GM atrophy.