FSL FIRST Research Articles

Evaluation of transorbital sonography measures of optic nerve diameter in the context of global and regional brain volume in multiple sclerosis

Transorbital sonography (TOS) could be a swift and convenient method to detect the atrophy of the optic nerve, possibly providing a marker that might reflect other quantitative structural markers of multiple sclerosis (MS). Here we evaluate the utility of TOS as a complementary tool for assessing optic nerve atrophy, and investigate how TOS-derived measures correspond to volumetric brain markers in MS. We recruited 25 healthy controls (HC) and 45 patients with relapsing–remitting MS and performed B-mode ultrasonographic examination of the optic nerve. Patients additionally underwent MRI scans to obtain T1-weighted, FLAIR and STIR images. Optic nerve diameters (OND) were compared between HC, MS patients with and without history of optic neuritis (non-ON) using a mixed-effects ANOVA model. The relationship between within-subject-average OND and global and regional brain volumetric measures was investigated using FSL SIENAX, voxel-based morphometry and FSL FIRST. OND was significantly different between HC-MS (HC = 3.2 ± 0.4 mm, MS = 3 ± 0.4 mm; p < 0.019) and we found significant correlation between average OND and normalised whole brain (β = 0.42, p < 0.005), grey matter (β = 0.33, p < 0.035), white matter (β = 0.38, p < 0.012) and ventricular cerebrospinal fluid volume (β = − 0.36, p < 0.021) in the MS group. History of ON had no impact on the association between OND and volumetric data. In conclusion, OND is a promising surrogate marker in MS, that can be simply and reliably measured using TOS, and its derived measures correspond to brain volumetric measures. It should be further explored in larger and longitudinal studies.

Subcortical shape in pediatric and adult obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) implicates alterations in cortico-striato-thalamo-cortical and fronto-limbic circuits. Building on prior structural findings, this is the largest study to date examining subcortical surface morphometry in OCD. Structural magnetic resonance imaging data were collected from 200 participants across development (5-55 years): 28 youth and 75 adults with OCD and 27 psychiatrically healthy youth and 70 adults. General linear models were used to assess group differences and group-by-age interactions on subcortical shape (FSL FIRST). Compared to healthy participants, those with OCD exhibited surface expansions on the right nucleus accumbens and inward left amygdala deformations, which were associated with greater OCD symptom severity ([Children's] Yale-Brown Obsessive-Compulsive Scale). Group-by-age interactions indicated that accumbens group differences were driven by younger participants and that right pallidum shape was associated inversely with age in healthy participants,but not in participants with OCD. No differences in the shape of other subcortical regions or in volumes (FreeSurfer) were detected in supplementary analyses. This study is the largest to date examining subcortical shape in OCD and the first to do so across the developmental spectrum. NAcc and amygdala shape deformation builds on extant neuroimaging findings and suggests subtle, subregional alterations beyond volumetric findings. Results shed light on morphometric alterations in OCD, informing current pathophysiological models.

Feasibility of accelerated 3D T1-weighted MRI using compressed sensing: application to quantitative volume measurements of human brain structures.

Scan time reduction is necessary for volumetric acquisitions to improve workflow productivity and to reduce motion artifacts during MRI procedures. We explored the possibility that Compressed Sensing-4 (CS-4) can be employed with 3D-turbo-field-echo T1-weighted (3D-TFE-T1W) sequence without compromising subcortical measurements on clinical 1.5T MRI. Thirty-three healthy volunteers (24 females, 9 males) underwent imaging scans on a 1.5T MRI equipped with a 12-channel head coil. 3D-TFE-T1W for whole-brain coverage was performed with different acceleration factors, including SENSE-2, SENSE-4, CS-4. Freesurfer, FSL's FIRST, and volBrain packages were utilized for subcortical segmentation. All processed data were assessed using the Wilcoxon signed-rank test. The results obtained from SENSE-2 were considered as references. For SENSE-4, the maximum signal-to-noise ratio (SNR) drop was detected in the Accumbens (51.96%). For CS-4, the maximum SNR drop was detected in the Amygdala (10.55%). Since the SNR drop in CS-4 is relatively small, the SNR in all of the subcortical volumes obtained from SENSE-2 and CS-4 are not statistically different (P > 0.05), and their Pearson's correlation coefficients are larger than 0.90. The maximum biases of SENSE-4 and CS-4 were found in the Thalamus with the mean of differences of 1.60ml and 0.18ml, respectively. CS-4 provided sufficient quality of 3D-TFE-T1W images for 1.5T MRI equipped with a 12-channel receiver coil. Subcortical volumes obtained from the CS-4 images are consistent among different post-processing packages.

Automated, open-source segmentation of the Hippocampus and amygdala with the open Vanderbilt archive of the temporal lobe

Examining volumetric differences of the amygdala and anterior-posterior regions of the hippocampus is important for understanding cognition and clinical disorders. However, the gold standard manual segmentation of these structures is time and labor-intensive. Automated, accurate, and reproducible techniques to segment the hippocampus and amygdala are desirable. Here, we present a hierarchical approach to multi-atlas segmentation of the hippocampus head, body and tail and the amygdala based on atlases from 195 individuals. The Open Vanderbilt Archive of the temporal Lobe (OVAL) segmentation technique outperforms the commonly used FreeSurfer, FSL FIRST, and whole-brain multi-atlas segmentation approaches for the full hippocampus and amygdala and nears or exceeds inter-rater reproducibility for segmentation of the hippocampus head, body and tail. OVAL has been released in open-source and is freely available.

Crossed Cerebellar Diaschisis in Alzheimer's Disease Detected by Arterial Spin-labelling Perfusion MRI.

Crossed cerebellar diaschisis (CCD) is a phenomenon with depressed metabolism and hypoperfusion in the cerebellum. Using arterial spin-labelling perfusion weighted magnetic resonance imaging (ASL PWI), we investigated the frequency of CCD in patients with Alzheimer's disease (AD) and differences between patients with and without CCD. In patients with AD who underwent a standardized magnetic resonance imaging including ASL PWI cerebral blood flow was evaluated in the cerebellum, and brain segmentation/volumetry was performed using mdbrain (mediaire GmbH, Berlin, Germany) and FSL FIRST (Functional Magnetic Resonance Imaging of the Brain Software Library). In total, 65 patients were included, and 22 (33.8%) patients were assessed as being CCD-positive. Patients with CCD had a significantly smaller whole brain volume (862.8±49.9 vs. 893.7±62.7 ml, p=0.049) as well as white matter volume (352.9±28.0 vs. 374.3±30.7, p=0.008) in comparison to patients without CCD. It was possible to detect CCD by ASL PWI in approximately one-third of patients with AD and was associated with smaller whole brain and white matter volume.

Cannabis use in patients with early psychosis is associated with alterations in putamen and thalamic shape.

Around half of patients with early psychosis have a history of cannabis use. We aimed to determine if there are neurobiological differences in these the subgroups of persons with psychosis with and without a history of cannabis use. We expected to see regional deflations in hippocampus as a neurotoxic effect and regional inflations in striatal regions implicated in addictive processes. Volumetric, T1w MRIs were acquired from people with a diagnosis psychosis with (PwP + C = 28) or without (PwP − C = 26) a history of cannabis use; and Controls with (C + C = 16) or without (C − C = 22) cannabis use. We undertook vertex‐based shape analysis of the brainstem, amygdala, hippocampus, globus pallidus, nucleus accumbens, caudate, putamen, thalamus using FSL FIRST. Clusters were defined through Threshold Free Cluster Enhancement and Family Wise Error was set at p < .05. We adjusted analyses for age, sex, tobacco and alcohol use. The putamen (bilaterally) and the right thalamus showed regional enlargement in PwP + C versus PwP − C. There were no areas of regional deflation. There were no significant differences between C + C and C − C. Cannabis use in participants with psychosis is associated with morphological alterations in subcortical structures. Putamen and thalamic enlargement may be related to compulsivity in patients with a history of cannabis use.

Lithium treatment impacts nucleus accumbens shape in bipolar disorder.

The effects of lithium treatment duration on deep grey matter structures in bipolar disorder are not well known. In this cross-sectional neuroimaging case-control study, we tested the hypothesis that shape characteristics of deep grey matter structures in bipolar disorder are associated with the duration of lithium treatment and with clinical phenomenology. In a setting of neuropsychiatry outpatient clinic, we included 74 patients with bipolar disorder (BD) and 74 matched healthy control subjects (HC). Both groups underwent a Magnetic Resonance Imaging acquisition and an exhaustive assessment of clinical and psychiatrics dimensions. Shape measures of seven deep grey matter structures (hippocampus, amygdala, caudate, nucleus accumbens, putamen, globus pallidus and thalamus) were obtained from T1 weighted images in both groups, using FSL FIRST segmentation tool. The segmented structures were then analysed vertex-by-vertex with FSL Randomise tool. First, we investigated the presence of significant associations between the duration of lithium treatment and shape measures in BD sample. Then, for structures that resulted significantly associated with the duration of lithium treatment, comparisons between BD and HC were performed either considering the BD group as a whole or dividing it in three groups based on the duration of treatment (lithium drug-naïve, short and long treated). Any deformation uncovered by group comparisons was subsequently associated with depressive and hypomanic/manic symptoms. The relationship between structures shape and the duration of lithium treatment in BD sample was significant for bilateral nucleus accumbens. Specifically, significant bilateral extroflection effects, related to longer duration of lithium treatment, were found bilaterally over the surface shape of core accumbens nuclei (r2R-Accu-Core=0.12, p=0.016, r2L-Accu-Core=0.1, p=0.031). Moreover, introflection effect related to longer duration of treatment resulted over the shell of right accumbens (r2R-Accu-Shell=0.17, p=0.002). Nucleus accumbens shape did not differ between BD and HC considering BD group as a whole. By contrast, categorizing BD in subgroups as a function of the duration of lithium treatment revealed significant inward deformation on the core of left accumbens nucleus and outward deformation on the shell of the right accumbens nucleus in lithium-naive patients, compared to both patients with long duration of lithium treatment (pL-Accu-Core=0.016, pR-Accu-Shell=0.005) and HC (pL-Accu-Core=0.002; pR-Accu-Shell=0.005). Moreover, compared to HC, inward deformation on the core of the left accumbens surface was found for patients with short duration of treatment (pLAccu-Core=0.027). Finally, measures of surface deformation on the core of left accumbens observed in the group comparison showed significant positive correlations with depressive symptoms severity, as assessed by the Hamilton Depression Rating Scale (total score: r2L-AccuCore=0.07, p=0.02, somatic score: r2L-Accu-Core=0.1, p=0.005) and Beck Hopelessness Scale (r2LAccu-Core=0.05, p=0.03). Findings demonstrate that lithium untreated BD patients are characterised by localized shape abnormalities in the nucleus accumbens. Lithium treatment could act modulating these morphometric features as part of its mechanism of action in mood stabilizing.

Test-retest of automated segmentation with different motion correction strategies: A comparison of prospective versus retrospective methods

Test-retest of automated image segmentation algorithms (FSL FAST, FSL FIRST, and FREESURFER) are computed on magnetic resonance images from 12 unsedated children aged 9.4±2.6 years ([min,max] ​= ​[6.5 years, 13.8 years]) using different approaches to motion correction (prospective versus retrospective). The prospective technique, PROMO MPRAGE, dynamically estimates motion using specially acquired navigator images and adjusts the remaining acquisition accordingly, whereas the retrospective technique, MPnRAGE, uses a self-navigation property to retrospectively estimate and account for motion during image reconstruction. To increase the likelihood and range of motions, participants heads were not stabilized with padding during repeated scans. When motion was negligible both techniques had similar performance. When motion was not negligible, the automated image segmentation and anatomical labeling software tools showed the most consistent performance with the retrospectively corrected MPnRAGE technique (≥80% volume overlaps for 15 of 16 regions for FIRST and FREESURFER, with greater than 90% volume overlaps for 12 regions with FIRST and 11 regions with FREESURFER). Prospectively corrected MPRAGE with linear view-ordering also demonstrated lower performance than MPnRAGE without retrospective motion correction.

Subcortical gray matter volumes in asthma: associations with asthma duration, control, and anxiety.

Asthma as a chronic inflammatory disease can be expected to affect central nervous system structures but little is known about subcortical structures in asthma and their potential association with illness-specific outcomes and anxiety. A total of 40 young adults (20 with asthma and 20 gender- and age-matched controls) underwent high-resolution T1-weighted MRI scan, viewed short distressing film clips, and filled in questionnaires about anxious and depressed mood, as well as asthma history, control, and catastrophizing thoughts about asthma, for those with asthma. The structural scans were processed in FSL's FIRST program to delineate subcortical structures of interest: amygdala, hippocampus, putamen, pallidum, caudate nucleus, nucleus accumbens, and thalamus. Findings showed no general reduction insubcortical gray matter volumes in asthma compared to controls. Asthma duration, asthma control, and catastrophizing of asthma and asthma attacks were negatively associated with volumes of putamen and pallidum, and to a weaker extent thalamus and amygdala, while controlling for gender, age, and corticosteroid inhaler use. In addition, stronger anxiety in response to distressing films was associated with lower volume of the pallidum, whereas general anxious and depressed mood was unrelated to subcortical structures. Thus, although there are no subcortical structural differences between young adults with asthma and healthy controls, longer asthma history, suboptimal management, and illness-related anxiety are reflected in lower gray matter volumes of subcortical structures, further emphasizing the importance of maintaining optimal asthma control.

Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility

Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ± 0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ± 0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ± 0.08 to manual labels and 0.89 ± 0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

Structural correlates of cognitive impairment in normal pressure hydrocephalus.

ObjectivesThe pathological bases for the cognitive and neuropsychiatric symptoms in normal pressure hydrocephalus (NPH) have not been elucidated. However, the symptoms may indicate dysfunction of subcortical regions. Previously, volume reductions of subcortical deep grey matter (SDGM) structures have been observed in NPH patients. The present study used automated segmentation methods to investigate whether SDGM structure volumes are associated with cognitive and neuropsychiatric measures.MethodsFourteen NPH patients and eight healthy controls were included in the study. Patients completed neuropsychological tests of general cognition, verbal learning and memory, verbal fluency and measures of apathy and depression pre‐ and postshunt surgery. Additionally, patients underwent 3 Tesla T1‐weighted magnetic resonance imaging at baseline and 6 months postoperatively. Controls were scanned once. SDGM structure volumes were estimated using automated segmentation (FSL FIRST). Since displacement of the caudate nuclei occurred for some patients due to ventriculomegaly, patient caudate volumes were also estimated using manual tracing. Group differences in SDGM structure volumes were investigated, as well as associations between volumes and cognitive and neuropsychiatric measures in patients.ResultsVolumes of the caudate, thalamus, putamen, pallidum, hippocampus and nucleus accumbens (NAcc) were significantly reduced in the NPH patients compared to controls. In the NPH group, smaller caudate and NAcc volumes were associated with poorer performance on neuropsychological tests and increased severity of neuropsychiatric symptoms, while reduced volume of the pallidum was associated with better performance on the MMSE and reduced apathy.ConclusionsStriatal volume loss appears to be associated with cognitive and neuropsychiatric changes in NPH.

Rapid fully automatic segmentation of subcortical brain structures by shape-constrained surface adaptation.

This work presents a novel approach for the rapid segmentation of clinically relevant subcortical brain structures in T1-weighted MRI by utilizing a shape-constrained deformable surface model. In contrast to other approaches for segmenting brain structures, its design allows for parallel segmentation of individual brain structures within a flexible and robust hierarchical framework such that accurate adaptation and volume computation can be achieved within a minute of processing time. Furthermore, adaptation is driven by local and not global contrast, potentially relaxing requirements with respect to preprocessing steps such as bias-field correction. Detailed evaluation experiments on more than 1000 subjects, including comparisons to FSL FIRST and FreeSurfer as well as a clinical assessment, demonstrate high accuracy and test-retest consistency of the presented segmentation approach, leading, for example, to an average segmentation error of less than 0.5mm. The presented approach might be useful in both, research as well as clinical routine, for automated segmentation and volume quantification of subcortical brain structures in order to increase confidence in the diagnosis of neuro-degenerative disorders, such as Alzheimer's disease, Parkinson's disease, Multiple Sclerosis, or clinical applications for other neurologic and psychiatric diseases.

Sex-specific hippocampus volume changes in obstructive sleep apnea.

IntroductionObstructive sleep apnea (OSA) patients show hippocampal-related autonomic and neurological symptoms, including impaired memory and depression, which differ by sex, and are mediated in distinct hippocampal subfields. Determining sites and extent of hippocampal sub-regional injury in OSA could reveal localized structural damage linked with OSA symptoms.MethodsHigh-resolution T1-weighted images were collected from 66 newly-diagnosed, untreated OSA (mean age ± SD: 46.3 ± 8.8 years; mean AHI ± SD: 34.1 ± 21.5 events/h;50 male) and 59 healthy age-matched control (46.8 ± 9.0 years;38 male) participants. We added age-matched controls with T1-weighted scans from two datasets (IXI, OASIS-MRI), for 979 controls total (426 male/46.5 ± 9.9 years). We segmented the hippocampus and analyzed surface structure with “FSL FIRST” software, scaling volumes for brain size, and evaluated group differences with ANCOVA (covariates: total-intracranial-volume, sex; P < .05, corrected).ResultsIn OSA relative to controls, the hippocampus showed small areas larger volume bilaterally in CA1 (surface displacement ≤0.56 mm), subiculum, and uncus, and smaller volume in right posterior CA3/dentate (≥ − 0.23 mm). OSA vs. control males showed higher bilateral volume (≤0.61 mm) throughout CA1 and subiculum, extending to head and tail, with greater right-sided increases; lower bilateral volumes (≥ − 0.45 mm) appeared in mid- and posterior-CA3/dentate. OSA vs control females showed only right-sided effects, with increased CA1 and subiculum/uncus volumes (≤0.67 mm), and decreased posterior CA3/dentate volumes (≥ − 0.52 mm). Unlike males, OSA females showed volume decreases in the right hippocampus head and tail.ConclusionsThe hippocampus shows lateralized and sex-specific, OSA-related regional volume differences, which may contribute to sex-related expression of symptoms in the sleep disorder. Volume increases suggest inflammation and glial activation, whereas volume decreases suggest long-lasting neuronal injury; both processes may contribute to dysfunction in OSA.

Does attentional dysfunction and thalamic atrophy predict decline in dementia with Lewy bodies?

IntroductionTo evaluate the clinical characteristics of DLB subjects who died within 1 year of assessment compared to those who survived and investigate their patterns of in vivo regional thalamic atrophy using structural MRI. MethodsSeventy subjects (35 DLB, 35 aged controls) underwent 3 T T1-weighted MR scanning as well as clinical and cognitive assessments, including a computerised assessment of attention. All subjects were contacted after 12 months for reassessment.For both hemispheres, using FSL FIRST, the thalamus was automatically segmented followed by inter-subject vertex-wise analyses involving group comparisons and behavioural correlates. ResultsThere was significant bilateral atrophy in the ventral-dorsal and pulvinar regions in DLB relative to controls (pcorrected < 0.05). The DLB group was then re-categorised based on 12-month mortality data: DLB-a (n = 26) and DLB-d (n = 9) (a = alive, d = death within 12 months of study assessment). Compared to controls, significant attentional dysfunction and bilateral atrophy of the pulvinar, ventral and dorsal nuclei were observed in DLB-d (pcorrected < 0.05), whereas in DLB-a, atrophy was far less extensive. ConclusionsDistinct patterns of thalamic atrophy occur in DLB that may relate to the attentional dysfunction and cognitive fluctuations that characterise this disorder. Relative to controls, the extent of attentional impairment and pattern of thalamic degeneration differ in those patients who died within 12 months of assessment, despite having an otherwise similar level of dementia severity. These findings may provide insight into the neurobiological changes underpinning important clinical characteristics and disease heterogeneity.

Fully Automatic MRI-Based Hippocampus Volumetry Using FSL-FIRST: Intra-Scanner Test-Retest Stability, Inter-Field Strength Variability, and Performance as Enrichment Biomarker for Clinical Trials Using Prodromal Target Populations at Risk for Alzheimer's Disease.

MRI-based hippocampus volume is a core clinical biomarker for identification of Alzheimer's disease (AD). To assess robustness of automatic hippocampus volumetry with the freely available FSL-FIRST software with respect to short-term repeat and across field strength imaging. FSL-FIRST hippocampus volume (FIRST-HV) was also evaluated as enrichment biomarker for mild cognitive impairment (MCI) trials. Robustness of FIRST-HV was assessed in 51 healthy controls (HC), 74 MCI subjects, and 28 patients with AD dementia from ADNI1, each with two pairs of back-to-back scans, one at 1.5T one at 3T. Enrichment performance was tested in a second sample of 287 ADNI MCI subjects. FSL-FIRST worked properly in all four scans in 147 out of 153 subjects of the first sample (49 HC, 72 MCI, 26 AD). In these subjects, FIRST-HV did not differ between the first and the second scan within an imaging session, neither at 1.5T nor at 3T (p≥0.302). FIRST-HV was on average 0.78% larger at 3T compared to 1.5T (p = 0.012). The variance of the FIRST-HV difference was larger in the inter-field strength setting than in the intra-scanner settings (p < 0.0005). Computer simulations suggested that the additional variability encountered in the inter-field strength scenario does not cause a relevant degradation of FIRST-HV's prognostic performance in MCI. FIRST-HV based enrichment resulted in considerably increased effect size of the 2-years change of cognitive measures. The impact of intra-scanner test-retest and inter-field strength variability of FIRST-HV on clinical tasks is negligible. In addition, FIRST-HV is useful for enrichment in clinical MCI trials.

The anteroposterior and primary-to-posterior limbic ratios as MRI-derived volumetric markers of Alzheimer's disease

Background/aimsAlzheimer's disease (AD) shows a characteristic pattern of brain atrophy, with predominant involvement of posterior limbic structures, and relative preservation of rostral limbic and primary cortical regions. We aimed to investigate the diagnostic utility of two gray matter volume ratios based on this pattern, and to develop a fully automated method to calculate them from unprocessed MRI files. Patients and methodsCross-sectional study of 118 subjects from the ADNI database, including normal controls and patients with mild cognitive impairment (MCI) and AD. Clinical variables and 3T T1-weighted MRI files were analyzed. Regional gray matter and total intracranial volumes were calculated with a shell script (gm_extractor) based on FSL. Anteroposterior and primary-to-posterior limbic ratios (APL and PPL) were calculated from these values. Diagnostic utility of variables was tested in logistic regression models using Bayesian model averaging for variable selection. External validity was evaluated with bootstrap sampling and a test set of 60 subjects. Resultsgm_extractor showed high test-retest reliability and high concurrent validity with FSL's FIRST. Volumetric measurements agreed with the expected anatomical pattern associated with AD. APL and PPL ratios were significantly different between groups, and were selected instead of hippocampal and entorhinal volumes to differentiate normal from MCI or cognitively impaired (MCI plus AD) subjects. ConclusionAPL and PPL ratios may be useful components of models aimed to differentiate normal subjects from patients with MCI or AD. These values, and other gray matter volumes, may be reliably calculated with gm_extractor.

Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates

IntroductionAdvances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30–80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. MethodMAGeT-Brain works by propagating atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method.We conduct two separate Monte Carlo cross-validation experiments comparing MAGeT-Brain and basic multi-atlas whole hippocampal segmentation using differing atlas and template library sizes, and registration and label fusion methods. The first experiment is a 10-fold validation (per parameter setting) over 60 subjects taken from the Alzheimer's Disease Neuroimaging Database (ADNI), and the second is a five-fold validation over 81 subjects having had a first episode of psychosis. In both cases, automated segmentations are compared with manual segmentations following the Pruessner-protocol. Using the best settings found from these experiments, we segment 246 images of the ADNI1:Complete 1Yr 1.5T dataset and compare these with segmentations from existing automated and semi-automated methods: FSL FIRST, FreeSurfer, MAPER, and SNT. Finally, we conduct a leave-one-out cross-validation of hippocampal subfield segmentation in standard 3T T1-weighted images, using five high-resolution manually segmented atlases (Winterburn et al., 2013). ResultsIn the ADNI cross-validation, using 9 atlases MAGeT-Brain achieves a mean Dice's Similarity Coefficient (DSC) score of 0.869 with respect to manual whole hippocampus segmentations, and also exhibits significantly lower variability in DSC scores than multi-atlas segmentation. In the younger, psychosis dataset, MAGeT-Brain achieves a mean DSC score of 0.892 and produces volumes which agree with manual segmentation volumes better than those produced by the FreeSurfer and FSL FIRST methods (mean difference in volume: 80mm3, 1600mm3, and 800mm3, respectively). Similarly, in the ADNI1:Complete 1Yr 1.5T dataset, MAGeT-Brain produces hippocampal segmentations well correlated (r>0.85) with SNT semi-automated reference volumes within disease categories, and shows a conservative bias and a mean difference in volume of 250mm3 across the entire dataset, compared with FreeSurfer and FSL FIRST which both overestimate volume differences by 2600mm3 and 2800mm3 on average, respectively. Finally, MAGeT-Brain segments the CA1, CA4/DG and subiculum subfields on standard 3T T1-weighted resolution images with DSC overlap scores of 0.56, 0.65, and 0.58, respectively, relative to manual segmentations. ConclusionWe demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods.

Extending provenance information in CBRAIN to address reproducibility issues across computing platforms

Event Abstract Back to Event Extending provenance information in CBRAIN to address reproducibility issues across computing platforms Tristan Glatard1, 2*, Lindsay B. Lewis1, Rafael F. Da Silva3, Marc-Etienne Rousseau1, Claude Lepage1, Pierre Rioux1, Najmeh Mahani1, Ewa Deelman3 and Alan C. Evans1 1 McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Canada 2 University of Lyon, CNRS, INSERM, CREATIS, France 3 University of Southern California, Information Sciences Institute, United States Context: Neuroimaging tools are prone to reproducibility issues across computing platforms due to the propagation of numerical errors along pipelines (Gronenschild, et al., 2012). When different computing systems are used in the same study, these issues may alter the results and even generate false positives. We are designing a system to identify and mitigate reproducibility issues in experiments executed on distributed computing platforms. This system will extend the provenance information available in the CBRAIN web platform (Sherif, et al., 2014) with system-level monitoring information captured by the Kickstart tool (Deelman, et al., 2006). Method: We processed the 150-subject ICBM dataset (Mazziotta et al., 2001) with 3 pipelines: (i) brain tissue segmentation using FSL FAST (Zhang, et al., 2001) (ii) subcortical structure segmentation with FSL FIRST (Patenaude, et al., 2011) (iii) cortical thickness estimation with Freesurfer (Fischl and Dale, 2000). We used FSL 5.0 (build 506) to compare results obtained on two clusters running Linux CentOS 5 and Fedora 20 respectively. We used Freesurfer 5.3.0 and compared the results obtained with CentOS 4 and CentOS 6 x86_64 builds, executed on the Linux Fedora 20 cluster. Results: Brain tissue segmentations computed in FSL on CentOS5 vs. Fedora 20 have a Dice coefficient higher than 0.999 for grey matter, white matter, and CSF. Numerical differences result in discrete noise-like segmentation errors mostly located at the tissue interfaces (see Figure 1). Using ltrace (http://ltrace.org), we identified that these differences are due to different implementations of the exponential function (expf) between CentOS 5 (glibc 2.5) and Fedora 20 (glibc 2.18). Subcortical structure segmentations computed on CentOS5 vs. Fedora 20 have a Dice coefficient ranging from 0.59 to 1 (see Figure 2). Cortical thickness difference maps thresholded with random field theory (RFT) show significant differences between CentOS4 and CentOS6 Freesurfer builds for p<0.05 and p<0.01 (see Figure 3). Discussion: Different computing platforms may produce substantially different results in neuroimaging pipelines. Therefore it is legitimate to avoid using multiple computing platforms in a study. However, this drastically reduces the amount of available computing resources, which slows down experiments. Our provenance-based system will help identify the maximal set of resources that can be used in a study without altering its results. Figure captions: * Figure 1: Sum of binarized differences between brain tissue segmentations of the 150 ICBM subjects with FSL FAST on Linux CentOS 5 vs. Linux Fedora 20. From top to bottom and left to right: z=33,53,73,93,113. * Figure 2: Histograms of DICE coefficients between segmentations obtained on CentOS5 vs. Fedora 20 with FSL FIRST. mu: mean; sigma: standard deviation. Figure 3: Comparison of cortical thickness maps between CentOS4 and CentOS6 Freesurfer builds. Top row: CentOS6 vs CentOS4; bottom row: CentOS4 vs. CentOS6. From left to right, column (1): t statistics; columns (2)-(4): random field theory (RFT) maps thresholded at p<0.05, p<0.01 and p<0.001, respectively. Figure 1 Figure 2 Figure 3

Cortical and subcortical volumes in adolescents with alcohol dependence but without substance or psychiatric comorbidities

Most prior studies of the effects of excessive alcohol intake on the adolescent brain examined alcohol-use-dependent samples with comorbid psychiatric and substance use disorders. In the Cape Town region, we identified a sizeable cohort of adolescents with alcohol use disorders (AUD) without externalizing or other psychiatric disorders. We examined brain morphology in 64 such adolescents compared to age- and gender-matched healthy controls. Magnetic resonance imaging data were analyzed using FSL's FIRST software for subcortical volumes, and cortical gray matter (GM) was analyzed using voxel-based morphometry (VBM) and regions of interest (ROI) analysis. AUD boys had smaller thalamic and putamen volumes compared to non-drinking boys, while AUD girls had larger thalamic and putamen volumes compared to non-drinking girls. VBM revealed a large region of decreased GM density in AUDs compared to controls located in the left lateral frontal, temporal, and parietal lobes, extending medially deep into the parietal lobe. Smaller GM volume in this region was also present when examined using ROI analysis. Our lack of findings in other brain regions, particularly the hippocampus, suggests that reports of smaller brain volumes in adolescent AUDs in the literature are a consequence of psychiatric and substance abuse comorbidities.

Spider phobia is associated with decreased left amygdala volume: a cross-sectional study

BackgroundEvidence from animal and human studies imply the amygdala as the most critical structure involved in processing of fear-relevant stimuli. In phobias, the amygdala seems to play a crucial role in the pathogenesis and maintenance of the disorder. However, the neuropathology of specific phobias remains poorly understood. In the present study, we investigated whether patients with spider phobia show altered amygdala volumes as compared to healthy control subjects.MethodsTwenty female patients with spider phobia and twenty age-matched healthy female controls underwent magnetic resonance imaging to investigate amygdala volumes. The amygdalae were segmented using an automatic, model-based segmentation tool (FSL FIRST). Differences in amygdala volume were investigated by multivariate analysis of covariance with group as between-subject factor and left and right amygdala as dependent factors. The relation between amygdala volume and clinical features such as symptom severity, disgust sensitivity, trait anxiety and duration of illness was investigated by Spearman correlation analysis.ResultsSpider phobic patients showed significantly smaller left amygdala volume than healthy controls. No significant difference in right amygdala volume was detected. Furthermore, the diminished amygdala size in patients was related to higher symptom severity, but not to higher disgust sensitivity or trait anxiety and was independent of age.ConclusionsIn summary, the results reveal a relation between higher symptom severity and smaller left amygdala volume in patients with spider phobia. This relation was independent of other potential confounders such as the disgust sensitivity or trait anxiety. The findings suggest that greater spider phobic fear is associated with smaller left amygdala. However, the smaller left amygdala volume may either stand for a higher vulnerability to develop a phobic disorder or emerge as a consequence of the disorder.