How Does the Accuracy of Intracranial Volume Measurements Affect Normalized Brain Volumes? Sample Size Estimates Based on 966 Subjects from the HUNT MRI Cohort

T1-MPRAGE and T2-FLAIR segmentation of cortical and subcortical brain regions-an MRI evaluation study

PURPOSE

Development of a warp-based automated brain segmentation approach of 3D fluid-attenuated inversion recovery (FLAIR) images and comparison to 3D T1-based segmentation.

METHODS

3D FLAIR and 3D T1-weighted sequences of 30 healthy subjects (mean age 29.9 ± 8.3 years, 8 female) were acquired on the same 3T MR scanner. Warp-based segmentation was applied for volumetry of total gray matter (GM), white matter (WM), and 116 atlas regions. Segmentation results of both sequences were compared using Pearson correlation (r).

RESULTS

Correlation of GM segmentation results based on FLAIR and T1 was overall good for cortical structures (mean r across all cortical structures = 0.76). Comparatively weaker results were found in the occipital lobe (r = 0.77), central region (mean r = 0.58), basal ganglia (mean r = 0.59), thalamus (r = 0.30), and cerebellum (r = 0.73). FLAIR segmentation underestimated volume of the central region compared to T1, but showed a better anatomic concordance with the occipital lobe on visual review and subcortical structures, when also compared to manual segmentation. Visual analysis of FLAIR-based WM segmentation revealed frequent misclassification of regions of high signal intensity as GM.

CONCLUSION

Warp-based FLAIR segmentation yields comparable results to T1 segmentation for most cortical GM structures and may provide anatomically more congruent segmentation of subcortical GM structures. Selected cortical regions, especially the central region and total WM, seem to be underestimated on FLAIR segmentation.

Trajectories of brain development in school-age children born preterm with very low birth weight

Preterm birth (gestational age < 37 weeks) with very low birth weight (VLBW, birth weight ≤ 1500 g) is associated with lifelong cognitive deficits, including in executive function, and persistent alterations in cortical and subcortical structures. However, it remains unclear whether “catch-up” growth is possible in the preterm/VLBW brain. Longitudinal structural MRI was conducted with children born preterm with VLBW (n = 41) and term-born peers participating in the Norwegian Mother and Child Cohort Study (MoBa) (n = 128) at two timepoints in early school age (mean ages 8.0 and 9.3 years). Images were analyzed with the FreeSurfer 5.3.0 longitudinal stream to assess differences in development of cortical thickness, surface area, and brain structure volumes, as well as associations with executive function development (NEPSY Statue and WMS-III Spatial Span scores) and perinatal health markers. No longitudinal group × time effects in cortical thickness, surface area, or subcortical volumes were seen, indicating similar brain growth trajectories in the groups over an approximately 16-month period in middle childhood. Higher IQ scores within the VLBW group were associated with greater surface area in left parieto-occipital and inferior temporal regions. Among VLBW preterm-born children, cortical surface area was smaller across the cortical mantle, and cortical thickness was thicker occipitally and frontally and thinner in lateral parietal and posterior temporal areas. Smaller volumes of corpus callosum, right globus pallidus, and right thalamus persisted in the VLBW group from timepoint 1 to 2. VLBW children had on average IQ 1 SD below term-born MoBa peers and significantly worse scores on WMS-III Spatial Span. Executive function scores did not show differential associations with morphometry between groups cross-sectionally or longitudinally. This study investigated divergent or “catch-up” growth in terms of cortical thickness, surface area, and volumes of subcortical gray matter structures and corpus callosum in children born preterm/VLBW and did not find group × time interactions. Greater surface area at mean age 9.3 in left parieto-occipital and inferior temporal cortex was associated with higher IQ in the VLBW group. These results suggest that preterm VLBW children may have altered cognitive networks, yet have structural growth trajectories that appear generally similar to their term-born peers in this early school age window.

Estimated intracranial volume from FreeSurfer is biased by total brain volume

Background

Estimated intracranial volume (eTIV) from FreeSurfer is not segmentation-based but calculated from the alignment of the input magnetic resonance (MR) images to the MNI305 brain atlas, an approach that could lead to a bias by total brain volume. If eTIV is unbiased, variance beyond that explained by intracranial volume should be random. Our null hypothesis was that no correlation would remain between eTIV and total brain volume when controlling for intracranial volume.

Methods

eTIV and total brain volume for 62 participants were calculated on 1.5-T, T1-weighted MR images using FreeSurfer (version 6.0.0). Manual delineations of the intracranial volume were also made for the same images. To evaluate the null hypothesis, the partial correlation between eTIV and total brain volume was calculated when controlling for intracranial volume.

Results

The partial correlation between eTIV and total brain volume when controlling for intracranial volume was 0.355 (p = 0.026). The null hypothesis was rejected.

Conclusion

eTIV from FreeSurfer is biased by total brain volume.

Electronic supplementary material

The online version of this article (10.1186/s41747-018-0055-4) contains supplementary material, which is available to authorized users.

A simple and clinically relevant combination of neuroimaging and functional indexes for the identification of those at highest risk of Alzheimer's disease

The current challenge in clinical practice is to identify those with mild cognitive impairment (MCI), who are at greater risk of Alzheimer's disease (AD) conversion in the near future. The aim of this study was to assess a clinically practical new hippocampal index-hippocampal volume normalized by cerebellar volume (hippocampus to cerebellum volume ratio) used alone or in combination with scores on the Mini-Mental State Examination, as a predictor of conversion from MCI to AD. The predictive value of the HCCR was also contrasted to that of the hippocampal volume to intracranial volume ratio. The findings revealed that the performance of the combination of measures was significantly better than that of each measure used individually. The combination of Mini-Mental State Examination and hippocampal volume, normalized by the cerebellum or by intracranial volume, accurately discriminated individuals with MCI who progress to AD within 5 years from other MCI types (stable, reverters) and those with intact cognition (area under receiver operating curve of 0.88 and 0.89, respectively). Normalization by cerebellar volume was as accurate as normalization by intracranial volume with the advantage of being more practical, particularly for serial assessments.

Volume and shape of subcortical grey matter structures related to headache: A cross-sectional population-based imaging study in the Nord-Trøndelag Health Study

BACKGROUND

The relationship between subcortical nuclei and headache is unclear. Most previous studies were conducted in small clinical migraine samples. In the present population-based MRI study, we hypothesized that headache sufferers exhibit reduced volume and deformation of the nucleus accumbens compared to non-sufferers. In addition, volume and deformation of the amygdala, caudate, hippocampus, pallidum, putamen and thalamus were examined.

METHODS

In all, 1006 participants (50-66 years) from the third Nord-Trøndelag Health Survey, were randomly selected to undergo a brain MRI at 1.5 T. Volume and shape of the subcortical nuclei from T1 weighted 3D scans were obtained in FreeSurfer and FSL. The association with questionnaire-based headache categories (migraine and tension-type headache included) was evaluated using analysis of covariance. Individuals not suffering from headache were used as controls. Age, sex, intracranial volume and Hospital Anxiety and Depression Scale were used as covariates.

RESULTS

No effect of headache status on accumbens volume and shape was present. Exploratory analyses showed significant but small differences in volume of caudate and putamen and in putamen shape between those with non-migrainous headache and the controls. A post hoc analysis showed that caudate volume was strongly associated with white matter hyperintensities.

CONCLUSION

We did not confirm our hypothesis that headache sufferers have smaller volume and different shape of the accumbens compared to non-sufferers. No or only small differences in volume and shape of subcortical nuclei between headache sufferers and non-sufferers appear to exist in the general population.

Regional brain volumetry and brain function in severely brain-injured patients

OBJECTIVE

The relationship between residual brain tissue in patients with disorders of consciousness (DOC) and the clinical condition is unclear. This observational study aimed to quantify gray (GM) and white matter (WM) atrophy in states of (altered) consciousness.

METHODS

Structural T1-weighted magnetic resonance images were processed for 102 severely brain-injured and 52 healthy subjects. Regional brain volume was quantified for 158 (sub)cortical regions using Freesurfer. The relationship between regional brain volume and clinical characteristics of patients with DOC and conscious brain-injured patients was assessed using a linear mixed-effects model. Classification of patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) using regional volumetric information was performed and compared to classification using cerebral glucose uptake from fluorodeoxyglucose positron emission tomography. For validation, the T1-based classifier was tested on independent datasets.

RESULTS

Patients were characterized by smaller regional brain volumes than healthy subjects. Atrophy occurred faster in UWS compared to MCS (GM) and conscious (GM and WM) patients. Classification was successful (misclassification with leave-one-out cross-validation between 2% and 13%) and generalized to the independent data set with an area under the receiver operator curve of 79% (95% confidence interval [CI; 67-91.5]) for GM and 70% (95% CI [55.6-85.4]) for WM.

INTERPRETATION

Brain volumetry at the single-subject level reveals that regions in the default mode network and subcortical gray matter regions, as well as white matter regions involved in long range connectivity, are most important to distinguish levels of consciousness. Our findings suggest that changes of brain structure provide information in addition to the assessment of functional neuroimaging and thus should be evaluated as well. Ann Neurol 2018;83:842-853.

Distinct functional and structural neural underpinnings of working memory

Working memory (WM), the short-term abstraction and manipulation of information, is an essential neurocognitive process in daily functioning. Few studies have concurrently examined the functional and structural neural correlates of WM and the current study did so to characterize both overlapping and unique associations. Participants were a large sample of adults from the Human Connectome Project (N = 1064; 54% female) who completed an in-scanner visual N-back WM task. The results indicate a clear dissociation between BOLD activation during the WM task and brain structure in relation to performance. In particular, while activation in the middle frontal gyrus was positively associated with WM performance, cortical thickness in this region was inversely associated with performance. Additional unique associations with WM were BOLD activation in superior parietal lobule, cingulate, and fusiform gyrus and gray matter volume in the orbitofrontal cortex and cuneus. Across findings, substantially larger effects were observed for functional associations relative to structural associations. These results provide further evidence implicating frontoparietal subunits of the brain in WM. Moreover, these findings reveal the distinct, and in some cases opposing, roles of brain structure and neural activation in WM, highlighting the lack of homology between structure and function in relation to cognition.

White matter hyperintensities and headache: A population-based imaging study (HUNT MRI)

Objective

To examine the relationship between white matter hyperintensities and headache.

Methods

White matter hyperintensities burden was assessed semi-quantitatively using Fazekas and Scheltens scales, and by manual and automated volumetry of MRI in a sub-study of the general population-based Nord-Trøndelag Health Study (HUNT MRI). Using validated questionnaires, participants were categorized into four cross-sectional headache groups: Headache-free (n = 551), tension-type headache (n = 94), migraine (n = 91), and unclassified headache (n = 126). Prospective questionnaire data was used to further categorize participants into groups according to the evolution of headache during the last 12 years: Stable headache-free, past headache, new onset headache, and persistent headache. White matter hyperintensities burden was compared across headache groups using adjusted multivariate regression models.

Results

Individuals with tension-type headache were more likely to have extensive white matter hyperintensities than headache-free subjects, with this being the case across all methods of white matter hyperintensities assessment (Scheltens scale: Odds ratio, 2.46; 95% CI, 1.44–4.20). Migraine or unclassified headache did not influence the odds of having extensive white matter hyperintensities. Those with new onset headache were more likely to have extensive white matter hyperintensities than those who were stable headache-free (Scheltens scale: Odds ratio, 2.24; 95% CI, 1.13–4.44).

Conclusions

Having tension-type headache or developing headache in middle age was linked to extensive white matter hyperintensities. These results were similar across all methods of assessing white matter hyperintensities. If white matter hyperintensities treatment strategies emerge in the future, this association should be taken into consideration.

The corpus callosum as anatomical marker of intelligence? A critical examination in a large-scale developmental study

Intellectual abilities are supported by a large-scale fronto-parietal brain network distributed across both cerebral hemispheres. This bihemispheric network suggests a functional relevance of inter-hemispheric coordination, a notion which is supported by a series of recent structural magnetic resonance imaging (MRI) studies demonstrating correlations between intelligence scores (IQ) and corpus-callosum anatomy. However, these studies also reveal an age-related dissociation: mostly positive associations are reported in adult samples, while negative associations are found in developing samples. In the present study, we re-examine the association between corpus callosum and intelligence measures in a large (734 datasets from 495 participants) developmental mixed cross-sectional and longitudinal sample (6.4–21.9 years) using raw test scores rather than deviation IQ measures to account for the ongoing cognitive development in this age period. Analyzing mid-sagittal measures of regional callosal thickness, a positive association in the splenium of the corpus callosum was found for both verbal and performance raw test scores. This association was not present when the participants’ age was considered in the analysis. Thus, we did not reveal any association that cannot be explained by a temporal co-occurrence of overall developmental trends in intellectual abilities and corpus callosum maturation in the present developing sample.

Simultaneous total intracranial volume and posterior fossa volume estimation using multi-atlas label fusion

Total intracranial volume (TICV) is an essential covariate in brain volumetric analyses. The prevalent brain imaging software packages provide automatic TICV estimates. FreeSurfer and FSL estimate TICV using a scaling factor while SPM12 accumulates probabilities of brain tissues. None of the three provide explicit skull/CSF boundary (SCB) since it is challenging to distinguish these dark structures in a T1-weighted image. However, explicit SCB not only leads to a natural way of obtaining TICV (i.e., counting voxels inside the skull) but also allows sub-definition of TICV, for example, the posterior fossa volume (PFV). In this article, they proposed to use multi-atlas label fusion to obtain TICV and PFV simultaneously. The main contributions are: (1) TICV and PFV are simultaneously obtained with explicit SCB from a single T1-weighted image. (2) TICV and PFV labels are added to the widely used BrainCOLOR atlases. (3) Detailed mathematical derivation of non-local spatial STAPLE (NLSS) label fusion is presented. As the skull is clearly distinguished in CT images, we use a semi-manual procedure to obtain atlases with TICV and PFV labels using 20 subjects who both have a MR and CT scan. The proposed method provides simultaneous TICV and PFV estimation while achieving more accurate TICV estimation compared with FreeSurfer, FSL, SPM12, and the previously proposed STAPLE based approach. The newly developed TICV and PFV labels for the OASIS BrainCOLOR atlases provide acceptable performance, which enables simultaneous TICV and PFV estimation during whole brain segmentation. The NLSS method and the new atlases have been made freely available. Hum Brain Mapp 38:599-616, 2017. © 2016 Wiley Periodicals, Inc.

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.

MR Imaging in Spinocerebellar Ataxias: A Systematic Review

BACKGROUND AND PURPOSE

Polyglutamine expansion spinocerebellar ataxias are autosomal dominant slowly progressive neurodegenerative diseases with no current treatment. MR imaging is the best-studied surrogate biomarker candidate for polyglutamine expansion spinocerebellar ataxias, though with conflicting results. We aimed to review quantitative central nervous system MR imaging technique findings in patients with polyglutamine expansion spinocerebellar ataxias and correlations with well-established clinical and molecular disease markers.

MATERIALS AND METHODS

We searched MEDLINE, LILACS, and Cochrane data bases of clinical trials between January 1995 and January 2016, for quantitative MR imaging volumetric approaches, MR spectroscopy, diffusion tensor imaging, or other quantitative techniques, comparing patients with polyglutamine expansion spinocerebellar ataxias (SCAs) with controls. Pertinent details for each study regarding participants, imaging methods, and results were extracted.

RESULTS

After reviewing the 706 results, 18 studies were suitable for inclusion: 2 studies in SCA1, 1 in SCA2, 15 in SCA3, 1 in SCA7, 1 in SCA1 and SCA6 presymptomatic carriers, and none in SCA17 and dentatorubropallidoluysian atrophy. Cerebellar hemispheres and vermis, whole brain stem, midbrain, pons, medulla oblongata, cervical spine, striatum, and thalamus presented significant atrophy in SCA3. The caudate, putamen and whole brain stem presented similar sensitivity to change compared with ataxia scales after 2 years of follow-up in a single prospective study in SCA3. MR spectroscopy and DTI showed abnormalities only in cross-sectional studies in SCA3. Results from single studies in other polyglutamine expansion spinocerebellar ataxias should be replicated in different cohorts.

CONCLUSIONS

Additional cross-sectional and prospective volumetric analysis, MR spectroscopy, and DTI studies are necessary in polyglutamine expansion spinocerebellar ataxias. The properties of preclinical disease biomarkers (presymptomatic) of MR imaging should be targeted in future studies.

A large-scale comparison of cortical thickness and volume methods for measuring Alzheimer's disease severity

Alzheimer's disease (AD) researchers commonly use MRI as a quantitative measure of disease severity. Historically, hippocampal volume has been favored. Recently, “AD signature” measurements of gray matter (GM) volumes or cortical thicknesses have gained attention. Here, we systematically evaluate multiple thickness- and volume-based candidate-methods side-by-side, built using the popular FreeSurfer, SPM, and ANTs packages, according to the following criteria: (a) ability to separate clinically normal individuals from those with AD; (b) (extent of) correlation with head size, a nuisance covariatel (c) reliability on repeated scans; and (d) correlation with Braak neurofibrillary tangle stage in a group with autopsy. We show that volume- and thickness-based measures generally perform similarly for separating clinically normal from AD populations, and in correlation with Braak neurofibrillary tangle stage at autopsy. Volume-based measures are generally more reliable than thickness measures. As expected, volume measures are highly correlated with head size, while thickness measures are generally not. Because approaches to statistically correcting volumes for head size vary and may be inadequate to deal with this underlying confound, and because our goal is to determine a measure which can be used to examine age and sex effects in a cohort across a large age range, we thus recommend thickness-based measures. Ultimately, based on these criteria and additional practical considerations of run-time and failure rates, we recommend an AD signature measure formed from a composite of thickness measurements in the entorhinal, fusiform, parahippocampal, mid-temporal, inferior-temporal, and angular gyrus ROIs using ANTs with input segmentations from SPM12.

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Evaluate thickness- and volume-based quantitative measures of AD severity

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Volume- and thickness-based measures perform similarly for separating by diagnosis.

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Volume-based measures are correlated with head size; thickness-based mostly aren't.

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We recommend an AD signature measure formed from cortical thickness measures.

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We recommend thicknesses using ANTs software with input segmentations from SPM12.

Marked effects of intracranial volume correction methods on sex differences in neuroanatomical structures: a HUNT MRI study

To date, there is no consensus whether sexual dimorphism in the size of neuroanatomical structures exists, or if such differences are caused by choice of intracranial volume (ICV) correction method. When investigating volume differences in neuroanatomical structures, corrections for variation in ICV are used. Commonly applied methods are the ICV-proportions, ICV-residuals and ICV as a covariate of no interest, ANCOVA. However, these different methods give contradictory results with regard to presence of sex differences. Our aims were to investigate presence of sexual dimorphism in 18 neuroanatomical volumes unrelated to ICV-differences by using a large ICV-matched subsample of 304 men and women from the HUNT-MRI general population study, and further to demonstrate in the entire sample of 966 healthy subjects, which of the ICV-correction methods gave results similar to the ICV-matched subsample. In addition, sex-specific subsamples were created to investigate whether differences were an effect of head size or sex. Most sex differences were related to volume scaling with ICV, independent of sex. Sex differences were detected in a few structures; amygdala, cerebellar cortex, and 3rd ventricle were larger in men, but the effect sizes were small. The residuals and ANCOVA methods were most effective at removing the effects of ICV. The proportions method suffered from systematic errors due to lack of proportionality between ICV and neuroanatomical volumes, leading to systematic mis-assignment of structures as either larger or smaller than their actual size. Adding additional sexual dimorphic covariates to the ANCOVA gave opposite results of those obtained in the ICV-matched subsample or with the residuals method. The findings in the current study explain some of the considerable variation in the literature on sexual dimorphisms in neuroanatomical volumes. In conclusion, sex plays a minor role for neuroanatomical volume differences; most differences are related to ICV.