Intracranial volume estimated with commonly used methods could introduce bias in studies including brain volume measurements

AbstractIn brain volumetric studies, intracranial volume (ICV) is often used as an estimate of pre-morbid brain size as well as to compensate for inter-subject variations in head size. However, if the estimated ICV is biased by for example gender or atrophy, it could introduce errors in study results. To evaluate how two commonly used methods for ICV estimation perform, computer assisted reference segmentations were created and evaluated. Segmentations were created for 399 MRI volumes from 75-year-old subjects, with 53 of these subjects having an additional scan and segmentation created at age 80. ICV estimates from Statistical Parametric Mapping (SPM, version 8) and Freesurfer (FS, version 5.1.0) were compared to the reference segmentations, and bias related to skull size (approximated with the segmentation measure), gender or atrophy were tested for. The possible ICV related effect on associations between normalized hippocampal volume and factors gender, education and cognition was evaluated by normalizing hippocampal volume with different ICV measures. Excellent agreement was seen for inter- (r=0.999) and intra- (r=0.999) operator reference segmentations. Both SPM and FS overestimated ICV. SPM showed bias associated with gender and atrophy while FS showed bias dependent on skull size. All methods showed good correlation between time points in the longitudinal data (reference: 0.998, SPM: 0.962, FS: 0.995). Hippocampal volume showed different associations with cognition and gender depending on which ICV measure was used for hippocampal volume normalization. These results show that the choice of method used for ICV estimation can bias results in studies including brain volume measurements

Valid and efficient manual estimates of intracranial volume from magnetic resonance images

Background: Manual segmentations of the whole intracranial vault in high-resolution magnetic resonance images are often regarded as very time-consuming. Therefore it is common to only segment a few linearly spaced intracranial areas to estimate the whole volume. The purpose of the present study was to evaluate how the validity of intracranial volume estimates is affected by the chosen interpolation method, orientation of the intracranial areas and the linear spacing between them. Methods: Intracranial volumes were manually segmented on 62 participants from the Gothenburg MCI study using 1.5 T, T-1-weighted magnetic resonance images. Estimates of the intracranial volumes were then derived using subsamples of linearly spaced coronal, sagittal or transversal intracranial areas from the same volumes. The subsamples of intracranial areas were interpolated into volume estimates by three different interpolation methods. The linear spacing between the intracranial areas ranged from 2 to 50 mm and the validity of the estimates was determined by comparison with the entire intracranial volumes. Results: A progressive decrease in intra-class correlation and an increase in percentage error could be seen with increased linear spacing between intracranial areas. With small linear spacing (<= 15 mm), orientation of the intracranial areas and interpolation method had negligible effects on the validity. With larger linear spacing, the best validity was achieved using cubic spline interpolation with either coronal or sagittal intracranial areas. Even at a linear spacing of 50 mm, cubic spline interpolation on either coronal or sagittal intracranial areas had a mean absolute agreement intra-class correlation with the entire intracranial volumes above 0.97. Conclusion: Cubic spline interpolation in combination with linearly spaced sagittal or coronal intracranial areas overall resulted in the most valid and robust estimates of intracranial volume. Using this method, valid ICV estimates could be obtained in less than five minutes per patient

Abnormal metabolite concentrations and amygdala volume in patients with recent-onset posttraumatic stress disorder

Background Previous psychoradiological studies of posttraumatic stress disorder (PTSD) were mainly of patients at a chronic stage, focusing on brain regions outside the amygdala. The goals of this study were to investigate the early biochemical and structural changes of anterior cingulate cortex (ACC) and amygdala in patients with PTSD and to explore their relationships. Methods Seventy-eight drug-naïve PTSD subjects and 71 non-PTSD age- and sex-matched control subjects were enrolled, all of whom had suffered the same earthquake about one year before. Single-voxel proton magnetic resonance spectroscopy (1H-MRS) was performed and absolute metabolite concentrations in ACC and bilateral amygdalae were estimated with LCModel. Bilateral amygdalae were manually outlined and their volumes were calculated and corrected for the total intracranial volume. Results The PTSD group showed significantly increased N-acetylaspartate (NAA) concentration in the ACC, increased creatine (Cr) concentration in the left amygdala, and increased myo-inositol (mI) concentration in the right amygdala, compared to non-PTSD controls. The NAA concentration in ACC was negatively correlated with the time since trauma. The PTSD group showed significantly decreased volumes of bilateral amygdalae compared to non-PTSD controls, but amygdala volumes were not correlated with metabolite concentrations. Limitations Longitudinal studies are needed to explore the metabolic and structural changes of PTSD at different stages. The volume of ACC was not measured. Conclusions This concurrent increase in some metabolite concentrations and decrease of amygdala volumes may represent a pattern of biochemical and morphological changes in recent-onset PTSD which is different from that reported in chronic PTSD

Exploration of gray matter correlates of cognitive training benefit in adolescents with chronic traumatic brain injury

Sustaining a traumatic brain injury (FBI) during adolescence has a profound effect on brain development and can result in persistent executive functioning deficits in daily life. Cognitive recovery from pediatric-TBI relies on the potential of neuroplasticity, which can be fostered by restorative training-programs. However the structural mechanisms underlying cognitive recovery in the immature brain are poorly understood. This study investigated gray matter plasticity following 2 months of cognitive training in young patients with TBI. Sixteen adolescents in the chronic stage of moderate-severe-TBI (9 male, mean age = 15y8m +/- 1y7m) were enrolled in a cognitive computerized training program for 8 weeks (5 times/week, 40 min/session). Pre-and post-intervention, and 6 months after completion of the training, participants underwent a comprehensive neurocognitive test-battery and anatomical Magnetic Resonance Imaging scans. We selected 9 cortical-subcortical Regions-Of-Interest associated with Executive Functioning (EF-ROIs) and 3 control regions from the Desikan-Killiany atlas. Baseline analyses showed significant decreased gray matter density in the superior frontal gyri p = 0.033, superior parietal gyri p = 0.015 and thalamus p = 0.006 in adolescents with TBI compared to age and gender matched controls. Linear mixed model analyses of longitudinal volumetric data of the EF-ROI revealed no strong evidence of training-related changes in the group with TBI. However, compared to the change over time in the control regions between post-intervention and 6 months follow-up, the change in the EF-ROIs showed a significant difference. Exploratory analyses revealed a negative correlation between the change on the Digit Symbol Substitution test and the change in volume of the putamen (r = - 0.596, p = 0.015). This preliminary study contributes to the insights of training-related plasticity mechanisms after pediatric-TBI

Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance

Total intracranial volume (TIV/ICV) is an important covariate for volumetric analyses of the brain and brain regions, especially in studies of neurodegenerative diseases, where it can provide a proxy of maximum pre-morbid brain volume. The gold-standard method is manual delineation of brain scans, but this requires careful work by trained operators. We evaluated Statistical Parametric Mapping 12 (SPM12) automated segmentation for TIV measurement in place of manual segmentation and also compared it with SPM8 and FreeSurfer 5.3.0. For T1-weighted MRI acquired from 288 participants in a multi-centre clinical trial in Alzheimer's disease we find a high correlation between SPM12 TIV and manual TIV (R2=0.940, 95% Confidence Interval (0.924, 0.953)), with a small mean difference (SPM12 40.4±35.4ml lower than manual, amounting to 2.8% of the overall mean TIV in the study). The correlation with manual measurements (the key aspect when using TIV as a covariate) for SPM12 was significantly higher (p<0.001) than for either SPM8 (R2=0.577 CI (0.500, 0.644)) or FreeSurfer (R2=0.801 CI (0.744, 0.843)). These results suggest that SPM12 TIV estimates are an acceptable substitute for labour-intensive manual estimates even in the challenging context of multiple centres and the presence of neurodegenerative pathology. We also briefly discuss some aspects of the statistical modelling approaches to adjust for TIV