Dataset Information

Brain atrophy measurement over a MRI scanner change in multiple sclerosis.

ABSTRACT:

Background

A change in MRI hardware impacts brain volume measurements. The aim of this study was to use MRI data from multiple sclerosis (MS) patients and healthy control subjects (HCs) to statistically model how to adjust brain atrophy measures in MS patients after a major scanner upgrade.

Methods

We scanned 20 MS patients and 26 HCs before and three months after a major scanner upgrade (1.5 T Siemens Healthineers Magnetom Avanto to 3 T Siemens Healthineers Skyra Fit). The patient group also underwent standardized serial MRIs before and after the scanner change. Percentage whole brain volume changes (PBVC) measured by Structural Image Evaluation using Normalization of Atrophy (SIENA) in the HCs was used to estimate a corrective term based on a linear model. The factor was internally validated in HCs, and then applied to the MS group.

Results

Mean PBVC during the scanner change was higher in MS than HCs (-4.1 ± 0.8 % versus -3.4 ± 0.6 %). A fixed corrective term of 3.4 (95% confidence interval: 3.13-3.67)% was estimated based on the observed average changes in HCs. Age and gender did not have a significant influence on this corrective term. After adjustment, a linear mixed effects model showed that the brain atrophy measures in MS during the scanner upgrade were not anymore associated with the scanner type (old vs new scanner; p = 0.29).

Conclusion

A scanner change affects brain atrophy measures in longitudinal cohorts. The inclusion of a corrective term based on changes observed in HCs helps to adjust for the known and unknown factors associated with a scanner upgrade on a group level.

SUBMITTER: Sinnecker T

PROVIDER: S-EPMC9424626 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Brain atrophy measurement over a MRI scanner change in multiple sclerosis.

Sinnecker Tim T Schädelin Sabine S Benkert Pascal P Ruberte Esther E Amann Michael M Lieb Johanna M JM Naegelin Yvonne Y Müller Jannis J Kuhle Jens J Derfuss Tobias T Kappos Ludwig L Wuerfel Jens J Granziera Cristina C Yaldizli Özgür Ö

NeuroImage. Clinical 20220810

<h4>Background</h4>A change in MRI hardware impacts brain volume measurements. The aim of this study was to use MRI data from multiple sclerosis (MS) patients and healthy control subjects (HCs) to statistically model how to adjust brain atrophy measures in MS patients after a major scanner upgrade.<h4>Methods</h4>We scanned 20 MS patients and 26 HCs before and three months after a major scanner upgrade (1.5 T Siemens Healthineers Magnetom Avanto to 3 T Siemens Healthineers Skyra Fit). The patien ...[more]

PMID: 36007437

Similar Datasets

Project description:BackgroundCerebral atrophy is common in multiple sclerosis (MS) and selectively involves gray matter (GM). Several fully automated methods are available to measure whole brain and regional deep GM (DGM) atrophy from MRI.ObjectiveTo assess the sensitivity of fully automated MRI segmentation pipelines in detecting brain atrophy in patients with relapsing-remitting (RR) MS and normal controls (NC) over five years.MethodsConsistent 3D T1-weighted sequences were performed on a 3T GE unit in 16 mildly disabled patients with RRMS and 16 age-matched NC at baseline and five years. All patients received disease-modifying immunotherapy on-study. Images were applied to two pipelines to assess whole brain atrophy [brain parenchymal fraction (BPF) from SPM12; percentage brain volume change (PBVC) from SIENA] and two other pipelines (FSL-FIRST; FreeSurfer) to assess DGM atrophy (thalamus, caudate, globus pallidus, putamen). MRI change was compared by two sample t-tests. Expanded Disability Status Scale (EDSS) and timed 25-foot walk (T25FW) change was compared by repeated measures proportional odds models.ResultsUsing FreeSurfer, the MS group had a ~10-fold acceleration in on-study volume loss than NC in the caudate (mean decrease 0.51 vs. 0.05 ml, p = 0.022). In contrast, caudate atrophy was not detected by FSL-FIRST (mean decrease 0.21 vs. 0.12 ml, p = 0.53). None of the other pipelines showed any difference in volume loss between groups, for whole brain or regional DGM atrophy (all p>0.38). The MS group showed on-study stability on EDSS (p = 0.47) but slight worsening of T25FW (p = 0.054).ConclusionsIn this real-world cohort of mildly disabled treated patients with RRMS, we identified ongoing atrophy of the caudate nucleus over five years, despite the lack of any significant whole brain atrophy, compared to healthy controls. The detectability of caudate atrophy was dependent on the MRI segmentation pipeline employed. These findings underscore the increased sensitivity gained when assessing DGM atrophy in monitoring MS.

Project description:Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in recently-diagnosed RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N = 354) underwent 3T structural MRI <6 months after diagnosis and 1-year follow-up, as part of the Scottish multicentre 'FutureMS' study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish regional patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the brain. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, cerebellar GM, brainstem, amygdala, basal ganglia, hippocampus, accumbens, thalamus and ventral diencephalon. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 26 regions and 16/26; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread GM and NAWM atrophy was observed in this large recently-diagnosed RRMS cohort, particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions; indicative of neurodegeneration across tissue types, and in accord with limited previous studies in early disease. Volumetric and VBM results emphasise different features of longitudinal lobar and loco-regional change, however identify consistent atrophy patterns across individuals. Atrophy measures targeted to specific brain regions may provide improved markers of neurodegeneration, and potential future imaging stratifiers and endpoints for clinical decision making and therapeutic trials.

Project description:A measure of lifetime brain atrophy (LBA) obtained from a single magnetic resonance imaging (MRI) scan could be an attractive candidate to boost statistical power in uncovering novel genetic signals and mechanisms of neurodegeneration. We analysed data from five young and old adult cohorts (MRi-Share, Human Connectome Project, UK Biobank, Generation Scotland Subsample, and Lothian Birth Cohort 1936 [LBC1936]) to test the validity and utility of LBA inferred from cross-sectional MRI data, i.e., a single MRI scan per participant. LBA was simply calculated based on the relationship between total brain volume (TBV) and intracranial volume (ICV), using three computationally distinct approaches: the difference (ICV-TBV), ratio (TBV/ICV), and regression-residual method (TBV~ICV). LBA derived with all three methods were substantially correlated with well-validated neuroradiological atrophy rating scales (r = 0.37-0.44). Compared with the difference or ratio method, LBA computed with the residual method most strongly captured phenotypic variance associated with cognitive decline (r = 0.36), frailty (r = 0.24), age-moderated brain shrinkage (r = 0.45), and longitudinally-measured atrophic changes (r = 0.36). LBA computed using a difference score was strongly correlated with baseline (i.e., ICV; r = 0.81) and yielded GWAS signal similar to ICV (rg = 0.75). We performed the largest genetic study of LBA to date (N = 43,110), which was highly heritable (h 2 SNP GCTA = 41% [95% CI = 38-43%]) and had strong polygenic signal (LDSC h 2 = 26%; mean χ2 = 1.23). The strongest association in our genome-wide association study (GWAS) implicated WNT16, a gene previously linked with neurodegenerative diseases such as Alzheimer, and Parkinson disease, and amyotrophic lateral sclerosis. This study is the first side-by-side evaluation of different computational approaches to estimate lifetime brain changes and their measurement characteristics. Careful assessment of methods for LBA computation had important implications for the interpretation of existing phenotypic and genetic results, and showed that relying on the residual method to estimate LBA from a single MRI scan captured brain shrinkage rather than current brain size. This makes this computationally-simple definition of LBA a strong candidate for more powerful analyses, promising accelerated genetic discoveries by maximising the use of available cross-sectional data.

Project description:Grey matter atrophy has been shown in primary progressive multiple sclerosis (PPMS), but its association with physical incapacity is unclear. We submitted 19 patients with PPMS to a neurological evaluation and brain magnetic resonance imaging (MRI) with volumetric analysis using FreeSurfer. We found no relation between the Expanded Disability Status Scale or disease duration and the grey matter or white matter structures analysed. Lesion load was negatively correlated with cortical and subcortical grey matter volumes, but not with total white matter volume. We concluded that physical disability in PPMS is not directly related to brain atrophy and that focal inflammatory white matter lesions may contribute to progressive neuronal degeneration.Primary progressive multiple sclerosis (PPMS) is characterized by chronic progression since onset, with predominant involvement of the spinal cord and prominent neurodegeneration. Grey matter atrophy has been shown in patients with PPMS, but its association with clinical incapacity is uncertain. We investigated the relationship between regional brain atrophy and physical disability in patients with PPMS.Patients with an established diagnosis of PPMS underwent a neurological evaluation followed by brain MRI at 1.5 T. Volumetric analysis was performed with FreeSurfer software, and evaluated the neocortex, total white matter, total subcortical grey matter, putamen, caudate, globus pallidus, thalamus, hippocampus, brainstem, corpus callosum and pre-central gyrus volumes. Clinical data obtained included physical disability as measured by the Expanded Disability Status Scale (EDSS).Nineteen patients were included, 14 female (73.7%), mean age of 55.7 (SD 7.6) and mean disease duration of 13.0 years (SD 8.8). Median EDSS score was 6.0 (3.5-8.0). The average T1 lesion load (4.9 cm³, SD 3.4) and T2 load (10.5 cm³, SD 9.9) did not relate to disease duration. There was no significant correlation between EDSS score or disease duration and the cortical grey matter, deep grey matter or white matter structures analysed. Lesion load was negatively correlated with cortical and subcortical grey matter volumes (p < 0.05), but not with total white matter volume.Physical disability in PPMS is not directly related to brain volume loss. Grey matter atrophy correlates with lesion load in patients with PPMS, indicating that focal inflammatory white matter lesions may contribute to progressive neuronal degeneration.

Dataset Information

Brain atrophy measurement over a MRI scanner change in multiple sclerosis.

Background

Methods

Results

Conclusion

Publications

Brain atrophy measurement over a MRI scanner change in multiple sclerosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets