Atlas based brain volumetry: How to distinguish regional volume changes due to biological or physiological effects from inherent noise of the methodology

Abstract

Fully-automated regional brain volumetry based on structural magnetic resonance imaging (MRI) plays an important role in quantitative neuroimaging. In clinical trials as well as in clinical routine multiple MRIs of individual patients at different time points need to be assessed longitudinally. Measures of inter- and intrascanner variability are crucial to understand the intrinsic variability of the method and to distinguish volume changes due to biological or physiological effects from inherent noise of the methodology. To measure regional brain volumes an atlas based volumetry (ABV) approach was deployed using a highly elastic registration framework and an anatomical atlas in a well-defined template space. We assessed inter- and intrascanner variability of the method in 51 cognitively normal subjects and 27 Alzheimer dementia (AD) patients from the Alzheimer's Disease Neuroimaging Initiative by studying volumetric results of repeated scans for 17 compartments and brain regions. Median percentage volume differences of scan-rescans from the same scanner ranged from 0.24% (whole brain parenchyma in healthy subjects) to 1.73% (occipital lobe white matter in AD), with generally higher differences in AD patients as compared to normal subjects (e.g., 1.01% vs. 0.78% for the hippocampus). Minimum percentage volume differences detectable with an error probability of 5% were in the one-digit percentage range for almost all structures investigated, with most of them being below 5%. Intrascanner variability was independent of magnetic field strength. The median interscanner variability was up to ten times higher than the intrascanner variability.

Longitudinal magnetic resonance imaging in progressive supranuclear palsy: A new combined score for clinical trials

“…Intra-scanner variability of atlas-based volumetry was less than 1% for most structures in a prior study comparing two MRIs in single subjects. 39 In the present study, atrophy rates (and subsequently effect sizes and sample sizes) are based on the average of N=99 patients. Consequently, intra-scanner variability influenced the results by a factor of 99 less, i.e., in the range of 0.01% of the measured volumes.…”

“…1). [9][10][11] In short, each T1-weighted volume dataset was normalized to Montreal Neurological Institute template space using diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) 16 and segmented into different brain compartments, that is, gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the unified segmentation algorithm of SPM12 with default parameters. Volumetric measures of brain structures were calculated by voxel-by-voxel multiplication and subsequent integration of normalized and modulated component images (GM, WM, or CSF) with predefined masks in the same space.…”

“…We used fully automated atlas-based volumetry (ABV) to quantify structural changes in individual patients with an intrascanner variability of <1%. 9,10 In the tideglusib study, this method revealed lower cerebral atrophy rates in verum-versus placebo-treated patients. 4 Furthermore, in conjunction with support vector machine classification, this method reliably identified PSP patients in a large mixture of parkinsonian syndromes.…”

Cortical Thickness Estimations of FreeSurfer and the CAT12 Toolbox in Patients with Alzheimer's Disease and Healthy Controls

“…23 The median, the 25th, and 75th percentiles are reported for each region for both methods. 24 Furthermore, Scatter-and Bland-Altman plots were used for graphical representation to depict the degree of agreement for the respective data. 25…”

Differentiation of neurodegenerative parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification

“…In PSP, it could demonstrate reduced progression of brain atrophy in a randomized, placebo‐controlled medication trial . To enhance the quality of mapping into atlas space, high‐dimensional registration methods have recently been introduced, and the intrascanner variability of volumetric results was shown to be <1% for the majority of investigated structures …”