Estimating Intracranial Volume in Brain Research: An Evaluation of Methods

Abstract

Intracranial volume (ICV) is a standard measure often used in morphometric analyses to correct for head size in brain studies. Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation across different subject groups in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and type of software most suitable for use in estimating the ICV measure. Four groups of 53 subjects are considered, including adult controls (AC, adults with Alzheimer's disease (AD), pediatric controls (PC) and group of pediatric epilepsy subjects (PE). Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (FreeSurfer Ver. 5.3.0, FSL Ver. 5.0, SPM8 and SPM12) were examined in their ability to automatically estimate ICV across the groups. Results on sub-sampling studies with a 95 % confidence showed that in order to keep the accuracy of the inter-leaved slice sampling protocol above 99 %, sampling period cannot exceed 20 mm for AC, 25 mm for PC, 15 mm for AD and 17 mm for the PE groups. The study assumes a priori knowledge about the population under study into the automated ICV estimation. Tuning of the parameters in FSL and the use of proper atlas in SPM showed significant reduction in the systematic bias and the error in ICV estimation via these automated tools. SPM12 with the use of pediatric template is found to be a more suitable candidate for PE group. SPM12 and FSL subjected to tuning are the more appropriate tools for the PC group. The random error is minimized for FS in AD group and SPM8 showed less systematic bias. Across the AC group, both SPM12 and FS performed well but SPM12 reported lesser amount of systematic bias.

Hippocampal Structure Predicts Statistical Learning and Associative Inference Abilities during Development

“…We then related HPC volumes to (1) age and (2) performance on the statistical learning and associative inference tasks as described below. As recent work suggests that FSL may be superior for estimating ICV in pediatric populations (Sargolzaei et al, 2015), we also verified our findings using ICV estimated using tools available through FSL (following the ENIGMA protocol; http://enigma.ini.usc.edu). Adjusting for overall head size using the FSL-based ICV estimates did not substantially change any of our findings (results not reported).…”

Cortical complexity as a measure of age-related brain atrophy

“…Here we sought to determine if FD is correlated with ICV, such that we can appropriately control for this relationship, if it exists. We estimated ICV using FreeSurfer (Buckner et al, 2004), which has been shown to correspond well with manual tracing (Sargolzaei et al, 2015). ICV was only weakly related to age differences [ r (416) = −.190, p <.001], though was found to be correlated with sex [ r (416) = −.572, p <.001].…”

Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database

“…In SPM, the TIV is calculated as the sum of the all intracranial tissues, with additional tissue class most introduced in the recent version of SPM 12 (e.g., external CSF as appose to part of the entire CSF classes in the early version) and regularized through wrapping the tissue segmentation with a manually corrected TIV mask (Keihaninejad et al, ) to improve the segmentation accuracy. The more rigorous definition of T1‐based TIV in SPM appears to be more consistent compared to FreeSurfer's scaling‐based estimation (Hansen et al, ; Keihaninejad et al, ; Sargolzaei et al, ; Sargolzaei et al, ; Sargolzaei et al, ), and is less affected by the brain atrophy (Pengas et al, ). However, both the FreeSurfer and the SPM8 automatic TIV estimation introduce systematic overestimation (Nordenskjold et al, ), which has been alleviated in SPM12 in which case a new method is introduced using template registration, which improves accuracy (Malone et al, ) and consistency (Heinen et al, ) of both TIV estimation, as well as brain volume measurements (Heinen et al, ; Vagberg et al, ).…”