Mesh-based method for measuring intracranial volume in patients with craniosynostosis

Length of synostosis and segmented intracranial volume correlate with age in patients with non-syndromic sagittal synostosis

PURPOSE

The aim of this study is to compare the length of synostosis and segmented intracranial volume (SIV) with age in children with non-syndromic sagittal synostosis.

METHODS

Thirty-three consecutive patients (22 boys) who had been operated by cranial vault remodeling because of sagittal synostosis were compared retrospectively from 3D-CT imaging data sets obtained from volumetric CT. The mean age of the patients at preoperative CT imaging was 0.49 (range 0.13-1.3) years and at 1-year postoperative imaging 1.8 (range 1.3-3) years. The mean interval between preoperative CT imaging and surgery was 0.25 (range 0-0.8) years. Pearson's correlation and Student's t test were used in the statistical analyses.

RESULTS

Length of sagittal synostosis correlated positively with age at preoperative CT (r = 0.688, p < 0.01). Children with total synostosis (n = 9) were significantly older (mean age 0.74 vs. 0.4 years, p < 0.01) than those with partial synostosis. Of partial synostoses, 9 were located anteriorly, 3 in the middle, and 12 posteriorly. The mean synostosis ratio (synostosis length/total sagittal suture length × 100) was 83%. Preoperative SIV correlated positively with age at preoperative CT (r = 0.788, p < 0.01), whereas the 1-year postoperative SIV did not correlate with age at operation. The older the child at the time of the operation, the less the percentage SIV increased.

CONCLUSIONS

Length of sagittal synostosis and SIV increased with age.

Estimating Intracranial Volume in Brain Research: An Evaluation of Methods

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.

Comparative reliability analysis of publicly available software packages for automatic intracranial volume estimation

Intracranial volume is an important measure in brain research often used as a correction factor in inter subject studies. The current study investigates the resulting outcome in terms of the type of software used for automatically estimating ICV measure. Five groups of 70 subjects are considered, including adult controls (AC) (n=11), adult with dementia (AD) (n=11), pediatric controls (PC) (n=18) and two groups of pediatric epilepsy subjects (PE1.5 and PE3) (n=30) using 1.5 T and 3T scanners, respectively. Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. Four publicly available software packages (AFNI, Freesurfer, FSL, and SPM) were examined in their ability to automatically estimate ICV across the five groups. Linear regression analyses suggest that reference measurement discrepancy could be explained best by SPM [R(2)= 0.67;p <; 0.01] for the AC group, Freesurfer [R(2) = 0.46; p = 0.02] for the AD group, AFNI [R(2)=0.97;p<; 0.01] for the PC group and FSL [R(2) = 0.6; p = 0.1] for the PE1.5 and [R(2) = 0.6; p <; 0.01] for PE3 groups. The study demonstrates that the choice of the automated software for ICV estimation is dependent on the population under consideration and whether the software used is atlas-based or not.

A practical guideline for intracranial volume estimation in patients with Alzheimer's disease

Background

Intracranial volume (ICV) is an important normalization measure used in morphometric analyses to correct for head size in studies of Alzheimer Disease (AD). Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation in patients with Alzheimer disease in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and the type of software most suitable for use in estimating the ICV measure.

Methods

Two groups of 22 subjects are considered, including adult controls (AC) and patients with Alzheimer Disease (AD). Reference measurements were calculated for each subject by manually tracing intracranial cavity by the means of visual inspection. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (Freesurfer, FSL, and SPM) were examined in their ability to automatically estimate ICV across the groups.

Results

Analysis of the results supported the significant effect of estimation method, gender, cognitive condition of the subject and the interaction among method and cognitive condition factors in the measured ICV. Results on sub-sampling studies with a 95% confidence showed that in order to keep the accuracy of the interleaved slice sampling protocol above 99%, the sampling period cannot exceed 20 millimeters for AC and 15 millimeters for AD. Freesurfer showed promising estimates for both adult groups. However SPM showed more consistency in its ICV estimation over the different phases of the study.

Conclusions

This study emphasized the importance in selecting the appropriate protocol, the choice of the sampling period in the manual estimation of ICV and selection of suitable software for the automated estimation of ICV. The current study serves as an initial framework for establishing an appropriate protocol in both manual and automatic ICV estimations with different subject populations.