Estimation of the Intracranial Volume Is Crucial in Multi-Site Studies: Reliability for Longitudinal Investigations and Traveling Subjects.
Shinsuke Koike, Norihide Maikusa, Lin Cai, Issei Ueda, Shuhei Shibukawa, Toshihiko Aso, Saori C Tanaka, Takuya Hayashi, Japanese Strategic Research Program for the Promotion of Brain Science (SRPBS) DecNef Study Project Group, Brain/MINDS Beyond Human Brain MRI (BMB‐HBM) Study Project Group
Abstract
Open AccessAccurate estimation of the total intracranial volume (TIV) is essential in brain magnetic resonance imaging (MRI) studies, particularly for multi-site longitudinal investigations. This study assessed the validity and reliability of segmentation-based TIV (sbTIV) implemented in FreeSurfer version 7.2 for large-scale multi-site MRI data, by comparing it with the widely used estimated TIV (eTIV). We analyzed 6524 structural MRI scans from two multi-site projects in Japan, consisting of 30 procedures across 21 sites, 13 MRI machine types, 3 vendors, and 4 protocol categories. We tested the intraclass correlation coefficients (ICCs) between eTIV and sbTIV for each procedure and identified procedural factors affecting these ICCs using a general linear model. Machine- and protocol-specific biases were considered by a traveling subject harmonization approach. To specifically examine the reliability and validity of the longitudinal scans, we employed a general linear mixed model (GLMM). Overall agreement between eTIV and sbTIV was good (ICC = 0.78) but varied across procedures (0.62-0.94). The 1.0 mm isotropic protocol showed the highest reliability. Notably, there was poor consistency in participants with eTIV values of 120,000 mm3 or smaller (ICC = 0.053). sbTIV demonstrated superior cross-procedural consistency in adolescent and adult longitudinal scans compared to eTIV. In longitudinal scans, sbTIV showed greater sex difference and sex-specific increase for adolescents, and greater consistency for adults, compared to eTIV. sbTIV offers more robust and reliable estimation compared to eTIV, particularly for multi-site longitudinal studies. These findings highlight the need for careful consideration when interpreting previous multi-site studies using eTIV.