Lifespan Volume Trajectories From Non–harmonized T1–Weighted MRI Do Not Differ After Site Correction Based on Traveling Human Phantoms

Abstract

Multi–site imaging consortiums strive to increase participant numbers by pooling data across sites, but scanner related differences can bias results. This study combines data from three research MRI centers, including three different scanner models from two vendors, to examine non–harmonized T1–weighted brain imaging protocols in two cohorts. First, 23 human traveling phantoms were scanned twice each at all three sites (six scans per person; 138 scans total) to quantify within–participant variability of brain volumes (total brain, white matter, gray matter, lateral ventricles, thalamus, caudate, putamen and globus pallidus), and to calculate site–specific correction factors for each structure. Sample size calculations were used to determine the number of traveling phantoms needed to achieve effect sizes for observed differences to help guide future studies. Next, cross–sectional lifespan volume trajectories were examined in 856 healthy participants (5—91 years of age) scanned at these sites. Cross–sectional trajectories of volume versus age for each structure were then compared before and after application of traveling phantom based site–specific correction factors, as well as correction using the open–source method ComBat. Although small systematic differences between sites were observed in the traveling phantom analysis, correction for site using either method had little impact on the lifespan trajectories. Only white matter had small but significant differences in the intercept parameter after ComBat correction (but not traveling phantom based correction), while no other fits differed. This suggests that age–related changes over the lifespan outweigh systematic differences between scanners for volumetric analysis. This work will help guide pooling of multisite datasets as well as meta–analyses of data from non–harmonized protocols.

A resource for development and comparison of multi-modal brain 3T MRI harmonisation approaches

“…We showed that both ComBat (Fortin et al, 2017) and CovBat (Chen et al, 2022) reduced the between-scanner variability for a range of IDPs derived from different modalities towards the level of the respective within-scanner variability. The relatively small difference in subcortical volumes corrected with ComBat compared to the uncorrected volumes is in agreement with findings from other studies (Treit et al, 2022). The authors in this study used ComBat to reduce systematic variations in the brain volumes of 23 travelling subjects scanned in 3 different scanners and they found minimal changes (of less than 5%) between corrected and raw volumes for several subcortical regions (caudate, globus pallidus, putamen, and thalamus).…”

“…The authors in this study used ComBat to reduce systematic variations in the brain volumes of 23 travelling subjects scanned in 3 different scanners and they found minimal changes (of less than 5%) between corrected and raw volumes for several subcortical regions (caudate, globus pallidus, putamen, and thalamus). The authors in (Treit et al, 2022) point out that the degree to which ComBat decreases inter-subject variability likely depends on the magnitude of site effects in the raw data implying that ComBat has less of an effect on results that are more robust to site effects. Our findings support this notion as of the three IDPs tested (subcortical volumes, T2* values and FA values), the subcortical volumes had on average the least between-scanner variability of the three and were also affected the least by ComBat.…”

Lifespan neurodegeneration of the human brain in multiple sclerosis

“…Due to partial and non‐harmonized information about imaging protocol over databases, we were not able to correct for scanner type that can be considered as a limitation of our study. However, it has been recently shown that scanner type does not have impact on lifespan volume trajectory (Treit et al, 2022 ). Finally, we also assumed that patients with disease‐modifying therapy (DMT) and without DMT had the same dynamic in terms of atrophy compared to normal aging.…”