학술논문

A comparison of methods to harmonize cortical thickness measurements across scanners and sites
Document Type
article
Author
Sun, DelinRakesh, GopalkumarHaswell, Courtney CLogue, MarkBaird, C LexiO'Leary, Erin NCotton, Andrew SXie, HongTamburrino, MarijoChen, TianDennis, Emily LJahanshad, NedaSalminen, Lauren EThomopoulos, Sophia IRashid, FaisalChing, Christopher RKKoch, Saskia BJFrijling, Jessie LNawijn, Lauravan Zuiden, MirjamZhu, XiSuarez-Jimenez, BenjaminSierk, AnikaWalter, HenrikManthey, AntjeStevens, Jennifer SFani, Negarvan Rooij, Sanne JHStein, MurrayBomyea, JessicaKoerte, Inga KChoi, Kylevan der Werff, Steven JAVermeiren, Robert RJMHerzog, JuliaLebois, Lauren AMBaker, Justin TOlson, Elizabeth AStraube, ThomasKorgaonkar, Mayuresh SAndrew, ElpinikiZhu, YeLi, GenIpser, JonathanHudson, Anna RPeverill, MatthewSambrook, KellyGordon, EvanBaugh, LeeForster, GinaSimons, Raluca MSimons, Jeffrey SMagnotta, VincentMaron-Katz, Adidu Plessis, StefanDisner, Seth GDavenport, NicholasGrupe, Daniel WNitschke, Jack BdeRoon-Cassini, Terri AFitzgerald, Jacklynn MKrystal, John HLevy, IfatOlff, MirandaVeltman, Dick JWang, LiNeria, YuvalDe Bellis, Michael DJovanovic, TanjaDaniels, Judith KShenton, Marthavan de Wee, Nic JASchmahl, ChristianKaufman, Milissa LRosso, Isabelle MSponheim, Scott RHofmann, David BerndBryant, Richard AFercho, Kelene AStein, Dan JMueller, Sven CHosseini, BobakPhan, K LuanMcLaughlin, Katie ADavidson, Richard JLarson, Christine LMay, GeoffreyNelson, Steven MAbdallah, Chadi GGomaa, HassaanEtkin, AmitSeedat, SorayaHarpaz-Rotem, IlanLiberzon, Israelvan Erp, Theo GMQuidé, YannWang, XinThompson, Paul MMorey, Rajendra A
Source
Subject
Good Health and Well Being
Adolescent
Adult
Aged
Aged
80 and over
Case-Control Studies
Child
Female
Humans
Magnetic Resonance Imaging
Male
Middle Aged
Neuroimaging
Stress Disorders
Post-Traumatic
Young Adult
Data Harmonization
Scanner Effects
Site Effects
Cortical Thickness
ComBat
ComBat-GAM
Linear Mixed-Effects Model
General Additive Model
PTSD
Medical and Health Sciences
Psychology and Cognitive Sciences
Neurology & Neurosurgery
Language
Abstract
Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.