TY - UNPB
T1 - Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain
T2 - Algorithm Benchmarking and Model Optimization
AU - Ge, Ruiyang
AU - Yu, Yuetong
AU - Qi, Yi Xuan
AU - Fan, Yunan Vera
AU - Chen, Shiyu
AU - Gao, Chuntong
AU - Haas, Shalaila S
AU - Modabbernia, Amirhossein
AU - New, Faye
AU - Agartz, Ingrid
AU - Asherson, Philip
AU - Ayesa-Arriola, Rosa
AU - Banaj, Nerisa
AU - Banaschewski, Tobias
AU - Baumeister, Sarah
AU - Bertolino, Alessandro
AU - Boomsma, Dorret I
AU - Borgwardt, Stefan
AU - Bourque, Josiane
AU - Brandeis, Daniel
AU - Breier, Alan
AU - Brodaty, Henry
AU - Brouwer, Rachel M
AU - Buckner, Randy
AU - Buitelaar, Jan K
AU - Cannon, Dara M
AU - Caseras, Xavier
AU - Cervenka, Simon
AU - Conrod, Patricia J
AU - Crespo-Facorro, Benedicto
AU - Crivello, Fabrice
AU - Crone, Eveline A
AU - de Haan, Liewe
AU - de Zubicaray, Greig I
AU - Di Giorgio, Annabella
AU - Erk, Susanne
AU - Fisher, Simon E
AU - Franke, Barbara
AU - Frodl, Thomas
AU - Glahn, David C
AU - Grotegerd, Dominik
AU - Gruber, Oliver
AU - Gruner, Patricia
AU - Gur, Raquel E
AU - Gur, Ruben C
AU - Pol, Hilleke E Hulshoff
AU - Kahn, René S
AU - Sommer, Iris E
AU - van Haren, Neeltje Em
AU - Wierenga, Lara M
PY - 2023/12/2
Y1 - 2023/12/2
N2 - We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).
AB - We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).
U2 - 10.1101/2023.01.30.523509
DO - 10.1101/2023.01.30.523509
M3 - Preprint
C2 - 38076938
BT - Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain
PB - BioRxiv
ER -