Publications by authors named "Yi Xuan Qi"
Article Synopsis
- The study evaluates different normative models for analyzing brain structure data to find the most effective approach for research and clinical applications.
- They tested eight algorithms using data from over 37,000 healthy individuals across multiple regions and identified multivariate fractional polynomial regression (MFPR) as the best-performing model.
- The MFPR proved to be highly accurate across various age groups and maintains stability over time, offering valuable insights for understanding brain development and assisting in future research.
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.
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