Pitfalls in brain age analyses

Have your doctor analyze this to see if you really have  5 lost years of brain cognition due to your stroke? Or is it more like 50?

 Pitfalls in brain age analyses

Ellyn R. Butler 1|  

Andrew Chen 2,3|  

Rabie Ramadan 4|  

Trang T. Le 5|

Kosha Ruparel 1|  

Tyler M. Moore 1|  

Theodore D. Satterthwaite 6|

Fengqing Zhang 7|  

Haochang Shou 2,3|  

Ruben C. Gur 1|

Thomas E. Nichols 8,9|  

Russell T. Shinohara 2,3

1 Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine,University of Pennsylvania, Philadelphia,Pennsylvania

2 Penn Statistics in Imaging and Visualization Endeavor, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania,Philadelphia, Pennsylvania

3 Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania

4 Mathematics Department, Temple University,Philadelphia, Pennsylvania

5 Department of Biostatistics, Epidemiology and Informatics, Institute for Biomedical Informatics, University of Pennsylvania,Philadelphia, Pennsylvania

6 Penn Lifespan Informatics & Neuroimaging Center, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania

7 Department of Psychology, Drexel University,Philadelphia, Pennsylvania

8 Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK9FMRIB, Wellcome Centre for Integrative Neuroimaging, Oxford, 

UK Correspondence Ellyn R. Butler, Brain Behavior Laboratory,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania,Philadelphia, PA 19104.Email: ellynrbutler@gmail.comFunding information National Institute of Mental Health, Grant/Award Numbers: MH107235, MH112847,

Abstract

Over the past decade, there has been an abundance of research on the difference between age and age predicted using brain features, which is commonly referred to as the“brain age gap.”Researchers have identified that the brain age gap, as a linear transformation of an out-of-sample residual, is dependent on age. As such, any group differences on the brain age gap could simply be due to group differences on age. To mitigate the brain age gap's dependence on age, it has been proposed that age be regressed out of the brain age gap. If this modified brain age gap is treated as a corrected deviation from age, model accuracy statistics such as R² will be artificially inflated to the extent that it is highly improbable that an R² value below .85 will be obtained no matter the true model accuracy. Given the limitations of proposed brain age analyses, further theoretical work is warranted to determine the best way to quantify deviation from normality.