A new virtue of phantom MRI data: explaining variance in human participant data.

ABSTRACT: Background: Magnetic resonance imaging (MRI) is an important yet complex data acquisition technology for studying the brain. MRI signals can be affected by many factors and many sources of variance are often simply attributed to "noise". Unexplained variance in MRI data hinders the statistical power of MRI studies and affects their reproducibility. We hypothesized that it would be possible to use phantom data as a proxy of scanner characteristics with a simplistic model of seasonal variation to explain some variance in human MRI data. Methods: We used MRI data from human participants collected in several studies, as well as phantom data collected weekly for scanner quality assurance (QA) purposes. From phantom data we identified the variables most likely to explain variance i

SUBMITTER: Cheng CP 

PROVIDER: S-EPMC7783534 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature