Procedures for collecting, segmenting, and analyzing images have evolved in parallel with rapid technological advances in MRI. Variables relevant to all structural MRI studies of AUDs and selected for analysis as moderators were field strength of the instrument, segmentation method, and adjustment for intracranial volume (ICV). Better resolution at higher field strengths increases the signal-to-noise ratio of MRI data, potentially increasing the ability to detect group differences (Moseley et al., 2009). Development of automated algorithms for classifying tissue on MRI images into WM, GM, and CSF has obviated the need for manual tracing of tissue compartments and may increase the precision of volume measures (Zhang et al., 2001). Adjusting tissue volumes for ICV has become standard practice in cross-sectional studies in recent years to reduce the influence of factors not associated with the mechanism of interest, including height (Friedman et al., 1997; Matsumae et al., 1996) and parental history of AUD (Gilman et al., 2007).
