Structural methods in gray matter

Abstract

Magnetic resonance imaging is the de facto imaging modality to non-invasively investigate the structure of the human brain and has been extensively used to study schizophrenia. The studies that have been performed since its introduction to schizophrenia research have resulted in important new insights into the disorder. These new insights required acquisition and processing methodology that are described for the brain’s gray matter in this chapter. Because schizophrenia research is characterized by small effect sizes, sophisticated image analysis and subsequent quantification in large image sets are needed to detect the subtle changes in brain structure. In addition, comparison with MRI brain scans of healthy individuals is needed to distinguish disorder-related changes from normal age and sex related influences. A key issue in such group comparisons is to define the feature(s) of interest in a valid and reliable manner. In this chapter, we briefly introduce the anatomy of gray matter, MRI methodology, and the most frequently used MRI contrasts in structural brain imaging. Next, we discuss gray matter tissue in more detail and focus on how gray matter brain structures are (in part) delineated from MRI images, ranging from laborious manual delineation to more recent fully-automated segmentation techniques. More complex study designs are then discussed followed by a discussion of machine learning in structural gray matter brain imaging.