ABSTRACT
High-resolution structural magnetic resonance imaging (sMRI) is used extensively in clinical practice, as it provides detailed anatomical information of the living organism, is sensitive to many pathologies, and assists in the diagnosis of disease (1). Applications of sMRI cover essentially every part of the human body from toes to brain and a wide variety of diseases from stroke, cancer, and multiple sclerosis (MS), to internal bleeding and torn ligaments. Since the introduction of MRI in the 1980s, the noninvasive nature of the technique, the continuously improving resolution of images, and the wide availability of MRI scanners have made sMRI instantly recognizable in the popular literature (30). Indeed, when one is asked to have an MRI in a clinical context it is almost certainly an sMRI. These images are fundamentally different from functional MRI (fMRI) in size, complexity, measurement target, type of measurement, and intended use. While fMRI aims to study brain activity, sMRI reveals anatomical information. This distinction is important as the scientific problems and statistical techniques for fMRI and sMRI analysis differ greatly (35), yet confusion between the two continues to exist in the statistical literature and among reviewers. Despite the enormous practical importance of sMRI, few biostatisticians have made research contributions in this field. This may be due to the subtle aspects of sMRI, the relatively steep learning curve, and the lack of contact between biostatisticians and the scientists working in clinical neuroimaging. Our goal is reduce the price of entry, accelerate learning, and provide the information required to progress from novice to initiated sMRI researcher.
