LORIS: a web-based data management system for multi-center studies

Longitudinal Online Research and Imaging System (LORIS) is a modular and extensible web-based data management system that integrates all aspects of a multi-center study: from heterogeneous data acquisition (imaging, clinical, behavior, and genetics) to storage, processing, and ultimately dissemination. It provides a secure, user-friendly, and streamlined platform to automate the flow of clinical trials and complex multi-center studies. A subject-centric internal organization allows researchers to capture and subsequently extract all information, longitudinal or cross-sectional, from any subset of the study cohort. Extensive error-checking and quality control procedures, security, data management, data querying, and administrative functions provide LORIS with a triple capability (1) continuous project coordination and monitoring of data acquisition (2) data storage/cleaning/querying, (3) interface with arbitrary external data processing “pipelines.” LORIS is a complete solution that has been thoroughly tested through a full 10 year life cycle of a multi-center longitudinal project1 and is now supporting numerous international neurodevelopment and neurodegeneration research projects

Genome-wide association studies of cerebral white matter lesion burden: The CHARGE consortium

White matter hyperintensities (WMH) detectable by magnetic resonance imaging (MRI)are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMH are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth

A Comparative Study of Model-Based Brain MRI Tissue Classification Methods

Abstract. A comparative study of the performance of two different approaches to fully automatic (model-based) brain anatomical MRI tissue classification is presented in this paper. Both simulated and real image data, as well as various subject brain morphologies (young-healthy, elderly, and diseased individuals) were used. The recently proposed “MNI” classification method was found to perform better, and to be more robust, than some of the existing state of the art for this application. Moreover, presented experimental results question the popular assumption that tissue class multi-spectral aMRI intensities have a Normal (Gaussian) distribution.