Neuroinformatics in clinical and translational medicine--novel approaches.

This special edition of Neuroinformatics was conceived as a way to highlight the new and rapidly developing field of clinical neuroinformatics. The application of neuroinformatics to the clinical domain encompasses support for clinical trials that use neuroimaging biomarkers as primary or secondary outcome measures, as well as the assembly of patient data into databases, development of tools to analyze these data and their application to addressing clinical translational research and treatment questions. The premise of clinical neuroinformatics is that valuable information can be mined from the vast volume of clinical research and treatment information which is now collected, including diagnostic studies and neuroimaging studies performed for a wide variety of disorders and purposes, if that data could be appropriately transmitted to the scientific community. Since much patient-oriented data are collected in a systematic and standard manner, large databases with deidentification may be an appropriate analytical approach. The strong federal impetus to advance medical informatics is galvanizing efforts to assemble patient-oriented data into such databases, helping to develop solutions to address the critical need for the protection of patient privacy. Rigorous procedures for proper de-identification must be used, since most patient data is sensitive and when initially acquired, completely linked to the patient’s identify; alternatively, robust methods to protect against inadvertent disclosure must be determined. Many areas of research in neuroinformatics critical to advancement of this field ranging from development of robust solutions for multisite data management to calibration of cross-site image acquisition are highlighted. The journal Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. Coverage extends to theory and methodology, including discussions on ontologies or structure of data, modeling approaches, database design, and meta-analyses. Further, there is interest in descriptions of developed databases and software tools, and of the methods for their distribution, massive data sets, and computational simulations of models integrating and organizing complex data (Morse 2008). As part of this overall goal, we would like to highlight the newly developing field of clinical neuroinformatics, that derives from a large volume of medical imaging and other patient data, acquired during both clinical care of patients as well as clinical research studies. Large collections of neurological data from cohorts of healthy and diseased patients are now currently available from publicly shared databases [e.g. EEG databases (https://epilepsy.uni-freiburg.de; Hunter et al. 2005), the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the OASIS databases of structural MRI data (Jack et al. 2008; Weiner et al. 2010; Marcus et al. 2007; 2010)]. However, in many of these databases the data [i.e., brain magnetic resonance imaging (MRI) or computed tomography (CT)] were acquired specifically for particular R. L. Gollub Departments of Psychiatry and Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA