The clinical perspective of large scale projects: a case study of multiparametric MR imaging of pediatric brain tumors.
Current developments in medical information technologies provide the clinical researcher with overwhelming amounts of data that need to be retrieved, organized, analyzed, and shared using secure, efficient, and robust protocols. The development of a local research database can provide an infrastructure for improved data management and detailed data analysis. For example, a pediatric brain tumor database of magnetic resonance imaging data, including conventional MRI imaging, hemodynamic MRI, diffusion weighted MRI and MR spectroscopic imaging, combined with neuropathological and neurological evaluation data, will significantly enhance the assessment and treatment of pediatric brain tumor patients. Furthermore, a negotiation system by which different clinical research facilities can share and combine data will permit re-analyses and meta-analyses of large data arrays that are beyond the focus or time constraints of the original researchers. Such a system will greatly enhance the utility of different data sets to a wide array of scientists. At present, efforts to organize medical data locally and between different sites is limited by diversity, interoperability, security, and accountability difficulties.
Astrakas
L
L
NMR Surgical Laboratory, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, 51 Blossom Street, Boston, MA 02114, USA.
Ye
Song
S
Zarifi
M
M
Makedon
F
F
Tzika
A Aria
AA
D001932:Brain Neoplasms / Q000473:pathology*; D002648:Child; D016208:Databases, Factual; D006801:Humans; D016247:Information Storage and Retrieval; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy