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©2014 Baishideng Publishing Group Co., Limited. All rights reserved.
Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques
Evangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Kyriaki Theodorou, Constastine Kappas, Ioannis Tsougos, Medical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece
Efthychia Kapsalaki, Department of Radiology, University Hospital of Larissa, Biopolis, 41110 Larissa, Greece
Author contributions: Tsolaki E and Tsougos I designed the research; Tsolaki E, Kousi E and Svolos P performed the research; Tsolaki E, Kousi E and Tsougos I wrote the paper; Kapsalaki E, Theodorou K and Kappas C performed a critical review and data analysis.
Correspondence to: Ioannis Tsougos, MSc, PhD, Assistant Professor in Medical Physics Department, University of Thessaly, Panepistimiou 2, Biopolis, 41110 Larissa, Greece. tsougos@med.uth.gr
Telephone: +30-241-3501863 Fax: +30-241-3501863
Received: November 12, 2013
Revised: January 23, 2014
Accepted: March 17, 2014
Published online: April 28, 2014
Revised: January 23, 2014
Accepted: March 17, 2014
Published online: April 28, 2014
Core Tip
Core tip: The quantification of the imaging profile of brain neoplasms by combining conventional magnetic resonance imaging and advanced imaging techniques introduces critical underlying pathophysiological information which seems to be the key to success. Thus, it is evident that the pursuit of this goal should be oriented towards the development of decision support software that will utilize large amounts of clinical data with extremely significant diagnostic value which often remain unexploited, hence resulting in a more valid and precise method of differential diagnosis and the selection of the most successful treatment scheme.