Ioannis Tsougos

TL;DR: 1H-MRS and dynamic susceptibility measurements in the peritumoral regions may definitely aid in the differentiation of glioblastomas and solitary metastases and the quantification of the diffusion properties in the intratumoral region is independent of the ROI size.

TL;DR: The present work reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

TL;DR: SPECT and PET have proposed to serve as biomarkers in recently revised diagnostic clinical criteria for the early diagnosis of AD and the prediction of progression to AD in mild cognitive impairment (MCI) subjects.

TL;DR: In conclusion, machine learning techniques may be used as an adjunctive diagnostic tool, which can be implemented into the clinical routine to optimize decision making.

TL;DR: Results demonstrate that quantitative analysis of phenotypic characteristics, based on advanced multiparametric MR neuroimaging data and texture features, utilizing state-of-the-art radiomic analysis methods, can significantly contribute to the pre-treatment glioma grade differentiation.