Shahidbeheshti university of Medical Sciences
Shahid Beheshti University of Medical Sciences
shahid beheshti university of medical sciences
Quantitative MR Imaging and Spectroscopy Group (QMISG), Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences
Shahid Beheshti University of Medical sciences
Department of Pathology, Shahid Beheshti University of Medical Sciences
Todays, definitive differential diagnosis of glioblastoma GBM) from cerebral lymphoma (CL) needs surgical operations which is highly invasive. Then, MR imaging methods could be of diagnostic choice if they have proper sensitivity and specificity for distinguishing tumor types. The aim of the current study is to investigate the potency of FOH features in differential diagnosis of GBM tumors from cerebral lymphoma.
Materials and Methods:
By preoperative MRimaging of patient with diagnosis of GBM and cerebral lymphoma, apparent diffusion coefficient (ADC) maps obtained and calculated from region of interest (ROI) in three different regions: 1. Tumor lesion itself (82 patients); 2. Area with enhancement and 3. Peritumoral Edema regions (47patients). FOH were analyzed statistically using Mann-Whitney or independent t-test for meaningfulness and Receiver-operator characteristic (ROC) curves plotted for determination of area under the curve (AUC), sensitivity (SE) and specificity (SP) of FOH in discrimination of GBM form cerebral lymphoma.
FOH were Maximum (Max), Mean, Median (MED), Minimum(Min), Normalized Mean, Standard Deviation, Third Moment, Uniformity (UNF), Entropy, Kurtosis, 25, 75 and 95 Percentiles of ADCs. Meaningful FOH were Mean, Max and Median in tumor group and enhanced area in addition to Smoothness, Uniformity and Entropy (P<0.05; CI=0.95). In the group peritumoral Edema, all FOH were significant between GBM and cerebral lymphoma except Max, Min, Smoothness, Uniformity and Kurtosis. Most meaningful variables had significant values with higher than 50 to 95 percent sensitivity or specificity for GBM discrimination from cerebral lymphoma.
differential diagnosis between GBM and cerebral lymphoma is possible with some FOH and using presented cut-off values. Radiographic methods are not as invasive as surgical pathology methods (SPMs); then, we propose FOH evaluations as the proper biomarkers instead SPMs. FOH will help neurologists and surgeons for desiring treatment or operation. Anyway, our presented information needs verification throughout other centers in the world and by other researchers.