Evaluation of apparent diffusion coefficient values in discriminating concurrent differential diagnosis of Glioblastoma, lymphoma, and metastatic tumors
Abstract
Introduction
Apparent diffusion coefficient (ADC) statistics can be valuable in distinguishing three types of brain tumors. The aim is to evaluate the capability of volume under the receiver operating characteristic (ROC) surface (VUS) for concurrent differential diagnosis of glioblastoma (GBM), lymphoma (LYM), and metastatic tumor(s) (MTTs) lesions of brain malignancies.
Methods
Investigated Magnetic Resonance Imaging (MRI) included 57 GBM, 25 LYM, and 25 MTT that were pathological diagnoses, after MR imaging. Region of interest (ROI) was taken from tumor regions (TUMOR), enhancement area (ENHANCED), and peritumoral edema (EDEM) regions. ADC maps were obtained after selecting a region of interest, and First-Order Histogram Features (FOHs) were extracted. Statistical analysis was performed by MedCalc version 15.8 for comparison of continuous variables between three groups of lesions and plotting the ROC curves. For VUS and correct classification rates (CCR) calculations the R software v2.13.1 with the DiagTest3grp package was used. The confidence interval level was 95% for significant results. Diagnostic accuracy of ADC in the differentiation of mentioned three groups was performed using ROC surface.
Results
ADCMin, ADC75 and ADC95 Percentile values in TUMOR groups of ROI, ADCMaximum, ADCMin, ADCMean, ADCMedian , ADCUniformity and ADCEntropy in ENHANCED and ADC25, ADC75, ADC95 Percentiles, ADCMean , ADCNormal Mean , ADCMedian, ADCEntropy, ADCThird Moment and ADCStandardDeviation in EDEM had significant VUS values results among GBM, LYM and MTTs .
Conclusion …