Evaluation of apparent diffusion coefficient values in discriminating concurrent differential diagnosis of Glioblastoma, lymphoma, and metastatic tumors

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 ۵۷ GBM, ۲۵ LYM, and ۲۵ 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 ۱۵.۸ 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 v۲.۱۳.۱ with the DiagTest۳grp package was used. The confidence interval level was ۹۵% for significant results. Diagnostic accuracy of ADC in the differentiation of mentioned three groups was performed using ROC surface.Results: ADCMin, ADC۷۵ and ADC۹۵ Percentile values in TUMOR groups of ROI, ADCMaximum, ADCMin, ADCMean, ADCMedian , ADCUniformity and ADCEntropy  in ENHANCED  and ADC۲۵, ADC۷۵, ADC۹۵ Percentiles, ADCMean , ADCNormal Mean , ADCMedian, ADCEntropy, ADCThird Moment and ADCStandardDeviation in EDEM had significant VUS values results among GBM, LYM and MTTs .Conclusion: VUS analysis is a helpful statistical method for categorizing types of brain tumors. Using the application of FOHs and proposed cut-off points for them by the VUS analysis, the differentiation of more than two types of brain tumors would be possible, concurrently. This will help neurologists and neurosurgeons to plan their treatment and surgery or monitor the status of patients’ therapeutic needs.

Keywords:

Apparent diffusion coefficient , Glioblastoma , Lymphoma , Magnetic resonance imaging , ROC surface (VUS)