Abstract #2811

The Role of Heterogeneity Analysis for Differential Diagnosis in Diffusion-Weighted Images of Meningioma Brain Tumors

Mojtaba Safari¹, Anahita Fathi Kazerooni^1,2, Maryam Babaie³, Mahnaz Nabil⁴, Mahsa Rostamie¹, Parvin Ghavami¹, Morteza Saneie Taheri³, and Hamidreza Saligheh Rad^1,2

¹Quantitative MR Imaging and Spectroscopy Group (QMISG), Research Center for Molecular and Cellular Imaging (RCMCI), Tehran University of Medical Sciences, Tehran, Iran, ²Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran, ³Radiology Department, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran, ⁴Department of Mathematics, Islamic Azad University, Qazvin Branch, Qazvin, Iran

Meningioma brain tumors constitute the majority of adult primary brain tumors, in which the role of apparent diffusion coefficient (ADC) is controversial. We hypothesize that analysis of the heterogeneity within a tumorous ecological region can reveal biological tissue properties, which could further assist decision making about the optimum patient-specific treatment strategy. In the present work, we propose an automated computer-aided diagnosis method for phenotyping meningioma brain tumors, based on features representing spatial heterogeneity in ADC-maps, with classification accuracy of 85.1%. In conclusion, it is demonstrated that heterogeneity of meningioma brain tumors can be a potential discriminating biomarker of tumor malignancy.

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