Abstract #1694

Differentiating lymphoma from grade-IV glioma using susceptibility weighted imaging based texture feature at 3T MRI

Rupsa Bhattacharjee^1,2, Rakesh Kumar Gupta³, Rana Patir⁴, Sandeep Vaishya⁴, Sunita Ahlawat⁴, and Anup Singh^1,5

¹Center for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, ²Philips Health Systems, Philips India Limited, Gurugram, India, ³Department of Radiology, Fortis Memorial Research Institute, Gurugram, India, ⁴Department of Neurosurgery, Fortis Memorial research Institute, Gurugram, India, ⁵Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, India

No standalone method is yet reported to differentiate PCNSL and grade-IV glioma with highest accuracy and diagnostic confidence. Imaging based differentiation between these two types has been a challenging problem. Objective of this study is to evaluate performance of texture-based features of SWI in improved differentiation of PCNSL from grade-IV gliomas. Proposed approach based upon texture feature-extraction from segmented SWI lesion, enabled automatic classification of tumors into primary central nervous system lymphoma and grade-IV glioma cases. One of the texture feature, Contrast, provided highest AUC along with high sensitivity and specificity. This classification might improve diagnosis and grading of tumors.

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