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Abstract #1694

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

Rupsa Bhattacharjee1,2, Rakesh Kumar Gupta3, Rana Patir4, Sandeep Vaishya4, Sunita Ahlawat4, and Anup Singh1,5
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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