Abstract #3931

Multi-parametric imaging based differentiation of primary CNS lymphoma from Glioblastoma using T1-Perfusion, Diffusion and Susceptibility-weighted MR Imaging

Pradeep Kumar Gupta¹, Jitender Saini², Ashish Awasthi³, Chandra M Pandey ⁴, Shreelekha Mohapatra¹, Anup Singh⁵, Rana Patir⁶, Sunita Ahlawat⁷, Manish Beniwal⁸, Anita Mahadevan ⁹, and Rakesh Kumar Gupta¹

¹Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, India, ²Department of Neuroimaging & Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India, ³Indian Institute of Public Health, Gandhinagar, India, ⁴Biostatistics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, ⁵Center for Biomedical Engineering, Indian Institute of Technology Delhi, Delhi, India, ⁶Department of Neurosurgery, Fortis Memorial Research Institute, Gurgaon, India, ⁷SRL Diagnostics, Fortis Memorial Research Institute, Gurgaon, India, ⁸Department of Neurosurgery, National Institute of Mental Health and Neurosciences, Bangalore, India, ⁹Neuropathology, National Institute of Mental Health and Neurosciences, Bangalore, India

Glioblastoma and primary CNS lymphoma (PCNSL) need differentiation on pre operative imaging as management strategies for these two pathologies are diverse. Due to the presence of atypical imaging findings in a significant number of cases, it becomes difficult to differentiate these two pathologies on conventional MRI. We utilized multi-parametric imaging methods (T1-perfusion, DWI, and SWI) for possible differentiation of these two entities. In linear discriminant analysis using various imaging parameters we achieved 84% accuracy with AUC 90.14%. We conclude that multi-parametric imaging may prove to be useful in accurate preoperative discrimination of these two pathologies.

This abstract and the presentation materials are available to members only; a login is required.

Join Here