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Abstract #0052

Cell-Specific Mapping of MR Spectroscopic Signatures: A Pilot Study in a Murine Glioma Model

Yizun Wang1,2, Urbi Saha3, Marina Milad4, Edward J Roy3,5, Andrew M Smith1,5, and Fan Lam1,2,5,6
1Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 3Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 4Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 5Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 6Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Synopsis

Keywords: Spectroscopy, Spectroscopy

Motivation: Effective monitoring of tumor progression and therapeutic efficacy should benefit from new in vivo imaging capability to resolve cell-specific contributions at tissue level.

Goal(s): To develop a new MRSI-based approach to resolve tumor cell-specific components at individual imaging voxels leveraging the spectral dimensions.

Approach: We proposed a multiscale experimental and computational MRSI framework that learns cell-specific spectroscopic signatures from glioma cell lines and resolves intravoxel nontumor and tumor-specific components in vivo using the learned signatures.

Results: Results from cellular mixtures and glioma-bearing mice demonstrated the potential of our method. Time-dependent, spatially-resolved tumor cell maps can be obtained, showing tumor growth in vivo.

Impact: The proposed approach marks a potential new paradigm to map cellular complexity at tissue level leveraging additional imaging dimensions and machine learning. It holds the promise to provide new tools for tumor grading, progression monitoring and treatment assessment.

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Keywords