Glioma Glycolysis, and Informed PET Interpretation: Metabolic Activity Diffusion Imaging (MADI) Tissue Cell Density

Motivation: Metabolic imaging generally employs minimally invasive radio-tracers (PET) or nuclear magnetic‑tracers (MRSI). Besides sub-optimal spatial resolution, these also suffer because tracer-bearing molecule compartmentalization is not present in the imaging signal. Goal(s): We wish to address these limitations. Approach: We compared completely non-invasive, relatively high-resolution MADI with routine 18FDG-PET in a rat brain glioma model. Results: The MADI kioV parameter outperforms PET SUVmax in discriminating these tumors and, with PET SUVmax, reveals a more glycolytic metabolism. Furthermore, the SUVmax biomarker is de-confounded with the independent MADI‑estimated tissue cell (number) density (ρ) factor. In this model, SUVmax is ρ-dominated. Impact: MADI is compatible with any MRI instrument, and shows promise for improved tumor detection, improved metabolic insights, and informing interpretation of other modality biomarkers. MADI mapping investigations can lead to deeper insights into in vivo pathology metabolism.