LAUSR

Abstract Introduction Tumor hypoxia is a centerpiece of disease progression mechanisms such as neoangiogenesis or aggressive hypoxia-resistant malignant cells selection that impacts on radiotherapy strategies. Early identification of regions at risk for recurrence and prognostic-based classification of patients is a necessity to devise tailored therapeutic strategies. We developed an image-based algorithm to spatially map areas of aerobic and anaerobic glycolysis (Glyoxia). Methods 18 F-FDG and 18 F-FMISO PET studies were used in the algorithm to produce DICOM-co-registered representations and maximum intensity projections combined with quantitative analysis of hypoxic volume (HV), hypoxic glycolytic volume (HGV), and anaerobic glycolytic volume (AGV) with CT/MRI co-registration. This was applied to a prospective clinical trial of 10 glioblastoma patients with post-operative, pre-radiotherapy, and early post-radiotherapy 18 F-FDG and 18 F-FMISO PET and MRI studies. Results In the 10 glioblastoma patients (5M:5F; age range 51–69 years), 14/18 18 F-FMISO PET studies showed detectable hypoxia. Seven patients survived to complete post-radiotherapy studies. The patient with the longest overall survival showed non-detectable hypoxia in both pre-radiotherapy and post-radiotherapy 18 F-FMISO PET. The three patients with increased HV, HGV, and AGV volumes after radiotherapy showed 2.8 months mean progression-free interval vs. 5.9 months for the other 4 patients. These parameters correlated at that time point with progression-free interval. Parameters combining hypoxia and glycolytic information (i.e., HGV and AGV) showed more prominent variation than hypoxia-based information alone (HV). Glyoxia-generated images were consistent with disease relapse topology; in particular, one patient had distant relapse anticipated by HV, HGV, and AGV maps. Conclusion Spatial mapping of aerobic and anaerobic glycolysis allows unique information on tumor metabolism and hypoxia to be evaluated with PET, providing a greater understanding of tumor biology and potential response to therapy.