Abstract
OBJECTIVE: The tumour-to-normal ratio (T/N) is a representative index reflecting brain tumour activity by (18)F-fluorodeoxyglucose (FDG) and (11)C-methionine (MET) PET. We proposed a new automated method of calculating the normal reference value (N-value) for use as the denomination of T/N. This method uses voxel-based analysis of FDG- and MET-PET images. We compared the results of this method with those of the standard region-of-interest (ROI) method. METHODS: Data sets were obtained from 32 patients with newly diagnosed glioma and 13 patients with recurrent brain tumour. Our methods were as follows: (1) FDG-PET and MET-PET images were co-registered. (2) The areas where the FDG uptake was higher than a set threshold were selected. (3) For the corresponding areas of MET-PET images, mode and mean voxel values were calculated as tentative MET N-values. (4) Applying the same coordinates to FDG-PET, the voxel values were averaged and used as tentative FDG N-values. (5) The threshold of FDG-PET and whether to use the mode or the mean voxel values were computationally optimized using learning data sets. (6) Applying the optimal threshold and either the mode or mean, N-values of FDG and MET were finally determined. RESULTS: N-values determined by our automated method showed excellent agreement with those determined by a manual ROI method (ICC(2,1) > 0.78). These values were significantly correlated with mean manual N-values (p < 0.001). CONCLUSIONS: Our new method shows sufficiently good agreement with the standard method and can provide a more objective metabolic index.