Abstract
Objective: To develop an auto-segmentation method for delineating the biological tumor volume of nasopharyngeal carcinoma from positron emission tomography images. Methods: A phantom consisting of a water tank with fixed background fluorodeoxyglucose [18F-FDG] activity and spheres with diameters ranging from 2.1 to 5 cm with varying activities of FDG were used to simulate tumors of different sizes and FDG uptake. The phantom was scanned with a PET/CT scan at different sphere to background intensity ratios. An optimum fixed percentage threshold (FT) approach and a signal-to-background ratio (SBR) approach were developed to estimate the true size of the spheres from the PET images. Both approaches were further evaluated in patient images for validation. Twenty-two patients with NPC from stage T1 to T4 were included. The PET based biological tumor volumes (BTV) were delineated with both FT (BTVFT) and SBR (BTVSBR) approaches and compared with the gross tumor volume localized from MRI (GTVMR). The mean volumes of BTVFT and BTVSBR were compared and the degree of overlap between GTVMR and both BTVs was evaluated. Paired t-tests were used for statistical analysis. Results: The optimal FT value was 36.5% of maximal intensity, and SBR approach was represented by an inverse linear regression model. The estimated volume of spheres segmented by both approaches shows no significant difference from the true volume of spheres (p > 0.05), but the average absolute errors were smaller from SBR approach than FT approach (p = 0.008). GTVMR was larger than both BTVFT (p = 0.003) and BTVSBR (p SBR with GTVMR is significantly larger than with BTVFT (0.52 and 0.42 respectively, p MR for radiotherapy planning purpose.
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