Abstract
Objective
A scheme, named SUV_Shape, for the gross tumor volume (GTV) delineation on positron emission tomography (PET) images was designed by a numerical approximation method, and evaluated during this study.
Methods
Twenty-one vacuous plastic balls of different shapes and sizes, their volumes ranged from 0.56 to 179.50 mL and were confirmed by a BL610 balance (Sartorius, Canada), consisted of four group models. Every group model was filled with a specific activity [18F]-FDG solution (55.1, 38.2, 23.7, and 36.3 kBq/mL) represented tumor, and fixed at the bottom of a barrel which was filled with unlike [18F]-FDG solution (5.4, 6.8, 8.1, and 4.0 kBq/mL, correspondingly) represented the background. The PET data of them were acquired by two-dimensional and three-dimensional mode in a PET/CT scanner (Discovery ST8, GE Healthcare, USA). The volume of each ball was measured by SUV_Shape, and the BL610 balance, labeled as GTVs and GTVt, respectively. Five rabbits implanted VX2 squamous carcinomas were acquired by [18F]-FDG PET/CT. These rabbits were mercy killed within 24 h after PET/CT acquisition. VX2 tumors were surgically removed, and their volumes were measured by SUV_Shape, and caliper, labeled as GTVs and GTVt. The Spearman’s ρ between GTVs and GTVt were done.
Results
The tumor-background ratios in four groups of phantom models were 10.3, 5.6, 2.9, and 9.0, respectively. The relationship between GTVt and GTVs for phantom models was significant (Spearman’s ρ > 0.95, P < 0.01), regardless of the different acquisition modes. Twelve VX2 tumor nodes or masses were measured; their GTVt ranged from 0.11 to 29.26 mL. The relationship between GTVt and GTVs was significant (Spearman’s ρ = 0.893, P < 0.01) for animal tumor models.
Conclusions
The SUV_Shape scheme could delineate tumors based on their radiopharmaceutical-avid PET images.
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This work was supported by the National Natural Science Foundation of China [Grant 30800274].
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Chen, Y., Chen, X., Li, F. et al. Delineation gross tumor volume based on positron emission tomography images by a numerical approximation method. Ann Nucl Med 28, 980–985 (2014). https://doi.org/10.1007/s12149-014-0894-x
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DOI: https://doi.org/10.1007/s12149-014-0894-x