Objectives: Tumor volume segmentation based on PET is of great interest in radiotherapy treatment planning. Currently most algorithms are based on a threshold which seems to be appropriate in phantom studies with homogeneously filled spheres. In general, tumors can not be considered homogeneous. Therefore we analyzed segmentation methods for inhomogeneous lesions. Methods: 3 different methods were compared: threshold of maximum (M1) or mean (M2) activity uptake in the lesion, and a gradient method based on the Marr-Hildreth operator (M3). The methods were applied to data from 4 phantom measurements using radioactive wax simulating inhomogeneous lesions (40 mm diameter) of different activity distribution. In addition, inhomogeneous lesions of different size (10 – 50 mm diameter) in the lung of a patient were simulated by Monte Carlo methods. Practicability of the algorithms was tested with 10 data sets of patients with solitary lung lesions. Results: In the phantom study lesion volumes determined by of M1 (M2; M3) were 54 (48; 3)% too small in case of higher activity concentrations in the center of the lesion. With lower uptake in the center of the lesion, M3 showed with 20% error only a slightly improved result compared to M1 (26%) and M2 (30%). For homogeneous lesions the results of all three methods were within 3% of the real volume. Similar results were found with the Monte Carlo data: All methods worked well in the homogeneous case, M1 and M2 resulted in underestimation of the volume of up to 77% in inhomogeneous lesions. For M3 this underestimation was much lower with a mean of 13% (range 5-24%). Especially in lesions >20 mm, M3 showed better results. Conclusions: In case of inhomogeneous uptake, current threshold based segmentation methods fail. Gradient based methods are superior in this case.
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Objectives: Tumor volume segmentation based on PET is of great interest in radiotherapy treatment planning. Currently most algorithms are based on a threshold which seems to be appropriate in phantom studies with homogeneously filled spheres. In general, tumors can not be considered homogeneous. Therefore we analyzed segmentation methods for inhomogeneous lesions. Methods: 3 different methods were compared: threshold of maximum (M1) or mean (M2) activity uptake in the lesion, and a gradient m...
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