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Nuclear Medicine Communications:
doi: 10.1097/MNM.0b013e32835fe1f4
Original Articles

Reproducibility of the adaptive thresholding calibration procedure for the delineation of 18F-FDG-PET-positive lesions

Doyeux, Kayaa,c; Vauclin, Sébastiena,c; Hapdey, Sébastiena,b; Daouk, Joëld,e; Edet-Sanson, Agathea,b; Vera, Pierrea,b; Gardin, Isabellea,b

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Abstract

Objective: The aim of the study was to evaluate the robustness of the calibration procedure against the counting statistics and lesion volumes when using an adaptive thresholding method for the delineation of 2-[18F]fluoro-2-deoxyglucose (18F-FDG)-PET-positive tissue.

Materials and methods: Three data sets obtained from physical and simulated images of a phantom containing hot spheres of known volume and contrast were used to study the robustness of the calibration procedure against the counting statistics and range of volumes and contrasts for a given PET model. The mathematical expression of the adaptive thresholding method used corresponds to a linear relationship between the optimal threshold value and the inverse of the local contrast. Robustness was evaluated by testing whether the slopes and intercepts of the linear expression found under two experimental conditions were significantly different (P<0.05).

Results: It was found that the calibration step was not sensitive to the PET device for the studied PET model, nor to the counting statistics for a signal-to-noise ratio higher than 5.7. No statistical difference was found in the calibration step when using a wide range of volumes (0.2–200 ml) and contrasts (2.0–20.6) or more restricted ones (0.43–97.3 ml and 2.0–7.7, respectively). Therefore, a calibration procedure using limited experimental conditions can be applied to a wider range of volumes and contrasts.

Conclusion: These results show that the manufacturer could propose simulated or experimental raw data corresponding to a given PET model with high counting statistics, allowing each clinical center to reconstruct calibration images according to the algorithm parameters used in the clinic.

© 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins

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