Literature DB >> 23478589

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

Kaya Doyeux1, Sébastien Vauclin, Sébastien Hapdey, Joël Daouk, Agathe Edet-Sanson, Pierre Vera, Isabelle Gardin.   

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.

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Year:  2013        PMID: 23478589     DOI: 10.1097/MNM.0b013e32835fe1f4

Source DB:  PubMed          Journal:  Nucl Med Commun        ISSN: 0143-3636            Impact factor:   1.690


  3 in total

1.  Delineation of lung cancer with FDG PET/CT during radiation therapy.

Authors:  J Ganem; S Thureau; I Gardin; R Modzelewski; S Hapdey; P Vera
Journal:  Radiat Oncol       Date:  2018-11-12       Impact factor: 3.481

2.  Evaluation of an Automatic Classification Algorithm Using Convolutional Neural Networks in Oncological Positron Emission Tomography.

Authors:  Pierre Pinochet; Florian Eude; Stéphanie Becker; Vijay Shah; Ludovic Sibille; Mathieu Nessim Toledano; Romain Modzelewski; Pierre Vera; Pierre Decazes
Journal:  Front Med (Lausanne)       Date:  2021-02-26

3.  Accurate FDG PET tumor segmentation using the peritumoral halo layer method: a study in patients with esophageal squamous cell carcinoma.

Authors:  Sungmin Jun; Jung Gu Park; Youngduk Seo
Journal:  Cancer Imaging       Date:  2018-09-26       Impact factor: 3.909

  3 in total

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