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

Doyeux, Kaya; Vauclin, Sébastien; Hapdey, Sébastien; Daouk, Joël; Edet-Sanson, Agathe; Véra, Pierre; Gardin, I.

doi:10.1097/mnm.0b013e32835fe1f4

Cited by 6 publications

(7 citation statements)

References 6 publications

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“…The performance of perPET-RT was compared to several segmentation methods, based on thresholding, applied by a third experienced physician, independently from the consensual delineation used for the gold standard: Fixed SUV-values: 2; 2.5; 3; 3.5; Fixed threshold corresponding to a percentile of the maximum SUV (% of SUV max ): 40, 50, 60, 70%; An adaptive thresholding method, called AOV, where the threshold to be applied corresponds to 1.5 times the mean SUV measured in an aorta volume of 1 cc [ 21 ]; Two adaptive thresholding methods: COA and ADT [ 20 , 22 ]. The two methods were calibrated according to the recommendations respectively from Schaefer et al [ 20 ] and Vauclin et al [ 23 ] for Biograph Sensation 16 Hi-Rez device. …”

Section: Methodsmentioning

confidence: 99%

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

et al. 2018

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ObjectivesTo propose an easily applicable segmentation method (perPET-RT) for delineation of tumour volume during radiotherapy on interim fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with non-small cell lung cancer (NSCLC).Material and methodsSixty-seven patients (51 primary tumours, 60 lymph nodes), from 4 prospective studies, underwent an FDG PET/CT scan during the fifth week of radiation therapy, using different generations of PET/CT. Per-therapeutic PET/CT scans were delineated in consensus by two experienced physicians leading to the gold standard threshold to be applied. The mathematical expression of Thopt, the optimal threshold to be applied as a function of the maximum standard uptake value (SUVmax), was determined. The performance of this method (perPET-RT) was assessed by computing the DICE similarity coefficient (DSC) and was compared with 8 fixed threshold values and 3 adaptive thresholding methods.ResultsThopt verified the following expression: Thopt = A.ln(1/SUVmax) + B where A and B were 2 constants. A and B were independent from the generation of PET/CT, but depended on the type of lesions (primary lung tumours vs. lymph nodes). PerPET-RT showed good to very good agreement in comparison to the gold standard. The mean and standard deviation of DSC value was 0.81 ± 0.13 for lung lesions and 0.78 ± 0.15 for lymph nodes. PerPET-RT showed a significant better agreement than the other segmentation methods (p < 0.001), except for one of the adaptive thresholding method ADT (p = 0.11).ConclusionOn the database used, perPET-RT has proven its reliability and accuracy for tumour delineation on per-therapeutic FDG PET/CT using only SUVmax measurement. This method may be used to delineate tumour volume for dose-escalation planning.Trial registrationNCT01261598, NCT01261585, NCT01576796.

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Section: Methodsmentioning

confidence: 99%

“…However, these methods are not optimal for low contrast or small volumes [ 20 ]. which can be the case on per-therapeutic PET/CT images.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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“…A variety of methods have been used to measure and segment MTV. These include visual segmentation methods (SegVisual), where the region of interest is drawn manually [ 7 , 8 ], fixed SUV threshold methods (SegSUV) [ 3 , 6 ], fixed percentage of SUVmax threshold methods (Seg%) [ 3 , 6 ], adaptive threshold methods (SegAdaptive) [ 6 , 9 ], and gradient methods (SegGradient) [ 6 , 10 , 11 ]. Among these various segmentation approaches, SegSUV or Seg% is widely used to measure MTV because nearly all PET/CT workstations have an auto-segmentation program for fixed threshold methods.…”

Section: Introductionmentioning

confidence: 99%

“…SegAdaptive and SegGradient are known to be more accurate than SegSUV or Seg% [ 6 , 10 , 11 ]. The main principle of SegAdaptive is to adapt the percentage threshold of the phantom or tumor according to signal-to-background ratio [ 6 , 9 , 13 ]. Several optimal regression functions can be obtained by fitting various regression models [ 6 , 9 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…The main principle of SegAdaptive is to adapt the percentage threshold of the phantom or tumor according to signal-to-background ratio [ 6 , 9 , 13 ]. Several optimal regression functions can be obtained by fitting various regression models [ 6 , 9 , 13 , 14 ]. MTV using SegGradient is a method used to detect a large gradient change in radioactivity around the tumor.…”

Section: Introductionmentioning

confidence: 99%

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

2018

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BackgroundIn a previous study, FDG PET tumor segmentation (SegPHL) using the peritumoral halo layer (PHL) was more reliable than fixed threshold methods in patients with thyroid cancer. We performed this study to validate the reliability and accuracy of the PHL method in patients with esophageal squamous cell carcinomas (ESCCs), which can be larger and more heterogeneous than thyroid cancers.MethodsA total of 121 ESCC patients (FDG avid = 85 (70.2%); FDG non-avid = 36 (29.8%)) were enrolled in this study. In FDG avid ESCCs, metabolic tumor length (ML) using SegPHL (MLPHL), fixed SUV 2.5 threshold (ML2.5), and fixed 40% of maximum SUV (SUVmax) (ML40%) were measured. Regression and Bland-Altman analyses were performed to evaluate associations between ML, endoscopic tumor length (EL), and pathologic tumor length (PL). A comparison test was performed to evaluate the absolute difference between ML and PL. Correlation with tumor threshold determined by the PHL method (PHL tumor threshold) and SUVmax was evaluated.ResultsMLPHL, ML2.5, and ML40% correlated well with EL (R2 = 0.6464, 0.5789, 0.3321, respectively; p < 0.001) and PL (R2 = 0.8778, 0.8365, 0.6266, respectively; p < 0.001). However, ML2.5 and ML40% showed significant proportional error with regard to PL; there was no significant error between MLPHL and PL. MLPHL showed the smallest standard deviation on Bland-Altman analyses. The absolute differences between ML and PL were significantly smaller for MLPHL and ML40% than for ML2.5 (p < 0.0001). The PHL tumor threshold showed an inverse correlation with SUVmax (σ = − 0.923, p < 0.0001).ConclusionsSegPHL was more accurate than fixed threshold methods in ESCC. The PHL tumor threshold was adjusted according to SUVmax of ESCC.

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Prognostic value of total tumour volume, adding necrosis to metabolic tumour volume, in advanced or metastatic non-small cell lung cancer treated with first-line pembrolizumab

et al. 2022

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

Abstract: 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.

Cited by 6 publications

References 6 publications

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

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

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

Prognostic value of total tumour volume, adding necrosis to metabolic tumour volume, in advanced or metastatic non-small cell lung cancer treated with first-line pembrolizumab

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