title: Impact of consensus contours from multiple PET segmentation methods on the accuracy of functional volume delineation.
abstract: OBJECTIVE
  The aim of this study was to evaluate the impact of consensus algorithms on segmentation results when applied to clinical PET images. In particular, whether the use of the majority vote or STAPLE algorithm could improve the accuracy and reproducibility of the segmentation provided by the combination of three semiautomatic segmentation algorithms was investigated.
  
  
  METHODS
  Three published segmentation methods (contrast-oriented, possibility theory and adaptive thresholding) and two consensus algorithms (majority vote and STAPLE) were implemented in a single software platform (Artiview®). Four clinical datasets including different locations (thorax, breast, abdomen) or pathologies (primary NSCLC tumours, metastasis, lymphoma) were used to evaluate accuracy and reproducibility of the consensus approach in comparison with pathology as the ground truth or CT as a ground truth surrogate.
  
  
  RESULTS
  Variability in the performance of the individual segmentation algorithms for lesions of different tumour entities reflected the variability in PET images in terms of resolution, contrast and noise. Independent of location and pathology of the lesion, however, the consensus method resulted in improved accuracy in volume segmentation compared with the worst-performing individual method in the majority of cases and was close to the best-performing method in many cases. In addition, the implementation revealed high reproducibility in the segmentation results with small changes in the respective starting conditions. There were no significant differences in the results with the STAPLE algorithm and the majority vote algorithm.
  
  
  CONCLUSIONS
  This study showed that combining different PET segmentation methods by the use of a consensus algorithm offers robustness against the variable performance of individual segmentation methods and this approach would therefore be useful in radiation oncology. It might also be relevant for other scenarios such as the merging of expert recommendations in clinical routine and trials or the multiobserver generation of contours for standardization of automatic contouring.
authors.affiliation: Department of Nuclear Medicine, Saarland University Medical Centre, 66421, Homburg, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Schaefer
authors.affiliation: University of Lille, Inserm, CHU Lille, U1189 - ONCO-THAI - Image Assisted Laser Therapy for Oncology, F-59000, Lille, France. m-vermandel@chru-lille.fr.|Nuclear Medicine Department, CHU Lille, F-59000, Lille, France. m-vermandel@chru-lille.fr.
authors.forename: M
authors.initials: M
authors.lastname: Vermandel
authors.affiliation: Nuclear Medicine Department, CHU Lille, F-59000, Lille, France.
authors.forename: C
authors.initials: C
authors.lastname: Baillet
authors.affiliation: University of Lille, Inserm, CHU Lille, U1189 - ONCO-THAI - Image Assisted Laser Therapy for Oncology, F-59000, Lille, France.
authors.forename: A S
authors.initials: AS
authors.lastname: Dewalle-Vignion
authors.affiliation: Centre Henri-Becquerel and LITIS EA4108, 76000, Rouen, France.
authors.forename: R
authors.initials: R
authors.lastname: Modzelewski
authors.affiliation: Centre Henri-Becquerel and LITIS EA4108, 76000, Rouen, France.
authors.forename: P
authors.initials: P
authors.lastname: Vera
authors.affiliation: Research and Innovation Department, AQUILAB, 59120, Loos Les Lille, France.
authors.forename: L
authors.initials: L
authors.lastname: Massoptier
authors.affiliation: Research and Innovation Department, AQUILAB, 59120, Loos Les Lille, France.
authors.forename: C
authors.initials: C
authors.lastname: Parcq
authors.affiliation: Research and Innovation Department, AQUILAB, 59120, Loos Les Lille, France.
authors.forename: D
authors.initials: D
authors.lastname: Gibon
authors.affiliation: Department for Radiation Oncology, University Medical Center Freiburg, Freiburg, Germany.|German Cancer Consortium (DKTK) Freiburg and German Cancer Research Center (DKFZ), Heidelberg, Germany.
authors.forename: T
authors.initials: T
authors.lastname: Fechter
authors.affiliation: Department of Nuclear Medicine, University Medical Center Freiburg, Freiburg, Germany.
authors.forename: U
authors.initials: U
authors.lastname: Nemer
authors.affiliation: Centre Henri-Becquerel and LITIS EA4108, 76000, Rouen, France.
authors.forename: I
authors.initials: I
authors.lastname: Gardin
authors.affiliation: Department for Radiation Oncology, University Medical Center Freiburg, Freiburg, Germany.|German Cancer Consortium (DKTK) Freiburg and German Cancer Research Center (DKFZ), Heidelberg, Germany.
authors.forename: U
authors.initials: U
authors.lastname: Nestle
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000592:standards; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008223:Lymphoma / Q000000981:diagnostic imaging*; D008297:Male; D049268:Positron-Emission Tomography; D019275:Radiopharmaceuticals; D012680:Sensitivity and Specificity
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: 18F-FDG PET; Consensus algorithms; Image segmentation; PET image segmentation; Radiation oncology; STAPLE