title: Automatic delineation of tumor volumes by co-segmentation of combined PET/MR data.
abstract: Combined PET/MRI may be highly beneficial for radiotherapy treatment planning in terms of tumor delineation and characterization. To standardize tumor volume delineation, an automatic algorithm for the co-segmentation of head and neck (HN) tumors based on PET/MR data was developed. Ten HN patient datasets acquired in a combined PET/MR system were available for this study. The proposed algorithm uses both the anatomical T2-weighted MR and FDG-PET data. For both imaging modalities tumor probability maps were derived, assigning each voxel a probability of being cancerous based on its signal intensity. A combination of these maps was subsequently segmented using a threshold level set algorithm. To validate the method, tumor delineations from three radiation oncologists were available. Inter-observer variabilities and variabilities between the algorithm and each observer were quantified by means of the Dice similarity index and a distance measure. Inter-observer variabilities and variabilities between observers and algorithm were found to be comparable, suggesting that the proposed algorithm is adequate for PET/MR co-segmentation. Moreover, taking into account combined PET/MR data resulted in more consistent tumor delineations compared to MR information only.
authors.affiliation: Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, 72076 Tübingen, Germany.
authors.forename: S
authors.initials: S
authors.lastname: Leibfarth
authors.forename: F
authors.initials: F
authors.lastname: Eckert
authors.forename: S
authors.initials: S
authors.lastname: Welz
authors.forename: C
authors.initials: C
authors.lastname: Siegel
authors.forename: H
authors.initials: H
authors.lastname: Schmidt
authors.forename: N
authors.initials: N
authors.lastname: Schwenzer
authors.forename: D
authors.initials: D
authors.lastname: Zips
authors.forename: D
authors.initials: D
authors.lastname: Thorwarth
mesh_terms: D000465:Algorithms; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015588:Observer Variation; D049268:Positron-Emission Tomography / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods; D047368:Tumor Burden