title: Image change detection using paradoxical theory for patient follow-up quantitation and therapy assessment.
abstract: In clinical oncology, positron emission tomography (PET) imaging can be used to assess therapeutic response by quantifying the evolution of semi-quantitative values such as standardized uptake value, early during treatment or after treatment. Current guidelines do not include metabolically active tumor volume (MATV) measurements and derived parameters such as total lesion glycolysis (TLG) to characterize the response to the treatment. To achieve automatic MATV variation estimation during treatment, we propose an approach based on the change detection principle using the recent paradoxical theory, which models imprecision, uncertainty, and conflict between sources. It was applied here simultaneously to pre- and post-treatment PET scans. The proposed method was applied to both simulated and clinical datasets, and its performance was compared to adaptive thresholding applied separately on pre- and post-treatment PET scans. On simulated datasets, the adaptive threshold was associated with significantly higher classification errors than the developed approach. On clinical datasets, the proposed method led to results more consistent with the known partial responder status of these patients. The method requires accurate rigid registration of both scans which can be obtained only in specific body regions and does not explicitly model uptake heterogeneity. In further investigations, the change detection of intra-MATV tracer uptake heterogeneity will be developed by incorporating textural features into the proposed approach.
authors.affiliation: LaTIM, INSERM, UMR1101, 29609 Brest, France. david.simon@ univ-brest.fr
authors.forename: Simon
authors.initials: S
authors.lastname: David
authors.forename: Dimitris
authors.initials: D
authors.lastname: Visvikis
authors.forename: Gwénolé
authors.initials: G
authors.lastname: Quellec
authors.forename: Catherine Cheze
authors.initials: CC
authors.lastname: Le Rest
authors.forename: Philippe
authors.initials: P
authors.lastname: Fernandez
authors.forename: Michèle
authors.initials: M
authors.lastname: Allard
authors.forename: Christian
authors.initials: C
authors.lastname: Roux
authors.forename: Mathieu
authors.initials: M
authors.lastname: Hatt
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016208:Databases, Factual; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008495:Medical Oncology / Q000379:methods; D009369:Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000473:pathology / Q000628:therapy; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D047368:Tumor Burden
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18