title: On the feasibility of automatic detection of range deviations from in-beam PET data.
abstract: In-beam PET is a clinically proven method for monitoring ion beam cancer treatment. The objective is predominantly the verification of the range of the primary particles. Due to different processes leading to dose and activity, evaluation is done by comparing measured data to simulated. Up to now, the comparison is performed by well-trained observers (clinicians, physicists). This process is very time consuming and low in reproducibility. However, an automatic method is desirable. A one-dimensional algorithm for range comparison has been enhanced and extended to three dimensions. System-inherent uncertainties are handled by means of a statistical approach. To test the method, a set of data was prepared. Distributions of β(+)-activity calculated from treatment plans were compared to measurements performed in the framework of the German Heavy Ion Tumor Therapy Project at GSI Helmholtz Centre for Heavy Ion Research, Darmstadt, Germany. Artificial range deviations in the simulations served as test objects for the algorithm. Range modifications of different depth (4, 6 and 10 mm water equivalent path length) can be detected. Even though the sensitivity and specificity of a visual evaluation are higher, the method is feasible as the basis for the selection of patients from the data pool for retrospective evaluation of treatment and treatment plans and correlation with follow-up data. Furthermore, it can be used for the development of an assistance tool for a clinical application.
authors.affiliation: OncoRay-National Center for Radiation Research in Oncology, Medical Faculty Carl Gustav Carus, TU Dresden, Fetscherstrasse 74, Dresden 01307, Germany. stephan.helmbrecht@oncoray.de
authors.forename: S
authors.initials: S
authors.lastname: Helmbrecht
authors.forename: A
authors.initials: A
authors.lastname: Santiago
authors.forename: W
authors.initials: W
authors.lastname: Enghardt
authors.forename: P
authors.initials: P
authors.lastname: Kuess
authors.forename: F
authors.initials: F
authors.lastname: Fiedler
mesh_terms: D000465:Algorithms; D001331:Automation; D003198:Computer Simulation; D006257:Head / Q000000981:diagnostic imaging / Q000473:pathology; D006801:Humans; D007477:Ions; D015233:Models, Statistical; D009010:Monte Carlo Method; D009369:Neoplasms / Q000532:radiotherapy*; D049268:Positron-Emission Tomography / Q000379:methods*; D011829:Radiation Dosage; D011874:Radiometry / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods
chemical_list: D007477:Ions