Purpose: To create a digital, online atlas for organs at risk (OAR) delineation in neuro-oncology based on high-quality computed tomography (Cr) and magnetic resonance (MR) imaging. Methods: CT and 3 Tesla (3T) MR images (slice thickness 1 mm with intravenous contrast agent) were obtained from the same patient and subsequently fused. In addition, a 7T MR without intravenous contrast agent was obtained from a healthy volunteer. Based on discussion between experienced radiation oncologists, the clinically relevant organs at risk (OARs) to be included in the atlas for neuro-oncology were determined, excluding typical head and neck OARs previously published. The draft atlas was delineated by a senior radiation oncologist, 2 residents in radiation oncology, and a senior neuro-radiologist incorporating relevant available literature. The proposed atlas was then critically reviewed and discussed by European radiation oncologists until consensus was reached. Results: The online atlas includes one CT-scan at two different window settings and one MR scan (3T) showing the OARs in axial, coronal and sagittal view. This manuscript presents the three-dimensional descriptions of the fifteen consensus OARs for neuro-oncology. Among these is a new OAR relevant for neuro-cognition, the posterior cerebellum (illustrated on 7T MR images). Conclusion: In order to decrease inter- and intra-observer variability in delineating OARs relevant for neuro-oncology and thus derive consistent dosimetric data, we propose this atlas to be used in photon and particle therapy. The atlas is available online at w.cancerdata.c and will be updated whenever required. (C) 2017 The Authors. Published by Elsevier B.V.


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    Titel :

    The EPTN consensus-based atlas for CT- and MR-based contouring in neuro-oncology


    Erscheinungsdatum :

    2018-07-01


    Anmerkungen:

    Taskforce European Particle 2018 , ' The EPTN consensus-based atlas for CT- and MR-based contouring in neuro-oncology ' , Radiotherapy and Oncology , vol. 128 , no. 1 , pp. 37-43 . https://doi.org/10.1016/j.radonc.2017.12.013



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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