TY  - JOUR
AU  - Handrack, Josefine
AU  - Bangert, Mark
AU  - Möhler, Christian
AU  - Bostel, Tilman
AU  - Greilich, Klaus-Steffen
TI  - Towards a generalised development of synthetic CT images and assessment of their dosimetric accuracy.
JO  - Acta oncologica
VL  - 59
IS  - 2
SN  - 0001-6926
CY  - Abingdon
PB  - Taylor & Francis Group
M1  - DKFZ-2019-02554
SP  - 180-187
PY  - 2020
N1  - 2020 Feb;59(2):180-187.#EA:E040#LA:E040#
AB  - Background: The interest in generating 'synthetic computed tomography (CT) images' from magnetic resonance (MR) images has been increasing over the past years due to advances in MR guidance for radiotherapy. A variety of methods for synthetic CT creation have been developed, from simple bulk density assignment to complex machine learning algorithms.Material and methods: In this study, we present a general method to determine simplistic synthetic CTs and evaluate them according to their dosimetric accuracy. It separates the requirements on the MR image and the associated calculation effort to generate a synthetic CT. To evaluate the significance of the dosimetric accuracy under realistic conditions, clinically common uncertainties including position shifts and Hounsfield lookup table (HLUT) errors were simulated. To illustrate our approach, we first translated CT images from a test set of six pelvic cancer patients to relative electron density (ED) via a clinical HLUT. For each patient, seven simplified ED images (simED) were generated at different levels of complexity, ranging from one to four tissue classes. Then, dose distributions optimised on the reference ED image and the simEDs were compared to each other in terms of gamma pass rates (2 mm/2
LB  - PUB:(DE-HGF)16
C6  - pmid:31694437
DO  - DOI:10.1080/0284186X.2019.1684558
UR  - https://inrepo02.dkfz.de/record/147498
ER  -