TY  - JOUR
AU  - Thummerer, Adrian
AU  - de Jong, Bas A
AU  - Zaffino, Paolo
AU  - Meijers, Arturs
AU  - Marmitt, Gabriel G
AU  - Seco, Joao
AU  - Steenbakkers, Roel J H M
AU  - Langendijk, Johannes A
AU  - Both, Stefan
AU  - Spadea, Maria Francesca
AU  - Knopf, Antje-Christin
TI  - Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.
JO  - Physics in medicine and biology
VL  - 65
IS  - 23
SN  - 1361-6560
CY  - Bristol
PB  - IOP Publ.
M1  - DKFZ-2020-02470
SP  - 235036
PY  - 2020
AB  - CBCT- and MR-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep convolutional neural networks (DCNN). In this study, we compared sCTs based on CBCTs and MRs for head and neck cancer patients in terms of image quality and proton dose calculation accuracy. A dataset of 27 H</td><td width="150">
AB  - N-patients, treated with proton therapy, containing planning CTs, repeat CTs, CBCTs and MRs were used to train two neural networks to convert either CBCTs or MRs into synthetic CTs. Image quality was quantified by calculating mean absolute error (MAE), mean error (ME) and dice similarity coefficient (DSC) for bones. The dose evaluation consisted of a systematic non-clinical analysis and a clinical recalculation of actually used proton treatment plans. Gamma analysis was performed for non-clinical and clinical treatment plans. For clinical treatment plans also dose to targets and organs at risk (OARs) and normal tissue complication probabilities (NTCP) were compared. CBCT-based sCTs resulted in higher image quality with an average MAE of 40±4 HU and a DSC of 0.95, while for MR-based sCTs a MAE of 65±4 HU and a DSC of 0.89 was observed. Also in clinical proton dose calculations, sCTCBCT achieved higher average gamma pass ratios (2
LB  - PUB:(DE-HGF)16
C6  - pmid:33179874
DO  - DOI:10.1088/1361-6560/abb1d6
UR  - https://inrepo02.dkfz.de/record/165913
ER  -