TY  - JOUR
AU  - Thummerer, Adrian
AU  - Oria, Carmen Seller
AU  - Zaffino, Paolo
AU  - Visser, Sabine
AU  - Meijers, Arturs
AU  - Marmitt, Gabriel Guterres
AU  - Wijsman, Robin
AU  - Seco, Joao
AU  - Langendijk, Johannes Albertus
AU  - Knopf, Antje Christin
AU  - Spadea, Maria Francesca
AU  - Both, Stefan
TI  - Deep learning based 4D-synthetic CTs from sparse-view CBCTs for dose calculations in adaptive proton therapy.
JO  - Medical physics
VL  - 49
IS  - 11
SN  - 0094-2405
CY  - College Park, Md.
PB  - AAPM
M1  - DKFZ-2022-01935
SP  - 6824-6839
PY  - 2022
N1  - 2022 Nov;49(11):6824-6839
AB  - Time resolved 4D cone beam computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose calculations. Deep learning can be used to correct CT numbers and generate synthetic CTs which can enable CBCT-based proton dose calculations.In this work, sparse view 4D-CBCTs were converted into 4D synthetic CTs (4D-sCT) utilizing a deep convolutional neural network (DCNN). 4D-sCTs were evaluated in terms of image quality and dosimetric accuracy to determine if accurate proton dose calculations for adaptive proton therapy workflows of lung cancer patients are feasible.A dataset of 45 thoracic cancer patients was utilized to train and evaluate a DCNN to generate 4D-sCTs, based on sparse view 4D-CBCTs reconstructed from projections acquired with a 3D acquisition protocol. Mean absolute error (MAE) and mean error (ME) were used as metrics to evaluate image quality of single phases and average 4D-sCTs against 4D-CTs acquired on the same day. The dosimetric accuracy was checked globally (gamma analysis) and locally for target volumes and organs at risk (lung, heart, and esophagus). Furthermore, 4D-sCTs were also compared to 3D-sCTs. To evaluate CT number accuracy, proton radiography simulations in 4D-sCT and 4D-CTs were compared in terms of range errors. The clinical suitability of 4D-sCTs was demonstrated by performing a 4D dose reconstruction using patient specific treatment delivery log-files and breathing signals.4D-sCTs resulted in average MAEs of 48.1 ± 6.5 HU (single phase) and 37.7 ± 6.2 HU (average). The global dosimetric evaluation showed gamma pass ratios of 92.3 ± 3.2 
KW  - 4D imaging (Other)
KW  - adaptive proton therapy (Other)
KW  - deep learning (Other)
KW  - synthetic CT (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:35982630
DO  - DOI:10.1002/mp.15930
UR  - https://inrepo02.dkfz.de/record/181308
ER  -