%0 Conference Proceedings
%A Yawson, Ama Katseena
%A Paul, Katharina Maria
%A Beyer, Cedric
%A Dorsch, Stefan
%A Klüter, Sebastian
%A Welzel, Thomas
%A Seidensaal, Katharina
%A Debus, Jürgen
%A Jäkel, Oliver
%A Giske, Kristina
%Y Waiter, Gordon
%Y Lambrou, Tryphon
%Y Leontidis, Georgios
%Y Oren, Nir
%Y Morris, Teresa
%Y Gordon, Sharon
%T Pseudo-SPR Map Generation from MRI Using U-Net Architecture for Ion Beam Therapy Application
%V 14122
%C Cham
%I Springer Nature Switzerland
%M DKFZ-2023-02516
%@ 978-3-031-48592-3
%B Lecture Notes in Computer Science
%D 2024
%Z   Medical Image Understanding and Analysis: 257–267
%X Stopping power ratio (SPR) maps are needed for dose deposition calculations and are typically estimated from single energy CT (SECT) in clinical routine. SECT-based SPR conversion leads to large variability due to the one-to-one relationship assumed by the conversion method. Dual-energy CT (DECT) involving the acquisition of two energy spectra captures both material-specific information and tissue characterization which is essential for an accurate SPR map conversion. The goal of this study is to train a U-Net architecture to generate pseudo-SPR map from MRI (Dixon) using a DECT-converted SPR map. The model performance was validated using Head </td><td width="150">
%X  Neck cohort of 16 patients with paired MRI and SPR maps. The proposed solution achieved a mean absolute error (MAE) and peak-signal-to-noise-ratio (PSNR) of 19.41 ± 8.67 HU and 58.76 ± 2.17 dB respectively for all test cases. From observation, the sequential incorporation of different Dixon MRI images such as fat-suppressed and water-suppressed yielded an accurate pseudo-SPR map which is comparable to its corresponding target SPR map. Furthermore, bone delineation integrated as additional channel to Dixon MRI sequence demonstrated an enhanced bone identification on predicted pseudo-SPR map. As future direction, we would like to extend this approach to a clinical SPR map which will enable dosimetric analysis of clinical target volume (CTV) to be possible in treatment planning application for ion beam therapy.
%B 27th Conference on Medical Image Understanding and Analysis 2023
%C 19 Jul 2023 - 21 Jul 2023, Aberdeeen (UK)
Y2 19 Jul 2023 - 21 Jul 2023
M2 Aberdeeen, UK
%F PUB:(DE-HGF)3 ; PUB:(DE-HGF)26
%9 BookProceedings
%R 10.1007/978-3-031-48593-0_19
%U https://inrepo02.dkfz.de/record/285708