King's College London

Research portal

Iterative framework for the joint segmentation and CT synthesis of MR images: Application to MRI-only radiotherapy treatment planning

Research output: Contribution to journalArticle

Ninon Burgos, Filipa Guerreiro, Jamie McClelland, Benoit Presles, Marc Modat, Simeon Nill, David Dearnaley, Nandita DeSouza, Uwe Oelfke, Antje Christin Knopf, Sebastien Ourselin, M. Jorge Cardoso

Original languageEnglish
Pages (from-to)4237-4253
Number of pages17
JournalPhysics in Medicine and Biology
Issue number11
Publication statusPublished - 5 May 2017

King's Authors


To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis. We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average 45.7±4.6 HU and the ME -1.6±7.7 HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of -0.14% in the PTV for D98%, and between -0.14% and 0.05% in the PTV, bladder, rectum and femur heads for Dmean and D2%. Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454