Eiben, B;
Bertholet, J;
Tran, EH;
Wetscherek, A;
Oelfke, U;
McClelland, J;
(2019)
Geometric accuracy of surrogate-driven respiratory motion models for MR-guided lung radiotherapy.
In:
Proceedings of the 19th International Conference on the Use of Computers in Radiation Therapy.
ICCR
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Abstract
MR-Linacs offer unprecedented motion monitoring potential during treatment with excellent soft tissue contrast, but high-quality 3D images cannot currently be acquired fast enough to image respiratory motion. 2D cine-MR images facilitate 2D lung tumour monitoring, but do not provide information outside the imaging plane, preventing downstream adaption methods that rely on temporally resolved volumetric patient information. Surrogate-driven motion models (SDMMs) can provide this information. Our method uses multi-slice 2D images to build an SDMM and generate a motion-compensated super-resolution reconstruction (MCSR) of the anatomy. We quantify the SDMM’s geometric accuracy using the XCAT anthropomorphic phantom. An XCAT patient anatomy with a tumour in the lower right lung was animated with a volunteer’s breathing trace and an MR-like image and ground-truth deformation vector field (DVF) was generated for every time point. An acquisition pattern of interleaved motion and surrogate slices was simulated. Motion slices capture the anatomy in sagittal and coronal orientations and overlap by 8mm to facilitate a super-resolution reconstruction. Each motion slice was acquired three times. From the surrogate slices the skin and diaphragm motion was measured to generate surrogate signals. An SDMM was fitted to the data and an MCSR was generated using our motion modelling methodology. Treatment delivery was simulated on a later part of the breathing trace. Surrogate signals were calculated and used as input to the SDMM to generate estimated DVFs. Representative instances were selected and evaluated in terms of deformation field error (DFE) and tumour centre of mass error (COM) against the ground truth simulation. Results were weighted according to the relative occurrence of each instance during beam-on time. The mean DFE/COM error was reduced by the SDMM from 3.1mm/3.9mm to 1.1mm/0.7mm, below the voxel size, highlighting the SDMM’s potential to produce volumetric patient information of high spatial and temporal resolution.
| Type: | Proceedings paper |
|---|---|
| Title: | Geometric accuracy of surrogate-driven respiratory motion models for MR-guided lung radiotherapy |
| Event: | The 19th International Conference on the Use of Computers in Radiation Therapy, International Conference on the Use of Computers in Radiation Therapy |
| Location: | Montreal (QC), Canada |
| Dates: | 17th-20th June 2019 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://iccr-mcma.org/abstracts/ |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10080108 |
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