Fast, MF;
Eiben, B;
Menten, MJ;
Wetscherek, A;
Hawkes, DJ;
McClelland, JR;
Oelfke, U;
(2017)
Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study.
Radiotherapy and Oncology
, 125
(3)
pp. 485-491.
10.1016/j.radonc.2017.09.013.
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Abstract
BACKGROUND AND PURPOSE: Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients. MATERIAL AND METHODS: Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty. RESULTS: Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance. CONCLUSION: Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance.
| Type: | Article |
|---|---|
| Title: | Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study |
| Location: | Ireland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.radonc.2017.09.013 |
| Publisher version: | http://doi.org/10.1016/j.radonc.2017.09.013 |
| Language: | English |
| Additional information: | © 2017 The Author(s). Published by Elsevier Ireland Ltd. Radiotherapy and Oncology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Keywords: | Auto-contouring, Locally advanced lung cancer, Lung tumour tracking, MRI-guided radiotherapy |
| 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/10027497 |
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