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Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study

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. Green open access

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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 > 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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