title: Validation of a Magnetic Resonance Imaging-based Auto-contouring Software Tool for Gross Tumour Delineation in Head and Neck Cancer Radiotherapy Planning.
abstract: To carry out statistical validation of a newly developed magnetic resonance imaging (MRI) auto-contouring software tool for gross tumour volume (GTV) delineation in head and neck tumours to assist in radiotherapy planning.
  
  
  
  Axial MRI baseline scans were obtained for 10 oropharyngeal and laryngeal cancer patients. GTV was present on 102 axial slices and auto-contoured using the modified fuzzy c-means clustering integrated with the level set method (FCLSM). Peer-reviewed (C-gold) manual contours were used as the reference standard to validate auto-contoured GTVs (C-auto) and mean manual contours (C-manual) from two expert clinicians (C1 and C2). Multiple geometric metrics, including the Dice similarity coefficient (DSC), were used for quantitative validation. A DSC≥0.7 was deemed acceptable. Inter- and intra-variabilities among the manual contours were also validated. The two-dimensional contours were then reconstructed in three dimensions for GTV volume calculation, comparison and three-dimensional visualisation.
  
  
  
  The mean DSC between C-gold and C-auto was 0.79. The mean DSC between C-gold and C-manual was 0.79 and that between C1 and C2 was 0.80. The average time for GTV auto-contouring per patient was 8 min (range 6-13 min; mean 45 s per axial slice) compared with 15 min (range 6-23 min; mean 88 s per axial slice) for C1. The average volume concordance between C-gold and C-auto volumes was 86.51% compared with 74.16% between C-gold and C-manual. The average volume concordance between C1 and C2 volumes was 86.82%.
  
  
  
  This newly designed MRI-based auto-contouring software tool shows initial acceptable results in GTV delineation of oropharyngeal and laryngeal tumours using FCLSM. This auto-contouring software tool may help reduce inter- and intra-variability and can assist clinical oncologists with time-consuming, complex radiotherapy planning.
authors: Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, UK. Electronic address: trushali.doshi@strath.ac.uk.
authors: T
authors: T
authors: Doshi
authors: Beatson West of Scotland Cancer Centre, Glasgow, UK.
authors: C
authors: C
authors: Wilson
authors: Beatson West of Scotland Cancer Centre, Glasgow, UK.
authors: C
authors: C
authors: Paterson
authors: Beatson West of Scotland Cancer Centre, Glasgow, UK.
authors: C
authors: C
authors: Lamb
authors: Beatson West of Scotland Cancer Centre, Glasgow, UK.
authors: A
authors: A
authors: James
authors: Glasgow Royal Infirmary, Glasgow, UK.
authors: K
authors: K
authors: MacKenzie
authors: Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, UK.
authors: J
authors: J
authors: Soraghan
authors: Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, UK.
authors: L
authors: L
authors: Petropoulakis
authors: Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, UK.
authors: G
authors: G
authors: Di Caterina
authors: Beatson West of Scotland Cancer Centre, Glasgow, UK.
authors: D
authors: D
authors: Grose
mesh_terms: D000368:Aged; D005260:Female; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D015588:Observer Variation; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012984:Software
keywords: Automatic delineation; head and neck GTV; magnetic resonance imaging; pharyngeal and laryngeal tumours; radiotherapy treatment planning; volume calculation and 3D visualisation