title: Identifying radiotherapy target volumes in brain cancer by image analysis.
abstract: To establish the optimal radiotherapy fields for treating brain cancer patients, the tumour volume is often outlined on magnetic resonance (MR) images, where the tumour is clearly visible, and mapped onto computerised tomography images used for radiotherapy planning. This process requires considerable clinical experience and is time consuming, which will continue to increase as more complex image sequences are used in this process. Here, the potential of image analysis techniques for automatically identifying the radiation target volume on MR images, and thereby assisting clinicians with this difficult task, was investigated. A gradient-based level set approach was applied on the MR images of five patients with grades II, III and IV malignant cerebral glioma. The relationship between the target volumes produced by image analysis and those produced by a radiation oncologist was also investigated. The contours produced by image analysis were compared with the contours produced by an oncologist and used for treatment. In 93% of cases, the Dice similarity coefficient was found to be between 60 and 80%. This feasibility study demonstrates that image analysis has the potential for automatic outlining in the management of brain cancer patients, however, more testing and validation on a much larger patient cohort is required.
authors.affiliation: Department of Oncology Physics , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK.
authors.forename: Kun
authors.initials: K
authors.lastname: Cheng
authors.affiliation: Department of Oncology Physics , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK.
authors.forename: Dean
authors.initials: D
authors.lastname: Montgomery
authors.affiliation: Department of Oncology Physics , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK.
authors.forename: Yang
authors.initials: Y
authors.lastname: Feng
authors.affiliation: Department of Oncology Physics , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK.
authors.forename: Robin
authors.initials: R
authors.lastname: Steel
authors.affiliation: Department of Electrical Engineering and Electronics , University of Liverpool , Liverpool L69 3GQ , UK.
authors.forename: Hanqing
authors.initials: H
authors.lastname: Liao
authors.affiliation: Department of Clinical Oncology , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK.
authors.forename: Duncan B
authors.initials: DB
authors.lastname: McLaren
authors.affiliation: Department of Clinical Oncology , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK.
authors.forename: Sara C
authors.initials: SC
authors.lastname: Erridge
authors.affiliation: School of Engineering and Physical Sciences , Heriot Watt University , David Brewster Building, Edinburgh EH14 4AS , UK.
authors.forename: Stephen
authors.initials: S
authors.lastname: McLaughlin
authors.affiliation: Department of Oncology Physics , Edinburgh Cancer Centre, Western General Hospital , Crewe Road South, Edinburgh EH4 2XU , UK ; School of Engineering , University of Edinburgh , King's Buildings, Mayfield Road, Edinburgh EH9 3JL , UK.
authors.forename: William H
authors.initials: WH
authors.lastname: Nailon
keywords: Dice similarity coefficient; MRI; automatic outlining; biomedical MRI; brain; brain cancer; brain cancer patients; cancer; complex image sequences; computerised tomography; computerised tomography images; gradient-based level set approach; image analysis techniques; image sequences; magnetic resonance images; malignant cerebral glioma; medical image processing; oncologist; optimal radiotherapy fields; radiation oncologist; radiation therapy; radiotherapy planning; radiotherapy target volumes; tumour volume; tumours