title: Building motion models of lung tumours from cone-beam CT for radiotherapy applications.
abstract: A method is presented to build a surrogate-driven motion model of a lung tumour from a cone-beam CT scan, which does not require markers. By monitoring an external surrogate in real time, it is envisaged that the motion model be used to drive gated or tracked treatments. The motion model would be built immediately before each fraction of treatment and can account for inter-fraction variation. The method could also provide a better assessment of tumour shape and motion prior to delivery of each fraction of stereotactic ablative radiotherapy. The two-step method involves enhancing the tumour region in the projections, and then fitting the surrogate-driven motion model. On simulated data, the mean absolute error was reduced to 1 mm. For patient data, errors were determined by comparing estimated and clinically identified tumour positions in the projections, scaled to mm at the isocentre. Averaged over all used scans, the mean absolute error was under 2.5 mm in superior-inferior and transverse directions.
authors: Centre for Medical Image Computing, University College London WC1E 6BT, UK. james.martin.09@ucl.ac.uk
authors: James
authors: J
authors: Martin
authors: Jamie
authors: J
authors: McClelland
authors: Connie
authors: C
authors: Yip
authors: Christopher
authors: C
authors: Thomas
authors: Clare
authors: C
authors: Hartill
authors: Shahreen
authors: S
authors: Ahmad
authors: Richard
authors: R
authors: O'Brien
authors: Ivan
authors: I
authors: Meir
authors: David
authors: D
authors: Landau
authors: David
authors: D
authors: Hawkes
mesh_terms: D054893:Cone-Beam Computed Tomography; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000503:physiopathology / Q000532:radiotherapy*; D008954:Models, Biological; D009068:Movement; D061089:Radiotherapy, Image-Guided