Building motion models of lung tumours from cone-beam CT for radiotherapy applications

James Martin, Jamie McClelland, Connie Yip, Christopher Thomas, Claire Hartill, Shahreen Ahmad, Richard O'Brien, Ivan Meir, David Landau, David Hawkes

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)1809-1822
Number of pages14
JournalPhysics in Medicine and Biology
Volume58
Issue number6
DOIs
Publication statusPublished - 21 Mar 2013

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