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dc.contributor.authorMackay, Ranald I
dc.contributor.authorGraham, Paul A
dc.contributor.authorMoore, Christopher J
dc.contributor.authorLogue, John P
dc.contributor.authorSharrock, Phillip J
dc.date.accessioned2009-12-14T15:03:48Z
dc.date.available2009-12-14T15:03:48Z
dc.date.issued1999-07
dc.identifier.citationAnimation and radiobiological analysis of 3D motion in conformal radiotherapy. 1999, 52 (1):43-9 Radiother Oncolen
dc.identifier.issn0167-8140
dc.identifier.pmid10577685
dc.identifier.doi10.1016/S0167-8140(99)00081-X
dc.identifier.urihttp://hdl.handle.net/10541/87894
dc.description.abstractPURPOSE: To allow treatment plans to be evaluated against the range of expected organ motion and set up error anticipated during treatment. METHODS: Planning tools have been developed to allow concurrent animation and radiobiological analysis of three dimensional (3D) target and organ motion in conformal radiotherapy. Surfaces fitted to structures outlined on CT studies are projected onto pre-treatment images or onto megavoltage images collected during the patient treatment. Visual simulation of tumour and normal tissue movement is then performed by the application of three dimensional affine transformations, to the selected surface. Concurrent registration of the surface motion with the 3D dose distribution allows calculation of the change in dose to the volume. Realistic patterns of motion can be applied to the structure to simulate inter-fraction motion and set-up error. The biologically effective dose for the structure is calculated for each fraction as the surface moves over the course of the treatment and is used to calculate the normal tissue complication probability (NTCP) or tumour control probability (TCP) for the moving structure. The tool has been used to evaluate conformal therapy plans against set up measurements recorded during patient treatments. NTCP and TCP were calculated for a patient whose set up had been corrected after systematic deviations from plan geometry were measured during treatment, the effect of not making the correction were also assessed. RESULTS: TCP for the moving tumour was reduced if inadequate margins were set for the treatment. Modelling suggests that smaller margins could have been set for the set up corrected during the course of the treatment. The NTCP for the rectum was also higher for the uncorrected set up due to a more rectal tissue falling in the high dose region. CONCLUSION: This approach provides a simple way for clinical users to utilise information incrementally collected throughout the whole of a patient's treatment. In particular it is possible to test the robustness of a patient plan against a range of possible motion patterns. The methods described represent a move from the inspection of static pre-treatment plans to a review of the dynamic treatment.
dc.language.isoenen
dc.subjectProstatic Canceren
dc.subject.meshComputer Graphics
dc.subject.meshHumans
dc.subject.meshImage Processing, Computer-Assisted
dc.subject.meshMale
dc.subject.meshMotion
dc.subject.meshProstatic Neoplasms
dc.subject.meshRadiotherapy Dosage
dc.subject.meshRadiotherapy Planning, Computer-Assisted
dc.subject.meshRadiotherapy, Conformal
dc.subject.meshRectum
dc.subject.meshTomography, X-Ray Computed
dc.titleAnimation and radiobiological analysis of 3D motion in conformal radiotherapy.en
dc.typeArticleen
dc.contributor.departmentNorth Western Medical Physics, Christie Hospital NHS Trust, Manchester, UK.en
dc.identifier.journalRadiotherapy and Oncologyen
html.description.abstractPURPOSE: To allow treatment plans to be evaluated against the range of expected organ motion and set up error anticipated during treatment. METHODS: Planning tools have been developed to allow concurrent animation and radiobiological analysis of three dimensional (3D) target and organ motion in conformal radiotherapy. Surfaces fitted to structures outlined on CT studies are projected onto pre-treatment images or onto megavoltage images collected during the patient treatment. Visual simulation of tumour and normal tissue movement is then performed by the application of three dimensional affine transformations, to the selected surface. Concurrent registration of the surface motion with the 3D dose distribution allows calculation of the change in dose to the volume. Realistic patterns of motion can be applied to the structure to simulate inter-fraction motion and set-up error. The biologically effective dose for the structure is calculated for each fraction as the surface moves over the course of the treatment and is used to calculate the normal tissue complication probability (NTCP) or tumour control probability (TCP) for the moving structure. The tool has been used to evaluate conformal therapy plans against set up measurements recorded during patient treatments. NTCP and TCP were calculated for a patient whose set up had been corrected after systematic deviations from plan geometry were measured during treatment, the effect of not making the correction were also assessed. RESULTS: TCP for the moving tumour was reduced if inadequate margins were set for the treatment. Modelling suggests that smaller margins could have been set for the set up corrected during the course of the treatment. The NTCP for the rectum was also higher for the uncorrected set up due to a more rectal tissue falling in the high dose region. CONCLUSION: This approach provides a simple way for clinical users to utilise information incrementally collected throughout the whole of a patient's treatment. In particular it is possible to test the robustness of a patient plan against a range of possible motion patterns. The methods described represent a move from the inspection of static pre-treatment plans to a review of the dynamic treatment.


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