At the Italian National Centre for Oncologic Hadrontherapy (CNAO) patients with upper-abdominal tumours are being treated with carbon ion therapy, adopting the respiratory gating technique in combination with layered rescanning and abdominal compression to mitigate organ motion. Since online imaging of the irradiated volume is not feasible, this study proposes a modelling approach for the estimation of residual motion of the target within the gating window. The model extracts a priori respiratory motion information from the planning 4DCT using deformable image registration (DIR), then combines such information with the external surrogate signal recorded during dose delivery. This provides estimation of a CT volume corresponding to any given respiratory phase measured during treatment. The method was applied for the retrospective estimation of tumour residual motion during irradiation, considering 16 patients treated at CNAO with the respiratory gating protocol. The estimated tumour displacement, calculated with respect to the reference end-exhale position, was always limited (average displacement is 0.32 ± 0.65 mm over all patients) and below the maximum motion defined in the treatment plan. This supports the hypothesis of target position reproducibility, which is the crucial assumption in the gating approach. We also demonstrated the use of the model as a simulation tool to establish a patient-specific relationship between residual motion and the width of the gating window. In conclusion, the implemented method yields an estimation of the repeatability of the internal anatomy configuration during gated treatments, which can be used for further studies concerning the dosimetric impact of the estimated residual organ motion.

Evaluation of residual abdominal tumour motion in carbon ion gated treatments through respiratory motion modelling

MESCHINI, GIORGIA;SEREGNI, MATTEO;RIBOLDI, MARCO;BARONI, GUIDO
2017

Abstract

At the Italian National Centre for Oncologic Hadrontherapy (CNAO) patients with upper-abdominal tumours are being treated with carbon ion therapy, adopting the respiratory gating technique in combination with layered rescanning and abdominal compression to mitigate organ motion. Since online imaging of the irradiated volume is not feasible, this study proposes a modelling approach for the estimation of residual motion of the target within the gating window. The model extracts a priori respiratory motion information from the planning 4DCT using deformable image registration (DIR), then combines such information with the external surrogate signal recorded during dose delivery. This provides estimation of a CT volume corresponding to any given respiratory phase measured during treatment. The method was applied for the retrospective estimation of tumour residual motion during irradiation, considering 16 patients treated at CNAO with the respiratory gating protocol. The estimated tumour displacement, calculated with respect to the reference end-exhale position, was always limited (average displacement is 0.32 ± 0.65 mm over all patients) and below the maximum motion defined in the treatment plan. This supports the hypothesis of target position reproducibility, which is the crucial assumption in the gating approach. We also demonstrated the use of the model as a simulation tool to establish a patient-specific relationship between residual motion and the width of the gating window. In conclusion, the implemented method yields an estimation of the repeatability of the internal anatomy configuration during gated treatments, which can be used for further studies concerning the dosimetric impact of the estimated residual organ motion.
4DCT; Deformable image registration; Gating; Motion modelling; Particle therapy; Abdominal Neoplasms; Four-Dimensional Computed Tomography; Heavy Ion Radiotherapy; Humans; Radiometry; Radiotherapy Planning, Computer-Assisted; Uncertainty; Models, Biological; Movement; Respiration; Respiratory-Gated Imaging Techniques; Biophysics; Radiology, Nuclear Medicine and Imaging; Physics and Astronomy (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1030170
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