The influence of the optimization starting conditions on the robustness of intensity-modulated proton therapy plans
| Autor: | Antony J. Lomax, Francesca Albertini, E.B. Hug |
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| Rok vydání: | 2010 |
| Předmět: |
Male
Mathematical optimization Radiological and Ultrasound Technology Radiotherapy Planning Computer-Assisted Chondrosarcoma Uncertainty Sobp Prostatic Neoplasms Uterine Cervical Neoplasms Inverse Radiotherapy Dosage Thoracic Neoplasms Edge (geometry) Wedge (geometry) Robustness (computer science) Proton Therapy Range (statistics) Humans Female Radiology Nuclear Medicine and imaging Radiotherapy Intensity-Modulated Constant (mathematics) Algorithm Proton therapy Mathematics |
| Zdroj: | Physics in Medicine and Biology. 55:2863-2878 |
| ISSN: | 1361-6560 0031-9155 |
| DOI: | 10.1088/0031-9155/55/10/005 |
| Popis: | In this paper the influence of varying the starting conditions on intensity-modulated proton therapy (IMPT) plans has been studied. In particular IMPT plans have been optimized based on four different starting conditions of initial beamlet fluences: (a) all beamlets with an initial constant weight, delivering a gradient from the proximal to the distal edge of the target (forward wedge approach); (b) beamlet weights reduced from the distal to the proximal aspect of the target such as to deliver a flat 'spread-out-Bragg-peak' (SOBP approach); (c) beamlet weights calculated to deliver a gradient from the distal (maximal dose) to the proximal edge (inverse wedge); (d) beamlet weights set universally to zero except the most distal one, for each given lateral direction (i.e. distal-edge-tracking, DET). An analysis of robustness to range errors has been performed by recalculating plans, assuming a systematic 3% error in CT values. Results showed that IMPT plans optimized with the forward wedge approach were very sensitive to range errors, since organs-at-risk (OAR) were spared by patching single-field lateral and distal fall-offs, the last ones being strongly sensitive to range errors. In addition a plan robust to range errors can be achieved by starting the optimization process in the case of low-dose constraints to OAR, with the initial flat SOBP approach, and with either the DET or the inverse wedge approaches, in the case of stringent dose-volume constraints to OAR. 'Starting condition-based optimization' as proposed here can therefore provide a tool to transparently 'steer' the optimization outcome to solutions more robust to uncertainties. |
| Databáze: | OpenAIRE |
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