| Autor: |
E. J. Her, A. Haworth, H. M. Reynolds, Y. Sun, A. Kennedy, V. Panettieri, M. Bangert, S. Williams, M. A. Ebert |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Radiation Oncology, Vol 15, Iss 1, Pp 1-13 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1748-717X |
| DOI: |
10.1186/s13014-020-01568-6 |
| Popis: |
Abstract Aims This study aimed to develop a framework for optimising prostate intensity-modulated radiotherapy (IMRT) based on patient-specific tumour biology, derived from multiparametric MRI (mpMRI). The framework included a probabilistic treatment planning technique in the effort to yield dose distributions with an improved expected treatment outcome compared with uniform-dose planning approaches. Methods IMRT plans were generated for five prostate cancer patients using two inverse planning methods: uniform-dose to the planning target volume and probabilistic biological optimisation for clinical target volume tumour control probability (TCP) maximisation. Patient-specific tumour location and clonogen density information were derived from mpMRI and geometric uncertainties were incorporated in the TCP calculation. Potential reduction in dose to sensitive structures was assessed by comparing dose metrics of uniform-dose plans with biologically-optimised plans of an equivalent level of expected tumour control. Results The planning study demonstrated biological optimisation has the potential to reduce expected normal tissue toxicity without sacrificing local control by shaping the dose distribution to the spatial distribution of tumour characteristics. On average, biologically-optimised plans achieved 38.6% (p-value: |
| Databáze: |
Directory of Open Access Journals |
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