CSTR:11738.11.ncdc.IMP.db2509.2022
10.12072/ncdc.IMP.db2509.2022
This document is an evaluation model for important parameters in particle therapy. The model is established by fully considering such parameters as tumor percentage dose coverage, volume dose of normal tissue and dangerous organs, evaluating the advantages and disadvantages of treatment plan and the effectiveness of treatment, and giving the evaluation results for doctors and pharmacists to select and modify treatment plans
In this study, we established the evaluation model of the combined treatment of photons, carbon ions and other particles, with the percentage dose coverage of tumor, the volume dose of normal tissues and organs at risk as parameters. An end-to-end method based on deep learning is established to predict the three-dimensional dose distribution of radiotherapy plan, and the above evaluation model is realized. Through the self-developed end-to-end convolution neural network and the preprocessing algorithm of structural images, the model can achieve more accurate prediction results. The model can be used for the prediction of photon or carbon ion or multi particle combined radiotherapy plan. The predicted dose can be directly used to calculate the probability of tumor control and the probability of normal tissue complications, such as the probability of hypothyroidism after intensity-modulated radiotherapy for nasopharyngeal carcinoma
In this study, we established the evaluation model of the combined treatment of photons, carbon ions and other particles, with the percentage dose coverage of tumor, the volume dose of normal tissues and organs at risk as parameters. An end-to-end method based on deep learning is established to predict the three-dimensional dose distribution of radiotherapy plan, and the above evaluation model is realized
The data are from clinical trials, and the data quality is good
| # | number | name | type |
| 1 | 2017YFC0107500 | Research and implementation of a new conformal intensity modulation technique for multi-particle biology guided by multi-modes | National key R & D plan |
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