Proposal of See-saw model – overcoming LQM difficulty

We propose the See-Saw (SS) model, which provides a unified description of the biological effect caused by radiation. This can be directly applied to clinical plans in radiotherapy and further provides the basic formula for radioprotection since it correctly describes the effects caused by radiation exposure by taking account of the dose rate effect without any additional concept of dose and dose rate effectiveness factor (DDREF). This can be done by introducing the cell exclusion effect. The model is very simple and intuitively acceptable by expressing the dose-rate effect and can be easily extended to the radiation clinic cases and overcomes the difficulties of the standard method using LQM-based biological equivalent dose (BED). The calculated result of our model reproduces the existing data of the time dependence of the cancer volume during the cancer treatment measurement. We demonstrate that different initial volumes, namely for the cases where irradiation starts with a smaller initial volume are more effective than a larger volume. Especially if the cancer volume is almost full in the tissue, the radiation effect of the cancer treatment is found to be less effective. On the other hand, for the smaller initial volume, the cancer treatment is found to work more effectively to reduce the cancer volume. After explaining the essential difference between our See-saw (SS) model and traditional LQ treatment with the BED index, we report the results of the SS model by displaying the comparison of our prediction with the relevant data. We are arranging the collaboration with the members of the radiation therapy sectional group of Osaka International Cancer Institute and will report detailed results in near future. We can also consider continuous but time-dependent irradiation cases and got interesting outcomes on the time dependence of the tumour volume for various clinic plans. Especially by choosing the value of the dose rate to be balanced with the total growth rate, the tumour volume is kept constant. Finally, I would like to emphasise that our SS model leads us not only with a unified description of radiation therapy but also indicates the misleading principle based on the LNT or LQM hypothesis which is still adopted in the society of radiation protection.

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Publication Details

Journal
Annals of the ICRP
Published
2024-12-01
DOI
https://doi.org/10.1177/01466453241283931am
Primary Topic
Effects of Radiation Exposure
Type
article
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article

Proposal of See-saw model – overcoming LQM difficulty

Yuichi Tsunoyama, Masako Bando, H. Toki, Kazuyo Suzuki
Annals of the ICRP
Effects of Radiation Exposure
article

Proposal of See-saw model – overcoming LQM difficulty

Yuichi Tsunoyama, Masako Bando, H. Toki, Kazuyo Suzuki
article en

Abstract

We propose the See-Saw (SS) model, which provides a unified description of the biological effect caused by radiation. This can be directly applied to clinical plans in radiotherapy and further provides the basic formula for radioprotection since it correctly describes the effects caused by radiation exposure by taking account of the dose rate effect without any additional concept of dose and dose rate effectiveness factor (DDREF). This can be done by introducing the cell exclusion effect. The model is very simple and intuitively acceptable by expressing the dose-rate effect and can be easily extended to the radiation clinic cases and overcomes the difficulties of the standard method using LQM-based biological equivalent dose (BED). The calculated result of our model reproduces the existing data of the time dependence of the cancer volume during the cancer treatment measurement. We demonstrate that different initial volumes, namely for the cases where irradiation starts with a smaller initial volume are more effective than a larger volume. Especially if the cancer volume is almost full in the tissue, the radiation effect of the cancer treatment is found to be less effective. On the other hand, for the smaller initial volume, the cancer treatment is found to work more effectively to reduce the cancer volume. After explaining the essential difference between our See-saw (SS) model and traditional LQ treatment with the BED index, we report the results of the SS model by displaying the comparison of our prediction with the relevant data. We are arranging the collaboration with the members of the radiation therapy sectional group of Osaka International Cancer Institute and will report detailed results in near future. We can also consider continuous but time-dependent irradiation cases and got interesting outcomes on the time dependence of the tumour volume for various clinic plans. Especially by choosing the value of the dose rate to be balanced with the total growth rate, the tumour volume is kept constant. Finally, I would like to emphasise that our SS model leads us not only with a unified description of radiation therapy but also indicates the misleading principle based on the LNT or LQM hypothesis which is still adopted in the society of radiation protection.

Annals of the ICRPVol. 53(1_suppl)
Kyoto University (JP), The University of Osaka (JP)
Openalex Percentile: Top 60%
Effects of Radiation Exposure
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