Measurement and analysis of the impact of time-interval, temperature and radiation dose on tumour cell survival and its application in thermoradiotherapy plan evaluation. (2nd January 2018)

• Record Type: Journal Article
• Authors: van Leeuwen, C. M.; Oei, A. L.; ten Cate, R.; Franken, N. A. P.; Bel, A.; Stalpers, L. J. A.; Crezee, J.; Kok, H. P.
• Is Part Of: International journal of hyperthermia. Volume 34:Number 1(2018)
• Page Start: 30
• Page End: 38
• Publication Date: 2018-01-02
• Subjects: Radiotherapy -- hyperthermia -- biological modelling -- time-interval -- temperature; Thermotherapy -- Periodicals; 615.832
• DOI: 10.1080/02656736.2017.1320812
• Languages: English
• ISSNs: 0265-6736

Abstract

Abstract: Purpose: Biological modelling of thermoradiotherapy may further improve patient selection and treatment plan optimisation, but requires a model that describes the biological effect as a function of variables that affect treatment outcome (e.g. temperature, radiation dose). This study aimed to establish such a model and its parameters. Additionally, a clinical example was presented to illustrate the application. Methods: Cell survival assays were performed at various combinations of radiation dose (0–8 Gy), temperature (37–42 °C), time interval (0–4 h) and treatment sequence (radiotherapy before/after hyperthermia) for two cervical cancer cell lines (SiHa and HeLa). An extended linear-quadratic model was fitted to the data using maximum likelihood estimation. As an example application, a thermoradiotherapy plan (23 × 2 Gy + weekly hyperthermia) was compared with a radiotherapy-only plan (23 × 2 Gy) for a cervical cancer patient. The equivalent uniform radiation dose (EUD) in the tumour, including confidence intervals, was estimated using the SiHa parameters. Additionally, the difference in tumour control probability (TCP) was estimated. Results: Our model described the dependency of cell survival on dose, temperature and time interval well for both SiHa and HeLa data ( R 2 =0.90 and R 2 =0.91, respectively), making it suitable for biological modelling. In the patient example, the thermoradiotherapy plan showed an increase in EUD of 9.8 Gy that was robust (95% CI: 7.7–14.3 Gy) against propagation of the uncertainty in radiobiological parameters. This corresponded to a 20% (95% CI: 15–29%) increase in TCP. Conclusions: This study presents a model that describes the cell survival as a function of radiation dose, temperature and time interval, which is essential for biological modelling of thermoradiotherapy treatments.