Risk of secondary cancer induced by radiotherapy

Transcription

1 Risk of secondary cancer induced by radiotherapy Iuliana Toma-Dasu Medical Radiation Physics Stockholm University and Karolinska Institutet

2 Radiation - the two-edged sword Risk of secondary cancer induced by radiotherapy a cross cutting theme The point of view of the medical physicist How dangerous is a particular type of treatment? Is the risk from treatment A larger than the risk from treatment B?

3 Risk estimations from A-bomb survivors A non-negligible excess of cancer incidence has been observed in long-term survivors. The results appear to indicate a linear risk relationship between 0.05 and.5 Sv. Radiation therapy Radiation protection Hall, 004

4 Risk of secondary cancer Extrapolations of risks from general populations to radiotherapy patients are not straightforward. Age distribution and the genetic features of the patients may differ from the general population. Best risk estimates would probably be obtained from long term survivors of radiotherapy. Control populations may be difficult to establish. Irradiation techniques have changed over the years. The relevance of the results from 30-year old treatments to modern techniques is questionable.

5 Experimental relationships for risk Experimental relationships Bell-shaped relationships The risk increases with dose, reaches a maximum at about 4-6 Gy and then decreases as cells are rather killed than mutated. Probability of carcinogenic mutation Optimal dose Dose Plateau relationships The risk increases with dose up to about Gy and then essentially remains the same. Complex nonlinear relationships Probability of carcinogenic mutation Levelling-off dose Dose

6 Risk of secondary cancer It would be useful to use risk predictions as a complementary criterion for the selection of successful plans. Risk calculations however require reliable models and accurate parameters which may not always be available from experimental studies! Most models aim to describe on mechanistic bases the shapes of the doseresponse relationships for risk observed in epidemiological studies: UNSCEAR (1993, 000) Davis 004, Dasu et al 005, Sachs and Brenner 005, Schneider 005, Schneider and Walsh 008, Schneider 009, etc

7 Competition risk models UNSCEAR (1993) has proposed an equation to describe the risk at large single doses Linear model Competition model (SD) Risk SD = ( α D + β D ) [ ( α D + β )] 1 1 exp D α 1 is calculated based on the average lifetime risk coefficient given by ICRP for low doses and dose rates adjusted for detriments. Predicted risk (%) Dose (Gy) α is the linear parameter describing the cell survival in the LQ model.

8 Competition risk models The equation proposed by UNSCEAR has been adapted to describe fractionated treatments (Dasu et al 005): β 1D βd Risk FX = α D + D + 1 exp α n n Predicted risk (%) Linear model Competition model (SD) Competition model (FX) There are considerable differences between the different models in the clinical dose range Dose (Gy)

9 Competition risk models Clinical data on cancer induction from radiotherapy are the result of many patients and therefore heterogeneity in the individual radiosensitivity has to be taken into consideration as a possible parameter that may influence the appearance of the dose response curve. Upper panel α/β=10 Gy Middle panel α/β=5 Gy Lower panel α/β=3 Gy (α 1 =0.05 Gy -1, SF =70%) Predicted risk (%) CV=50% CV=0% CV=0% CV=50% CV=0% CV=0% CV=50% CV=0% CV=0% Dose in 30 fractions (Gy)

10 Model for heterogeneous irradiation 0.6 For heterogeneous fractionated irradiations: Predicted risk (%) Risk = i v i β 1Di α1di + exp α D n v i i i βd + n i Tissue volume (%) Dose in 39 fractions (Gy)

11 Model for heterogeneous irradiation Example: risk for bladder Average organ dose 3. Gy Linear risk model 19.3% Competition model and average dose 0.00% Competition model and full DVH 0.8% Clinically observed risk % Average organ dose > 30 Gy Reference Boice et al 1985 Risk for secondary cancers (%) Percent volume irradiated Mean dose: 3. Gy Dose in 39 fractions (Gy)

12 Risk of secondary cancer How dangerous is a particular type of treatment? Is the risk from treatment A larger than the risk from treatment B? CRT IMRT Changes in the treatment fractionation schedule Changes in the planning target volumes (PTV) according to the frequency of image guidance etc. Dasu et al 011

13 Clinical application of the risk models Risk assessments were carried out for 10 H&N patients. Two plans for each patient: an IMRT plan and a clinically equivalent CRT plan. The prescribed dose to the tumour was 68 Gy in Gy fractions. Four tissues of interest were included in the risk calculations: parotid glands, oesophagus, lungs and the remaining tissues.

14 Competition risk models for clinical use Competition model (Dasu et al 005): Risk β 1D βd = α1d + exp αd + n n Linear-exponential model (Schneider 005): ( D) Risk = α1d exp α Plateau model (Davis 004): [ 1 ( δ )] α = exp δ 1 Risk orgd org Ardenfors et al 014

15 Dose contributions and risk assessment Risk calculations were performed taking three dose contributors into account: Ardenfors et al Primary treatment radiation => from DVHs. Secondary radiation => TLD measurements in anthropomorphic phantom 3. Imaging radiation from repeated CBCTs

16 Average lifetime risk of secondary cancer Ardenfors et al 014 The risk to the lungs from scattered radiation was significant and similar for both treatment techniques. Repeated CBCT diagnostic imaging contributed little to the total risk in comparison to the treatment-associated radiation burden. The total lifetime risk from treatment, scatter radiation, and CBCT imaging was in the order of 0.9.5% for both IMRT and CRT.

17 Conclusions Quantification of the risks for cancer induction from RT becomes increasingly necessary as the life expectancy of patients increases. Conventional risk estimates might not be appropriate for radiotherapy applications due to differences in the irradiation pattern. Knowledge about risk is in a continuous update. Models rely on epidemiological studies for parameters. Epidemiological studies may in turn benefit from theoretical modelling to highlight aspects of interest. Current knowledge indicate that radiotherapy might result in a small but significant risk of inducing cancers.

18 Considerations for the future Irradiation techniques change continuously. How could the results from epidemiological studies analysing data from patients irradiated in the 1970s and 1980s be extrapolated to modern therapy techniques? How could the results from current treatment methods (CRT, IMRT, TT) be extrapolated to the treatments of the 040s and 050s? How much of the information available nowadays must we record for the future? The use of particle therapy employing protons and heavier ions is on the increase. How could the results from photon therapy be extrapolated to particle therapy?

19 Acknowledgements OSCAR ARDENFORS IRENA GUDOWSKA Stockholm University and Karolinska Institutet ALEXANDRU DASU Linköping University and Linköping University Hospital This work was partially supported by the Swedish Radiation Safety Authority under the contract SSM