Can dose convolution modelling explain bath and shower effects in rat spinal cord?

Objective. ‘Bath and shower’ effects were first seen in proton irradiations of rat spinal cord, where a low dose ‘bath’ reduced the smaller field ‘shower’ dose needed for limb paralysis giving the appearance of sensitisation of the cord or disproportionate response. This was difficult to reconcile with existing tissue complication models. The purpose of this investigation is to explore a different approach using a dose convolution algorithm to model the 50% isoeffect endpoint. Approach. Bath and shower dose distributions were convolved with Gaussian functions with widths specified by the σ parameter. The hypothesis was that the maximum value from the convolved distributions was constant for isoeffect across the modelled scenarios. A simpler field length dependent relative biological effectiveness (FLRBE) approach was also used for a subset of the data which gave results independent of σ. Main results. The maximum values from the convolved distributions were constant within ±17% across the bath and shower experiments for σ = 3.5 mm, whereas the maximum dose varied by a factor of four. The FLRBE results were also within ±14% confirming the validity of the dose convolution approach. Significance. A simple approach using dose convolution modelling of the 50% isotoxicity gave compelling consistency with the full range of bath and shower results, while the FLRBE approach confirmed the results for the symmetric field data. Convolution modelling and the effect of time interval were consistent with a signalling factor diffusion mechanism such as the ‘bystander effect’. The results suggest biological effectiveness is reduced for very small field sizes, requiring a higher isoeffect dose. By implication, the bath dose does not sensitise the cord to the shower dose; when biological effectiveness is accounted for, a small increase in the bath dose requires a significantly larger reduction in shower dose for isoeffect.

A new plan quality index for dose painting radiotherapy

Dose painting radiotherapy is considered a promising radiotherapy technology that enables more targeted dose delivery to tumor rich regions while saving critical normal tissues. Obviously, dose painting planning would be more complicated and hard to be evaluated with current plan quality index systems that were developed under the paradigm of uniform dose prescription. In this study, we introduce a new plan quality index, named “index of achievement (IOA)” that assesses how close the planned dose distribution is to the prescribed one in a dose painting radiotherapy plan. By using voxel‐based comparison between planned and prescribed dose distributions in its formulation, the index allows for a single‐value evaluation regardless of the number of prescribed dose levels, which cannot be achieved with the conventional indices such as conventional homogeneity index. Benchmark calculations using patient data demonstrated feasibility of the index not only for contour‐based dose painting plans, but also for dose painting by numbers plans. Also, it was shown that there is strong correlation between the new index and conventional indices, which indicates a potential of the new index as an alternative to conventional ones in general radiotherapy plan evaluation.

PACS number: 87.55.D‐

Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution

Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.

Do we need fractionation-corrected doses in sequential two-phase treatments? A quantification of dose differences between non-corrected and corrected combined non-uniform dose distributions in normal tissue

BACKGROUND

For many tumour sites, external beam radiation therapy (EBRT) is delivered with a sequential two-phase treatment regime. Yet, there is a lack of consensus of how to add two different non-uniform dose distributions in order to evaluate the late radiation effect for normal tissue. The purpose of this novel investigation is to quantify the dose differences between non-corrected and fractionation-corrected combined non-uniform dose distributions.

MATERIAL AND METHODS

We used a model of an organ at risk (OAR) located in six different positions relative the treated volume giving 16 clinically representative two-phase treatment situations (46 Gy + 22 Gy). The linear-quadratic model was applied to correct for fractionation effects in each voxel before the doses were added. Dose differences were quantified using mean and maximum doses with corresponding fractionation-corrected doses as reference.

RESULTS

Non-corrected doses were higher than fractionation-corrected doses in all treatment situations (mean dose: p<0.001; maximum dose: p=0.003). With the OAR outside the treated volume, non-corrected doses were 3-6 Gy higher representing 10-50% of the reference dose (10-25 Gy); with the OAR included in the treated volume, 1-6 Gy higher representing 1-15% (30-60 Gy). Mean dose differences were generally larger than maximum dose differences.

CONCLUSION

Substantial dose differences were present in all of the simulated treatment situations but more apparent when the OAR was located outside the treated volume in both phases. Our findings require verification in clinical cases but nevertheless indicate a need for fractionation-corrected doses in two-phase treatments both in the daily clinical routine as well as in the modelling of late radiation effects. Our data suggest that adjusting for fractionation effects would lead to lower tolerance doses than currently suggested, in particular for OARs with parallel tissue architecture.