Objective: The purpose of this study was to seek radiation dose responses separately for primary hepatocellular carcinoma (HCC) and metastatic (MET) colorectal liver tumours to establish tumour control probabilities (TCPs) for radiotherapy (RT) of liver tumours. Methods: The records of 36 HCC and 26 MET colorectal liver tumour patients were reviewed. The median dose per fraction and total dose were 4 Gy (2-10 Gy) and 52 Gy (29-83 Gy) for the HCC group and 3.6 Gy (2.0-13.0 Gy) and 55 Gy (30-80 Gy) for the MET group, respectively. Median tumour diameter was 6.6 cm (3.0-18.0 cm) and 5.0 cm (1.0-13.0 cm) for the HCC and MET groups, respectively. A logistic TCP model was fitted to the response data for each group using the maximum likelihood method.Results: 50% and 90% probabilities of 6-month local control were estimated to be achievable by 2 Gy per fraction equivalent doses (a/b510 Gy) of 53 Gy and 84 Gy for the HCC group and 70 Gy and 95 Gy for the MET group, respectively. Actuarial 1-year local control for the HCC and MET groups was 65% (45-85%) and 32% (6-58%), respectively, whereas median time to failure was 543 days (374-711 days) and 183 days (72-294 days), respectively. Conclusion: Dose-response relationships were found and modelled for the HCC and MET patient groups, with a higher dose required to control MET tumours. RT offers better local control for HCC than for MET colorectal liver tumours at our institution. Advances in knowledge: An improved understanding of radiation dose-response relationships for primary and MET colorectal liver tumours will help inform future dose prescriptions.

No abstract

Parametric response map (PRM) analysis is a voxel-wise technique for predicting overall treatment outcome, which shows promise as a tool for guiding personalized locally adaptive radiotherapy (RT). However, image registration error (IRE) introduces uncertainty into this analysis which may limit its use for guiding RT. Here we extend the PRM method to include an IRE-related PRM analysis confidence interval and also incorporate multiple graded classification thresholds to facilitate visualization. A Gaussian IRE model was used to compute an expected value and confidence interval for PRM analysis. The augmented PRM (A-PRM) was evaluated using CT-perfusion functional image data from patients treated with RT for glioma and hepatocellular carcinoma. Known rigid IREs were simulated by applying one thousand different rigid transformations to each image set. PRM and A-PRM analyses of the transformed images were then compared to analyses of the original images (ground truth) in order to investigate the two methods in the presence of controlled IRE. The A-PRM was shown to help visualize and quantify IRE-related analysis uncertainty. The use of multiple graded classification thresholds also provided additional contextual information which could be useful for visually identifying adaptive RT targets (e.g. sub-volume boosts). The A-PRM should facilitate reliable PRM guided adaptive RT by allowing the user to identify if a patient's unique IRE-related PRM analysis uncertainty has the potential to influence target delineation.

No abstract

Purpose At present, commercially available treatment planning systems (TPS) only offer manual planning functionality for cone‐based stereotactic radiosurgery (SRS) leading to labor intensive treatment planning. Our objective was to reduce treatment planning time through development of a simple inverse TPS for cone‐based SRS. Methods The iCONE TPS was developed using MATLAB (R2015a, The MathWorks Inc.) and serves as an inverse planning adjunct to a commercially available TPS. Simulated annealing is used to determine optimal table angle, gantry start and stop angles, and cone sizes for a user‐defined number of non‐coplanar arcs relative to user‐defined dose objectives. iCONE and clinically generated plans were compared through a retrospective planning study of 60 patients treated for 1–3 brain metastases (total of 100 lesions). Results Planning target volume (PTV) coverage was enforced for all plans through normalization. PTV maximum dose was constrained to be within 120%–135% of the prescription dose. The median conformity index for iCONE plans was 1.35, 1.33, and 1.32 for 1, 2, and 3‐target cases respectively corresponding to a median increase of 0.05 (range = −0.1 to 0.5, P < 0.05), 0.06 (range = −0.83 to 0.53, P < 0.05), and 0.03 (range = −1.21 to 0.74, P > 0.05) relative to the clinical plans. No clinically significant differences were found with respect to the dose to organs‐at‐risk. Median iCONE planning times were approximately a factor of five lower than consensus estimates for manual planning provided by local experienced SRS planners. Conclusions A simple inverse TPS for cone‐based SRS was developed. Plan quality was found to be similar to manually generated plans; however, degradation was observed in some cases highlighting the need for continued oversight and manual adjustment by experienced planners if implemented in the clinic. A factor of five reduction in treatment planning time was estimated.