Automation to facilitate optimisation of breast radiotherapy treatments using EPID-basedin vivodosimetry.

Objective. To use automation to facilitate the monitoring of each treatment fraction using an electronic portal imaging device (EPID) basedin vivodosimetry (IVD) system, allowing optimisation of breast radiotherapy delivery for individual patients and cohorts.Approach. A suite of in-house software was developed to reduce the number of manual interactions with the commercial IVD system, dosimetry check. An EPID specific pixel sensitivity map facilitated use of the EPID panel away from the central axis. Point dose difference and the change in standard deviation in dose were identified as useful dose metrics, with standard deviation used in preference to gamma in the presence of a systematic dose offset. Automated IVD was completed for 3261 fractions across 704 patients receiving breast radiotherapy.Main results. Multiple opportunities for treatment optimisation were identified for individual patients and across patient cohorts as a result of successful implementation of automated IVD. 5.1% of analysed fractions were out of tolerance with 27.1% of these considered true positives. True positive results were obtained on any fraction of treatment and if IVD had only been completed on the first fraction, 84.4% of true positive results would have been missed. This was made possible due to the automation that saved over 800 h of manual intervention and stored data in an accessible database.Significance. An improved EPID calibration to allow off-axis measurement maximises the number of patients eligible for IVD (36.8% of patients in this study). We also demonstrate the importance in selecting context-specific assessment metrics and how these can lead to a managable false positive rate. We have shown that the use of fully automated IVD facilitates use on every fraction of treatment. This leads to identification of areas for treatment improvement for both individuals and across a patient cohort, expanding the uses of IVD from simply gross error detection towards treatment optimisation.

Evaluation of the RadCalc collapsed cone dose calculation algorithm against measured data.

This work describes the experimental validation of the RadCalc (Lifeline software Inc, Tyler) collapsed cone dose calculation algorithm against measured data for a range of scenarios. 6 MV photon beam data were measured in a large water tank on a Varian TrueBeam linear accelerator. These were input into the RadCalc software, in conjunction with head geometry and output calibration information, then used to create a collapsed cone beam model. The model performance was assessed by comparison against measurement, using a selection of homogeneous and inhomogeneous geometries not incorporated into the original beam model. Dose calculations generated using the collapsed cone algorithm are generally in good agreement with measurement. However, the primary collimating of the linac is not accounted for in the RadCalc model and hence dose in the corners of large fields is significantly overestimated. Percentage depth doses were within 0.5% beyond a depth of 2 cm. The dose in the build-up region was underestimated by RadCalc Version 7.1.4.1, with (Distance To Agreement) discrepancies of up to 3 mm which were corrected in Version 7.2.2.0. Beam profiles for homogeneous phantom comparisons were within 2% in the central 80% of the field with out of field dose underestimated by no more than 3%. Dose comparisons in heterogeneous geometries were acceptable and generally within 3.5%. The largest observed differences were found at density interfaces and a result of the RadCalc dose resolution of 2 mm against 1 mm measured. Absolute dose comparisons demonstrated that RadCalc agreed with measurement to within 1.2% under homogeneous media irradiation geometries. For static beam IMRT deliveries agreement was within 2% or 2 mm of measured data, and for complex VMAT deliveries within 3% or 2 mm. The implementation of the (model-based) photon collapsed cone algorithm in RadCalc shows generally good agreement with measured data over a range of simple and complex scenarios considered.