Application of failure mode and effects analysis to validate a novel hybrid Linac QC program that integrates automated and conventional QC testing.

A hybrid quality control (QC) program was developed that integrates automated and conventional Linac QC, realizing the benefits of both automated and conventional QC, increasing efficiency and maintaining independent measurement methods. Failure mode and effects analysis (FMEA) was then applied in order to validate the program prior to clinical implementation. The hybrid QC program consists of automated QC with machine performance check and DailyQA3 array on the TrueBeam Linac, and Delta4 volumetric modulated arc therapy (VMAT) standard plan measurements, alongside conventional monthly QC at a reduced frequency. The FMEA followed the method outlined in TG-100. Process maps were created for each treatment type at our center: VMAT, stereotactic body radiotherapy (SBRT), conformal, and palliative. Possible failure modes were established by evaluating each stage in the process map. The FMEA followed semiquantitative methods, using data from our QC records from eight Linacs over 3 years for the occurrence estimates, and simulation of failure modes in the treatment planning system, with scoring surveys for severity and detectability. The risk priority number (RPN) was calculated from the product of the occurrence, severity, and detectability scores and then normalized to the maximum and ranked to determine the most critical failure modes. The highest normalized RPN values (100, 90) were found to be for MLC position dynamic for both VMAT and SBRT treatments. The next highest score was 35 for beam position for SBRT, and the majority of scores were less than 20. Overall, these RPN scores for the hybrid Linac QC program indicated that it would be acceptable, but the high RPN score associated with the dynamic MLC failure mode indicates that it would be valuable to perform more rigorous testing of the MLC. The FMEA proved to be a useful tool in validating hybrid QC.

Long-term experience of MPC across multiple TrueBeam linacs: MPC concordance with conventional QC and sensitivity to real-world faults.

Machine Performance Check (MPC) is an automated Quality Control (QC) tool that is integrated into the TrueBeam and Halcyon linear accelerators (Linacs), utilizing the imaging systems to verify the Linac beam and geometry. This work compares the concordance of daily MPC results with conventional QC tests over a 3-year period for eight Linacs in order to assess the sensitivity of MPC in detecting faults. The MPC output measurements were compared with the monthly ionization chamber measurements for 6 and 10 MV photon beams and 6, 9, 12, 16, and 18 MeV electron beams. All 6 MV Beam and Geometry (6MVBG) MPC test failures were analyzed to determine the failure rate and the number of true and false negative results, using the conventional QC record as the reference. The concordance between conventional QC test failures and MPC test failures was investigated. The mean agreement across 1933 MPC output and monthly comparison chamber measurements for all beam energies was 0.2%, with 97.8% within 1.5%, and a maximum difference of 2.9%. Of the 5000-6000 MPC individual test parameter results for the 6MVBG test, the highest failure rate was BeamOutputChange (0.5%), then BeamCenterShift (0.3%), and was ≤ 0.1% for the remaining parameters. There were 50 true negative and 27 false negative out of tolerance MPC results, with false negatives resolved by repeating MPC or by independent measurement. The analysis of conventional QC failures demonstrated that MPC detected all failures, except occasions when MPC reported output within tolerance, a result of the MPC-chamber response variation. The variation in MPC output versus chamber measurement indicates MPC is appropriate for daily output constancy but not for the measurement of absolute output. The comparison of the 6MVBG results and conventional records provides evidence that MPC is a sensitive method of performing beam and mechanical checks in a clinical setting.

Effect of synthetic CT on dose-derived toxicity predictors for MR-only prostate radiotherapy.

Objectives: Toxicity-driven adaptive radiotherapy (RT) is enhanced by the superior soft tissue contrast of magnetic resonance (MR) imaging compared with conventional computed tomography (CT). However, in an MR-only RT pathway synthetic CTs (sCT) are required for dose calculation. This study evaluates 3 sCT approaches for accurate rectal toxicity prediction in prostate RT. Methods: Thirty-six patients had MR (T2-weighted acquisition optimized for anatomical delineation, and T1-Dixon) with same day standard-of-care planning CT for prostate RT. Multiple sCT were created per patient using bulk density (BD), tissue stratification (TS, from T1-Dixon) and deep-learning (DL) artificial intelligence (AI) (from T2-weighted) approaches for dose distribution calculation and creation of rectal dose volume histograms (DVH) and dose surface maps (DSM) to assess grade-2 (G2) rectal bleeding risk. Results: Maximum absolute errors using sCT for DVH-based G2 rectal bleeding risk (risk range 1.6% to 6.1%) were 0.6% (BD), 0.3% (TS) and 0.1% (DL). DSM-derived risk prediction errors followed a similar pattern. DL sCT has voxel-wise density generated from T2-weighted MR and improved accuracy for both risk-prediction methods. Conclusions: DL improves dosimetric and predicted risk calculation accuracy. Both TS and DL methods are clinically suitable for sCT generation in toxicity-guided RT, however, DL offers increased accuracy and offers efficiencies by removing the need for T1-Dixon MR. Advances in knowledge: This study demonstrates novel insights regarding the effect of sCT on predictive toxicity metrics, demonstrating clear accuracy improvement with increased sCT resolution. Accuracy of toxicity calculation in MR-only RT should be assessed for all treatment sites where dose to critical structures will guide adaptive-RT strategies. Clinical trial registration number: Patient data were taken from an ethically approved (UK Health Research Authority) clinical trial run at Guy's and St Thomas' NHS Foundation Trust. Study Name: MR-simulation in Radiotherapy for Prostate Cancer. ClinicalTrials.gov Identifier: NCT03238170.

Neural network dose prediction for rectal spacer stratification in dose-escalated prostate radiotherapy.

PURPOSE: To develop a knowledge-based decision-support system capable of stratifying patients for rectal spacer (RS) insertion based on neural network predicted rectal dose, reducing the need for time- and resource-intensive radiotherapy (RT) planning. METHODS: Forty-four patients treated for prostate cancer were enrolled into a clinical trial (NCT03238170). Dose-escalated prostate RT plans were manually created for 30 patients with simulated boost volumes using a conventional treatment planning system (TPS) and used to train a hierarchically dense 3D convolutional neural network to rapidly predict RT dose distributions. The network was used to predict rectal doses for 14 unseen test patients, with associated toxicity risks calculated according to published data. All metrics obtained using the network were compared to conventionally planned values. RESULTS: The neural network stratified patients with an accuracy of 100% based on optimal rectal dose-volume histogram constraints and 78.6% based on mandatory constraints. The network predicted dose-derived grade 2 rectal bleeding risk within 95% confidence limits of -1.9% to +1.7% of conventional risk estimates (risk range 3.5%-9.9%) and late grade 2 fecal incontinence risk within -0.8% to +1.5% (risk range 2.3%-5.7%). Prediction of high-resolution 3D dose distributions took 0.7 s. CONCLUSIONS: The feasibility of using a neural network to provide rapid decision support for RS insertion prior to RT has been demonstrated, and the potential for time and resource savings highlighted. Directly after target and healthy tissue delineation, the network is able to (i) risk stratify most patients with a high degree of accuracy to prioritize which patients would likely derive greatest benefit from RS insertion and (ii) identify patients close to the stratification threshold who would require conventional planning.

Guidance on the use of MRI for treatment planning in radiotherapy clinical trials.

The aim of this article is to propose meaningful guidance covering the technical and safety issues involved when designing or conducting radiotherapy clinical trials that use MRI for treatment planning. The complexity of imaging requirements will depend on the trial aims, design and MRI methods used.The use of MRI within the RT pathway is becoming more prevalent and clinically appropriate as access to MRI increases, treatment planning systems become more versatile and potential indications for MRI-planning in RT are documented. Novel MRI-planning opportunities are often initiated and validated within clinical trials.The guidance in this document is intended to assist researchers designing RT clinical trials involving MRI, so that they may provide sufficient information about the appropriate methods to be used for image acquisition, post-processing and quality assurance such that participating sites complete MRI to consistent standards. It has been produced in collaboration with the National Radiotherapy Trials Quality Assurance Group (RTTQA).As the use of MRI in RT is developed, it is highly recommended for researchers writing clinical trial protocols to include imaging guidance as part of their clinical trial documentation covering the trial-specific requirements for MRI procedures. Many of the considerations and recommendations in this guidance may well apply to MR-guided treatment machines, where clinical trials will be crucial. Similarly, many of these recommendations will apply to the general use of MRI in RT, outside of clinical trials.This document contains a large number of recommendations, not all of which will be relevant to any particular trial. Designers of RT clinical trials must therefore take this into account. They must also use their own judgement as to the appropriate compromise between accessibility of the trial and its technical rigour.

Guidance on the use of PET for treatment planning in radiotherapy clinical trials.

The aim of this article is to propose meaningful guidance covering the practical and technical issues involved when planning or conducting clinical trials involving positron emission tomography (PET)-guided radiotherapy. The complexity of imaging requirements will depend on the study aims, design and PET methods used. Where PET is used to adapt radiotherapy, a high level of accuracy and reproducibility is required to ensure effective and safe treatment delivery. The guidance in this document is intended to assist researchers designing clinical trials involving PET-guided radiotherapy to provide sufficient information about the appropriate methods to complete PET-CT imaging to a consistent standard at participating centres. The guidance is divided into six categories: application of PET in radiotherapy, resource requirements, quality assurance, imaging protocol design, data management and image processing. Each section provides an overview of the recent literature to support the specific recommendations. This guidance builds on previous recommendations from the National Cancer Research Institute PET Research Network and has been produced in collaboration with the National Radiotherapy Trials Quality Assurance Group.