ABSTRACT
BACKGROUND: Arc therapy allows for better dose deposition conformation, but the radiotherapy plans (RT plans) are more complex, requiring patient-specific pre-treatment quality assurance (QA). In turn, pre-treatment QA adds to the workload. The objective of this study was to develop a predictive model of Delta4-QA results based on RT-plan complexity indices to reduce QA workload. METHODS: Six complexity indices were extracted from 1632 RT VMAT plans. A machine learning (ML) model was developed for classification purpose (two classes: compliance with the QA plan or not). For more complex locations (breast, pelvis and head and neck), innovative deep hybrid learning (DHL) was trained to achieve better performance. RESULTS: For not complex RT plans (with brain and thorax tumor locations), the ML model achieved 100% specificity and 98.9% sensitivity. However, for more complex RT plans, specificity falls to 87%. For these complex RT plans, an innovative QA classification method using DHL was developed and achieved a sensitivity of 100% and a specificity of 97.72%. CONCLUSIONS: The ML and DHL models predicted QA results with a high degree of accuracy. Our predictive QA online platform is offering substantial time savings in terms of accelerator occupancy and working time.
ABSTRACT
PURPOSE: Static beam intensity-modulated-radiation-therapy (IMRT) and/or Volumetric-Modulated-Arc-Therapy (VMAT) are now available in many regional radiotherapy departments. The aim of this multi-institutional audit was to design a new methodology based on radiochromic films to perform an independent quality control. METHODS: A set of data were sent to all participating centres for two clinical localizations: prostate and Head and Neck (H&N) cancers. The agreement between calculations and measurements was verified in the Octavius phantom (PTW) by point measurements using ionization chambers and by 2D measurements using EBT3 radiochromic films. Due to uncertainties in the whole procedure, criteria were set to 5% and 3% in local dose and 3mm in distance excluding doses lower than 10% of the maximum doses. No normalization point or area was used for the quantitative analysis. RESULTS: 13 radiotherapy centres participated in this audit involving 28 plans (12 IMRT, 16 VMAT). For point measurements, mean errors were -0.18±1.54% and 0.00±1.58% for prostate and H&N cases respectively. For 2D measurements with 5%/3mm criteria, gamma map analysis showed a pixel pass rate higher than 95% for prostate and H&N. Mean gamma index was lower than 0.4 for prostate and 0.5 for H&N. Both techniques yielded similar results. CONCLUSION: This study showed the feasibility of an independent quality control by peers for conventional IMRT and VMAT. Results from all participating centres were found to be in good agreement. This regional study demonstrated the feasibility of our new methodology based on radiochromic films without dose normalization on a specific point.
