IntroductionTo compare the differences in setup errors measured with electronic portal image (EPI) and cone‐beam computed tomography (CBCT) in patients undergoing tangential breast radiotherapy (RT). Relationship between setup errors, body mass index (BMI) and breast size was assessed.MethodsTwenty‐five patients undergoing postoperative RT to the breast were consented for this study. Weekly CBCT scans were acquired and retrospectively registered to the planning CT in three dimensions, first using bony anatomy for bony registration (CBCT‐B) and again using breast tissue outline for soft tissue registration (CBCT‐S). Digitally reconstructed radiographs (DRR) generated from CBCT to simulate EPI were compared to the planning DRR using bony anatomy in the V (parallel to the cranio‐caudal axis) and U (perpendicular to V) planes. The systematic (Σ) and random (σ) errors were calculated and correlated with BMI and breast size.ResultsThe systematic and random errors for EPI (Σ
V = 3.7 mm, Σ
U = 2.8 mm and σ
V = 2.9 mm, σ
U = 2.5) and CBCT‐B (Σ
V = 3.5 mm, Σ
U = 3.4 mm and σ
V = 2.8 mm, σ
U = 2.8) were of similar magnitude in the V and U planes. Similarly, the differences in setup errors for CBCT‐B and CBCT‐S in three dimensions were less than 1 mm. Only CBCT‐S setup error correlated with BMI and breast size.Conclusions
CBCT and EPI show insignificant variation in their ability to detect setup error. These findings suggest no significant differences that would make one modality considered superior over the other and EPI should remain the standard of care for most patients. However, there is a correlation with breast size, BMI and setup error as detected by CBCT‐S, justifying the use of CBCT‐S for larger patients.
Image registration is a process that underlies many new techniques in radiation oncologyfrom multimodal imaging and contour propagation in treatment planning to dose accumulation throughout treatment. Deformable image registration (DIR) is a subset of image registration subject to high levels of complexity in process and validation. A need for local guidance to assist in high-quality utilisation and best practice was identified within the Australian community, leading to collaborative activity and workshops. This report communicates the current limitations and best practice advice from early adopters to help guide those implementing DIR in the clinic at this early stage. They are based on the state of image registration applications in radiotherapy in Australia and New Zealand (ANZ), and consensus discussions made at the 'Deforming to Best Practice' workshops in 2018. The current status of clinical application use cases is presented, including multimodal imaging, automatic segmentation, adaptive radiotherapy, retreatment, dose accumulation and response assessment, along with uptake, accuracy and limitations. Key areas of concern and preliminary suggestions for commissioning, quality assurance, education and training, and the use of automation are also reported. Many questions remain, and the radiotherapy community will benefit from continued research in this area. However, DIR is available to clinics and this report is intended to aid departments using or about to use DIR tools now.
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