Purpose: Breast cancer radiotherapy delivered using voluntary deep inspiration breath‐hold (DIBH) requires reproducible breath holds, particularly when matching supraclavicular fields to tangential fields. We studied the impact of variation in DIBHs on CTV and OAR dose metrics by comparing the dose distribution computed on two DIBH CT scans taken at the time of simulation. Methods: Ten patients receiving 50Gy in 25 fractions to the left chestwall and regional lymph nodes were studied. Two simulation CT scans were taken during separate DIBHs along with a free‐breathing (FB) scan. The treatment was planned using one DIBH CT. The dose was recomputed on the other two scans using adaptive planning (Pinnacle 9.10) in which the scans are registered using a cross‐correlation algorithm. The chestwall, lymph nodes and OARs were contoured on the scans following the RTOG consensus guidelines. The overall translational and rotational variation between the DIBH scans was used to estimate positional variation between breath‐holds. Dose metrics between plans were compared using paired t‐tests (p < 0.05) and means and standard deviations were reported. Results: The registration parameters were sub‐millimeter and sub‐degree. Although DIBH significantly reduced mean heart dose by 2.4Gy compared to FB (p < 0.01), no significant changes in dose were observed for targets or OARs between the two DIBH scans. Nodal coverage as assessed by V90% was 90%±8% and 89%±8% for supraclavicular and 99%±2% and 97%±22% for IM nodes. Though a significant decrease (10.5%±12.4%) in lung volume in the second DIBH CT was observed, the lung V20Gy was unchanged (14±2% and 14±3%) between the two DIBH scans. Conclusion: While the lung volume often varied between DIBHs, the CTV and OAR dose metrics were largely unchanged. This indicates that manual DIBH has the potential to provide consistent dose delivery to the chestwall and regional nodes targets when using matched fields.
Purpose: Compares surface imaging (SI) to MV films for positioning of 13 patients receiving whole‐breast irradiation. Methods: AlignRT v5.0 was used to capture non‐gated, 3D surface images during filmed fractions (n=55) after positioning with skin marks and correction for rotations. Registrations of SI to a reference surface, generated from 3mm‐thick CT data, were analyzed off‐line for both the “entire” and the “breast” regions. MV films were compared to digitally‐reconstructed radiographs generated from the same CT dataset. The group mean, systematic error (σ), and random error (g) were calculated for positioning with MV and SI both before and after positioning correction. The 95% limits of agreement (LOA) were used for statistical comparisons. Results: Inter‐fraction systematic/random errors calculated from MV filming were 1.6/2.1mm (Anterior‐Posterior), 2.9/3.0mm (Cranio‐Caudal), and 2.4/4.1mm (Left‐Right), resulting in a setup margin of 5.5/9.4/9.0mm in AP/CC/LR dimensions using the van Herk formulation. Registering the “entire” and “breast” surfaces acquired before MV positioning correction resulted in setup margins that were larger by 1.6– 3.3mm in AP/LR but smaller by 0.4–0.6mm in CC direction, thereby indicating comparable inter‐fraction errors. After positioning with films, group means for the “entire” surface decreased by 0.5–2mm and the systematic/random errors decreased by 0.3–0.9mm. In contrast, group mean for “breast” increased in the CC direction. The LOA showed large discrepancies between the two modalities (smallest:‐3.5 to 10.3mm along AP for “entire”, largest:‐11.3 to 9.9mm along CC for “breast”). Conclusion: This study shows that the two modalities provide comparable systematic/random errors for breast positioning. However, MV positioning of bony anatomy led to a consistent cranio‐caudal offset (i.e., larger group mean) from the position indicated by AlignRT probably due to deformation of the breast tissue. These results suggest that the use of MV and SI should be integrated to ensure simultaneous coverage of chestwall and soft tissue targets.
Recent use of HDR has increased while planning has become more complex often necessitating 3D image‐based planning. While many guidelines for the use of HDR exist, they have not kept pace with the increased complexity of 3D image‐based planning. Furthermore, no comprehensive document exists to describe the wide variety of current HDR clinical indications. This educational session aims to summarize existing national and international guidelines for the safe implementation of an HDR program. A summary of HDR afterloaders available on the market and their existing applicators will be provided, with guidance on how to select the best fit for each institution's needs. Finally, the use of checklists will be discussed as a means to implement a safe and efficient HDR program and as a method by which to verify the quality of an existing HDR program. This session will provide the perspective of expert HDR physicists as well as the perspective of a new HDR user. Learning Objectives: Summarize national and international safety and staffing guidelines for HDR implementation Discuss the process of afterloader and applicator selection for gynecologic, prostate, breast, interstitial, surface treatments Learn about the use of an audit checklist tool to measure of quality control of a new or existing HDR program Describe the evolving use of checklists within an HDR program
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