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Background: Surface‐guided radiation therapy (SGRT) systems have been widely installed and utilized on linear accelerators. However, the use of SGRT with proton therapy is still a newly developing field, and published reports are currently very limited. Purpose: To assess the clinical application and alignment agreement of SGRT with CT‐on‐rails (CTOR) and kV‐2D image‐guided radiation therapy (IGRT) for breast treatment using proton therapy. Methods: Four patients receiving breast or chest wall treatment with proton therapy were the subjects of this study. Patient #1′s IGRT modalities were a combination of kV‐2D and CTOR. CTOR was the only imaging modality for patients #2 and #3, and kV‐2D was the only imaging modality for patient #4. The patients' respiratory motions were assessed using a 2‐min surface position recorded by the SGRT system during treatment. SGRT offsets reported after IGRT shifts were recorded for each fraction of treatment. The agreement between SGRT and either kV‐2D or CTOR was evaluated. Results: The respiratory motion amplitude was <4 mm in translation and <2.0° in rotation for all patients. The mean and maximum amplitude of SGRT offsets after application of IGRT shifts were ≤(2.6 mm, 1.6°) and (6.8 mm, 4.5°) relative to kV‐2D‐based IGRT; ≤(3.0 mm, 2.6°) and (5.0 mm, 4.7°) relative to CTOR‐based IGRT without breast tissue inflammation. For patient #3, breast inflammation was observed for the last three fractions of treatment, and the maximum SGRT offsets post CTOR shifts were up to (14.0 mm, 5.2°). Conclusions: Due to the overall agreement between SGRT and IGRT within reasonable tolerance, SGRT has the potential to serve as a valuable auxiliary IGRT tool for proton breast treatment and may improve the efficiency of proton breast treatment. [ABSTRACT FROM AUTHOR]

Background: It has been shown that a significant reduction of mean heart dose and left anterior descending artery (LAD) dose can be achieved through the use of DIBH for left breast radiation therapy. Surface‐guided DIBH has been widely adopted during the last decade, and there are mainly three commercially available SGRT systems. The reports of the performance of a newly released SGRT system for DIBH application are currently very limited. Purpose: To evaluate the clinical performance of a newly released SGRT system on DIBH for left breast radiation therapy. Methods: Twenty‐five left breast cancer patients treated with DIBH utilizing Varian's Identify system were included (total 493‐fraction treatments). Four aspects of the clinical performance were evaluated: Identify offsets of free breathing post patient setup from tattoos, Identify offsets during DIBH, Identify agreement with radiographic ports during DIBH, and DIBH reference surface re‐capture post patient shifts. The systematic and random errors of free breathing Identify offsets post patient setup were calculated for each patient, as well as for offsets during DIBH. Radiographic ports were taken when the patient's DIBH position was within the clinical tolerance of (± 0.3 cm, ± 30), and these were then compared with treatment field DRRs. If the ports showed that the patient alignment did not agree with the DRRs within 3 mm, a patient shift was performed. A new reference surface was captured and verification ports were taken. Results: The all‐patient average systematic and random errors of Identify offsets for free breathing were within (0.4 cm, 1.50) post tattoo setup. The maximum per‐patient systematic and random errors were (1.1 cm, 6.20) and (0.9 cm, 20), and the maximum amplitude of Identify offsets were (2.59 cm, 90). All 493‐fraction DIBH treatments were delivered and successfully guided by the Identify SGRT system. The systematic and random errors of Identify offsets for DIBH were within (0.2 cm, 2.30). Seven patients needed re‐captured surface references due to surface variation or position shifts based on the ports. All patient DIBH verification ports guided by Identify were approved by attending physicians. Conclusion: This evaluation showed that the Identify system performed effectively for surface‐guided patient setup and surface‐guided DIBH imaging and treatment delivery. The feature of color‐coded real‐time patient surface matching feedback facilitated the evaluation of the patient alignment accuracy and the adjustment of the patient position to match the reference. [ABSTRACT FROM AUTHOR]

Purpose: Surface‐guided radiation therapy (SGRT) is a nonionizing imaging approach for patient setup guidance, intra‐fraction monitoring, and automated breath‐hold gating of radiation treatments. SGRT employs the premise that the external patient surface correlates to the internal anatomy, to infer the treatment isocenter position at time of treatment delivery. Deformations and posture variations are known to impact the correlation between external and internal anatomy. However, the degree, magnitude, and algorithm dependence of this impact are not intuitive and currently no methods exist to assess this relationship. The primary aim of this work was to develop a framework to investigate and understand how a commercial optical surface imaging system (C‐RAD, Uppsala, Sweden), which uses a nonrigid registration algorithm, handles rotations and surface deformations. Methods: A workflow consisting of a female torso phantom and software‐introduced transformations to the corresponding digital reference surface was developed. To benchmark and validate the approach, known rigid translations and rotations were first applied. Relevant breast radiotherapy deformations related to breast size, hunching/arching back, distended/deflated abdomen, and an irregular surface to mimic a cover sheet over the lower part of the torso were investigated. The difference between rigid and deformed surfaces was evaluated as a function of isocenter location. Results: For all introduced rigid body transformations, C‐RAD computed isocenter shifts were determined within 1 mm and 1˚. Additional translational shifts to correct for rotations as a function of isocenter location were determined with the same accuracy. For yaw setup errors, the difference in shift corrections between a plan with an isocenter placed in the center of the breast (BrstIso) and one located 12 cm superiorly (SCFIso) was 2.3 mm/1˚ in lateral direction. Pitch setup errors resulted in a difference of 2.1 mm/1˚ in vertical direction. For some of the deformation scenarios, much larger differences up to 16 mm and 7˚ in the calculated shifts between BrstIso and SCFIso were observed that could lead to large unintended gaps or overlap between adjacent matched fields if uncorrected. Conclusions: The methodology developed lends itself well for quality assurance (QA) of SGRT systems. The deformable C‐RAD algorithm determined accurate shifts for rigid transformations, and this was independent of isocenter location. For surface deformations, the position of the isocenter had considerable impact on the registration result. It is recommended to avoid off‐axis isocenters during treatment planning to optimally utilize the capabilities of the deformable image registration algorithm, especially when multiple isocenters are used with fields that share a field edge. [ABSTRACT FROM AUTHOR]