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Background and purpose When treating lung tumors with stereotactic body radiation therapy (SBRT), patient immobilization is of outmost importance. In this study, the intra‐fractional shifts of the patient (based on bony anatomy) and the tumor (based on the visible target volume) are quantified, and the associated impact on the delivered dose is estimated for a frameless immobilization approach in combination with surface guided radiation therapy (SGRT) monitoring. Methods Cone beam computed tomographies (CBCT) were collected in free breathing prior and after each treatment for 25 patients with lung tumors, in total 137 fractions. The CBCT collected after each treatment was registered to the CBCT collected before each treatment with focus on bony anatomy to determine the shift of the patient, and with focus on the visible target volume to determine the shift of the tumor. Rigid registrations with 6 degrees of freedom were used. The patients were positioned in frameless immobilizations with their position and respiration continuously monitored by a commercial SGRT system. The patients were breathing freely within a preset gating window during treatment delivery. The beam was automatically interrupted if isocenter shifts >4 mm or breathing amplitudes outside the gating window were detected by the SGRT system. The time between the acquisition of the CBCTs was registered for each fraction to examine correlations between treatment time and patient shift. The impact of the observed shifts on the dose to organs at risk (OAR) and the gross tumor volume (GTV) was assessed. Results The shift of the patient in the CBCTs was ≤2 mm for 132/137 fractions in the vertical (vrt) and lateral (lat) directions, and 134/137 fractions in the longitudinal (lng) direction and ≤4 mm in 134/137 (vrt) and 137/137 (lat, lng) of the fractions. The shift of the tumor was ≤2 mm in 116/137 (vrt), 123/137 (lat) and 115/137 (lng) fractions and ≤4 mm in 136/137 (vrt), 137/137 (lat), and 135/137 (lng) fractions. The maximal observed shift in the evaluated CBCT data was 4.6 mm for the patient and 7.2 mm for the tumor. Rotations were ≤3.3ᵒ for all fractions and the mean/standard deviation were 0.2/1.0ᵒ (roll), 0.1/0.8ᵒ (yaw), and 0.3/1.0ᵒ (pitch). The SGRT system interrupted the beam due to intra‐fractional isocenter shifts >4 mm for 21% of the fractions, but the patients always returned within tolerance without the need of repositioning. The maximal observed isocenter shift by the SGRT system during the beam holds was 8 mm. For the respiration monitoring, the beam was interrupted at least one time for 54% of the fractions. The visual tumor was within the planned internal target volume (ITV) for 136/137 fractions in the evaluated CBCT data collected at the end of each fraction. For the fraction where the tumor was outside the ITV, the D98% for the GTV decreased with 0.4 Gy. For the OARs, the difference between planned and estimated dose from the CBCT data (D2% or Dmean) was ≤2.6% of the prescribed PTV dose. No correlation was found between treatment time and the magnitude of the patient shift. Conclusions Using SGRT for motion management and respiration monitoring in combination with a frameless immobilization is a feasible approach for lung SBRT.

Purpose Surface guided radiotherapy (SGRT) is reported as a feasible setup technique for whole‐breast radiotherapy in deep inspiration breath hold (DIBH), but position errors of bony structures related to deeper parts of the target are not fully known. The aim of this study was to estimate patient setup accuracy and margins obtained with two different SGRT workflows with and without daily kV‐ and/or MV‐based image guidance (IGRT). Methods A total of 50 breast cancer patients were treated in DIBH, using SGRT for the patient setup, and IGRT for isocenter corrections. The patients were treated at two different departments, one using AlignRT® (25 patients) and the other using Catalyst™ (25 patients). Inter‐fractional position errors were analyzed retrospectively in orthogonal and tangential setup images, and analyzed with and without IGRT. Results In the orthogonal kV‐kV images, the systematic residual errors of the bony structures were ≤ 3 mm in both groups with SGRT‐only. When fine‐adjusted by daily IGRT, the errors decreased to ≤ 2 mm; except for the shoulder joint. The residual errors of the ribs in tangential images were between 1 and 2 mm with both workflows. The heart planning margins were between 3 and 7 mm. Conclusions The frequency of IGRT may be considerably reduced with a well‐planned SGRT‐workflow for whole‐breast DIBH with residual errors ≤ 3 mm. This accuracy can be further improved with an IGRT scheme.

Purpose Evaluate the performance of three commercial deformable image registration (DIR) solutions on computed tomography (CT) image-series of the thorax. Methods DIRs were performed on CT image-series of a thorax phantom with tumor inserts and on six 4-dimensional patient CT image-series of the thorax. The center of mass shift (CMS), dice similarity coefficient (DSC) and dose-volume-histogram (DVH) parameters were used to evaluate the accuracy. Dose calculations on deformed patient images were compared to calculations on un-deformed images for the gross tumor volume (GTV) (Dmean, D98%), lung (V20Gy, V12Gy), heart and spinal cord (D2%). Results Phantom structures with constant volume and shifts ≤30 mm were reproduced with visually acceptable accuracy (DSC ≥ 0.91, CMS ≤ 0.9 mm) for all software solutions. Deformations including volume changes were less accurate with 9/12 DIRs considered visually unacceptable. In patients, organs were reproduced with DSC ≥ 0.83. GTV shifts ≤1.6 cm were reproduced with visually acceptable accuracy by all software while larger shifts resulted in failures for at least one of the software. In total, the best software succeeded in 18/25 DIRs while the worst succeeded in 12/25 DIRs. Visually acceptable DIRs resulted in deviations ≤3.0% of the prescribed dose and ≤3.6% of the total structure volume in the evaluated DVH-parameters. Conclusions The take home message from the results of this study is the importance to have a visually acceptable registration. DSC and CMS are not predictive of the associated dose deviation. Visually acceptable DIRs implied dose deviations ≤3.0%.

Purpose Evaluate the performance of three commercial deformable image registration (DIR) algorithms for computed tomography (CT) images of the thorax. Methods Deformable registrations were performed on CT-images of a thorax phantom with tumor inserts and on six 4-dimensional patient CT-series of the thorax. For each DIR the shape and position of the deformed structures and the corresponding structures in the target image that the DIRs were set to reproduce, were compared for shifts between 0–53 mm. Two quantitative measures were used, the center of mass shift (CMS) and the Dice Similarity Coefficient (DSC) as well as visual examination of the registered images. Dose calculations on the deformed patient images were compared to calculations on the un-deformed target images for the gross tumor volume (GTV) (mean dose and D98%), lung (V20Gy, V12Gy), heart and spinal cord (D2%). Results In phantoms, moving structures with constant volume and shifts ⩽30 mm were reproduced with DSC⩾0.91 and CMS⩽0.9 mm by all the algorithms. For shifts >30 mm two algorithms failed. Deformations including volume changes were less accurate with 3/12 and 9/12 DIRs considered visually unacceptable, corresponding to CMS>2.0 mm and DSC Conclusions Visually acceptable DIRs were achievable for moving structures with constant volume and shifts ⩽30 mm in phantoms and shifts⩽16 mm in patients. Visually acceptable DIRs implied dose deviations ⩽3.6 percentage units on patient CT-images of the thorax region.

Background Respiratory-induced lung tumor motion may decrease robustness and outcome of radiation therapy (RT) if not accounted for. This study provides detailed information on the motion distribution of lung tumors for a group of 126 patients treated with stereotactic body RT. Material and methods Four-dimensional computed tomography scans were reviewed to assess lung tumor motion. The tumor motion was determined by the center of mass shift based on a rigid registration of the breathing phases containing the largest positional differences in the inferior-superior (IS), left-right (LR), and anterior-posterior (AP) directions. The patients were divided into subgroups depending on tumor diameter (φ 5.0 cm) and tumor location within the lung (upper, middle, or lower lobe). The observed motion distributions were evaluated for each group separately to assess the dependence on tumor size and location. For each tumor size, the motion pattern in each direction (IS, LR, and AP) was analyzed for every tumor moving >5 mm. Sinusoidal trigonometric functions were fitted to the measured data using the least mean square method to determine which type of function best describes the motion pattern. Tumor volumes between 1.6 and 52.3 cm3 were evaluated. Mann-Whitney statistical tests were used for statistical analyses. Results The mean amplitude for the tumors in this study was 1.5 mm (LR), 2.5 mm (AP), and 6.9 mm (IS) while the maximum amplitude was 11.0 mm (LR), 9.0 mm (AP), and 53.0 mm (IS). In total, 95% of the tumors moved ≤20 mm in the IS direction, ≤3 mm in the LR direction, and ≤6 mm in the AP direction. The observed motion distributions showed no statistically significant correlation with tumor size or location within the lung except for motion in the IS direction, where the mean and maximum amplitudes significantly increased for tumors located in the middle and lower parts of the lung. The motion pattern of a tumor in any direction was best described using a squared trigonometric function of the type [Formula: see text], where A is the maximum amplitude of the motion in the current direction, t is the time of measurement, T is the total time of the breathing cycle and B is a constant used to synchronize the starting point of the breathing cycle. Conclusion Lung tumor movements were generally larger in the IS direction and the motion amplitude in this direction increased for tumors located in the middle and lower parts of the lungs. Motions in LR or AP showed no such relation. Tumor size was not found to have any correlation with the motion amplitude in any direction. The motion pattern of a lung tumor in any direction is best described with a squared sinusoidal function independently of the tumor size or tumor location.