UNASSIGNED: Dynamic trajectory radiotherapy (DTRT) has been shown to improve healthy tissue sparing compared to volumetric arc therapy (VMAT). This study aimed to assess and compare the robustness of DTRT and VMAT treatment-plans for head and neck (H&N) cancer to patient-setup (PS) and machine-positioning uncertainties.
UNASSIGNED: The robustness of DTRT and VMAT plans previously created for 46 H&N cases, prescribed 50-70 Gy to 95 % of the planning-target-volume, was assessed. For this purpose, dose distributions were recalculated using Monte Carlo, including uncertainties in PS (translation and rotation) and machine-positioning (gantry-, table-, collimator-rotation and multi-leaf collimator (MLC)). Plan robustness was evaluated by the uncertainties\' impact on normal tissue complication probabilities (NTCP) for xerostomia and dysphagia and on dose-volume endpoints. Differences between DTRT and VMAT plan robustness were compared using Wilcoxon matched-pair signed-rank test (α = 5 %).
UNASSIGNED: Average NTCP for moderate-to-severe xerostomia and grade ≥ II dysphagia was lower for DTRT than VMAT in the nominal scenario (0.5 %, p = 0.01; 2.1 %, p < 0.01) and for all investigated uncertainties, except MLC positioning, where the difference was not significant. Average differences compared to the nominal scenario were ≤ 3.5 Gy for rotational PS (≤ 3°) and machine-positioning (≤ 2°) uncertainties, <7 Gy for translational PS uncertainties (≤ 5 mm) and < 20 Gy for MLC-positioning uncertainties (≤ 5 mm).
UNASSIGNED: DTRT and VMAT plan robustness to the investigated uncertainties depended on uncertainty direction and location of the structure-of-interest to the target. NTCP remained on average lower for DTRT than VMAT even when considering uncertainties.

BACKGROUND: The dosimetric effect of setup uncertainty and tissue deformations in left-sided whole-breast irradiation with complementary surface-guided radiotherapy (SGRT) and cone-beam computed tomography (CBCT) setup was evaluated.
METHODS: Treatment courses of 40.05 Gy prescribed dose in 15 fractions were simulated for 29 patients by calculating the dose on deformed CT images, that were based on daily CBCT images, and deforming and accumulating the dose onto the planning CT image. Variability in clinical target volume (CTV) position and shape was assessed as the 95% Hausdorff distance (HD95) between the planning CTV and deformed CTV structures. DVH metrics were evaluated between the planned and simulated cumulative dose distributions using two treatment techniques: tangential volumetric modulated arc therapy (tVMAT) and conventional 3D-conformal radiotherapy (3D-CRT).
RESULTS: Based on the HD95 values, the variations in CTV shape and position were enclosed by the 5 mm CTV-PTV margin in 85% of treatment fractions using complementary CBCT and SGRT setup. A residual error of 8.6 mm was observed between the initial SGRT setup and CBCT setup. The median CTV V95% coverage was 98.1% (range 93.1-99.8%) with tVMAT and 98.2% (range 84.5-99.7%) with 3D-CRT techniques with CBCT setup. With the initial SGRT-only setup, the corresponding coverages were 96.3% (range 92.6-99.4%) and 96.6% (range 84.2-99.4%), respectively. However, a considerable bias in vertical residual error between initial SGRT setup and CBCT setup was observed. Clinically relevant changes between the planned and cumulative doses to organs-at-risk (OARs) were not observed.
CONCLUSIONS: The CTV-to-PTV margin should not be reduced below 5 mm even with daily CBCT setup. Both tVMAT and 3D-CRT techniques were robust in terms of dose coverage to the target and OARs. Based on the shifts between setup methods, CBCT setup is recommended as a complementary method with SGRT.

This study quantifies setup uncertainty in brain tumor patients who received image-guided proton therapy. Patients analyzed include 165 children, adolescents, and young adults (median age at radiotherapy: 9 years (range: 10 months to 24 years); 80 anesthetized and 85 awake) enrolled in a single-institution prospective study from 2020 to 2023. Cone-beam computed tomography (CBCT) was performed daily to calculate and correct manual setup errors, once per course after setup correction to measure residual errors, and weekly after treatments to assess intrafractional motion. Orthogonal radiographs were acquired consecutively with CBCT for paired comparisons of 40 patients. Translational and rotational errors were converted from 6 degrees of freedom to a scalar by a statistical approach that considers the distance from the target to the isocenter. The 95th percentile of setup uncertainty was reduced by daily CBCT from 10 mm (manual positioning) to 1-1.5 mm (after correction) and increased to 2 mm by the end of fractional treatment. A larger variation existed between the roll corrections reported by radiographs vs. CBCT than for pitch and yaw, while there was no statistically significant difference in translational variation. A quantile mixed regression model showed that the 95th percentile of intrafractional motion was 0.40 mm lower for anesthetized patients (p=0.0016). Considering additional uncertainty in radiation-imaging isocentricity, the commonly used total plan robustness of 3 mm against positional uncertainty would be appropriate for our study cohort.

OBJECTIVE: Tumor treating fields (TTFields) with concurrent radiation therapy (RT) might improve the outcome of patients with newly diagnosed glioblastoma. Several trials, including that conducted in our center, have allowed patients to wear TTFields during RT. We aimed to evaluate the setup uncertainty introduced by TTFields and calculate the planning target volume (PTV) margin for clinical reference.
METHODS: We collected and analyzed 201 cone beam computed tomography images of 22 patients in our center. Patients with or without TTFields were divided into the control and TTFields groups. We evaluated the setup errors in 6 degrees of freedom and 3 degrees of freedom and the magnitudes in the 3-dimensional vectors. An estimated PTV margin for patients requiring nonimaging-guided RT was recommended.
RESULTS: A significant difference was observed in the longitudinal axis between the TTFields and control groups (P < .05). These results were consistent with that of the intragroup comparison of the TTFields group. The position error of the longitudinal axis (from head to feet) was -0.51 ± 2.05 mm in the TTFields group.
CONCLUSIONS: Wearing TTFields during RT increased the uncertainty, especially in the longitudinal axis, with a system error of 1.40 mm and a random error of 1.28 mm. Daily image guided RT for TTFields patients seems necessary. However, the recommended expansion margin of the PTV is 5 mm for patients requiring nonimage-guided RT to enhance the safety and efficacy of treatment.

BACKGROUND: To develop a fully automated in-house gamma analysis software for the \"Cheese\" phantom-based delivery quality assurance (QA) of helical tomotherapy plans.
METHODS: The developed in-house software was designed to automate several procedures, which need to be manually performed using commercial software packages. The region of interest for the analysis was automatically selected by cropping out film edges and thresholding dose values (>10% of the maximum dose). The film-measured dose was automatically aligned to the computed dose using an image registration algorithm. An optimal film scaling factor was determined to maximize the percentage of pixels passing gamma (gamma passing rate) between the measured and computed doses (3%/3 mm criteria). This gamma analysis was repeated by introducing setup uncertainties in the anterior-posterior direction. For 73 tomotherapy plans, the gamma analysis results using the developed software were compared to those analyzed by medical physicists using a commercial software package.
RESULTS: The developed software successfully automated the gamma analysis for the tomotherapy delivery quality assurance. The gamma passing rate (GPR) calculated by the developed software was higher than that by the clinically used software by 3.0%, on average. While, for 1 of the 73 plans, the GPR by the manual gamma analysis was higher than 90% (pass/fail criteria), the gamma analysis using the developed software resulted in fail (GPR < 90%).
CONCLUSIONS: The use of automated and standardized gamma analysis software can improve both the clinical efficiency and veracity of the analysis results. Furthermore, the gamma analyses with various film scaling factors and setup uncertainties will provide clinically useful information for further investigations.

OBJECTIVE: The single isocenter for multiple-target (SIMT) technique has become a popular treatment technique for multiple brain metastases. We have implemented a method to obtain a nonuniform margin for SIMT technique. In this study, we further propose a method to determine the isocenter position so that the total expanded margin volume is minimal.
METHODS: Based on a statistical model, the relationship between nonuniform margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. Due to the existence of rotational error, there is a nonlinear relationship between the margin volume and the isocenter position. Using numerical simulation, we study the relationship between optimal isocenter position and translational error, rotational error, and target size. In order to find the optimal isocenter position quickly, adaptive simulated annealing (ASA) algorithm was used. This method was implemented in the Pinnacle3 treatment planning system and compared with isocenter at center-of-geometric (COG), center-of-volume (COV), and center-of-surface (COS). Ten patients with multiple brain metastasis targets treated with the SIMT technique was selected for evaluation.
RESULTS: When the size of tumors is equal, the optimal isocenter obtained by ASA and numerical simulation coincides with COG, COV, and COS. When the size of tumors is different, the optimal isocenter is close to the large tumor. The position of COS point is closer to the optimal point than the COV point for nearly all cases. Moreover, in some cases the COS point can be approximately selected as the optimal point. The ASA algorithm can reduce the calculating time from several hours to tens of seconds for three or more tumors. Using multiple brain metastases targets, a series of volume difference and calculating time were obtained for various tumor number, tumor size, and separation distances. Compared with the margin volume with isocenter at COG, the margin volume for optimal point can be reduced by up to 27.7%.
CONCLUSIONS: Optimal treatment isocenter selection of multiple targets with large differences could reduce the total margin volume. ASA algorithm can significantly improve the speed of finding the optimal isocenter. This method can be used for clinical isocenter selection and is useful for the protection of normal tissue nearby.

BACKGROUND: In a recent study, setup uncertainties in the direction of the heart were shown to impact the overall survival of non-small cell lung cancer (NSCLC) patients after radiotherapy, indicating the causal effect between heart irradiation and survival. The current study aims to externally evaluate this observation within a patient cohort treated using daily IGRT.
METHODS: NSCLC patients with locally-advanced disease and daily CBCT were included. For all treatment fractions, the distance between the isocenter and the heart was evaluated based on the clinical setup registrations. The variation in heart position between planning and treatment (DeltaDistance) was estimated from these registrations. The possible impact of DeltaDistance on survival was analysed by a multivariable Cox model of overall survival, allowing for a time-dependent impact of DeltaDistance to allow for toxicity latency.
RESULTS: Daily CBCT information was available for 489 patients at Odense University Hospital. The primary Cox model contained GTV volume, patient age, performance status, and DeltaDistance. DeltaDistance significantly impacted overall survival approximately 50 months after radiotherapy. Subanalyses indicated that the observed effect is mainly present among the patients with the least clinical risk factors.
CONCLUSIONS: Our results confirm the impact of setup variations in the direction of the heart on the survival of NSCLC patients, even within a cohort using daily CBCT setup guidance. This result indicates a causal effect between heart irradiation and survival. It will be challenging to reduce the setup uncertainty even further; thus, increased focus on dose constraints on the heart seems warranted.

Margin concepts in proton therapy aim to ensure full dose coverage of the clinical target volume (CTV) in presence of setup and range uncertainty. Due to inter-observer variability (IOV), the CTV itself is uncertain. We present a framework to evaluate the combined impact of IOV, setup and range uncertainty in a variance-based sensitivity analysis (SA). For ten patients with skull base meningioma, the mean calculation time to perform the SA including 1.6 × 104 dose recalculations was 59 min. For two patients in this dataset, IOV had a relevant impact on the estimated CTV D95% uncertainty.

OBJECTIVE: In this work, we implemented a method to obtain a nonuniform clinical target volume (CTV) to planning target volume (PTV) margin caused by both rotational and translational uncertainties and evaluated it in the treatment planning system (TPS).
METHODS: Based on a previously published statistical model, the relationship between a target margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. For a single CTV, it can be thought as a combination of many small volume elements or target points. The margin of each point could be obtained using the suggested statistical model. The whole nonuniform CTV-PTV margin was determined by the union of all possible margins of the CTV boundary points. This method was implemented in the Pinnacle3 treatment planning system and compared with uniform margin algorithm. Ten vertebral metastases targets and multiple brain metastases targets were chosen for evaluation.
RESULTS: The combined CTV-PTV margin as a function of d for various initial translational margin and rotational uncertainties was calculated. The combined margin increases as d, rotational uncertainties and translational margin increase. For the same rotational uncertainty, a smaller initial translational margin requires a larger rotational margin to compensate for the rotational error. Compared with the uniform margin algorithm, the advantage of this method is that it could minimize the PTVs volume for given CTVs to obtain same significance level. Using vertebral metastases targets and multiple brain metastases targets, a series of volume difference was obtained for various translational margins and rotational uncertainties. The volume difference of PTV could be more than 17% when translational margin is 2 mm and rotational uncertainty is 1.4°.
CONCLUSIONS: Nonuniform margin algorithm could avoid excessive compensation for the CTV boundary points near isocenter. This method could be used for clinical margin determination and might be useful for the protection of risk organs.

BACKGROUND: Target localization in radiation therapy is affected by numerous sources of uncertainty. Despite measures to minimize the breathing motion, the treatment of hypofractionated liver radiation therapy is further challenged by residual uncertainty coming from involuntary organ motion and daily changes in the shape and location of abdominal organs. To address the residual uncertainty, clinics implement image-guided radiation therapy at varying levels of soft-tissue contrast. This study utilized the treatment records from the patients that have received hypofractionated liver radiation therapy using in-room computed tomography (CT) imaging to assess the setup uncertainty and to estimate the appropriate planning treatment volume (PTV) margins in the absence of in-room CT imaging.
METHODS: We collected 917 pre-treatment daily in-room CT images from 69 patients who received hypofractionated radiation therapy to the liver with the inspiration breath-hold technique. For each treatment, the daily CT was initially aligned to the planning CT based on the shape of the liver automatically using a CT-CT alignment software. After the initial alignment, manual shift corrections were determined by visual inspection of the two images, and the corrections were applied to shift the patient to the physician-approved treatment position. Considering the final alignment as the gold-standard setup, systematic and random uncertainties in the automatic alignment were quantified, and the uncertainties were used to calculate the PTV margins.
RESULTS: The median discrepancy between the final and automatic alignment was 1.1 mm (0-24.3 mm), and 38% of treated fractions required manual corrections of ≥3 mm. The systematic uncertainty was 1.5 mm in the anterior-posterior (AP) direction, 1.1 mm in the left-right (LR) direction, and 2.4 mm in the superior-inferior (SI) direction. The random uncertainty was 2.2 mm in the AP, 1.9 mm in the LR, and 2.2 mm in the SI direction. The PTV margins recommended to be used in the absence of in-room CT imaging were 5.3 mm in the AP, 3.5 mm in the LR, and 5.1 mm in the SI direction.
CONCLUSIONS: Manual shift correction based on soft-tissue alignment is substantial in the treatment of the abdominal region. In-room CT can reduce PTV margin by up to 5 mm, which may be especially beneficial for dose escalation and normal tissue sparing in hypofractionated liver radiation therapy.