OBJECTIVE: This study aims to externally validate a predictive model for distant metastasis (DM) with computed tomography (CT)-based radiomics features in prospectively enrolled non-small-cell lung cancer patients undergoing dynamic tumor-tracking stereotactic body radiation therapy (DTT-SBRT).
METHODS: The study collected retrospective data from 567 patients across 11 institutions as the training dataset and prospectively enrolled 42 patients from four institutions as the external test dataset. Four clinical features were collected, and 944 CT-based radiomic features were extracted from gross tumor volumes. After standardization and feature selection, DM predictive models were developed using fine and gray regression (FG) and random survival forest (RSF), incorporating clinical and radiomic features, and their combinations within the training dataset. Then, the model was applied to the test dataset, dividing patients into high- and low-risk groups based on medians of risk scores. Model performance was assessed using the concordance index (C-index), and the statistical significance between groups was evaluated using Gray\'s test.
RESULTS: In the training dataset, 122 of 567 patients (21.5%) developed DM, compared to 9 of 42 patients (21.4%) in the test dataset. In the test dataset, the C-indices of the clinical, radiomics, and hybrid models with FG were 0.559, 0.544, and 0.560, respectively, whereas those with RSF were 0.576, 0.604, and 0.627, respectively. The hybrid model with RSF, which exhibited the best predictive performance of all models, identified 7 of 23 patients (30.4%) as high risk and 2 of 19 patients (10.5%) as low risk for DM incidence in the test dataset (p = 0.116).
CONCLUSIONS: Although predictive models for DM lack significance when applied to prospectively enrolled cases undergoing DTT-lung SBRT, the model with RSF exhibits a consistent capacity to effectively classify patients at a high risk of developing DM.

BACKGROUND: In single-isocenter multitarget stereotactic body radiotherapy (SBRT), geometric miss risks arise from uncertainties in intertarget position. However, its assessment is inadequate, and may be interfered by the reconstructed tumor position errors (RPEs) during simulated CT and cone beam CT (CBCT) acquisition. This study aimed to quantify intertarget position variations and assess factors influencing it.
METHODS: We analyzed data from 14 patients with 100 tumor pairs treated with single-isocenter SBRT. Intertarget position variation was measured using 4D-CT simulation to assess the intertarget position variations (ΔD) during routine treatment process. Additionally, a homologous 4D-CBCT simulation provided RPE-free comparison to determine the impact of RPEs, and isolating purely tumor motion induced ΔD to evaluate potential contributing factors.
RESULTS: The median ΔD was 4.3 mm (4D-CT) and 3.4 mm (4D-CBCT). Variations exceeding 5 mm and 10 mm were observed in 31.1% and 5.5% (4D-CT) and 20.4% and 3.4% (4D-CBCT) of fractions, respectively. RPEs necessitated an additional 1-2 mm safety margin. Intertarget distance and breathing amplitude variability showed weak correlations with variation (Rs = 0.33 and 0.31). The ΔD differed significantly by locations (upper vs. lower lobe and right vs. Left lung). Notably, left lung tumor pairs exhibited the highest risk.
CONCLUSIONS: This study provide a reliable way to assess intertarget position variation by using both 4D-CT and 4D-CBCT simulation. Consequently, single-isocenter SBRT for multiple lung tumors carries high risk of geometric miss. Tumor motion and RPE constitute a substantial portion of intertarget position variation, requiring correspondent strategies to minimize the intertarget uncertainties.

OBJECTIVE: Target positions should be acquired during beam delivery for accurate lung stereotactic body radiotherapy. We aimed to perform kilovoltage (kV) imaging during beam irradiation (intra-irradiation imaging) under phase-gated conditions and evaluate its performance.
METHODS: Catphan 504 and QUASAR respiratory motion phantoms were used to evaluate image quality and target detectability, respectively. TrueBeam STx linac and the Developer Mode was used. The imaging parameters were 125 kVp and 1.2 mAs/projection. Flattened megavoltage (MV) X-ray beam energies 6, 10 and 15 MV and un-flattened beam energies 6 and 10 MV were used with field sizes of 5 × 5 and 15 × 15 cm2 and various frame rates for intra-irradiation imaging. In addition, using a QUASAR phantom, intra-irradiation imaging was performed during intensity-modulated plan delivery. The root-mean-square error (RMSE) of the CT-number for the inserted rods, image noise, visual assessment, and contrast-to-noise ratio (CNR) were evaluated.
RESULTS: The RMSEs of intra-irradiation cone-beam computed tomography (CBCT) images under gated conditions were 50-230 Hounsfield Unit (HU) (static < 30 HU). The noise of the intra-irradiation CBCT images under gated conditions was 15-35 HU, whereas that of the standard CBCT images was 8.8-27.2 HU. Lower frame rates exhibited large RMSEs and noise; however, the iterative reconstruction algorithm (IR) was effective at improving these values. Approximately 7 fps with the IR showed an equivalent CNR of 15 fps without the IR. The target was visible on all the gated intra-irradiation CBCT images.
CONCLUSIONS: Several image quality improvements are required; however, intra-irradiated CBCT images showed good visual target detection.

UNASSIGNED: Motion management techniques are important to spare the healthy tissue adequately. However, they are complex and need dedicated quality assurance. The aim of this study was to create a dynamic phantom designed for quality assurance and to replicate a patient\'s size, anatomy, and tissue density.
UNASSIGNED: A computed tomography (CT) scan of a cancer patient was used to create molds for the lungs, heart, ribs, and vertebral column via additive manufacturing. A pump system and software were developed to simulate respiratory dynamics. The extent of respiratory motion was quantified using a 4DCT scan. End-to-end tests were conducted to evaluate two motion management techniques for lung stereotactic body radiotherapy (SBRT).
UNASSIGNED: The chest wall moved between 4 mm and 13 mm anteriorly and 2 mm to 7 mm laterally during the breathing. The diaphragm exhibited superior-inferior movement ranging from 5 mm to 16 mm in the left lung and 10 mm to 36 mm in the right lung. The left lung tumor displaced ± 7 mm superior-inferiorly and anterior-posteriorly. The CT numbers were for lung: -716 ± 108 HU (phantom) and -713 ± 70 HU (patient); bone: 460 ± 20 HU (phantom) and 458 ± 206 HU (patient); soft tissue: 92 ± 9 HU (phantom) and 60 ± 25 HU (patient). The end-to-end testing showed an excellent agreement between the measured and the calculated dose for ion chamber and film dosimetry.
UNASSIGNED: The phantom is recommended for quality assurance, evaluating the institution\'s specific planning and motion management strategies either through end-to-end testing or as an external audit phantom.

BACKGROUND: Rescanning is a common technique used in proton pencil beam scanning to mitigate the interplay effect. Advances in machine operating parameters across different generations of particle therapy systems have led to improvements in beam delivery time (BDT). However, the potential impact of these improvements on the effectiveness of rescanning remains an underexplored area in the existing research.
METHODS: We systematically investigated the impact of proton machine operating parameters on the effectiveness of layer rescanning in mitigating interplay effect during lung SBRT treatment, using the CIRS phantom. Focused on the Hitachi synchrotron particle therapy system, we explored machine operating parameters from our institution\'s current (2015) and upcoming systems (2025A and 2025B). Accumulated dynamic 4D dose were reconstructed to assess the interplay effect and layer rescanning effectiveness.
RESULTS: Achieving target coverage and dose homogeneity within 2% deviation required 6, 6, and 20 times layer rescanning for the 2015, 2025A, and 2025B machine parameters, respectively. Beyond this point, further increasing the number of layer rescanning did not further improve the dose distribution. BDTs without rescanning were 50.4, 24.4, and 11.4 s for 2015, 2025A, and 2025B, respectively. However, after incorporating proper number of layer rescanning (six for 2015 and 2025A, 20 for 2025B), BDTs increased to 67.0, 39.6, and 42.3 s for 2015, 2025A, and 2025B machine parameters. Our data also demonstrated the potential problem of false negative and false positive if the randomness of the respiratory phase at which the beam is initiated is not considered in the evaluation of interplay effect.
CONCLUSIONS: The effectiveness of layer rescanning for mitigating interplay effect is affected by machine operating parameters. Therefore, past clinical experiences may not be applicable to modern machines.

This study exposed the implementation of a novel technique (VMATLSL) for the planning of moving targets in lung stereotactic body radiation therapy (SBRT). This new technique has been compared to static conformal radiotherapy (3D-CRT), volumetric-modulated arc therapy (VMAT), and dynamic conformal arc (DCA). The rationale of this study was to lower geometric complexity (54.9% lower than full VMAT) and hence ensure the reproducibility of the treatment delivery by reducing the risk for interplay errors induced by respiratory motion. Dosimetry metrics were studied with a cohort of 30 patients. Our results showed that leaf speed limitation provided conformal number (CN) close to the VMAT (median CN of VMATLSL is 0.78 vs 0.82 for full VMAT) and was a significant improvement on 3D-CRT and DCA with segment-weight optimized (respectively 0.55 and 0.57). This novel technique is an alternative to VMAT or DCA for lung SBRT treatments, combining independence from the patient\'s breathing pattern, from the size and amplitude of the lesion, free from interplay effect, and with dosimetry metrics close to the best that could be achieved with full VMAT.

This study presents the clinical experiences of the New York Proton Center in employing proton pencil beam scanning (PBS) for the treatment of lung stereotactic body radiation therapy. It encompasses a comprehensive examination of multiple facets, including patient simulation, delineation of target volumes and organs at risk, treatment planning, plan evaluation, quality assurance, and motion management strategies. By sharing the approaches of the New York Proton Center and providing recommendations across simulation, treatment planning, and treatment delivery, it is anticipated that the valuable experience will be provided to a broader proton therapy community, serving as a useful reference for future clinical practice and research endeavors in the field of stereotactic body proton therapy for lung tumors.

UNASSIGNED: Report the outcomes of patients with non-small cell lung cancer (NSCLC) and peripheral tumors treated with simultaneous integrated biologically equivalent dose (BED)-escalation (SIBE) lung stereotactic body radiation therapy (SBRT) to achieve dose escalation.
UNASSIGNED: Patients with NSCLC within 5 mm of the chest wall treated with a SIBE approach were eligible. Patients received 60 Gy in 5 fractions, with dose decreased to 50 Gy based on proximity to the chest wall. Dosimetry, oncologic outcomes, and toxicity were evaluated.
UNASSIGNED: Twenty-four patients met inclusion criteria. Median BED to the PTV was 135.4 Gy. Median chest wall V30 was 18.7 cc. The 3-year LC, OS, and PFS of the non-metastatic cohort was 93%, 35%, and 39%, respectively. The crude rate of chest wall toxicity was 12.5%, with no rib fractures.
UNASSIGNED: SIBE lung SBRT appears to be well tolerated and achieves favorable local control rates and survival.

Objective. Dose calculation in lung stereotactic body radiation therapy (SBRT) is challenging due to the low density of the lungs and small volumes. Here we assess uncertainties associated with tissue heterogeneities using different dose calculation algorithms and quantify potential associations with local failure for lung SBRT.Approach. 164 lung SBRT plans were used. The original plans were prepared using Pencil Beam Convolution (PBC, n = 8) or Anisotropic Analytical Algorithm (AAA, n = 156). Each plan was recalculated with AcurosXB (AXB) leaving all plan parameters unchanged. A subset (n = 89) was calculated with Monte Carlo to verify accuracy. Differences were calculated for the planning target volume (PTV) and internal target volume (ITV) Dmean[Gy], D99%[Gy], D95%[Gy], D1%[Gy], and V100%[%]. Dose metrics were converted to biologically effective doses (BED) usingα/β= 10Gy. Regression analysis was performed for AAA plans investigating the effects of various parameters on the extent of the dosimetric differences. Associations between the magnitude of the differences for all plans and outcome were investigated using sub-distribution hazards analysis.Main results. For AAA cases, higher energies increased the magnitude of the difference (ΔDmean of -3.6%, -5.9%, and -9.1% for 6X, 10X, and 15X, respectively), as did lung volume (ΔD99% of -1.6% per 500cc). Regarding outcome, significant hazard ratios (HR) were observed for the change in the PTV and ITV D1% BEDs upon univariate analysis (p = 0.042, 0.023, respectively). When adjusting for PTV volume and prescription, the HRs for the change in the ITV D1% BED remained significant (p = 0.039, 0.037, respectively).Significance. Large differences in dosimetric indices for lung SBRT can occur when transitioning to advanced algorithms. The majority of the differences were not associated with local failure, although differences in PTV and ITV D1% BEDs were associated upon univariate analysis. This shows uncertainty in near maximal tumor dose to potentially be predictive of treatment outcome.

To evaluate the effects of arc geometry on lung stereotactic body radiation therapy (SBRT) plan quality, using collision check software to select safe beam angles. Thirty lung SBRT cases were replanned 10Gy x 5 using 4 volumetric modulated arc therapy (VMAT) geometries: coplanar lateral (cpLAT), coplanar oblique (cpOBL), noncoplanar lateral (ncpLAT) and noncoplanar oblique (ncpOBL). Lateral arcs spanned 180° on the affected side whereas the 180° oblique arcs crossed midline to spare healthy tissues. Couch angles were separated by 30° on noncoplanar plans. Clearance was verified with Radformation CollisionCheck software. Optimization objectives were the same across the four plans for each case. Planning target volume (PTV) coverage was set to 95% and then plans were evaluated for dose conformity, healthy tissue doses, and monitor units. Clinically treated plans were used to benchmark the results. The volumes of the 25%, 50% and 75% isodoses were smaller with noncoplanar than coplanar arcs. The volume of the 50% isodose line relative to the PTV (CI50%) was as follows: clinical 3.75±0.72, cpLAT 3.39 ± 0.37, cpOBL 3.36 ± 0.34, ncpLAT 3.02 ± 0.21 and ncpOBL 3.02 ± 0.22. The Wilcoxon signed rank test with Bonferroni correction showed p < 0.005 in all CI50% comparisons except between the cpLat and cpObl arcs and between the ncpLat and ncpObl arcs. The best lung sparing was achieved using ncpObl arcs, which was statistically significant (p < 0.001) compared with the other four plans at V12.5Gy, V13.5Gy and V20Gy. Chest wall V30Gy was significantly better using noncoplanar arcs in comparison to the other plan types (p < 0.001). The best heart sparing at V10Gy from the ncpOBL arcs was significant compared with the clinical and cpLat plans (p < 0.005). Arc geometry has a substantial effect on lung SBRT plan quality. Noncoplanar arcs were superior to coplanar arcs at compacting the dose distribution at the 25%, 50% and 75% isodose levels, thereby reducing the dose to healthy tissues. Further healthy tissue sparing was achieved using oblique arcs that minimize the pathlength through healthy tissues and avoid organs at risk. The dosimetric advantages of the noncoplanar and oblique arcs require careful beam angle selection during treatment planning to avoid collisions during treatment, which may be facilitated by commercial software.