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Purpose: High-quality CBCT and AI-enhanced adaptive planning techniques allow CBCT-guided stereotactic adaptive radiotherapy (CT-STAR) to account for inter-fractional anatomic changes. Studies of intra-fractional respiratory motion management with a surface imaging solution for CT-STAR have not been fully conducted. We investigated intra-fractional motion management in breath-hold Ethos-based CT-STAR and CT-SBRT (stereotactic body non-adaptive radiotherapy) using optical surface imaging combined with onboard CBCTs., Methods: Ten cancer patients with mobile lower lung or upper abdominal malignancies participated in an IRB-approved clinical trial (Phase I) of optical surface image-guided Ethos CT-STAR/SBRT. In the clinical trial, a pre-configured gating window (± 2 mm in AP direction) on optical surface imaging was used for manually triggering intra-fractional CBCT acquisition and treatment beam irradiation during breath-hold (seven patients for the end of exhalation and three patients for the end of inhalation). Two inter-fractional CBCTs at the ends of exhalation and inhalation in each fraction were acquired to verify the primary direction and range of the tumor/imaging-surrogate (donut-shaped fiducial) motion. Intra-fractional CBCTs were used to quantify the residual motion of the tumor/imaging-surrogate within the pre-configured breath-hold window in the AP direction. Fifty fractions of Ethos RT were delivered under surface image-guidance: Thirty-two fractions with CT-STAR (adaptive RT) and 18 fractions with CT-SBRT (non-adaptive RT). The residual motion of the tumor was quantified by determining variations in the tumor centroid position. The dosimetric impact on target coverage was calculated based on the residual motion., Results: We used 46 fractions for the analysis of intra-fractional residual motion and 43 fractions for the inter-fractional motion analysis due to study constraints. Using the image registration method, 43 pairs of inter-fractional CBCTs and 100 intra-fractional CBCTs attached to dose maps were analyzed. In the motion range study (image registration) from the inter-fractional CBCTs, the primary motion (mean ± std) was 16.6 ± 9.2 mm in the SI direction (magnitude: 26.4 ± 11.3 mm) for the tumors and 15.5 ± 7.3 mm in the AP direction (magnitude: 20.4 ± 7.0 mm) for the imaging-surrogate, respectively. The residual motion of the tumor (image registration) from intra-fractional breath-hold CBCTs was 2.2 ± 2.0 mm for SI, 1.4 ± 1.4 mm for RL, and 1.3 ± 1.3 mm for AP directions (magnitude: 3.5 ± 2.1 mm). The ratio of the actual dose coverage to 99%, 90%, and 50% of the target volume decreased by 0.95 ± 0.11, 0.96 ± 0.10, 0.99 ± 0.05, respectively. The mean percentage of the target volume covered by the prescribed dose decreased by 2.8 ± 4.4%., Conclusion: We demonstrated the intra-fractional motion-managed treatment strategy in breath-hold Ethos CT-STAR/SBRT using optical surface imaging and CBCT. While the controlled residual tumor motion measured at 3.5 mm exceeded the predetermined setup value of 2 mm, it is important to note that this motion still fell within the clinically acceptable range defined by the PTV margin of 5 mm. Nonetheless, additional caution is needed with intra-fractional motion management in breath-hold Ethos CT-STAR/SBRT using optical surface imaging and CBCT., (© 2024 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Purpose: The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment., Methods: Ten patients with lung cancer treated with marker-implanted RTTT were included. The prescription dose was 50 Gy in four fractions, using seven- to nine-port non-coplanar static beams. This corresponds to 14-18 X-ray tube angles for an orthogonal X-ray imaging system rotating with the gantry. All patients underwent 10 respiratory phases four-dimensional computed tomography. After a data augmentation approach, for each X-ray tube angle of a patient, 2250 digitally reconstructed radiograph (DRR) images with gross tumor volume (GTV) contour labeled were obtained. These images were adopted to train the patient and X-ray tube angle-specific GTV contour prediction model. During the testing, the model trained with DRR images predicted GTV contour on X-ray projection images acquired during treatment. The predicted three-dimensional (3D) positions of the GTV were calculated based on the centroids of the contours in the orthogonal images. The 3D positions of GTV determined by the marker-implanted RTTT during the treatment were considered as the ground truth. The 3D deviations between the prediction and the ground truth were calculated to evaluate the performance of the model., Results: The median GTV volume and motion range were 7.42 (range, 1.18-25.74) cm 3 and 22 (range, 11-28) mm, respectively. In total, 8993 3D position comparisons were included. The mean calculation time was 85 ms per image. The overall median value of the 3D deviation was 2.27 (interquartile range: 1.66-2.95) mm. The probability of the 3D deviation smaller than 5 mm was 93.6%., Conclusions: The evaluation results and calculation efficiency show the proposed deep learning-based markerless RTTT method may be feasible for patients with lung cancer., (© 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

Background and Objective: During lung cancer radiotherapy, the position of infrared reflective objects on the chest can be recorded to estimate the tumor location. However, radiotherapy systems have a latency inherent to robot control limitations that impedes the radiation delivery precision. Prediction with online learning of recurrent neural networks (RNN) allows for adaptation to non-stationary respiratory signals, but classical methods such as real-time recurrent learning (RTRL) and truncated backpropagation through time are respectively slow and biased. This study investigates the capabilities of unbiased online recurrent optimization (UORO) to forecast respiratory motion and enhance safety in lung radiotherapy., Methods: We used nine observation records of the three-dimensional (3D) position of three external markers on the chest and abdomen of healthy individuals breathing during intervals from 73s to 222s. The sampling frequency was 10Hz, and the amplitudes of the recorded trajectories range from 6mm to 40mm in the superior-inferior direction. We forecast the 3D location of each marker simultaneously with a horizon value (the time interval in advance for which the prediction is made) between 0.1s and 2.0s, using an RNN trained with UORO. We compare its performance with an RNN trained with RTRL, least mean squares (LMS), and offline linear regression. We provide closed-form expressions for quantities involved in the gradient loss calculation in UORO, thereby making its implementation efficient. Training and cross-validation were performed during the first minute of each sequence., Results: On average over the horizon values considered and the nine sequences, UORO achieves the lowest root-mean-square (RMS) error and maximum error among the compared algorithms. These errors are respectively equal to 1.3mm and 8.8mm, and the prediction time per time step was lower than 2.8ms (Dell Intel core i9-9900K 3.60 GHz). Linear regression has the lowest RMS error for the horizon values 0.1s and 0.2s, followed by LMS for horizon values between 0.3s and 0.5s, and UORO for horizon values greater than 0.6s., Conclusions: UORO can accurately predict the 3D position of external markers for intermediate to high response times with an acceptable time performance. This will help limit unwanted damage to healthy tissues caused by radiotherapy., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2022. Published by Elsevier B.V.)

Background: Dynamic tumor tracking (DTT) is a method of respiratory motion management in radiotherapy. It reduces the radiation field but risks delivering an insufficient radiation dose to the tumor. We investigated the local control of DTT-stereotactic body radiotherapy (SBRT) for lung tumors., Methods: Patients treated with SBRT for early-stage, non-small-cell lung cancer and lung metastases (2013-18) were retrospectively reviewed. Patients with tumor motion >1 cm were treated with DTT-SBRT (DTT group); those with tumor motion ≤1 cm were treated with static-SBRT (static group). A static planning target volume for the static-SBRT plan was also created for patients in the DTT group, and planning target volume reduction relative to the planning target volume for the DTT-SBRT plan was assessed. Patients were matched in a 1:1 ratio using a propensity score predictive of the SBRT technique., Results: Of the 245 lesions in 218 patients (median follow-up, 25.4 months), 69 were treated with DTT-SBRT and 176 with static-SBRT. The median planning target volume reduction in the DTT group was 30.3%. After propensity score matching, 124 lesions were included (62 per group). Two-year local control rates for the DTT and static groups were 94.2 and 95.9%, respectively, for all lesions (P = 0.19) and 96.3 and 94.5%, respectively, for matched lesions (P = 0.79). In univariate analysis, DTT-SBRT was not associated with local control for all lesions (hazard ratio, 2.06; P = 0.20) or matched lesions (hazard ratio, 1.22; P = 0.79). No grade 4/5 toxicities were observed., Conclusions: DTT-SBRT for lung tumors reduced the planning target volume, but not local control rates. DTT was useful for respiratory motion management., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Stereotactic ablative radiotherapy (SABR) is a radiation technique delivering high doses of radiation in a small number of treatments, to extracranial targets. It is standard of care in patients with inoperable early stage non-small cell lung cancer, and it is increasingly used in patients with oligometastatic disease. The main advantage of SABR is a steep dose gradient, allowing delivery of high biologically effective doses to the target, while minimizing irradiation exposure of the neighboring normal tissues. This results in high rates of local control of the treated target and minimal toxicity risks, and minimal impact on the quality of life of the patients. However, it requires high precision, accuracy and reproducibility during the entire process, from simulation to treatment planning and treatment delivery. This article will focus on general principles of SABR treatment planning and delivery, with emphasis on the strategies to reduce errors related to immobilization, respiratory management and treatment verification.

Purpose: Advanced radiotherapeutic techniques and apparatus have been developed and widely applied in stereotactic body radiation therapy for early-stage non-small cell lung cancer, but their clinical benefits have not necessarily been confirmed. This study was performed to review our 10-year experience with therapy for the disease and to evaluate whether the advanced radiotherapeutic system implemented in our hospital 5 years after we began the therapy improved the clinical outcomes of patients., Materials and Methods: Patients who underwent the therapy at our hospital between April 2008 and March 2018 were retrospectively reviewed. They were divided into 2 groups treated with the conventional system or the advanced system, and the characteristics and clinical outcomes were compared between the groups. The same analyses were also performed in propensity-matched patients from the 2 groups., Results: Among the 73 patients eligible for this study, 42 were treated with the conventional system and 31 with the advanced system. All were treated as planned, and severe adverse events were rare. The local progression-free survival rate in the advanced system group was significantly higher than in the conventional system group (P = 0.025). In the propensity-matched patients, both the local progression-free survival rate and the overall survival rate were significantly higher compared in the advanced system group than the conventional system group (P = 0.089 and 0.080, respectively)., Conclusion: The advanced system improved the outcomes of patients with the disease, suggesting that technological development has had a strong impact on clinical outcomes.

Purpose: Lung motion phantoms used to validate radiotherapy motion management strategies have fairly simplistic designs that do not adequately capture complex phenomena observed in human respiration such as external and internal deformation, variable hysteresis and variable correlation between different parts of the thoracic anatomy. These limitations make reliable evaluation of sophisticated motion management techniques quite challenging. In this work, we present the design and implementation of a programmable, externally and internally deformable lung motion phantom that allows for a reproducible change in external-internal and internal-internal correlation of embedded markers., Methods: An in-house-designed lung module, made from natural latex foam was inserted inside the outer shell of a commercially available lung phantom (RSD, Long Beach, CA, USA). Radiopaque markers were placed on the external surface and embedded into the lung module. Two independently programmable high-precision linear motion actuators were used to generate primarily anterior-posterior (AP) and primarily superior-inferior (SI) motion in a reproducible fashion in order to enable (a) variable correlation between the displacement of interior volume and the exterior surface, (b) independent changes in the amplitude of the AP and SI motions, and (c) variable hysteresis. The ability of the phantom to produce complex and variable motion accurately and reproducibly was evaluated by programming the two actuators with mathematical and patient-recorded lung tumor motion traces, and recording the trajectories of various markers using kV fluoroscopy. As an example application, the phantom was used to evaluate the performance of lung motion models constructed from kV fluoroscopy and 4DCT images., Results: The phantom exhibited a high degree of reproducibility and marker motion ranges were reproducible to within 0.5 mm. Variable correlation was observed between the displacements of internal-internal and internal-external markers. The SI and AP components of motion of a specific marker had a correlation parameter that varied from -11 to 17. Monitoring a region of interest on the phantom's surface to estimate internal marker motion led to considerably lower uncertainties than when a single point was monitored., Conclusions: We successfully designed and implemented a programmable, externally and internally deformable lung motion phantom that allows for a reproducible change in external-internal and internal-internal correlation of embedded markers., (© 2019 American Association of Physicists in Medicine.)

Introduction: Stereotactic body radiotherapy (SBRT) has emerged as an important modality in malignant lung tumor treatment both in early localized primary and oligometastatic setting. This study aims to present the results of lung SBRT both in terms of dosimetry and clinical outcome., Materials and Methods: Twenty-seven patients were assessed from 2012 to 2016. Both the primary and oligometastatic lung tumors were evaluated. Respiratory motion management was done employing ANZAI (Siemens, Germany) based four-dimensional computed tomography (CT). Commonly used fractionations were 60 Gy/5 fractions for peripheral tumors and 48 Gy/6 fractions for central tumors. Radiation Therapy Oncology Group toxicity criteria were used for toxicity and whole-body positron emission tomography-CT scan was done at follow-up for response evaluation., Results: Twenty-seven patients were evaluated, 18 (66.7%) patients had a primary, and 9 (33.3%) patients had metastatic lung tumors. The male-to-female ratio for the entire cohort was 2:1. The median age at diagnosis was 65.8 years. Mean planning target volume (PTV) D2cc was 54.9 ± 9.04 Gy and mean internal target volume diameter was 3.0 ± 1.07 cm. Mean V20 Gy, V10 Gy, and V5 Gy of (lungs total-PTV) and (Lung ipsilateral - PTV) were 5.4 ± 4% and 10.9 ± 7.9%, 11.7 ± 5.8% and 24.2 ± 14.0%, and 22.05 ± 12.4% and 33.2 ± 15.3%, respectively. In total 21 (84%) patients and 4 patients (16%) showed a complete and partial response, respectively. One (3%) patient developed Gr 3 radiation pneumonitis. One year local control was in 18 (81%) patients whereas 4 (14%) patients progressed and three patients did not report. A higher prescribed dose significantly correlated with 1 year tumor control (P = 0.036)., Conclusion: This study infers the feasibility and a favorable outcome for lung cancer amenable to SBRT in addition to being one of the largest clinical experiences for lung stereotactic treatment in our country., Competing Interests: None

Purpose: Real-time tracking of lung tumors using magnetic resonance imaging (MRI) has been proposed as a potential strategy to mitigate the ill-effects of breathing motion in radiation therapy. Several autocontouring methods have been evaluated against a "gold standard" of a single human expert user. However, contours drawn by experts have inherent intra- and interobserver variations. In this study, we aim to evaluate our user-trained autocontouring algorithm with manually drawn contours from multiple expert users, and to contextualize the accuracy of these autocontours within intra- and interobserver variations., Methods: Six nonsmall cell lung cancer patients were recruited, with institutional ethics approval. Patients were imaged with a clinical 3 T Philips MR scanner using a dynamic 2D balanced SSFP sequence under free breathing. Three radiation oncology experts, each in two separate sessions, contoured 130 dynamic images for each patient. For autocontouring, the first 30 images were used for algorithm training, and the remaining 100 images were autocontoured and evaluated. Autocontours were compared against manual contours in terms of Dice's coefficient (DC) and Hausdorff distances (d H ). Intra- and interobserver variations of the manual contours were also evaluated., Results: When compared with the manual contours of the expert user who trained it, the algorithm generates autocontours whose evaluation metrics (same session: DC = 0.90(0.03), d H  = 3.8(1.6) mm; different session DC = 0.88(0.04), d H  = 4.3(1.5) mm) are similar to or better than intraobserver variations (DC = 0.88(0.04), and d H  = 4.3(1.7) mm) between two sessions. The algorithm's autocontours are also compared to the manual contours from different expert users with evaluation metrics (DC = 0.87(0.04), d H  = 4.8(1.7) mm) similar to interobserver variations (DC = 0.87(0.04), d H  = 4.7(1.6) mm)., Conclusions: Our autocontouring algorithm delineates tumor contours (<20 ms per contour), in dynamic MRI of lung, that are comparable to multiple human experts (several seconds per contour), but at a much faster speed. At the same time, the agreement between autocontours and manual contours is comparable to the intra- and interobserver variations. This algorithm may be a key component of the real time tumor tracking workflow for our hybrid Linac-MR device in the future., (© 2017 American Association of Physicists in Medicine.)

Purpose: Respiratory motion-management techniques (MMT) aim to ensure tumor dose coverage while sparing lung tissue. Dynamic treatment-couch tracking of the moving tumor is a promising new MMT and was compared to the internal-target-volume (ITV) concept, the mid-ventilation (MidV) principle and the gating approach in a planning study based on 4D dose calculations., Methods: For twenty patients with lung lesions, planning target volumes (PTV) were adapted to the MMT and stereotactic body radiotherapy treatments were prepared with the 65%-isodose enclosing the PTV. For tracking, three concepts for target volume definition were considered: Including the gross tumor volume of one phase (single-phase tracking), including deformations between phases (multi-phase tracking) and additionally including tracking latencies of a couch tracking system (reliable couch tracking). The accumulated tumor and lung doses were estimated with 4D dose calculations based on 4D-CT datasets and deformable image registration., Results: Single-phase tracking showed the lowest ipsilateral lung Dmean (median: 3.3Gy), followed by multi-phase tracking, gating, reliable couch tracking, MidV and ITV concepts (3.6, 3.8, 4.1, 4.3 and 4.8Gy). The 4D dose calculations showed the MidV and single-phase tracking overestimated the target mean dose (-2.3% and -1.3%), while it was slightly underestimated by the other MMT (<+1%)., Conclusion: The ITV concept ensures tumor coverage, but exposes the lung tissue to a higher dose. The MidV, gating and tracking concepts were shown to reduce the lung dose. Neglecting non-translational changes of the tumor in the target volume definition for tracking results in a slightly reduced target coverage. The slightly inferior dose coverage for MidV should be considered when applying this technique clinically., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background and Purpose: The objective of this study was to compare the latest respiratory motion-management strategies, namely the internal-target-volume (ITV) concept, the mid-ventilation (MidV) principle, respiratory gating and dynamic couch tracking., Materials and Methods: An anthropomorphic, deformable and dynamic lung phantom was used for the dosimetric validation of these techniques. Stereotactic treatments were adapted to match the techniques and five distinct respiration patterns, and delivered to the phantom while radiographic film measurements were taken inside the tumor. To report on tumor coverage, these dose distributions were used to calculate mean doses (D mean ), changes in homogeneity indices (ΔH 2 - 98 ), gamma agreement, and areas covered by the planned minimum dose (A >Dmin )., Results: All techniques achieved good tumor coverage (A >Dmin >99.0%) and minor changes in D mean (±3.2%). Gating and tracking strategies showed superior results in gamma agreement and ΔH 2 - 98 compared to ITV and MidV concepts, which seem to be more influenced by the interplay and the gradient effect. For lung, heart and spinal cord, significant dose differences between the four techniques were found (p<0.05), with lowest doses for gating and tracking strategies., Conclusion: Active motion-management techniques, such as gating or tracking, showed superior tumor dose coverage and better organ dose sparing than the passive techniques based on tumor margins., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)