The first clinical implementation of real-time image-guided adaptive radiotherapy using a standard linear accelerator

Keall, Paul J.; Nguyen, Doan Trang; O’Brien, Ricky; Caillet, Vincent; Hewson, Emily; Poulsen, Per Rugaard; Bromley, Regina; Bell, Linda; Eade, Thomas; Kneebone, Andrew; Martin, Jarad; Booth, Jeremy

doi:10.1016/j.radonc.2018.01.001

Cited by 62 publications

(50 citation statements)

References 24 publications

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“…Using a miniature prototype of the PRS with a small phantom, the position of the target during rotation was measured using KIM and sent to an MLC tracking algorithm to compensate for motion. The MLC tracking algorithm reshapes the beam aperture in real time to maintain coverage of the target volume . Gamma analysis of the dose delivered to moving target showed equivalent dose distributions compared to the treatment planning system.…”

Section: Discussionmentioning

confidence: 99%

Development and commissioning of a full‐size prototype fixed‐beam radiotherapy system with horizontal patient rotation

et al. 2019

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Purpose Compared to conventional linacs with rotating gantries, a fixed‐beam radiotherapy system could be smaller, more robust and more cost‐effective. In this work, we developed and commissioned a prototype x‐ray radiotherapy system utilizing a fixed vertical radiation beam and horizontal patient rotation. Methods The prototype system consists of an Elekta Synergy linac with gantry fixed at 0° and a custom‐built patient rotation system (PRS). The PRS was designed to immobilize patients and safely rotate them about the horizontal axis. The interlocks and emergency stops of the linac and PRS were connected. Custom software was developed to monitor the system status, control the motion of the PRS and modify treatment plans for the fixed‐beam configuration. Following installation, the prototype system was commissioned for three‐dimensional (3D) conformal therapy based on guidelines specified in AAPM TG‐45 and TG‐142, with modifications for the fixed‐beam geometry made where necessary. Results The system and control software was tested in a variety of machine states and executed motion, stop and beam gating commands as expected. Interlocks and emergency stops of the linac and PRS were found to correctly stop PRS motion and both kV and MV radiation beams when triggered. For 3D conformal treatments, the prototype system met all AAPM TG‐45 and TG‐142 specifications for geometric and dosimetric accuracy. Motion of the PRS was within 0.6 ± 0.3 mm and 0.10° ± 0.07° of input values for translation and rotation respectively. The axis of rotation of the PRS was coincident with the radiation beam axis to less than 1 mm. End‐to‐end treatment verification for 6 MV conformal treatments showed less than 2% difference between planned and delivered dose for all fields. Conclusion In this work, we have developed and commissioned a radiotherapy system that utilizes a fixed vertical radiation beam and horizontal patient rotation. This system is a proof‐of‐concept prototype for a fixed‐beam treatment system without a rotating gantry. Fixed‐beam systems that are smaller and more cost‐effective could help in improving global access to radiotherapy.

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Section: Discussionmentioning

confidence: 99%

Development and commissioning of a full‐size prototype fixed‐beam radiotherapy system with horizontal patient rotation

et al. 2019

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“…However, IGRT techniques do not account for intrafraction tumor motion, which could lead to mistargeting of the tumor during treatment. Real‐time image‐guided adaptive radiation therapy (IGART) tracks the target and aligns the radiation beam to improve dosage and reduce the exposure of healthy tissue to damaging radiation . Kilovoltage intrafraction monitoring (KIM) is an example of an IGART monitoring system that uses the equipment of standard linear accelerators …”

Section: Introductionmentioning

confidence: 99%

“…Real-time image-guided adaptive radiation therapy (IGART) tracks the target and aligns the radiation beam to improve dosage and reduce the exposure of healthy tissue to damaging radiation. 4,5 Kilovoltage intrafraction monitoring (KIM) is an example of an IGART monitoring system that uses the equipment of standard linear accelerators. 5,6 Most IGART systems rely heavily on the accurate and efficient segmentation of implanted fiducial markers in each image to resolve the 3D motion based on 2D images.…”

Section: Introductionmentioning

confidence: 99%

“…4,5 Kilovoltage intrafraction monitoring (KIM) is an example of an IGART monitoring system that uses the equipment of standard linear accelerators. 5,6 Most IGART systems rely heavily on the accurate and efficient segmentation of implanted fiducial markers in each image to resolve the 3D motion based on 2D images. Many current segmentation methods are based on template matching which require prior information of the marker.…”

Section: Introductionmentioning

confidence: 99%

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A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images

et al. 2019

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Purpose Real‐time image‐guided adaptive radiation therapy (IGART) requires accurate marker segmentation to resolve three‐dimensional (3D) motion based on two‐dimensional (2D) fluoroscopic images. Most common marker segmentation methods require prior knowledge of marker properties to construct a template. If marker properties are not known, an additional learning period is required to build the template which exposes the patient to an additional imaging dose. This work investigates a deep learning‐based fiducial marker classifier for use in real‐time IGART that requires no prior patient‐specific data or additional learning periods. The proposed tracking system uses convolutional neural network (CNN) models to segment cylindrical and arbitrarily shaped fiducial markers. Methods The tracking system uses a tracking window approach to perform sliding window classification of each implanted marker. Three cylindrical marker training datasets were generated from phantom kilovoltage (kV) and patient intrafraction images with increasing levels of megavoltage (MV) scatter. The cylindrical shaped marker CNNs were validated on unseen kV fluoroscopic images from 12 fractions of 10 prostate cancer patients with implanted gold fiducials. For the training and validation of the arbitrarily shaped marker CNNs, cone beam computed tomography (CBCT) projection images from ten fractions of seven lung cancer patients with implanted coiled markers were used. The arbitrarily shaped marker CNNs were trained using three patients and the other four unseen patients were used for validation. The effects of full training using a compact CNN (four layers with learnable weights) and transfer learning using a pretrained CNN (AlexNet, eight layers with learnable weights) were analyzed. Each CNN was evaluated using a Precision‐Recall curve (PRC), the area under the PRC plot (AUC), and by the calculation of sensitivity and specificity. The tracking system was assessed using the validation data and the accuracy was quantified by calculating the mean error, root‐mean‐square error (RMSE) and the 1st and 99th percentiles of the error. Results The fully trained CNN on the dataset with moderate noise levels had a sensitivity of 99.00% and specificity of 98.92%. Transfer learning of AlexNet resulted in a sensitivity and specificity of 99.42% and 98.13%, respectively, for the same datasets. For the arbitrarily shaped marker CNNs, the sensitivity was 98.58% and specificity was 98.97% for the fully trained CNN. The transfer learning CNN had a sensitivity and specificity of 98.49% and 99.56%, respectively. The CNNs were successfully incorporated into a multiple object tracking system for both cylindrical and arbitrarily shaped markers. The cylindrical shaped marker tracking had a mean RMSE of 1.6 ± 0.2 pixels and 1.3 ± 0.4 pixels in the x‐ and y‐directions, respectively. The arbitrarily shaped marker tracking had a mean RMSE of 3.0 ± 0.5 pixels and 2.2 ± 0.4 pixels in the x‐ and y‐directions, respectively. Conclusion With deep learning CNNs, high classification...

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“…In rare cases (with little predicted toxicity), it may even be possible to simply expand treatment margins to ensure coverage. On the other hand, in challenging dose-escalated scenarios, it may be appropriate to implement real-time imaging methods to increase the accuracy of treatment to better than 5 mm [39].…”

Section: Discussionmentioning

confidence: 99%

Quantifying Allowable Motion to Achieve Safe Dose Escalation in Pancreatic SBRT

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Campbell

Miften

et al. 2019

Practical Radiation Oncology

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Background and purpose: Tumor motion plays a key role in the safe delivery of Stereotactic Body Radiotherapy (SBRT) for pancreatic cancer. The purpose of this study was to use tumor motion data measured in patients to establish limits on motion magnitude for safe delivery of pancreatic SBRT, and to help guide motion-management decisions in potential dose-escalation scenarios. Materials and methods: Using 91 sets of pancreatic tumor motion data measured in patients, we calculated motion-convolved dose of the gross tumor volume (GTV), the duodenum and the stomach for 25 pancreatic cancer patients. We derived simple linear or quadratic models relating motion to changes in dose, and used these models to establish the maximum amount of motion allowable while satisfying error thresholds on key dose metrics. In the same way, we studied the effects of dose escalation and tumor volume on allowable motion. Results: In our patient cohort, the mean [minimum-maximum] allowable motion for 33/40/50 Gy to the PTV was 11.9 [6. 3-22.4], 10.4 [5.2-19.1] and 9.0 [4.2-16.0] mm, respectively. Maximum allowable motion decreased as dose was escalated, and was smaller in patients with larger tumors. We found significant differences in allowable motion between different plans, suggesting a patient-specific approach to motion management is possible. Conclusion: The effects of motion on pancreatic SBRT are highly variable between patients and there is potential to allow more motion in certain patients, even in dose-escalated scenarios. In our dataset, a conservative limit of 6.3 mm would ensure safe treatment of all patients treated to 33 Gy in 5 fractions.

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The first clinical implementation of real-time image-guided adaptive radiotherapy using a standard linear accelerator

Abstract: The clinical implementation of real-time image-guided adaptive radiotherapy on a standard linear accelerator using KIM and MLC tracking is feasible. This achievement paves the way for real-time IGART to be a mainstream treatment option.

Cited by 62 publications

References 24 publications

Development and commissioning of a full‐size prototype fixed‐beam radiotherapy system with horizontal patient rotation

Development and commissioning of a full‐size prototype fixed‐beam radiotherapy system with horizontal patient rotation

A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images

Quantifying Allowable Motion to Achieve Safe Dose Escalation in Pancreatic SBRT

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