Acquisition of MV-scatter-free kilovoltage CBCT images during RapidArc™ or VMAT

Ling, C. Clifton; Zhang, Pengpeng; Etmektzoglou, Thanos; Star‐Lack, Josh; Sun, Mengtao; Shapiro, Edward G.; Hunt, Margie

doi:10.1016/j.radonc.2011.07.010

Cited by 50 publications

(63 citation statements)

References 25 publications

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“…Existing techniques for MV scatter noise correction may further improve the tracking accuracy. These techniques include gating the MV (Ling et al , 2011) or kV beam (van Herk et al , 2011), correction using pre-acquired data (Boylan et al , 2012), and increasing the kV frame rate (Ng et al , 2012). The comparison with the standard of care in terms of the 95th-percentile errors highlighted the potential reduction in margins achievable with markerless tumor tracking, especially for tumors with large SI motions.…”

Section: Discussionmentioning

confidence: 99%

A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy

et al. 2017

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The ability to monitor tumor motion without implanted markers can potentially enable broad access to more accurate and precise lung radiotherapy. A major challenge is that kilovoltage (kV) imaging based methods are rarely able to continuously track the tumor due to the inferior tumor visibility on 2D kV images. Another challenge is the estimation of 3D tumor position based on only 2D imaging information. The aim of this work is to address both challenges by proposing a Bayesian approach for markerless tumor tracking for the first time. The proposed approach adopts the framework of the extended Kalman filter, which combines a prediction and measurement steps to make the optimal tumor position update. For each imaging frame, the tumor position is first predicted by a respiratory-correlated model. The 2D tumor position on the kV image is then measured by template matching. Finally, the prediction and 2D measurement is combined based on the 3D distribution of tumor positions in the past 10 seconds and the estimated uncertainty of template matching. To investigate the clinical feasibility of the proposed method, a total of 13 lung cancer patient datasets were used for retrospective validation, including 11 cone-beam CT scan pairs and two stereotactic ablative body radiotherapy cases. The ground truths for tumor motion were generated from the the 3D trajectories of implanted markers or beacons. The mean, standard deviation, and 95th percentile of the 3D tracking error was found to range from 1.6–2.9 mm, 0.6–1.5 mm, and 2.6–5.8 mm, respectively. Markerless tumor tracking always resulted in smaller errors compared to the standard of care. The improvement was the most pronounced in the superior-inferior (SI) direction, with up to 9.5 mm reduction in the 95th-percentile SI error for patients with >10 mm 5th-to-95th percentile SI tumor motion. The percentage of errors with 3D magnitude <5 mm was 96.5% for markerless tumor tracking and 84.1% for the standard of care. The feasibility of markerless tumor tracking has been demonstrated on realistic clinical scenarios for the first time. The clinical implementation of the proposed method will enable more accurate and precise lung radiotherapy using existing hardware and workflow. Future work is focused on the clinical and real-time implementation of this method.

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Section: Discussionmentioning

confidence: 99%

A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy

et al. 2017

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“…This allows the kV frame rate to be reduced. 13 • Temporarily halting the MV beam during kV acquisition as proposed by Ling et al 28 • Utilizing patient and gantry angle specific field sizes. 13 • Varying the exposure with gantry angle.…”

Section: Discussionmentioning

confidence: 99%

Quality assurance for the clinical implementation of kilovoltage intrafraction monitoring for prostate cancer VMAT

Booth

O’Brien

et al. 2014

Medical Physics

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“…[22][23][24] One disadvantage of continuous image acquisition during radiation dose delivery is that the kV projections are contaminated with scatter from the MV beam, which negatively affects the quality of the reconstructed image. Although methods to effectively deal with the MV scatter have been proposed, 23,24 they more or less require some modification of the existing system hardware/software. Another drawback is the increased radiation dose from continuous imaging, which is typically 1-2 orders of magnitude higher than our triggered beam-level imaging approach.…”

Section: Discussionmentioning

confidence: 99%

First study of on‐treatment volumetric imaging during respiratory gated VMAT

Choi

Koong

et al. 2013

Medical Physics

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Purpose: To obtain on-treatment volumetric patient anatomy during respiratory gated volumetric modulated arc therapy (VMAT). Methods: On-board imaging device integrated with Linacs offers a viable tool for obtaining patient anatomy during radiation treatment delivery. In this study, the authors acquired beam-level kV images during gated VMAT treatments using a Varian TrueBeam TM STx Linac. These kV projection images are triggered by a respiratory gating signal and can be acquired immediately before treatment MV beam on at every breathing cycle during delivery. Because the kV images are acquired with an on-board imaging device during a rotational arc therapy, they provide the patient anatomical information from many different angles or projection views (typically 20-40). To reconstruct the volumetric image representing patient anatomy during the VMAT treatment, the authors used a compressed sensing method with a fast first-order optimization algorithm. The conventional FDK reconstruction was also used for comparison purposes. The method was tested on a dynamic anthropomorphic physical phantom as well as a lung patient. Results: The reconstructed volumetric images for a dynamic anthropomorphic physical phantom and a lung patient showed clearly visible soft-tissue target as well as other anatomical structures, with the proposed compressed sensing-based image reconstruction method. Compared with FDK, the compressed sensing method leads to a ∼two and threefold increase in contrast-to-noise ratio around the target area in the phantom and patient case, respectively. Conclusions:The proposed technique provides on-treatment volumetric patient anatomy, with only a fraction (<10%) of the imaging dose used in conventional CBCT procedures. This anatomical information may be valuable for geometric verification and treatment guidance, and useful for verification of treatment dose delivery, accumulation, and adaptation in the future.

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Acquisition of MV-scatter-free kilovoltage CBCT images during RapidArc™ or VMAT

Cited by 50 publications

References 25 publications

A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy

A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy

Quality assurance for the clinical implementation of kilovoltage intrafraction monitoring for prostate cancer VMAT

First study of on‐treatment volumetric imaging during respiratory gated VMAT

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