Use of dMLC for implementation of dynamic respiratory‐gated radiation therapy

Pepin, Eric W.; Wu, Huanmei; Shirato, Hiroki

doi:10.1118/1.4820534

Cited by 5 publications

(3 citation statements)

References 55 publications

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“…A control algorithm uses the detected motion, to adapt the aperture to avoid the OAR (figure 1). This proof-of-concept prototype was verified using a virtual DMLC (Lucas and Kanade 1981, Pepin et al 2013, Teo et al 2019. Since most OARs move as a result of respiration-induced motion, we have used a lung phantom to generate images of a generic OAR intruding into a treatment field with known velocity.…”

Section: Global and Local Motion Tracking With Optical Flowmentioning

confidence: 99%

“…This work focuses on detecting local motions at the edges and adapting the MLC leaves accordingly. Tracking of the global motion due to the primary target has been well investigated in previous studies (Teo et al 2013, Pepin et al 2013, Teo and Pistorius 2014, Teo et al 2019 and hence, has not been repeated in this paper. AAPM Task-Group (TG-132) report recommends the use of both physical and virtual phantom to verify accuracies of image registration algorithms prior to clinical implementation (Brock et al 2017).…”

Section: Future Workmentioning

confidence: 99%

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Evaluating a potential technique with local optical flow vectors for automatic organ-at-risk (OAR) intrusion detection and avoidance during radiotherapy

et al. 2019

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Various techniques of deep inspiration breath hold (DIBH) have been used to mitigate the likelihood and risk of exposing the heart, an organ-at-risk (OAR) for unintended radiation during left breast radiotherapy. However, issues of reproducibility of these techniques warrant further investigation into the feasibility of detecting the intrusion of an OAR into the treatment field during intra-fractional treatment delivery. The increase of high-dose, low-fraction radiotherapy treatments makes it important to immediately adapt treatment once an OAR is detected in the treatment field. This proof-of-concept implementation includes an algorithm that detects and tracks the motion at the edges of a treatment field and a control algorithm that adapts the treatment aperture according to the motion detected. In accordance to the AAPM Task-Group (TG-132) report, image registration techniques should be verified with virtual and physical phantoms prior to clinical application. Since most OARs move as a result of respiration-induced motion, we have used a lung phantom to generate images of a generic OAR intruding into a treatment field with known velocity. The phantom was programmed to move with sinusoidal and lung patient tumor motion patterns and the accuracy of intrusion tracking and MLC adaptation were benchmarked with the ground truth—programmed motion of the OAR. The motions were recorded with an electronic portal imaging device (EPID). An optimal cluster size of 9 × 9 motion vectors was found to provide the smallest average absolute position error of 0.3 mm. A strong linear correlation between the adapted MLC leaves and the actual OAR position was observed. The algorithm had a mean position tracking error of −0.4 ± 0.3 mm and a precision of 1.1 mm. It is possible to adapt MLC leaves based on the motion detected at the edges of the irradiated field, and it would be feasible to shield an unplanned intrusion of an OAR into the treatment field.

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Section: Global and Local Motion Tracking With Optical Flowmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%

Evaluating a potential technique with local optical flow vectors for automatic organ-at-risk (OAR) intrusion detection and avoidance during radiotherapy

et al. 2019

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“…Wink et al have studied an individualized gating technique, where tumor motion extent was used to determine the optimal length for the gating window [12]. Other researchers studied image guidance and internal markers for creating an adaptive or dynamic gating window [15–17]. In these personalized gating studies, the gating phase was predetermined and kept fixed on either EI or EE, as in standard gating, while the window length was changed.…”

Section: Introductionmentioning

confidence: 99%

Inversed-Planned Respiratory Phase Gating in Lung Conformal Radiation Therapy

Modiri

Sabouri

et al. 2017

International Journal of Radiation Oncology*Biology*Physics

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Background and Purpose Respiratory gating is a frequently-used clinical motion-management strategy in lung radiotherapy. In conventional gating, the beam is turned on during a pre-determined window; typically, around end-exhalation (EE). In this work, we postulate that the optimal gating window for each beam will be dependent on a variety of patient-specific factors, such as tumor size and location, and the extent of relative tumor and organ motion. Material and Methods In order to create optimal gating treatment plans, we started from an optimized clinical plan, created a plan per respiratory phase using the same beam arrangements, and used an inverse planning optimization approach to determine the optimal gating window for each beam and optimal beam weights, i.e., monitor units (MUs). Two pieces of information were used for optimization: (i) the state of the anatomy at each phase, extracted from 4D CT scans, and (ii) the time spent in each state, estimated from a 2-minute monitoring of the patient’s breathing motion. We retrospectively studied 15 lung cancer patients clinically treated by hypofractionated conformal radiation therapy, where 45 – 60 Gy was administered over 3 – 15 fractions using 7 – 13 beams. Mean gross tumor volume and respiratory-induced tumor motion was 82.5 cc and 1.0 cm, respectively. Results Although patients spent most of their respiratory cycle in EE, our optimal gating plans used EE for only 34% of the beams. Using optimal gating, maximum and mean doses to esophagus, heart and spinal cord were reduced by an average of 15 – 26% and the beam-on times were reduced by an average of 23% compared to equivalent single-phase EE gated plans (p < 0.034, paired, two – tailed T – test). Conclusions We introduce a personalized respiratory-gating technique where inverse planning optimization is used to determine patient- and beam-specific gating phases towards enhancing dosimetric quality of radiotherapy treatment plans.

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