Optimizing fiducial visibility on periodically acquired megavoltage and kilovoltage image pairs during prostate volumetric modulated arc therapy

Zhang, Pengpeng; Happersett, Laura; Ravindranath, Bosky; Zeléfsky, Michael J.; Mageras, G.; Hunt, Margie A.

doi:10.1118/1.4944737

Cited by 7 publications

(15 citation statements)

References 21 publications

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“…To address this issue, we are developing the following approach as an initial step. (28) At each control point at which an MV SA-DTS/kV pair will be acquired, the VMAT MLC aperture is modified if needed to ensure visualization of at least one fiducial with margin sufficient to cover typical motion. A new dose calculation is performed with the modified apertures and compared to the original plan.…”

Section: Discussionmentioning

confidence: 99%

Simultaneous MV‐kV imaging for intrafractional motion management during volumetric‐modulated arc therapy delivery*

Hunt

Sonnick

Pham

et al. 2016

J Applied Clin Med Phys

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The purpose of this study was to evaluate the accuracy and clinical feasibility of a motion monitoring method employing simultaneously acquired MV and kV images during volumetric-modulated arc therapy (VMAT). Short-arc digital tomosynthesis (SA-DTS) is used to improve the quality of the MV images that are then combined with orthogonally acquired kV images to assess 3D motion. An anthropomorphic phantom with implanted gold seeds was used to assess accuracy of the method under static, typical prostatic, and respiratory motion scenarios. Automatic registration of kV images and single MV frames or MV SA-DTS reconstructed with arc lengths from 2° to 7° with the appropriate reference fiducial template images was performed using special purpose-built software. Clinical feasibility was evaluated by retrospectively analyzing images acquired over four or five sessions for each of three patients undergoing hypofractionated prostate radiotherapy. The standard deviation of the registration error in phantom using MV SA-DTS was similar to single MV images for the static and prostate motion scenarios (σ = 0.25 mm). Under respiratory motion conditions, the standard deviation of the registration error increased to 0.7mm and 1.7 mm for single MV and MV SA-DTS, respectively. Registration failures were observed with the respiratory scenario only and were due to motion-induced fiducial blurring. For the three patients studied, the mean and standard deviation of the difference between automatic registration using 4° MV SA-DTS and manual registration using single MV images results was 0.07±0.52mm. The MV SA-DTS results in patients were, on average, superior to single-frame MV by nearly 1 mm — significantly more than what was observed in phantom. The best MV SA-DTS results were observed with arc lengths of 3° to 4°. Registration failures in patients using MV SA-DTS were primarily due to blockage of the gold seeds by the MLC. The failure rate varied from 2% to 16%. Combined MV SA-DTS and kV imaging is feasible for intratreatment motion monitoring during VMAT of anatomic sites where limited motion is expected, and improves registration accuracy compared to single MV/kV frames. To create a clinically robust technique, further improvements to ensure visualization of fiducials at the desired control points without degradation of the treatment plan are needed.

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Section: Discussionmentioning

confidence: 99%

Simultaneous MV‐kV imaging for intrafractional motion management during volumetric‐modulated arc therapy delivery*

Hunt

Sonnick

Pham

et al. 2016

J Applied Clin Med Phys

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“…The authors addressed the marker detection failure in MV images by developing an automatic plan optimization strategy ensuring that at least one fiducial was always visible (Zhang et al 2016 ). Exposing one fiducial was feasible without loss of plan quality.…”

Section: Real-time Intrafraction Motion Monitoring Methodsmentioning

confidence: 99%

Real-time intrafraction motion monitoring in external beam radiotherapy

et al. 2019

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Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to ‘see what we treat, as we treat’ and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

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“…This offers a more streamlined solution, as it is readily integrated on modern linear accelerators and has lower costs and better localization. 13 , 14 However, on‐board kV imaging cannot image motion along the kV beam direction and may miss dosimetrically significant motions.…”

Section: Introductionmentioning

confidence: 99%

“…This technique accurately calculates 3D fiducial displacement from orthogonal kV and MV images acquired by standard gantry‐mounted onboard imaging systems. 13 , 14 , 22 , 23 In‐house software automatically identifies fiducials in MV and kV images, registers them to template images in the “ideal” fiducial position derived from the treatment plan, and generates the central position of the fiducials in 3D. Our institution began implementing this approach clinically in 2016, and it is now the standard clinical routine for prostate SBRT treatment.…”

Section: Introductionmentioning

confidence: 99%

“…This is implemented through triggered kV images, such as Varian's Intrafraction Motion Review (IMR), which displays fiducial contours retrieved from the treatment planning scan against fiducial projections on kV images acquired during treatment. This offers a more streamlined solution, as it is readily integrated on modern linear accelerators and has lower costs and better localization 13,14 . However, on‐board kV imaging cannot image motion along the kV beam direction and may miss dosimetrically significant motions.…”

Section: Introductionmentioning

confidence: 99%

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Retrospective analysis of MV–kV imaging‐based fiducial tracking in prostate SBRT treatment

Crotteau

Berry

et al. 2022

J Applied Clin Med Phys

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Motion management is critical for prostate stereotactic body radiotherapy (SBRT) due to its high fractional dose and proximity to organs at risk. This study seeks to quantify the advantages of MV-kV tracking over kV imaging alone through a retrospective analysis of over 300 patients who underwent prostate SBRT treatment using MV-kV tracking. Methods: An MV-kV imaging-based fiducial tracking technique has been developed at our institute and become a standard clinical practice. This technique calculates three-dimensional (3D) fiducial displacement in real time from orthogonal kV and MV images acquired simultaneously. The patient will be repositioned if for two consecutive MV-kV data points, the motion is larger than a tolerance of 1.5 mm in any of the lateral, superior-inferior, and/or anterior-posterior directions. This study retrospectively analyzed detected 3D motions using an MV-kV approach of 324 patients who recently underwent prostate SBRT treatments. An algorithm was developed to recover the 2D motion components as if they were detected by kV or MV imaging alone. Results: Our results indicated that out-of -tolerance motions were primarily limited to the range of 1.5-3 mm (>95%). The motions are primarily anteriorposterior and superior-inferior, with less than 14.8% of the occurrences in the lateral direction. Compared to out-of -tolerance occurrences detected by MV-kV approach, kV alone caught 46.6% of motions in all three directions, and MV alone caught 46.7%. kV alone shows an overall missing rate of 45.8% for superior-inferior motions and 38.6% for lateral motions. It is also demonstrated that the detectability of motion in specific directions greatly depends on gantry angles, as does the missing rate. Conclusions: Our study demonstrated that MV-kV imaging-based intrafraction motion tracking is superior to single kV imaging for prostate SBRT in clinical practice.

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Optimizing fiducial visibility on periodically acquired megavoltage and kilovoltage image pairs during prostate volumetric modulated arc therapy

Abstract: VMAT plans can be made to accommodate MV-kV imaging of fiducials. Fiducial visualization rate and workflow efficiency are significantly improved with an automatic modification and reoptimization approach.

Cited by 7 publications

References 21 publications

Simultaneous MV‐kV imaging for intrafractional motion management during volumetric‐modulated arc therapy delivery*

Simultaneous MV‐kV imaging for intrafractional motion management during volumetric‐modulated arc therapy delivery*

Real-time intrafraction motion monitoring in external beam radiotherapy

Retrospective analysis of MV–kV imaging‐based fiducial tracking in prostate SBRT treatment

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