No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
First evaluation of the feasibility of MLC tracking using ultrasound motion estimation
E. Colvill, J. T. Booth, R. T. O’Brien, T. N. Eade, A. B. Kneebone, P. R. Poulsen, and P. J. Keall, “Multileaf collimator tracking improves dose delivery for prostate cancer radiation therapy: Results of the first clinical trial,” Int. J. Radiat. Oncol., Biol., Phys. 92(5), 1141–1147 (2015).
M. F. Fast, C. P. Kamerling, P. Ziegenhein, M. J. Menten, J. L. Bedford, S. Nill, and U. Oelfke, “Assessment of MLC tracking performance during hypofractionated prostate radiotherapy using real-time dose reconstruction,” Phys. Med. Biol. 61(4), 1546–1562 (2016).
P. R. Poulsen, B. Cho, A. Sawant, D. Ruan, and P. J. Keall, “Detailed analysis of latencies in image-based dynamic MLC tracking,” Med. Phys. 37(9), 4998–5005 (2010).
J. A. Ng, J. T. Booth, P. R. Poulsen, W. Fledelius, E. S. Worm, T. Eade, F. Hegi, A. Kneebone, Z. Kuncic, and P. J. Keall, “Kilovoltage intrafraction monitoring for prostate intensity modulated arc therapy: First clinical results,” Int. J. Radiat. Oncol., Biol., Phys. 84(5), e655–e661 (2012).
T. P. O’Shea, L. J. Garcia, K. E. Rosser, E. J. Harris, P. M. Evans, and J. C. Bamber, “4D ultrasound speckle tracking of intra-fraction prostate motion: A phantom-based comparison with x-ray fiducial tracking using CyberKnife,” Phys. Med. Biol. 59(7), 1701–1720 (2014).
T. P. O’Shea, J. C. Bamber, D. Fontanarosa, S. van der Meer, F. Verhaegen, and E. J. Harris, “Review of ultrasound image guidance in external beam radiotherapy part 2: Intra-fraction motion management and novel applications,” Phys. Med. Biol. 61(8), R90–R137 (2016).
M. F. Fast, S. Nill, J. L. Bedford, and U. Oelfke, “Dynamic tumor tracking using the Elekta agility MLC,” Med. Phys. 41(11), 111719 (5pp.) (2014).
M. Lachaine and T. Falco, “Intrafractional prostate motion management with the clarity autoscan system,” Med. Phys. Int. 1(1), 72–80 (2013).
J. L. Bedford, M. F. Fast, S. Nill, F. M. McDonald, M. Ahmed, V. N. Hansen, and U. Oelfke, “Effect of MLC tracking latency on conformal volumetric modulated arc therapy (VMAT) plans in 4D stereotactic lung treatment,” Radiother. Oncol. 117(3), 491–495 (2015).
G. Davies, P. Clowes, J. Bedford, P. Evans, S. Webb, and G. Poludniowski, “An experimental evaluation of the Agility MLC for motion-compensated VMAT delivery,” Phys. Med. Biol. 58(13), 4643–4657 (2013).
A. Krauss, S. Nill, and U. Oelfke, “The comparative performance of four respiratory motion predictors for real-time tumour tracking,” Phys. Med. Biol. 56(16), 5303–5317 (2011).
J. L. Bedford, Y. K. Lee, P. Wai, C. P. South, and A. P. Warrington, “Evaluation of the Delta4 phantom for IMRT and VMAT verification,” Phys. Med. Biol. 54(9), N167–N176 (2009).
E. J. Harris, N. R. Miller, J. C. Bamber, J. R. N. Symonds-Tayler, and P. M. Evans, “The effect of object speed and direction on the performance of 3D speckle tracking using a 3D swept-volume ultrasound probe,” Phys. Med. Biol. 56(22), 7127–7143 (2011).
W. Fledelius, P. J. Keall, B. Cho, X. Yang, D. Morf, S. Scheib, and P. R. Poulsen, “Tracking latency in image-based dynamic MLC tracking with direct image access,” Acta Oncol. 50(6), 952–959 (2011).
M. A. L. Bell, B. C. Byram, E. J. Harris, P. M. Evans, and J. C. Bamber, “In vivo liver tracking with a high volume rate 4D ultrasound scanner and a 2D matrix array probe,” Phys. Med. Biol. 57(5), 1359–1374 (2012).
Article metrics loading...
To quantify the performance of the Clarity ultrasound
imaging system (Elekta AB, Stockholm, Sweden) for real-time dynamic multileaf collimator
The Clarity calibration and quality assurance phantom was mounted on a motion platform moving with a periodic sine wave trajectory. The detected position of a 30 mm hypoechogenic sphere within the phantom was continuously reported via Clarity’s real-time streaming interface to an in-house tracking and delivery software and subsequently used to adapt the MLC aperture. A portal imager measured MV treatment field/MLC apertures and motion platform positions throughout each experiment to independently quantify system latency and geometric error. Based on the measured range of latency values, a prostate stereotactic body radiation therapy (SBRT) delivery was performed with three realistic motion trajectories. The dosimetric impact of system latency on MLC tracking was directly measured using a 3D
dosimeter mounted on the motion platform.
For 2D US
imaging, the overall system latency, including all delay times from the imaging and delivery chain, ranged from 392 to 424 ms depending on the lateral sector size. For 3D
imaging, the latency ranged from 566 to 1031 ms depending on the elevational sweep. The latency-corrected geometric root-mean squared error was below 0.75 mm (2D US) and below 1.75 mm (3D
US). For the prostate SBRT delivery, the impact of a range of system latencies (400–1000 ms) on the MLC tracking performance was minimal in terms of gamma failure rate.
Real-time MLC tracking based on a noninvasive US input is technologically feasible. Current system latencies are higher than those for x-ray imaging systems, but US can provide full volumetric image data and the impact of system latency was measured to be small for a prostate SBRT case when using a US-like motion input.
Full text loading...
Most read this month