Literature DB >> 20647609

Image-guided adaptive gating of lung cancer radiotherapy: a computer simulation study.

Michalis Aristophanous1, Joerg Rottmann, Sang-June Park, Seiko Nishioka, Hiroki Shirato, Ross I Berbeco.   

Abstract

The purpose of this study is to investigate the effect that image-guided adaptation of the gating window during treatment could have on the residual tumor motion, by simulating different gated radiotherapy techniques. There are three separate components of this simulation: (1) the 'Hokkaido Data', which are previously measured 3D data of lung tumor motion tracks and the corresponding 1D respiratory signals obtained during the entire ungated radiotherapy treatments of eight patients, (2) the respiratory gating protocol at our institution and the imaging performed under that protocol and (3) the actual simulation in which the Hokkaido Data are used to select tumor position information that could have been collected based on the imaging performed under our gating protocol. We simulated treatments with a fixed gating window and a gating window that is updated during treatment. The patient data were divided into different fractions, each with continuous acquisitions longer than 2 min. In accordance to the imaging performed under our gating protocol, we assume that we have tumor position information for the first 15 s of treatment, obtained from kV fluoroscopy, and for the rest of the fractions the tumor position is only available during the beam-on time from MV imaging. The gating window was set according to the information obtained from the first 15 s such that the residual motion was less than 3 mm. For the fixed gating window technique the gate remained the same for the entire treatment, while for the adaptive technique the range of the tumor motion during beam-on time was measured and used to adapt the gating window to keep the residual motion below 3 mm. The algorithm used to adapt the gating window is described. The residual tumor motion inside the gating window was reduced on average by 24% for the patients with regular breathing patterns and the difference was statistically significant (p-value = 0.01). The magnitude of the residual tumor motion depended on the regularity of the breathing pattern suggesting that image-guided adaptive gating should be combined with breath coaching. The adaptive gating window technique was able to track the exhale position of the breathing cycle quite successfully. Out of a total of 53 fractions the duty cycle was greater than 20% for 42 fractions for the fixed gating window technique and for 39 fractions for the adaptive gating window technique. The results of this study suggest that real-time updating of the gating window can result in reliably low residual tumor motion and therefore can facilitate safe margin reduction.

Entities:  

Mesh:

Year:  2010        PMID: 20647609     DOI: 10.1088/0031-9155/55/15/009

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  5 in total

1.  Inversed-Planned Respiratory Phase Gating in Lung Conformal Radiation Therapy.

Authors:  Arezoo Modiri; Pouya Sabouri; Xuejun Gu; Robert Timmerman; Amit Sawant
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-06-01       Impact factor: 7.038

2.  2D/4D marker-free tumor tracking using 4D CBCT as the reference image.

Authors:  Mengjiao Wang; Gregory C Sharp; Simon Rit; Vivien Delmon; Guangzhi Wang
Journal:  Phys Med Biol       Date:  2014-04-08       Impact factor: 3.609

3.  Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study.

Authors:  S R Bowen; M J Nyflot; C Herrmann; C M Groh; J Meyer; S D Wollenweber; C W Stearns; P E Kinahan; G A Sandison
Journal:  Phys Med Biol       Date:  2015-04-17       Impact factor: 3.609

4.  Tumor control probability reduction in gated radiotherapy of non-small cell lung cancers: a feasibility study.

Authors:  R Alfredo Siochi; Yusung Kim; Sudershan Bhatia
Journal:  J Appl Clin Med Phys       Date:  2014-10-16       Impact factor: 2.102

5.  External respiratory motion analysis and statistics for patients and volunteers.

Authors:  Sarah Quirk; Nathan Becker; W L Smith
Journal:  J Appl Clin Med Phys       Date:  2013-03-04       Impact factor: 2.102

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.