Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-14T21:29:45.992Z Has data issue: false hasContentIssue false
  • English
  • Français

Impact of intra-fractional motion on dose distributions in lung IMRT

Published online by Cambridge University Press:  09 January 2020

Mikhail A. Chetvertkov ,
Oleg N. Vassiliev Open the ORCID record for Oleg N. Vassiliev [Opens in a new window] ,
Jinzhong Yang ,
He C. Wang ,
Amy Y. Liu ,
Zhongxing Liao  and
Radhe Mohan
Mikhail A. Chetvertkov
Affiliation:
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA
Oleg N. Vassiliev*
Affiliation:
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA
Jinzhong Yang
Affiliation:
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA
He C. Wang
Affiliation:
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA
Amy Y. Liu
Affiliation:
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA
Zhongxing Liao
Affiliation:
Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX77030, USA
Radhe Mohan
Affiliation:
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA
*
Author for correspondence: Oleg N. Vassiliev, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX77030, USA. Tel: 713-745-7995; Fax: 713-563-6949; Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Aim:

To investigate the impact of intra-fractional motion on dose distribution in patients treated with intensity-modulated radiotherapy (IMRT) for lung cancer.

Materials and methods:

Twenty patients who had undergone IMRT for non-small cell lung cancer were selected for this retrospective study. For each patient, a four-dimensional computed tomography (CT) image set was acquired and clinical treatment plans were developed using the average CT. Dose distributions were then recalculated for each of the 10 phases of respiratory cycle and combined using deformable image registration to produce cumulative dose distributions that were compared with the clinical treatment plans.

Results:

Intra-fractional motion reduced planning target volume (PTV) coverage in all patients. The median reduction of PTV covered by the prescription isodose was 3·4%; D98 was reduced by 3·1 Gy. Changes in the mean lung dose were within ±0·7 Gy. V20 for the lung increased in most patients; the median increase was 1·6%. The dose to the spinal cord was unaffected by intra-fractional motion. The dose to the heart was slightly reduced in most patients. The median reduction in the mean heart dose was 0·22 Gy, and V30 was reduced by 2·5%. The maximum dose to the oesophagus was also reduced in most patients, by 0·74 Gy, whereas V50 did not change significantly. The median number of points in which dose differences exceeded 3%/3 mm was 6·2%.

Findings:

Intra-fractional anatomical changes reduce PTV coverage compared to the coverage predicted by clinical treatment planning systems that use the average CT for dose calculation. Doses to organs at risk were mostly over-predicted.

Keywords

dose accuracyintra-fractional motionlung IMRTPTV coverage
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 20 , Issue 1 , March 2021 , pp. 12 - 16
Check for updates
Copyright
© The Authors, 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

a

Present address: Department of Radiation Oncology, Allegheny General Hospital, 320 E North Ave, Pittsburgh, PA 15212, USA

References

Flampouri, S, Jiang, SB, Sharp, GC et al. Estimation of the delivered patient dose in lung IMRT treatment based on deformable registration of 4D-CT data and Monte Carlo simulations. Phys Med Biol 2006; 51: 2763–2779.10.1088/0031-9155/51/11/006CrossRefGoogle ScholarPubMed
Guckenberger, M, Wilbert, J, Krieger, T et al. Four-dimensional treatment planning for stereotactic body radiotherapy. Int J Radiat Oncol Biol Phys 2007; 69: 276–285.10.1016/j.ijrobp.2007.04.074CrossRefGoogle ScholarPubMed
Rosu, M, Chetty, IJ, Tatro, DS, Ten Haken, RK.. The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning. Med Phys 2007; 34: 1462–1473.10.1118/1.2713427CrossRefGoogle ScholarPubMed
Admiraal, MA, Schuring, D, Hurkmans, CW. Dose calculations accounting for breathing motion in stereotactic lung radiotherapy based on 4D-CT and the internal target volume. Radiother Oncol 2008; 86: 55–60.10.1016/j.radonc.2007.11.022CrossRefGoogle ScholarPubMed
Roland, T, Mavroidis, P, Gutierrez, A, Goytia, V, Papanikolaou, N. A radiobiological analysis of the effect of 3D versus 4D image-based planning in lung cancer radiotherapy. Phys Med Biol 2009; 54: 5509–5523.10.1088/0031-9155/54/18/011CrossRefGoogle ScholarPubMed
Huang, TC, Liang, JA, Dilling, T, Wu, TH, Zhang, G. Four-dimensional dosimetry validation and study in lung radiotherapy using deformable image registration and Monte Carlo techniques. Radiat Oncol 2010; 5: 45 10.1186/1748-717X-5-45CrossRefGoogle ScholarPubMed
Chan, MKH, Kwong, DLW, Ng, SCY, Tam, EK, Tong, AS. Investigation of four-dimensional (4D) Monte Carlo dose calculation in real-time tumor tracking stereotactic body radiotherapy for lung cancers. Med Phys 2012; 39: 79–87 10.1118/1.4739249CrossRefGoogle ScholarPubMed
Li, H, Park, P, Liu, W et al. Patient-specific quantification of respiratory motion-induced dose uncertainty for step-and-shoot IMRT of lung cancer. Med Phys 2013; 40: 121712 10.1118/1.4829522CrossRefGoogle ScholarPubMed
Wang, H, Dong, L, Lii, MF et al. Implementation and validation of a three-dimensional deformable registration algorithm for targeted prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys 2005; 61: 725–735 10.1016/j.ijrobp.2004.07.677CrossRefGoogle ScholarPubMed
Wang, H, Garden, AS, Zhang, L et al. Performance evaluation of automatic anatomy segmentation algorithm on repeat or four-dimensional computed tomography images using deformable image registration method. Int J Radiat Oncol Biol Phys 2008; 72: 210–219 10.1016/j.ijrobp.2008.05.008CrossRefGoogle ScholarPubMed