Literature DB >> 16095848

Evaluating the influence of setup uncertainties on treatment planning for focal liver tumors.

James M Balter1, Kristy K Brock, Kwok L Lam, Daniel Tatro, Laura A Dawson, Daniel L McShan, Randall K Ten Haken.   

Abstract

PURPOSE: A mechanism has been developed to evaluate the influence of random setup variations on dose during treatment planning. The information available for studying these factors shifts from population-based models toward patient-specific data as treatment progresses and setup measurements for an individual patient become available. This study evaluates the influence of population as well as patient-specific setup distributions on treatment plans for focal liver tumors. METHODS AND MATERIALS: Eight patients with focal liver tumors were treated on a protocol that involved online setup measurement and adjustment, as well as ventilatory immobilization. Summary statistics from these three-dimensional conformal treatments yielded individual and population distributions of position at initial setup for each fraction. A convolution model for evaluation of the influence of random setup variation on calculated dose distributions has been previously described and investigated for application to focal liver radiotherapy by our department. Individual patient doses based on initial setup positions were calculated by convolving the calculated dose distribution with an anisotropic probability distribution function representing the individual patient's random variations. A separate convolution using population-averaged random variations was performed. Individual beam apertures were then adjusted to provide plans that ensured proper dose to the clinical target volume following convolution with population distributions, as well as individual patient position uncertainty models.
RESULTS: Individual patient setup distributions for the course of treatment had random setup variations (sigma) that ranged from 2.5 to 5.7 mm (left-right), 2.1 to 8.3 mm (anterior-posterior), and 4.1 to 10.8 mm (cranial-caudal). The population random components were 4.2 mm (left-right), 4.1 mm (anterior-posterior), and 7.0 mm (cranial-caudal) at initial setup. The initial static planned dose distribution overestimated the volume of liver irradiated to high doses, because inclusion of setup uncertainties generally blurred the resulting doses, shifting the higher-dose region of normal liver dose-volume histograms to lower doses. Furthermore, the population-based dose convolution tended to predict a higher risk of radiation damage to the liver (based on an in-house parameterization of the Lyman normal tissue complication probability model) than the individual patient calculations. For an individual plan, application of different individual random variations yielded change in effective volume differences with a 3% range. Plan adjustment to account for random setup variations generally resulted in a lower change in effective volume than initial planning using a planning target volume followed by calculation of delivered dose based on random offsets.
CONCLUSION: This study hints at the factors that most strongly influence planning of liver treatments taking into account geometric variations. Given a setup verification methodology that rapidly reduces systematic offsets, the importance of realistic incorporation of geometric variations as an initial step in treatment planning, as well as possible plan refinement, is demonstrated.

Entities:  

Mesh:

Year:  2005        PMID: 16095848     DOI: 10.1016/j.ijrobp.2005.05.014

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  8 in total

1.  Patient setup verification procedure for a portal image in a computed radiography system with a high-resolution liquid-crystal display monitor.

Authors:  Hideki Fujita; Michihiro Yamaguchi; Yuichi Bessho; Tomio Fujioka; Haruyuki Fukuda; Kenya Murase
Journal:  Radiol Phys Technol       Date:  2009-11-20

2.  Comparisons of treatment optimization directly incorporating systematic patient setup uncertainty with a margin-based approach.

Authors:  Joseph A Moore; J James Gordon; Mitchell Anscher; Joaquin Silva; Jeffrey V Siebers
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

3.  A simplified method of four-dimensional dose accumulation using the mean patient density representation.

Authors:  Carri K Glide-Hurst; Geoffrey D Hugo; Jian Liang; Di Yan
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

4.  Tumor trailing strategy for intensity-modulated radiation therapy of moving targets.

Authors:  Alexei Trofimov; Christian Vrancic; Timothy C Y Chan; Gregory C Sharp; Thomas Bortfeld
Journal:  Med Phys       Date:  2008-05       Impact factor: 4.071

5.  Biological impact of geometric uncertainties: what margin is needed for intra-hepatic tumors?

Authors:  Hsiang-Chi Kuo; Wen-Shan Liu; Andrew Wu; Dennis Mah; Keh-Shih Chuang; Linda Hong; Ravi Yaparpalvi; Chandan Guha; Shalom Kalnicki
Journal:  Radiat Oncol       Date:  2010-06-03       Impact factor: 3.481

6.  Comparisons of treatment optimization directly incorporating random patient setup uncertainty with a margin-based approach.

Authors:  Joseph A Moore; John J Gordon; Mitchell S Anscher; Jeffrey V Siebers
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

7.  Adequacy of inhale/exhale breathhold CT based ITV margins and image-guided registration for free-breathing pancreas and liver SBRT.

Authors:  Wensha Yang; Benedick A Fraass; Robert Reznik; Nicholas Nissen; Simon Lo; Laith H Jamil; Kapil Gupta; Howard Sandler; Richard Tuli
Journal:  Radiat Oncol       Date:  2014-01-09       Impact factor: 3.481

8.  Assessment of setup uncertainty in hypofractionated liver radiation therapy with a breath-hold technique using automatic image registration-based image guidance.

Authors:  Gye Won Choi; Yelin Suh; Prajnan Das; Joseph Herman; Emma Holliday; Eugene Koay; Albert C Koong; Sunil Krishnan; Bruce D Minsky; Grace L Smith; Cullen M Taniguchi; Sam Beddar
Journal:  Radiat Oncol       Date:  2019-08-30       Impact factor: 3.481

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.