Literature DB >> 11955756

Inclusion of geometric uncertainties in treatment plan evaluation.

Marcel van Herk1, Peter Remeijer, Joos V Lebesque.   

Abstract

PURPOSE: To correctly evaluate realistic treatment plans in terms of absorbed dose to the clinical target volume (CTV), equivalent uniform dose (EUD), and tumor control probability (TCP) in the presence of execution (random) and preparation (systematic) geometric errors.
MATERIALS AND METHODS: The dose matrix is blurred with all execution errors to estimate the total dose distribution of all fractions. To include preparation errors, the CTV is randomly displaced (and optionally rotated) many times with respect to its planned position while computing the dose, EUD, and TCP for the CTV using the blurred dose matrix. Probability distributions of these parameters are computed by combining the results with the probability of each particular preparation error. We verified the method by comparing it with an analytic solution. Next, idealized and realistic prostate plans were tested with varying margins and varying execution and preparation error levels.
RESULTS: Probability levels for the minimum dose, computed with the new method, are within 1% of the analytic solution. The impact of rotations depends strongly on the CTV shape. A margin of 10 mm between the CTV and planning target volume is adequate for three-field prostate treatments given the accuracy level in our department; i.e., the TCP in a population of patients, TCP(pop), is reduced by less than 1% due to geometric errors. When reducing the margin to 6 mm, the dose must be increased from 80 to 87 Gy to maintain the same TCP(pop). Only in regions with a high-dose gradient does such a margin reduction lead to a decrease in normal tissue dose for the same TCP(pop). Based on a rough correspondence of 84% minimum dose with 98% EUD, a margin recipe was defined. To give 90% of patients at least 98% EUD, the planning target volume margin must be approximately 2.5 Sigma + 0.7 sigma - 3 mm, where Sigma and sigma are the combined standard deviations of the preparation and execution errors. This recipe corresponds accurately with 1% TCP(pop) loss for prostate plans with clinically reasonable values of Sigma and sigma.
CONCLUSION: The new method computes in a few minutes the influence of geometric errors on the statistics of target dose and TCP(pop) in clinical treatment plans. Too small margins lead to a significant loss of TCP(pop) that is difficult to compensate for by dose escalation.

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Mesh:

Year:  2002        PMID: 11955756     DOI: 10.1016/s0360-3016(01)02805-x

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


  53 in total

1.  Consideration of the likely benefit from implementation of prostate image-guided radiotherapy using current margin sizes: a radiobiological analysis.

Authors:  G S J Tudor; Y L Rimmer; T B Nguyen; M A Cowen; S J Thomas
Journal:  Br J Radiol       Date:  2012-02-14       Impact factor: 3.039

2.  Dosimetric effect of intrafraction motion and residual setup error for hypofractionated prostate intensity-modulated radiotherapy with online cone beam computed tomography image guidance.

Authors:  Justus Adamson; Qiuwen Wu; Di Yan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-06-18       Impact factor: 7.038

3.  Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion.

Authors:  J J Gordon; J V Siebers
Journal:  Med Phys       Date:  2009-03       Impact factor: 4.071

4.  Evaluation of dosimetric margins in prostate IMRT treatment plans.

Authors:  J J Gordon; J V Siebers
Journal:  Med Phys       Date:  2008-02       Impact factor: 4.071

5.  Use of planar kV vs. CBCT in evaluation of setup errors in oesophagus carcinoma radiotherapy.

Authors:  Liliana Martins; Jose Guilherme Couto; Barbara Barbosa
Journal:  Rep Pract Oncol Radiother       Date:  2015-11-14

Review 6.  Robustness Analysis for External Beam Radiation Therapy Treatment Plans: Describing Uncertainty Scenarios and Reporting Their Dosimetric Consequences.

Authors:  Adam D Yock; Radhe Mohan; Stella Flampouri; Walter Bosch; Paige A Taylor; David Gladstone; Siyong Kim; Jason Sohn; Robert Wallace; Ying Xiao; Jeff Buchsbaum
Journal:  Pract Radiat Oncol       Date:  2018-12-15

7.  Linearity of patient positioning detection : a phantom study of skin markers, cone beam computed tomography, and 3D ultrasound.

Authors:  Hendrik Ballhausen; Sheila Hieber; Minglun Li; Katia Parodi; Claus Belka; Michael Reiner
Journal:  Strahlenther Onkol       Date:  2015-01-30       Impact factor: 3.621

8.  Target volume motion during anal cancer image guided radiotherapy using cone-beam computed tomography.

Authors:  Corrinne J Brooks; Laurence Bernier; Vibeke N Hansen; Diana M Tait
Journal:  Br J Radiol       Date:  2018-03-06       Impact factor: 3.039

9.  Method comparison of automated matching software-assisted cone-beam CT and stereoscopic kilovoltage x-ray positional verification image-guided radiation therapy for head and neck cancer: a prospective analysis.

Authors:  Clifton D Fuller; Todd J Scarbrough; Jan-Jakob Sonke; Coen R N Rasch; Mehee Choi; Joe Y Ting; Samuel J Wang; Niko Papanikolaou; David I Rosenthal
Journal:  Phys Med Biol       Date:  2009-11-24       Impact factor: 3.609

10.  Dosimetric impact of intrafractional patient motion in pediatric brain tumor patients.

Authors:  Chris Beltran; John Trussell; Thomas E Merchant
Journal:  Med Dosim       Date:  2009-02-07       Impact factor: 1.482

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