Literature DB >> 16964857

The susceptibility of IMRT dose distributions to intrafraction organ motion: an investigation into smoothing filters derived from four dimensional computed tomography data.

Catherine Coolens1, Phil M Evans, Joao Seco, Steve Webb, Jane M Blackall, Eike Rietzel, George T Y Chen.   

Abstract

This study investigated the sensitivity of static planning of intensity-modulated beams (IMBs) to intrafraction deformable organ motion and assessed whether smoothing of the IMBs at the treatment-planning stage can reduce this sensitivity. The study was performed with a 4D computed tomography (CT) data set for an IMRT treatment of a patient with liver cancer. Fluence profiles obtained from inverse-planning calculations on a standard reference CT scan were redelivered on a CT scan from the 4D data set at a different part of the breathing cycle. The use of a nonrigid registration model on the 4D data set additionally enabled detailed analysis of the overall intrafraction motion effects on the IMRT delivery during free breathing. Smoothing filters were then applied to the beam profiles within the optimization process to investigate whether this could reduce the sensitivity of IMBs to intrafraction organ motion. In addition, optimal fluence profiles from calculations on each individual phase of the breathing cycle were averaged to mimic the convolution of a static dose distribution with a motion probability kernel and assess its usefulness. Results from nonrigid registrations of the CT scan data showed a maximum liver motion of 7 mm in superior-inferior direction for this patient. Dose-volume histogram (DVH) comparison indicated a systematic shift when planning treatment on a motion-frozen, standard CT scan but delivering over a full breathing cycle. The ratio of the dose to 50% of the normal liver to 50% of the planning target volume (PTV) changed up to 28% between different phases. Smoothing beam profiles with a median-window filter did not overcome the substantial shift in dose due to a difference in breathing phase between planning and delivery of treatment. Averaging of optimal beam profiles at different phases of the breathing cycle mainly resulted in an increase in dose to the organs at risk (OAR) and did not seem beneficial to compensate for organ motion compared with using a large margin. Additionally, the results emphasized the need for 4D CT scans when aiming to reduce the internal margin (IM). Using only a single planning scan introduces a systematic shift in the dose distribution during delivery. Smoothing beam profiles either based on a single scan or over the different breathing phases was not beneficial for reducing this shift.

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Year:  2006        PMID: 16964857     DOI: 10.1118/1.2219329

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  6 in total

1.  Inverse 4D conformal planning for lung SBRT using particle swarm optimization.

Authors:  A Modiri; X Gu; A Hagan; R Bland; P Iyengar; R Timmerman; A Sawant
Journal:  Phys Med Biol       Date:  2016-08-01       Impact factor: 3.609

2.  Inverse-planned deliverable 4D-IMRT for lung SBRT.

Authors:  Mahdi Hamzeei; Arezoo Modiri; Narges Kazemzadeh; Aaron Hagan; Amit Sawant
Journal:  Med Phys       Date:  2018-10-01       Impact factor: 4.071

3.  Three-dimensional conformal planning with low-segment multicriteria intensity modulated radiation therapy optimization.

Authors:  Fazal Khan; David Craft
Journal:  Pract Radiat Oncol       Date:  2014-08-21

4.  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

5.  An energy transfer method for 4D Monte Carlo dose calculation.

Authors:  Jeffrey V Siebers; Hualiang Zhong
Journal:  Med Phys       Date:  2008-09       Impact factor: 4.071

6.  Monte Carlo dose mapping on deforming anatomy.

Authors:  Hualiang Zhong; Jeffrey V Siebers
Journal:  Phys Med Biol       Date:  2009-09-09       Impact factor: 3.609

  6 in total

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