gms | German Medical Science

48th Meeting of the Particle Therapy Co-Operative Group

Particle Therapy Co-Operative Group (PTCOG)

28.09. - 03.10.2009, Heidelberg

4D Lung IMPT Planning and Evaluation on Multiple Deformable Geometries

Meeting Abstract

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  • M. Söhn - Section for Biomedical Physics, Radiooncological Clinic, University of Tübingen, Tübingen
  • M. Soukup - Elekta CMS Software, Freiburg
  • M. Alber - Section for Biomedical Physics, Radiooncological Clinic, University of Tübingen, Tübingen

PTCOG 48. Meeting of the Particle Therapy Co-Operative Group. Heidelberg, 28.09.-03.10.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. Doc09ptcog189

DOI: 10.3205/09ptcog189, URN: urn:nbn:de:0183-09ptcog1893

Published: September 24, 2009

© 2009 Söhn et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

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Background: The high sensitivity of proton dose distributions against tissue density changes renders free-breathing treatment of moving lung lesions difficult. This is especially pronounced in intensity-modulated proton therapy (IMPT) where respiratory tumor motion along with varying tissue inhomogeneities causes large changes of the Bragg-peak positions and lateral dose deposition of the proton spots over the breathing cycle.

To fully address these challenges, the dose-to-moving-tissue instead of a static dose distribution as in conventional, margin-based approaches should be optimized in IMPT-planning. This requires dose warping for plan optimization based on deformation fields obtained from deformable registration between multiple phases of a respiratory correlated CT (RCCT) dataset.

Material and methods: For 4D-IMPT optimization, the proton spot doses are simultaneously calculated in multiple (8–10) CTs of different breathing phases as given by a RCCT dataset. These instance doses are warped to a common reference geometry (e.g. exhale CT) using the deformation fields, where the different phases are weighted according to the probability density function (pdf) of respiratory motion from the RCCT data. The resulting expected dose as warped to the reference geometry represents the dose-to-moving-tissue, which allows dose prescription directly to the moving CTV and OARs for IMPT optimization.

Accumulated DVHs and EUDs of the moving CTV and OARs resulting from this 4D-IMPT planning approach (4Dp) were compared to the results of static, margin-based IMPT planning (STATICp) for free-breathing treatment of an example patient with a small lesion and large breathing excursion.

IMPT treatment plans with a 2-beam configuration were created for both methods. 55Gy target dose were prescribed to the moving CTV (4Dp) or ITV (STATICp), respectively.

Results: Both 4Dp and STATICp managed to meet the target prescription for a given constraint of 2Gy mean dose to the ipsilateral lung.

However, the dose values calculated by STATICp differed from the actual dose-to-moving tissue as determined by dose recalculation of the static plan in the different RCCT geometries (4D-evaluation). Only when a density override of the ITV region with the tumor density is used for STATICp optimization, similar coverage of the moving CTV could be achieved as compared to 4Dp. However, 4D-evaluation of STATICp revealed over 30% higher mean lung dose as compared to 4Dp.

Conclusion: 4D-IMPT treatment planning for free-breathing lung treatment with dose calculation in multiple patient geometries and deformable dose warping is necessary to address the challenges of IMPT in the presence of dynamically varying tissue inhomogeneities. It provides superior treatment plans for patients with large breathing excursion in terms of OAR sparing compared to margin-based static planning.