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A fast model for prediction of respiratory lung motion for image-guided radiotherapy: A feasibility study
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M. Zehtabian   , R. Faghihi , M.A. Mosleh-Shirazi , A.R. Shakibafard , M. Mohammadi , M. Baradaran-Ghahfarokhi |
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Abstract: (8292 Views) |
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Background: The aim of this work was to study the
feasibility of constructing a fast thorax model suitable
for simulating lung motion due to respiration using
only one CT dataset. Materials and Methods: For
each of six patients with different thorax sizes, two
sets of CT images were obtained in single-breath-hold
inhale and exhale stages in the supine position. The
CT images were then analyzed by measurements of
the displacements due to respiration in the thorax
region. Lung and thorax were 3D reconstructed and
then transferred to the ABAQUS software for
biomechanical fast finite element (FFE) modeling. The
FFE model parameters were tuned based on three of
the patients, and then was tested in a predictive
mode for the remaining patients to predict lung and
thorax motion and deformation following respiration.
Results: Starting from end-exhale stage, the model,
tuned for a patient created lung wall motion at
end-inhale stage that matched the measurements for
that patient within 1 mm (its limit of accuracy). In the
predictive mode, the mean discrepancy between the
imaged landmarks and those predicted by the model
(formed from averaged data of two patients) was 4.2
mm. The average computation time in the fast predictive
mode was 89 sec. Conclusion: Fast prediction of
approximate, lung and thorax shapes in the respiratory
cycle has been feasible due to the linear elastic
material approximation, used in the FFE model. Iran.
J. Radiat. Res., 2012 10(2): 73‐81
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| Keywords: Finite element modeling, lung motion, image-guided radiotherapy |
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Full-Text [PDF 989 kb]
(2476 Downloads)
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Type of Study: Original Research |
Subject:
Radiation Biology
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