4D-CT lung motion estimation with deformable registration: quantification of motion nonlinearity and hysteresis. - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Medical Physics Année : 2008

4D-CT lung motion estimation with deformable registration: quantification of motion nonlinearity and hysteresis.

Vlad Boldea
  • Fonction : Auteur
Gregory C Sharp
  • Fonction : Auteur
Steve B Jiang
  • Fonction : Auteur

Résumé

In this article, our goal is twofold. First, we propose and compare two methods which process deformable registration to estimate patient specific lung and tumor displacements and deformation during free breathing from four-dimensional computed tomography (4D-CT) data. Second, we propose techniques to quantify the physiological parameters of motion nonlinearity and hysteresis. A Fréchet distance-based criterion is introduced to measure the motion hysteresis. Experiments were conducted with 4D-CT data of five patients treated in radiotherapy for non-small cell lung cancer. The accuracy of deformation fields assessed against expert-selected landmarks was found to be within image voxel tolerance. The second method gave slightly better results in terms of accuracy and consistency, although the differences were not statistically significant between the two methods. Lung motion nonlinearity and hysteresis are patient specific, and vary across regions within the lung during respiration. For all patients, motion between end-exhale and end-inhale was well approximated with a straight line trajectory for the majority of lung points. Hysteresis was found to be globally correlated with trajectory length. The main limitation to the proposed method is that intensity-based deformable registration is dependent on image quality and image resolution. Another limitation is the absence of gold standard which makes the validation of the computed motion difficult. However, the proposed tools provide patient specific motion information which, in radiotherapy for example, can ease the definition of precise internal margins. In the future, the integration of physiological information from multiple patients could help to create a general lung atlas with different clinical applications.
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Dates et versions

hal-00631157 , version 1 (11-10-2011)

Identifiants

  • HAL Id : hal-00631157 , version 1
  • PUBMED : 18404936

Citer

Vlad Boldea, Gregory C Sharp, Steve B Jiang, David Sarrut. 4D-CT lung motion estimation with deformable registration: quantification of motion nonlinearity and hysteresis.. Medical Physics, 2008, 35 (3), pp.1008-18. ⟨hal-00631157⟩
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