Literature DB >> 20426131

Modeling respiratory motion for cancer radiation therapy based on patient-specific 4DCT data.

Jaesung Eom1, Chengyu Shi, Xie George Xu, Suvranu De.   

Abstract

Prediction of respiratory motion has the potential to substantially improve cancer radiation therapy. A nonlinear finite element (FE) model of respiratory motion during full breathing cycle has been developed based on patient specific pressure-volume relationship and 4D Computed Tomography (CT) data. For geometric modeling of lungs and ribcage we have constructed intermediate CAD surface which avoids multiple geometric smoothing procedures. For physiologically relevant respiratory motion modeling we have used pressure-volume (PV) relationship to apply pressure loading on the surface of the model. A hyperelastic soft tissue model, developed from experimental observations, has been used. Additionally, pleural sliding has been considered which results in accurate deformations in the superior-inferior (SI) direction. The finite element model has been validated using 51 landmarks from the CT data. The average differences in position is seen to be 0.07 cm (SD = 0.20 cm), 0.07 cm (0.15 cm), and 0.22 cm (0.18 cm) in the left-right, anterior-posterior, and superior-inferior directions, respectively.

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Year:  2009        PMID: 20426131     DOI: 10.1007/978-3-642-04271-3_43

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  2 in total

1.  Computational modeling of airway and pulmonary vascular structure and function: development of a "lung physiome".

Authors:  Merryn Tawhai; A Clark; G Donovan; K Burrowes
Journal:  Crit Rev Biomed Eng       Date:  2011

2.  A biomechanical modeling-guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction.

Authors:  Xiaokun Huang; You Zhang; Jing Wang
Journal:  Phys Med Biol       Date:  2018-02-08       Impact factor: 3.609

  2 in total

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