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In this article a biophysical approach for modeling respiratory lung motion is described: Major aspects of the process of lung ventilation are formulated as a contact problem of elasticity theory which is solved by finite element methods; lung tissue is assumed to be isotropic, homogeneous, and linearly elastic. A main focus of the article is to assess the impact of biomechanical parameters (values of elastic constants) on the modeling process and to evaluate modeling accuracy. Patient\u2010specific models are generated based on 4D CT data of 12 lung tumor patients. Simulated motion patterns of inner lung landmarks are compared with corresponding motion patterns observed in the 4D CT data. Mean absolute differences between model\u2010based predicted landmark motion and corresponding breathing\u2010induced landmark displacements as observed in the CT data sets are in the order of <jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/mp1820-math-0001.png\" xlink:title=\"urn:x-wiley:00942405:media:mp1820:mp1820-math-0001\"\/> (end expiration to end inspiration) and <jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/mp1820-math-0002.png\" xlink:title=\"urn:x-wiley:00942405:media:mp1820:mp1820-math-0002\"\/> (end expiration to midrespiration). Modeling accuracy decreases with increasing tumor size both locally (landmarks close to tumor) and globally (landmarks in other parts of the lung). The impact of the values of the elastic constants appears to be small. Outcomes show that the modeling approach is an adequate strategy in predicting lung dynamics due to lung ventilation. Nevertheless, the decreased prediction quality in cases of large tumors demands further study of the influence of lung tumors on global and local lung elasticity properties.<\/jats:p>","DOI":"10.1118\/1.3101820","type":"journal-article","created":{"date-parts":[[2009,4,27]],"date-time":"2009-04-27T22:26:39Z","timestamp":1240871199000},"page":"1500-1511","source":"Crossref","is-referenced-by-count":143,"title":["Patient\u2010specific finite element modeling of respiratory lung motion using 4D CT image data"],"prefix":"10.1002","volume":"36","author":[{"given":"Ren\u00e9","family":"Werner","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Ehrhardt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rainer","family":"Schmidt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heinz","family":"Handels","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2009,4,7]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.2349696"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0360\u20103016(99)00154\u20106"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0360\u20103016(03)00712\u20100"},{"key":"e_1_2_6_5_1","unstructured":"ICRU ICRU Report No. 62. 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