ArticlePhysics in medicine and biology2015
Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.
Article in Physics in medicine and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A novel personalized time-varying biomechanical model for estimating lung tumor motion and deformation.Medical physics · 2025Article
- Biomechanics-driven dose stress metrics for radiation-induced acute xerostomia prediction among head and neck radiation therapy.Physical and engineering sciences in medicine · 2025Article
- Biomechanics of flail chest injuries: tidal volume and respiratory work changes in multiple segmental rib fractures.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Article
- Mechanical signatures in cancer metastasis.npj biological physics and mechanics · 2025Review
- Magnetic Resonance Elastography and Computational Modeling Identify Heterogeneous Lung Biomechanical Properties during Cystic Fibrosis.Research square · 2024Article
- A novel computer modeling and simulation technique for bronchi motion tracking in human lungs under respiration.Physical and engineering sciences in medicine · 2023Article
- Data-driven gated CT: An automated respiratory gating method to enable data-driven gated PET/CT.Medical physics · 2022Article
- Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio).Medical physics · 2021Article
- A hybrid, image-based and biomechanics-based registration approach to markerless intraoperative nodule localization during video-assisted thoracoscopic surgery.Medical image analysis · 2021Article
- Validation of a CT-based motion model with in-situ fluoroscopy for lung surface deformation estimation.Physics in medicine and biology · 2021Article
- Development and prospective in-patient proof-of-concept validation of a surface photogrammetry + CT-based volumetric motion model for lung radiotherapy.Medical physics · 2019Article
- Enhancing liver tumor localization accuracy by prior-knowledge-guided motion modeling and a biomechanical model.Quantitative imaging in medicine and surgery · 2019Article
- 4D liver tumor localization using cone-beam projections and a biomechanical model.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2019Article
- Advanced 4-dimensional cone-beam computed tomography reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning.Visual computing for industry, biomedicine, and art · 2019Article
- Article
- A biomechanical modeling-guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction.Physics in medicine and biology · 2018Article
- Quantification of Age-Related Lung Tissue Mechanics under Mechanical Ventilation.Medical sciences (Basel, Switzerland) · 2017Article
- A Biomechanical Modeling Guided CBCT Estimation Technique.IEEE transactions on medical imaging · 2017Article
- Article
- A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities.International journal of radiation oncology, biology, physics · 2016Article
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7 authors.
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Abstract
Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.
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