A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

作者：Yang Y X; Teo S K; Van Reeth E; Tan C H; Tham I W K; Poh C L^*

来源：Medical Physics, 2015, 42(8): 4484-4496.

DOI：10.1118/1.4923167

• image fusion
• DIR
• FEM
• lung cancer
• radiotherapy

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors' proposed approach.
Methods: A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset.
Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors' proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques.
Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

• 出版日期2015-8
• 单位南阳理工学院