Volumetric Cine Imaging for On-board Target Localization in Radiation Therapy.
저자
발행사항
Ann Arbor : ProQuest Dissertations & Theses, 2018
학위수여대학
Duke University Medical Physics
수여연도
2018
작성언어
영어
주제어
학위
Ph.D.
페이지수
171 p.
지도교수/심사위원
Advisers: Lei Ren; Fang-Fang Yin.
Accurate target localization is critical for liver and lung cancers due to uncertainties caused by respiratory motions. On-board four-dimensional (4D) or real-time verification of the tumor before and during Stereotactic Body Radiation Therapy (SBRT) is necessary because SBRT uses high fractional doses, tight Planning Target Volume (PTV) margins and a long treatment time. Current imaging of moving targets for on-board localization cannot image full volumetric information in real-time. The purposes of this dissertation research are to do the following. (1) Develop a real-time quasi-cine CBCT reconstruction method for on-board CBCT-guided target verification; (2) Develop a volumetric cine MRI (VC-MRI) technique for on-board MRI-guided target verification using an MRI-guided radiotherapy machine; (3) Develop an on-board 4D MRI technique for on-board MRI-guided target verification using kV projections from a conventional linear accelerator (LINAC); (4) Accelerate VC-MRI through undersampling acquisition while maintaining image quality; and (5) Improve geometric accuracy of VC-MRI through novel undersampling acquisition and deformation models.
A technique for 4D CBCT estimation was previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D CBCT was generated by deforming a prior CT volume acquired during simulation. The DFM was solved by a global motion model (GMM) extracted by a global Principal Component Analysis (PCA) from prior 4D-CT and free-form deformation (FD) technique, using a data fidelity constraint. In the new proposed study of this dissertation, a quasi-cine CBCT estimation technique was developed to address these issues for real-time application. Specifically, a new structural PCA method was developed to build a structural motion model (SMM) instead of GMM by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4D CT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. . Different on-board projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy. The method was also evaluated against three lung patients.
The first technique developed in this dissertation showed that compared to the GMM-FD technique, the SMM-WFD technique can substantially improve the CBCT estimation accuracy using extremely small scan angles and low number of projections to provide fast low dose 4D target verification.
Next, a technique was developed to explore the feasibility of using an on-board kV imaging system and patient prior MRI knowledge to generate on-board quasi-cine volumetric MRI for target localization. Very few clinics have MRI-guided radiotherapy units, but most clinics have kV imaging capabilities with a conventional LINAC. The technique developed in this section of the dissertation aims to utilize conventional LINAC imaging capabilities, along with prior patient 4D MRI to estimate on-board 4D MRI for MRI-guided radiotherapy. Prior 4D MRI volumes were separated into end-of-expiration (EOE) phase and all other phases. MRIprior was used to generate a synthetic CT at EOE phase. On-board quasi-cine 3D or 4D MRI at each respiratory phase was considered a deformation of MRIprior. The Deformation Field Map (DFM) was estimated by matching Digitally Reconstructed Radiographs (DRRs) of the deformed sCTprior to on-board kV projections using a MM-FD deformation optimization algorithm.
The last section of the dissertation aims to accelerate the VC-MRI technique developed and improve the estimation accuracy by using novel undersampling and deformation models. VC-MRI was accelerated by using undersampled 2D cine MRI to provide real-time 3D guidance. Undersampled Cartesian and radial k-space acquisition strategies were investigated. The effects of k-space sampling percentage (SP) and distribution, tumor sizes and noise on the VC-MRI estimation were studied. The accelerated VC-MRI estimation was evaluated using XCAT simulation of lung cancer patients and data from liver cancer patients. VPD and COMS of the tumor volumes and tumor tracking errors were calculated.
In conclusion, the work presented in his dissertation builds upon previous research and develops novel solutions for generating real-time volumetric cine images for both CBCT and MRI. The completed research dissertation presents the following: (1) develops a quasi-real-time cine CBCT reconstruction method using structural PCA and weighted free-form deformation, (2) develops a VC-MRI technique using motion modeling and single slice 2D cine acquisition, (3) develops an on-board 4D-MRI technique using limited on-board kV projections from a conventional LINAC and deformation models, (4) accelerates VC-MRI through undersampling acquisition while maintaining image quality, and (5) improve geometric accuracy of VC-MRI through novel undersampling acquisition and deformation models. (Abstract shortened by ProQuest.).
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