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Markerless Four-Dimensional-Cone Beam Computed Tomography Projection-Phase Sorting Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study.

Publication ,  Journal Article
Zhang, L; Zhang, Y; Zhang, Y; Harris, WB; Yin, F-F; Cai, J; Ren, L
Published in: Cancer Transl Med
2017

AIM: During cancer radiotherapy treatment, on-board four-dimensional-cone beam computed tomography (4D-CBCT) provides important patient 4D volumetric information for tumor target verification. Reconstruction of 4D-CBCT images requires sorting of acquired projections into different respiratory phases. Traditional phase sorting methods are either based on external surrogates, which might miscorrelate with internal structures; or on 2D internal structures, which require specific organ presence or slow gantry rotations. The aim of this study is to investigate the feasibility of a 3D motion modeling-based method for markerless 4D-CBCT projection-phase sorting. METHODS: Patient 4D-CT images acquired during simulation are used as prior images. Principal component analysis (PCA) is used to extract three major respiratory deformation patterns. On-board patient image volume is considered as a deformation of the prior CT at the end-expiration phase. Coefficients of the principal deformation patterns are solved for each on-board projection by matching it with the digitally reconstructed radiograph (DRR) of the deformed prior CT. The primary PCA coefficients are used for the projection-phase sorting. RESULTS: PCA coefficients solved in nine digital phantoms (XCATs) showed the same pattern as the breathing motions in both the anteroposterior and superoinferior directions. The mean phase sorting differences were below 2% and percentages of phase difference < 10% were 100% for all the nine XCAT phantoms. Five lung cancer patient results showed mean phase difference ranging from 1.62% to 2.23%. The percentage of projections within 10% phase difference ranged from 98.4% to 100% and those within 5% phase difference ranged from 88.9% to 99.8%. CONCLUSION: The study demonstrated the feasibility of using PCA coefficients for 4D-CBCT projection-phase sorting. High sorting accuracy in both digital phantoms and patient cases was achieved. This method provides an accurate and robust tool for automatic 4D-CBCT projection sorting using 3D motion modeling without the need of external surrogate or internal markers.

Duke Scholars

Published In

Cancer Transl Med

ISSN

2395-3977

Publication Date

2017

Volume

3

Issue

6

Start / End Page

185 / 193

Location

India
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhang, L., Zhang, Y., Harris, W. B., Yin, F.-F., Cai, J., & Ren, L. (2017). Markerless Four-Dimensional-Cone Beam Computed Tomography Projection-Phase Sorting Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study. Cancer Transl Med, 3(6), 185–193.
Zhang, Lei, Yawei Zhang, You Zhang, Wendy B. Harris, Fang-Fang Yin, Jing Cai, and Lei Ren. “Markerless Four-Dimensional-Cone Beam Computed Tomography Projection-Phase Sorting Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study.Cancer Transl Med 3, no. 6 (2017): 185–93.

Published In

Cancer Transl Med

ISSN

2395-3977

Publication Date

2017

Volume

3

Issue

6

Start / End Page

185 / 193

Location

India