Extracting respiratory signals from thoracic cone beam CT projections

H. Yan, X. Wang, W. Yin, T. Pan, M. Ahmad, X. Mou, L. Cervino, X. Jia, S.B. Jiang

Published Physics in medicine and biology.

Overview

During cone beam CT (CBCT), the patient breath affects the CBCT projection. Recovering the patient respiratory signal is important for lung cancer radiotherapy.

In contrast to monitoring an external surrogate of respiration, this paper introduces a method to directly extract the signal from the CBCT projections. A novel local principle component analysis (LPCA) method is proposed to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections.

The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods: the Amsterdam Shroud (AS) method, the intensity analysis (IA) method, and the Fourier-transform based phase analysis (FT-p) method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting respiratory signal. We also identified the applicability of each existing method.

Citation

H. Yan, X. Wang, W. Yin, T. Pan, M. Ahmad, X. Mou, L. Cervino, X. Jia, and S.B. Jiang, Extracting respiratory signals from thoracic cone beam CT projections, Physics in medicine and biology 58, 1447-1464, 2013.


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