2,002 research outputs found
Effect of Statistical Fluctuation in Monte Carlo Based Photon Beam Dose Calculation on Gamma Index Evaluation
The gamma-index test has been commonly adopted to quantify the degree of
agreement between a reference dose distribution and an evaluation dose
distribution. Monte Carlo (MC) simulation has been widely used for the
radiotherapy dose calculation for both clinical and research purposes. The goal
of this work is to investigate both theoretically and experimentally the impact
of the MC statistical fluctuation on the gamma-index test when the fluctuation
exists in the reference, the evaluation, or both dose distributions. To the
first order approximation, we theoretically demonstrated in a simplified model
that the statistical fluctuation tends to overestimate gamma-index values when
existing in the reference dose distribution and underestimate gamma-index
values when existing in the evaluation dose distribution given the original
gamma-index is relatively large for the statistical fluctuation. Our numerical
experiments using clinical photon radiation therapy cases have shown that 1)
when performing a gamma-index test between an MC reference dose and a non-MC
evaluation dose, the average gamma-index is overestimated and the passing rate
decreases with the increase of the noise level in the reference dose; 2) when
performing a gamma-index test between a non-MC reference dose and an MC
evaluation dose, the average gamma-index is underestimated when they are within
the clinically relevant range and the passing rate increases with the increase
of the noise level in the evaluation dose; 3) when performing a gamma-index
test between an MC reference dose and an MC evaluation dose, the passing rate
is overestimated due to the noise in the evaluation dose and underestimated due
to the noise in the reference dose. We conclude that the gamma-index test
should be used with caution when comparing dose distributions computed with
Monte Carlo simulation
Extracting respiratory signals from thoracic cone beam CT projections
Patient respiratory signal associated with the cone beam CT (CBCT)
projections is important for lung cancer radiotherapy. In contrast to
monitoring an external surrogate of respiration, such signal can be extracted
directly from the CBCT projections. In this paper, we propose a novel local
principle component analysis (LPCA) method 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,
namely, 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.Comment: 21 pages, 11 figures, submitted to Phys. Med. Bio
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