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Comparison of projection- and image-based methods for proton stopping power estimation using dual energy CT
Author(s) -
Gloria VilchesFreixas,
Vicki Trier Taasti,
L.P. Muren,
Jørgen Breede Baltzer Petersen,
Jean Michel Létang,
David C. Hansen,
Simon Rit
Publication year - 2017
Publication title -
physics and imaging in radiation oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.777
H-Index - 12
ISSN - 2405-6316
DOI - 10.1016/j.phro.2017.08.001
Subject(s) - projection (relational algebra) , digital enhanced cordless telecommunications , imaging phantom , mean squared error , mathematics , radon transform , energy (signal processing) , range (aeronautics) , artificial intelligence , algorithm , nuclear medicine , statistics , computer science , materials science , medicine , telecommunications , composite material , wireless
Background and Purpose: Several strategies for estimating stopping power ratio (SPR) from dual-energy CT (DECT) have been proposed to improve accuracy of proton dose calculations. DECT methods can mainly be categorized into projection-based methods, where material decomposition is performed prior to image reconstruction, and image-based methods, where decomposition takes place after image reconstruction. With the advent of photon-counting and dual-layer technology, projection-based methods could be considered for SPR estimation. In this simulation-based study we compared the SPR accuracy of one projection- and three image-based DECT methods.Materials and Methods: X-ray CT projections of the female ICRP phantom were simulated using two different X-ray spectra with a realistic detector response and noise levels. ICRP slices at four different locations were selected. Reference SPR-maps were computed at 200 MeV. The SPR comparison was based on percentage deviation inside ROIs and relative range errors calculated with Radon transform of difference maps.Results: SPR root-mean-square errors (RMSE) over the selected ROIs were 0.54% for the projection-based method and 0.68%, 0.61% and 0.70% for the three image-based methods. The RMSE for the relative range errors were slightly smaller for the projection-based approach, but close to zero for all decomposition domains as positive and negative errors averaged out over the slice.Conclusions: SPR estimations with the projection-based method produced slightly better results (though not statistically significant) than the three image-based methods used in this simulation-based study, therefore, with the advent of technological developments, projection-based methods could be considered for SPR estimation if projection data is available

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