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Simplified derivation of stopping power ratio in the human body from dual‐energy CT data
Author(s) -
Saito Masatoshi,
Sagara Shota
Publication year - 2017
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.12386
Subject(s) - effective atomic number , imaging phantom , digital enhanced cordless telecommunications , scanner , physics , subtraction , attenuation , calibration , stopping power , nuclear medicine , computational physics , materials science , optics , mathematics , detector , computer science , medicine , telecommunications , arithmetic , quantum mechanics , wireless
Purpose The main objective of this study is to propose an alternative parameterization for the empirical relation between mean excitation energies ( I ‐value) and effective atomic numbers ( Z eff ) of human tissues, and to present a simplified formulation (which we called DEEDZ ‐ SPR ) for deriving the stopping power ratio ( SPR ) from dual‐energy ( DE ) CT data via electron density ( ρ e ) and Z eff calibration. Methods We performed a numerical analysis of this DEEDZ ‐ SPR method for the human‐body‐equivalent tissues of ICRU Report 46, as objects of interest with unknown SPR and ρ e . The attenuation coefficients of these materials were calculated using the XCOM photon cross‐sections database. We also applied the DEEDZ ‐ SPR conversion to experimental DECT data available in the literature, which was measured for the tissue‐characterization phantom using a dual‐source CT scanner at 80 kV and 140 kV /Sn. Results It was found that the DEEDZ ‐ SPR conversion enables the calculation of SPR simply by means of the weighted subtraction of an electron‐density image and a low‐ or high‐ kV CT image. The simulated SPR s were in excellent agreement with the reference values over the SPR range from 0.258 (lung) to 3.638 (bone mineral‐hydroxyapatite). The relative deviations from the reference SPR were within ±0.6% for all ICRU ‐46 human tissues, except for the thyroid that presented a −1.1% deviation. The overall root‐mean‐square error was 0.21%. Application to experimental DECT data confirmed this agreement within the experimental accuracy, which demonstrates the practical feasibility of the method. Conclusions The DEEDZ ‐ SPR conversion method could facilitate the construction of SPR images as accurately as a recent DECT ‐based calibration procedure of SPR parameterization based directly on the CT numbers in a DECT data set.