A simple formulation for deriving effective atomic numbers via electron density calibration from dual-energy CT data in the human body

Saito, Masatoshi; Sagara, S.

doi:10.1002/mp.12176

Cited by 52 publications

(51 citation statements)

References 25 publications

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“…Very recently, we proposed a new, simpler conversion method (which we called DEEDZ) to obtain Z eff images from DECT data, via q e calibration. 7 By performing numerical analysis, we showed that the DEEDZ conversion yielded Z eff values that were in excellent agreement with the reference values. The main objective of this study is to propose an alternative empirical parameterization for the correlation between I-value and Z eff , and to present a simplified formulation for deriving SPR from DECT data via the DEEDZ conversion (hereafter, we refer to this method as "DEEDZ-SPR").…”

Section: Introductionsupporting

confidence: 69%

“…7,8 Here, HU k is the CT number in Hounsfield units for high-kV (k = H) and low-kV (k = L) scans, which is related to the so-called "reduced CT number", u k = HU k / 1000 + 1. a is the weighting factor for subtraction and c L is the proportionality constant for the low-energy u L data. These two can be regarded as material-independent but scanner-and protocol-specific fit parameters.…”

Section: A Derivation Of Spr From Dect Data Via Q E and Z Eff Calimentioning

confidence: 99%

“…(3) was defined by c k 1/Q(E k ). 7 By considering the special case of water, that is, u k = q e = 1 and Z eff = Z eff,w , this equation yields the constraint…”

Section: Appendix Calculation Of Spr Using Dect Datamentioning

confidence: 99%

“…Simulated and experimental values of scanner-specific parameters for a DSCT scanner at 80 kV (E L = 63 keV) and 140 kV/Sn (E H = 99 keV). These parameters are reproduced from Ref [7]…”

mentioning

confidence: 99%

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Simplified derivation of stopping power ratio in the human body from dual‐energy CT data

Saito

Sagara

2017

Medical Physics

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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 (q e ) and Z eff calibration. Methods: We performed a numerical analysis of this DEEDZ-SPR method for the human-bodyequivalent tissues of ICRU Report 46, as objects of interest with unknown SPR and q 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 SPRs 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 AE0.6% for all ICRU-46 human tissues, except for the thyroid that presented a À1.1% 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.

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Section: Introductionsupporting

confidence: 69%

Section: A Derivation Of Spr From Dect Data Via Q E and Z Eff Calimentioning

confidence: 99%

“…(3) was defined by c k 1/Q(E k ). 7 By considering the special case of water, that is, u k = q e = 1 and Z eff = Z eff,w , this equation yields the constraint…”

Section: Appendix Calculation Of Spr Using Dect Datamentioning

confidence: 99%

“…Simulated and experimental values of scanner-specific parameters for a DSCT scanner at 80 kV (E L = 63 keV) and 140 kV/Sn (E H = 99 keV). These parameters are reproduced from Ref [7]…”

mentioning

confidence: 99%

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Simplified derivation of stopping power ratio in the human body from dual‐energy CT data

Saito

Sagara

2017

Medical Physics

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“…Several formalisms for converting CT numbers from DECT to SPR were proposed in literature. Most of these formalisms are parameter‐based and aim at the extraction of ED and effective atomic number (EAN) or photon absorption cross section, which are used to estimate the mean excitation energy ( I ‐value) or the stopping number, respectively. Alternative methods parameterize the I ‐value or the SPR directly, while other groups focus on calibrating pseudo‐monoenergetic images derived from DECT to predict the SPR of tissues .…”

Section: Introductionmentioning

confidence: 99%

Experimental validation of two dual‐energy CT methods for proton therapy using heterogeneous tissue samples

et al. 2017

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The present work uses experimental measurements in a realistic clinical environment to show potential benefits of DECT for proton therapy treatment planning. Our results show clear improvements over SECT in tissue-equivalent plastic materials and animal tissues. Further work towards using Monte Carlo simulations for treatment planning with DECT data and a more detailed investigation of the uncertainties on I-value and limitations on the Bragg additivity rule could potentially further enhance the benefits of this imaging technology for proton therapy.

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Comment on: Methodological accuracy of image‐based electron density assessment using dual‐energy computed tomography [Med. Phys. 44(6), 2429–2437 (2017)]

A simple formulation for deriving effective atomic numbers via electron density calibration from dual-energy CT data in the human body

Abstract: The DEEDZ conversion method based on the simple formulation proposed could facilitate the construction of ρ and Z images from acquired DECT data.

Cited by 52 publications

References 25 publications

Simplified derivation of stopping power ratio in the human body from dual‐energy CT data

Simplified derivation of stopping power ratio in the human body from dual‐energy CT data

Experimental validation of two dual‐energy CT methods for proton therapy using heterogeneous tissue samples

Comment on: Methodological accuracy of image‐based electron density assessment using dual‐energy computed tomography [Med. Phys. 44(6), 2429–2437 (2017)]

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