Literature DB >> 23571116

Conversion of the energy-subtracted CT number to electron density based on a single linear relationship: an experimental verification using a clinical dual-source CT scanner.

Masayoshi Tsukihara1, Yoshiyuki Noto, Takahide Hayakawa, Masatoshi Saito.   

Abstract

In radiotherapy treatment planning, the conversion of the computed tomography (CT) number to electron density is one of the main processes that determine the accuracy of patient dose calculations. However, in general, the CT number and electron density of tissues cannot be interrelated using a simple one-to-one correspondence. This study aims to experimentally verify the clinical feasibility of an existing novel conversion method proposed by the author of this note, which converts the energy-subtracted CT number (ΔHU) to the relative electron density (ρe) via a single linear relationship by using a dual-energy CT (DECT). The ΔHU-ρe conversion was performed using a clinical second-generation dual-source CT scanner operated in the dual-energy mode with tube potentials of 80 kV and 140 kV with and without an additional tin filter. The ΔHU-ρe calibration line was obtained from the DECT image acquisition for tissue substitutes in an electron density phantom. In addition, the effect of object size on ΔHU-ρe conversion was also experimentally investigated. The plot of the measured ΔHU versus nominal ρe values exhibited a single linear relationship over a wide ρe range from 0.00 (air) to 2.35 (aluminum). The ΔHU-ρe conversion performed with the tin filter yielded a lower dose and more reliable ρe values that were less affected by the object-size variation when compared to the corresponding values obtained for the case without the tin filter.

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Year:  2013        PMID: 23571116     DOI: 10.1088/0031-9155/58/9/N135

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

Review 1.  Status and innovations in pre-treatment CT imaging for proton therapy.

Authors:  Patrick Wohlfahrt; Christian Richter
Journal:  Br J Radiol       Date:  2019-11-11       Impact factor: 3.039

2.  Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning.

Authors:  Jessica Scholey; Luciano Vinas; Vasant Kearney; Sue Yom; Peder Eric Zufall Larson; Martina Descovich; Atchar Sudhyadhom
Journal:  Phys Med Biol       Date:  2022-05-02       Impact factor: 4.174

3.  Evaluation of raw-data-based and calculated electron density for contrast media with a dual-energy CT technique.

Authors:  Daisuke Kawahara; Shuichi Ozawa; Kazushi Yokomachi; Toru Higaki; Takehiro Shiinoki; Yoshimi Ohno; Yuji Murakami; Kazuo Awai; Yasushi Nagata
Journal:  Rep Pract Oncol Radiother       Date:  2019-08-20

Review 4.  Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy.

Authors:  Shailaja Sajja; Young Lee; Markus Eriksson; Håkan Nordström; Arjun Sahgal; Masoud Hashemi; James G Mainprize; Mark Ruschin
Journal:  Adv Radiat Oncol       Date:  2019-07-30

5.  On the molecular relationship between Hounsfield Unit (HU), mass density, and electron density in computed tomography (CT).

Authors:  Atchar Sudhyadhom
Journal:  PLoS One       Date:  2020-12-31       Impact factor: 3.240

6.  The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations.

Authors:  Raymond Fang; Thomas Mazur; Sasa Mutic; Rao Khan
Journal:  Phys Imaging Radiat Oncol       Date:  2018-11-02

Review 7.  Dual-Energy CT in Head and Neck Imaging.

Authors:  Elise D Roele; Veronique C M L Timmer; Lauretta A A Vaassen; Anna M J L van Kroonenburgh; A A Postma
Journal:  Curr Radiol Rep       Date:  2017-03-29
  7 in total

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