Literature DB >> 33382794

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

Atchar Sudhyadhom1,2,3,4.   

Abstract

Accurate determination of physical/mass and electron densities are critical to accurate spatial and dosimetric delivery of radiotherapy for photon and charged particles. In this manuscript, the biology, chemistry, and physics that underly the relationship between computed tomography (CT) Hounsfield Unit (HU), mass density, and electron density was explored. In standard radiation physics practice, quantities such as mass and electron density are typically calculated based off a single kilovoltage CT (kVCT) scan assuming a one-to-one relationship between HU and density. It is shown that, in absence of mass density assumptions on tissues, the relationship between HU and density is not one-to-one with uncertainties as large as 7%. To mitigate this uncertainty, a novel multi-dimensional theoretical approach is defined between molecular (water, lipid, protein, and mineral) composition, HU, mass density, and electron density. Empirical parameters defining this relationship are x-ray beam energy/spectrum dependent and, in this study, two methods are proposed to solve for them including through a tissue mimicking phantom calibration process. As a proof of concept, this methodology was implemented in a separate in-house created tissue mimicking phantom and it is shown that sub 1% accuracy is possible for both mass and electron density. As molecular composition is not always known, the sensitivity of this model to uncertainties in molecular composition was investigated and it was found that, for soft tissue, sub 1% accuracy is achievable assuming nominal organ/tissue compositions. For boney tissues, the uncertainty in mineral content may lead to larger errors in mass and electron density compared with soft tissue. In this manuscript, a novel methodology to directly determine mass and electron density based off CT HU and knowledge of molecular compositions is presented. If used in conjunction with a methodology to determine molecular compositions, mass and electron density can be accurately calculated from CT HU.

Entities:  

Year:  2020        PMID: 33382794      PMCID: PMC7775093          DOI: 10.1371/journal.pone.0244861

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  29 in total

1.  Radiation characteristics of helical tomotherapy.

Authors:  Robert Jeraj; Thomas R Mackie; John Balog; Gustavo Olivera; Dave Pearson; Jeff Kapatoes; Ken Ruchala; Paul Reckwerdt
Journal:  Med Phys       Date:  2004-02       Impact factor: 4.071

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Authors:  D R White; E M Widdowson; H Q Woodard; J W Dickerson
Journal:  Br J Radiol       Date:  1991-02       Impact factor: 3.039

3.  Performance characterization of megavoltage computed tomography imaging on a helical tomotherapy unit.

Authors:  Sanford L Meeks; Joseph F Harmon; Katja M Langen; Twyla R Willoughby; Thomas H Wagner; Patrick A Kupelian
Journal:  Med Phys       Date:  2005-08       Impact factor: 4.071

4.  The five-level model: a new approach to organizing body-composition research.

Authors:  Z M Wang; R N Pierson; S B Heymsfield
Journal:  Am J Clin Nutr       Date:  1992-07       Impact factor: 7.045

5.  Extracting atomic numbers and electron densities from a dual source dual energy CT scanner: experiments and a simulation model.

Authors:  Guillaume Landry; Brigitte Reniers; Patrick Vincent Granton; Bart van Rooijen; Luc Beaulieu; Joachim E Wildberger; Frank Verhaegen
Journal:  Radiother Oncol       Date:  2011-09-15       Impact factor: 6.280

6.  Systematic analysis of the impact of imaging noise on dual-energy CT-based proton stopping power ratio estimation.

Authors:  Hugh H C Lee; Bin Li; Xinhui Duan; Linghong Zhou; Xun Jia; Ming Yang
Journal:  Med Phys       Date:  2019-04-01       Impact factor: 4.071

7.  The use of megavoltage CT (MVCT) images for dose recomputations.

Authors:  K M Langen; S L Meeks; D O Poole; T H Wagner; T R Willoughby; P A Kupelian; K J Ruchala; J Haimerl; G H Olivera
Journal:  Phys Med Biol       Date:  2005-08-31       Impact factor: 3.609

8.  Bone models for use in radiotherapy dosimetry.

Authors:  H Q Woodard; D R White
Journal:  Br J Radiol       Date:  1982-04       Impact factor: 3.039

9.  The direct use of CT numbers in radiotherapy dosage calculations for inhomogeneous media.

Authors:  R P Parker; P A Hobday; K J Cassell
Journal:  Phys Med Biol       Date:  1979-07       Impact factor: 3.609

10.  Comprehensive analysis of proton range uncertainties related to stopping-power-ratio estimation using dual-energy CT imaging.

Authors:  B Li; H C Lee; X Duan; C Shen; L Zhou; X Jia; M Yang
Journal:  Phys Med Biol       Date:  2017-08-09       Impact factor: 3.609

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  2 in total

1.  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

2.  Diagnostic Value of Coronary Computed Tomography Angiography Image under Automatic Segmentation Algorithm for Restenosis after Coronary Stenting.

Authors:  Xinrong He; Juan Zhao; Yunpeng Xu; Huini Lei; Xianbin Zhang; Ting Xiao
Journal:  Contrast Media Mol Imaging       Date:  2022-04-16       Impact factor: 3.009

  2 in total

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