Evaluation of counting efficiencies of a whole-body counter using Monte Carlo simulation with voxel phantoms

Takahashi, Miwako; Kinase, Sakae; Kramer, Richard A.

doi:10.1093/rpd/ncq417

Cited by 20 publications

(11 citation statements)

References 7 publications

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“…But this level of accuracy is not that relevant considering the uncertainties related to a mispositioning of the phantom itself. While some authors consider them 'significant tools' for the calibration of WBC (35) , others believe that 'for in vivo counting in the context of radiation protection, efficiencies can be deduced with sufficient accuracy from measurements or simulations of simple phantoms' (5) . Guardini and Ferrari (10) argue that the accuracy in geometry representation improved by voxel models is only one contributor to the overall accuracy of a WBC measurement and not the most important.…”

Section: Discussionmentioning

confidence: 99%

“…Various MC computer codes have been used so far: 'FLUktuierende KAskade' (FLUKA) (25) , 'Monte Carlo N-Particle' (MCNP) (26 -33) , 'Electron Gamma Shower' (EGS) (5,6,34,35) , 'PENetration and Energy LOss of Positrons and Electrons' (PENELOPE) (32) , 'GEometry ANd Tracking' (GEANT) (36) or local codes developed ad hoc (37) . MC calculation has been used to compare different mathematical phantoms used in WBCs (10,26,27,29,31,35,38) or to compare the measurements obtained with a physical phantom with the results obtained by a simulated version of this phantom (5,6,30,35,37) . MC calculations are also used to investigate how the counting efficiency of the WCB depends on various parameters of the system that may be sources of uncertainty, such as the difference between the shape and size of the person to be monitored and the phantom, the measuring geometry, notably the position of the detector, the phantomdetector distance, the distribution of the radionuclides in the body, etc.…”

Section: Introductionmentioning

confidence: 99%

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Monte Carlo simulation of a whole-body counter using IGOR phantoms

Bochud

Laedermann

Baechler

et al. 2013

Radiation Protection Dosimetry

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Whole-body counting is a technique of choice for assessing the intake of gamma-emitting radionuclides. An appropriate calibration is necessary, which is done either by experimental measurement or by Monte Carlo (MC) calculation. The aim of this work was to validate a MC model for calibrating whole-body counters (WBCs) by comparing the results of computations with measurements performed on an anthropomorphic phantom and to investigate the effect of a change in phantom's position on the WBC counting sensitivity. GEANT MC code was used for the calculations, and an IGOR phantom loaded with several types of radionuclides was used for the experimental measurements. The results show a reasonable agreement between measurements and MC computation. A 1-cm error in phantom positioning changes the activity estimation by >2 %. Considering that a 5-cm deviation of the positioning of the phantom may occur in a realistic counting scenario, this implies that the uncertainty of the activity measured by a WBC is ∼10-20 %.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monte Carlo simulation of a whole-body counter using IGOR phantoms

Bochud

Laedermann

Baechler

et al. 2013

Radiation Protection Dosimetry

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“…The authors reported that it was difficult to develop these phantoms with the FFD algorithm and the internal organs are not adjusted to age-dependent values. The Otoko phantom was recently used in a study to calculate dose conversion coefficients for the Japanese population (Takahashi et al 2011). …”

Section: The Evolution Of Computational Phantomsmentioning

confidence: 99%

An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history

2014

Phys. Med. Biol.

229

227

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Radiation dose calculation using models of the human anatomy has been a subject of great interest to radiation protection, medical imaging, and radiotherapy. However, early pioneers of this field did not foresee the exponential growth of research activity as observed today. This review article walks the reader through the history of the research and development in this field of study which started some 50 years ago. This review identifies a clear progression of computational phantom complexity which can be denoted by three distinct generations. The first generation of stylized phantoms, representing a grouping of less than dozen models, was initially developed in the 1960s at Oak Ridge National Laboratory to calculate internal doses from nuclear medicine procedures. Despite their anatomical simplicity, these computational phantoms were the best tools available at the time for internal/external dosimetry, image evaluation, and treatment dose evaluations. A second generation of a large number of voxelized phantoms arose rapidly in the late 1980s as a result of the increased availability of tomographic medical imaging and computers. Surprisingly, the last decade saw the emergence of the third generation of phantoms which are based on advanced geometries called boundary representation (BREP) in the form of Non-Uniform Rational B-Splines (NURBS) or polygonal meshes. This new class of phantoms now consists of over 287 models including those used for non-ionizing radiation applications. This review article aims to provide the reader with a general understanding of how the field of computational phantoms came about and the technical challenges it faced at different times. This goal is achieved by defining basic geometry modeling techniques and by analyzing selected phantoms in terms of geometrical features and dosimetric problems to be solved. The rich historical information is summarized in four tables that are aided by highlights in the text on how some of the most well-known phantoms were developed and used in practice. Some of the information covered in this review has not been previously reported, for example, the CAM and CAF phantoms developed in 1970s for space radiation applications. The author also clarifies confusion about “population-average” prospective dosimetry needed for radiological protection under the current ICRP radiation protection system and “individualized” retrospective dosimetry often performed for medical physics studies. To illustrate the impact of computational phantoms, a section of this article is devoted to examples from the author’s own research group. Finally the author explains an unexpected finding during the course of preparing for this article that the phantoms from the past 50 years followed a pattern of exponential growth. The review ends on a brief discussion of future research needs (A supplementary file “3DPhantoms.pdf” to Figure 15 is available for download that will allow a reader to interactively visualize the phantoms in 3D).

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“…The authors reported that it was difficult to develop these phantoms with the FFD algorithm and the internal organs are not adjusted to agedependent values. The Otoko phantom was recently used in a study to calculate dose conversion coefficients for the Japanese population [80].…”

Section: Second-generation Voxel Phantoms (From Late 1980 To Early 20mentioning

confidence: 99%

Computational Phantoms for Organ Dose Calculations in Radiation Protection and Imaging

2013

The Phantoms of Medical and Health Physics

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Dosimetry for ionizing radiation has to do with the determination of amount and distribution pattern of the energy deposited in a part or parts of the human body from internal or external radiation sources. To protect against occupational exposures, dose limits for radiosensitive organs are recommended by international organizations and are adopted as national regulations. In both diagnostic radiology and nuclear medicine, X-ray photons and gamma rays traverse through body tissues to form images of the anatomy, depositing radiation energy in organs along the pathway via secondary electrons. Accurate radiation dosimetry is essential but also quite challenging for three reasons: (1) there are many diverse exposure scenarios resulting in unique spatial and temporal relationships between the source and human body; (2) an exposure can involve multiple radiation types, each of which is governed by different radiation physics principles, such as photons (X-ray photons, gamma rays, and positrons), electrons, alpha particles, neutrons, and protons; (3) the human body consists of a large number of anatomical structures of diverse shape, composition and density, leading to complex radiation interaction patterns. Since it is inconvenient to place a dosimeter inside the human body, organ dose estimates have been obtained mostly using a physical phantom or a computational phantom that mimics the interior and exterior anatomical features of the human body.Historically, the term phantom was used in most radiological science literature to mean a physical model of the human body. In the radiation protection community, however, the term has also been used to refer to a mathematically defined anatomical model that is distinctly different from a physiologically based model such as that related to respiration or blood flow. In this chapter, the phrases, ''computational phantom'' and ''physical phantom,'' are used to avoid confusion.

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Evaluation of counting efficiencies of a whole-body counter using Monte Carlo simulation with voxel phantoms

Cited by 20 publications

References 7 publications

Monte Carlo simulation of a whole-body counter using IGOR phantoms

Monte Carlo simulation of a whole-body counter using IGOR phantoms

An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history

Computational Phantoms for Organ Dose Calculations in Radiation Protection and Imaging

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