Organ dose conversion coefficients for external photon irradiation using the Chinese voxel phantom (CVP)

Li, Junli; Qiu, Rui; Zhang, Zhan; Liu, Liye; Zeng, Zhi; Bi, Lei; Li, Wenqian

doi:10.1093/rpd/ncp087

Cited by 11 publications

(5 citation statements)

References 18 publications

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“…Korean voxel phantoms include Korean Man (KORMAN), Korean Typical MAN-1 (KTMAN-1), Korean Typical Man-2 (KTMAN-2), High-Definition Reference Korean (HDRK), and Korean WOMAN (KORWOMAN) [19,[85][86][87]. Chinese voxel phantoms include Chinese Man (CNMAN) [88], Visible Chinese Human (VCH) [89][90][91], Chinese Voxel Phantom (CVP) [92,93], and Reference Taiwanese Adult phantoms [94]. Voxel phantoms by groups from other coun-JRPR tries include NUDEL (NUmerical moDEL) from Italy [95], work from France [96,97], work from Austria [98], work from Iran [99], and work from India [100].…”

Section: ) Voxel Phantoms (From the 1980s To Present)mentioning

confidence: 99%

A Review of Computational Phantoms for Quality Assurance in Radiology and Radiotherapy in the Deep-Learning Era

Zhao

Gao

et al. 2022

J Radiat Prot Res

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The exciting advancement related to the “modeling of digital human” in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation- transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.

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Section: ) Voxel Phantoms (From the 1980s To Present)mentioning

confidence: 99%

A Review of Computational Phantoms for Quality Assurance in Radiology and Radiotherapy in the Deep-Learning Era

Zhao

Gao

et al. 2022

J Radiat Prot Res

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“…Zhang et al (2009) summarized three Chinese voxel phantoms developed by three separate groups in China: Chinese Man (CNMAN) produced from color photographs of a cadaver by the China Institute for Radiation Protection (Zhang et al 2007a), Visible Chinese Human (VCH) produced from a different set of cadaver color photographs by the Huazhong University of Science and Technology (HUST) (Zhang et al 2007b, Zhang et al 2008a, Zhang et al 2008b), and Chinese Voxel Phantom (CVP) produced from MRI images by Tsinghua University (Li et al 2009, Zeng et al 2006). The lead developer of the CNMAN phantom, Binquan Zhang, served as a visiting scholar at RPI during 2007–2008.…”

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.

228

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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“…Three voxel phantoms representing an adult Chinese male have been reported since 2007: CNMAN produced from color photographs of a cadaver by the China Institute for Radiation Protection [85], VCH produced from a different set of cadaver color photographs by the Huazhong University of Science and Technology [86][87][88], and CVP produced from MR images by Tsinghua University [89,51] [89] at the Key Laboratory of Particle and Radiation Imaging in Beijing. The phantom was named the Chinese voxel phantom (CVP) and was used to determine conversion coefficients for the Chinese populace.…”

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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Organ dose conversion coefficients for external photon irradiation using the Chinese voxel phantom (CVP)

Cited by 11 publications

References 18 publications

A Review of Computational Phantoms for Quality Assurance in Radiology and Radiotherapy in the Deep-Learning Era

A Review of Computational Phantoms for Quality Assurance in Radiology and Radiotherapy in the Deep-Learning Era

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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