Proton radiography and fluoroscopy of lung tumors: A Monte Carlo study using patient‐specific 4DCT phantoms

Han, Bin; Xu, Xiaobin; Chen, George T.Y.

doi:10.1118/1.3555039

Cited by 18 publications

(17 citation statements)

References 34 publications

(23 reference statements)

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“…The image reconstruction method adopted by the pCT collaboration uses the MLP concept for an iterative reconstruction algorithm, which allows extrapolating the curved proton path to produce tomographic reconstructions with sufficient spatial resolution and to minimize the effect of multiple Coulomb scattering. Several authors have modeled the multiple Coulomb scattering effects on proton path while crossing uniform material . The compact, matrix‐based MLP formalism chosen by the pCT collaboration used a scattering model similar to the one described by Williams but employed Bayesian statistics to determine the lateral displacement and direction of maximum likelihood at any intermediate depth within a uniform absorbing material .…”

Section: Methodsmentioning

confidence: 99%

The effect of beam purity and scanner complexity on proton CT accuracy

et al. 2017

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Purpose To determine the dependence of the accuracy in reconstruction of relative stopping power (RSP) with proton computerized tomography (pCT) scans on the purity of the proton beam and the technological complexity of the pCT scanner using standard phantoms and a digital representation of a pediatric patient. Methods The Monte Carlo method was applied to simulate the pCT scanner, using both a pure proton beam (uniform 200 MeV mono-energetic, parallel beam) and the Northwestern Medicine Chicago Proton Center (NMCPC) clinical beam in uniform scanning mode. The accuracy of the simulation was validated with measurements performed at NMCPC including reconstructed RSP images obtained with a preclinical prototype pCT scanner. The pCT scanner energy detector was then simulated in three configurations of increasing complexity: an ideal totally absorbing detector, a single stage detector and a multi-stage detector. A set of 15 cm diameter water cylinders containing either water alone or inserts of different material, size, and position were simulated at 90 projection angles (4° steps) for the pure and clinical proton beams and the three pCT configurations. A pCT image of the head of a detailed digital pediatric phantom was also reconstructed from the simulated pCT scan with the prototype detector. Results The RSP error increased for all configurations for insert sizes under 7.5 mm in radius, with a sharp increase below 5 mm in radius, attributed to a limit in spatial resolution. The highest accuracy achievable using the current pCT calibration step-phantom and reconstruction algorithm, calculated for the ideal case of a pure beam with totally absorbing energy detector, was 1.3% error in RSP for inserts of 5 mm radius or more, 0.7 mm in range for the 2.5 mm radius inserts, or better. When the highest complexity of the scanner geometry was introduced, some artifacts arose in the reconstructed images, particularly in the center of the phantom. Replacing the step-phantom used for calibration with a wedge phantom led to RSP accuracy close to the ideal case, with no significant dependence of RSP error on insert location or material. The accuracy with the multi-stage detector and NMCPC beam for the cylindrical phantoms was 2.2% in RSP error for inserts of 5 mm radius or more, 0.7 mm in range for the 2.5 mm radius inserts, or better. The pCT scan of the pediatric phantom resulted in mean RSP values within 1.3% of the reference RSP, with a range error under 1 mm, except in exceptional situations of parallel incidence on a boundary between low and high density. Conclusions The pCT imaging technique proved to be a precise and accurate imaging tool, rivalling the current x-rays based techniques, with the advantage of being directly sensitive to proton stopping power rather than photon interaction coefficients. Measured and simulated pCT images were obtained from a wobbled proton beam for the first time. Since the in-silico results are expected to accurately represent the prototype pCT, upcoming measurements using the wedge p...

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Section: Methodsmentioning

confidence: 99%

The effect of beam purity and scanner complexity on proton CT accuracy

et al. 2017

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“…RPI research activities highlighted in the article were based on the following Ph.D. or M.S. projects (the year of graduation indicated): Ahmet Bozkurt (2000), TC Ephraim Chao (2001), Chengyu Shi (2004), Mark Winslow, (2005), Brian Wang (2005), Peter Caracappa (2006), Bryan Bednarz (2008), Juying Zhang (2009), Yong Hum Na (2009), Jianwei Gu (2010), Bin Han (2011), Aiping Ding (2012), Matthew Mille (2013), and Justin Vazquez (2013). Grants Funding for these projects include: National Science Foundation (BES-9875532), National Library of Medicine (R03LM007964, R01LM009362, and R01LM009362-03S1), National Cancer Institute (R01CA116743 and R42CA115122), National Institute of Biomedical Imaging and Bioengineering (R42EB010404), and National Institute of Standards and Technology (70NANB9H9198).…”

Section: Acknowledgmentsmentioning

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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“…Computational phantoms have been used extensive at RPI for diverse health physics and medical physics applications, including external photon beams from 10 keV to 10 MeV [132,133], external electron beams [134,135], external neutron beam in low energies (10 -9 -20 MeV) and in high energy (20-10,000 MeV) [134,136], external proton beams [137], photon dose to the red bone marrow [174], internal electron dosimetry [138,139], SPECT and PET brain imaging [140], X-ray radiographs [141], X-ray image quality ROC/AUC analysis [142], interventional cardiological examinations [143], adjoint Monte Carlo algorithm for external-beam prostate radiation treatment planning [231], non-target organ doses from proton radiation treatments [145], respiration management in IGRT [233], imaging doses in IGRT [44], kV CBCT and MDCT [146], and time-resolved proton range telescope [147]. More information can be found at the website for Rensselaer Radiation Dosimetry and Measurement Group (http://rrmdg.rpi.edu).…”

Section: Applications Of Computational Phantoms At Rpimentioning

confidence: 99%

“…Research at RPI, which is highlighted in this article, involved the following former PhD students: Bozkurt et al [134,132,236], Winslow et al [169,144,239] Bednarz (2008), [240][241][242], Han et al [147], Ding et al [113,243]. These research projects at RPI were supported by the following grants: National Science Foundation (BES-9875532), National Library of Medicine (R03LM007964, R01LM009362, and R01LM009362-03S1), National Cancer Institute (R01CA116743 and R42CA115122), National Institute of Biomedical Imaging and Bioengineering (R42EB010404), and National Institute of Standards and Technology (70NANB9H9198).…”

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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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Proton radiography and fluoroscopy of lung tumors: A Monte Carlo study using patient‐specific 4DCT phantoms

Cited by 18 publications

References 34 publications

The effect of beam purity and scanner complexity on proton CT accuracy

The effect of beam purity and scanner complexity on proton CT accuracy

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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