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      Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

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          Abstract

          <p class="first" id="P1">The four dimensional (4D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT’s design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community. </p>

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          Managing radiation use in medical imaging: a multifaceted challenge.

          This special report aims to inform the medical community about the many challenges involved in managing radiation exposure in a way that maximizes the benefit-risk ratio. The report discusses the state of current knowledge and key questions in regard to sources of medical imaging radiation exposure, radiation risk estimation, dose reduction strategies, and regulatory options. © RSNA, 2010.
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            An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history.

            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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              Four-dimensional magnetic resonance imaging (4D-MRI) using image-based respiratory surrogate: a feasibility study.

              Four-dimensional computed tomography (4D-CT) has been widely used in radiation therapy to assess patient-specific breathing motion for determining individual safety margins. However, it has two major drawbacks: low soft-tissue contrast and an excessive imaging dose to the patient. This research aimed to develop a clinically feasible four-dimensional magnetic resonance imaging (4D-MRI) technique to overcome these limitations. The proposed 4D-MRI technique was achieved by continuously acquiring axial images throughout the breathing cycle using fast 2D cine-MR imaging, and then retrospectively sorting the images by respiratory phase. The key component of the technique was the use of body area (BA) of the axial MR images as an internal respiratory surrogate to extract the breathing signal. The validation of the BA surrogate was performed using 4D-CT images of 12 cancer patients by comparing the respiratory phases determined using the BA method to those determined clinically using the Real-time position management (RPM) system. The feasibility of the 4D-MRI technique was tested on a dynamic motion phantom, the 4D extended Cardiac Torso (XCAT) digital phantom, and two healthy human subjects. Respiratory phases determined from the BA matched closely to those determined from the RPM: mean (± SD) difference in phase: -3.9% (± 6.4%); mean (± SD) absolute difference in phase: 10.40% (± 3.3%); mean (± SD) correlation coefficient: 0.93 (± 0.04). In the motion phantom study, 4D-MRI clearly showed the sinusoidal motion of the phantom; image artifacts observed were minimal to none. Motion trajectories measured from 4D-MRI and 2D cine-MRI (used as a reference) matched excellently: the mean (± SD) absolute difference in motion amplitude: -0.3 (± 0.5) mm. In the 4D-XCAT phantom study, the simulated "4D-MRI" images showed good consistency with the original 4D-XCAT phantom images. The motion trajectory of the hypothesized "tumor" matched excellently between the two, with a mean (± SD) absolute difference in motion amplitude of 0.5 (± 0.4) mm. 4D-MRI was able to reveal the respiratory motion of internal organs in both human subjects; superior-inferior (SI) maximum motion of the left kidney of Subject #1 and the diaphragm of Subject #2 measured from 4D-MRI was 0.88 and 1.32 cm, respectively. Preliminary results of our study demonstrated the feasibility of a novel retrospective 4D-MRI technique that uses body area as a respiratory surrogate.
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                Author and article information

                Journal
                IEEE Transactions on Medical Imaging
                IEEE Trans. Med. Imaging
                Institute of Electrical and Electronics Engineers (IEEE)
                0278-0062
                1558-254X
                March 2018
                March 2018
                : 37
                : 3
                : 680-692
                Article
                10.1109/TMI.2017.2738448
                5809240
                28809677
                aa7cf83e-0882-4ccb-bebe-8189b1faaf53
                © 2018
                History

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