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Wang S, Yang Y, Pal D, Yin Z, Maltz JS, Pelc NJ, Wang AS. Spectral optimization using fast kV switching and filtration for photon counting CT with realistic detector responses: a simulation study. J Med Imaging (Bellingham) 2024; 11:S12805. [PMID: 39072221 PMCID: PMC11272100 DOI: 10.1117/1.jmi.11.s1.s12805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/16/2024] [Accepted: 07/08/2024] [Indexed: 07/30/2024] Open
Abstract
Purpose Photon counting CT (PCCT) provides spectral measurements for material decomposition. However, the image noise (at a fixed dose) depends on the source spectrum. Our study investigates the potential benefits from spectral optimization using fast kV switching and filtration to reduce noise in material decomposition. Approach The effect of the input spectra on noise performance in both two-basis material decomposition and three-basis material decomposition was compared using Cramer-Rao lower bound analysis in the projection domain and in a digital phantom study in the image domain. The fluences of different spectra were normalized using the CT dose index to maintain constant dose levels. Four detector response models based on Si or CdTe were included in the analysis. Results For single kV scans, kV selection can be optimized based on the imaging task and object size. Furthermore, our results suggest that noise in material decomposition can be substantially reduced with fast kV switching. For two-material decomposition, fast kV switching reduces the standard deviation (SD) by ∼ 10 % . For three-material decomposition, greater noise reduction in material images was found with fast kV switching (26.2% for calcium and 25.8% for iodine, in terms of SD), which suggests that challenging tasks benefit more from the richer spectral information provided by fast kV switching. Conclusions The performance of PCCT in material decomposition can be improved by optimizing source spectrum settings. Task-specific tube voltages can be selected for single kV scans. Also, our results demonstrate that utilizing fast kV switching can substantially reduce the noise in material decomposition for both two- and three-material decompositions, and a fixed Gd filter can further enhance such improvements for two-material decomposition.
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Affiliation(s)
- Sen Wang
- Stanford University, Department of Radiology, Stanford, California, United States
| | - Yirong Yang
- Stanford University, Department of Radiology, Stanford, California, United States
- Stanford University, Department of Electrical Engineering, Stanford, California, United States
| | | | - Zhye Yin
- GE HealthCare, Waukesha, Wisconsin, United States
| | - Jonathan S. Maltz
- GE HealthCare, Waukesha, Wisconsin, United States
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California, United States
| | - Norbert J. Pelc
- Stanford University, Department of Radiology, Stanford, California, United States
| | - Adam S. Wang
- Stanford University, Department of Radiology, Stanford, California, United States
- Stanford University, Department of Electrical Engineering, Stanford, California, United States
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Zhou W, Ataei A, Huo D, Ren L, Browne LP, Zhou X, Weinman JP. Optimal Spectral Performance on Pediatric Photon-Counting CT: Investigating Phantom-Based Size-Dependent kV Selection for Spectral Body Imaging. Invest Radiol 2024:00004424-990000000-00247. [PMID: 39159359 DOI: 10.1097/rli.0000000000001119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/21/2024]
Abstract
PURPOSE The comprehensive evaluation of kV selection on photon-counting computed tomography (PCCT) has yet to be performed. The aim of the study is to evaluate and determine the optimal kV options for variable pediatric body sizes on the PCCT unit. MATERIALS AND METHODS In this study, 4 phantoms of variable sizes were utilized to represent abdomens of newborn, 5-year-old, 10-year-old, and adult-sized pediatric patients. One solid water and 4 solid iodine inserts with known concentrations (2, 5, 10, and 15 mg I/mL) were inserted into phantoms. Each phantom setting was scanned on a PCCT system (Siemens Alpha) with 4 kV options (70 and 90 kV under Quantum Mode, 120 and 140 kV under QuantumPlus Mode) and clinical dual-source (3.0 pitch) protocol. For each phantom setting, radiation dose (CTDIvol) was determined by clinical dose settings and matched for all kV acquisitions. Sixty percent clinical dose images were also acquired. Reconstruction was matched across all acquisitions using Qr40 kernel and QIR level 3. Virtual monoenergetic images (VMIs) between 40 and 80 keV with 10 keV interval were generated on the scanner. Low-energy and high-energy images were reconstructed from each scan and subsequently used to generate an iodine map (IM) using an image-based 2-material decomposition method. Image noise of VMIs from each kV acquisition was calculated and compared between kV options. Absolute percent error (APE) of iodine CT number accuracy in VMIs was calculated and compared. Root mean square error (RMSE) and bias of iodine quantification from IMs were compared across kV options. RESULTS At the newborn size and 50 keV VMI, noise is lower at low kV acquisitions (70 kV: 10.5 HU, 90 kV: 10.4 HU), compared with high kV acquisitions (120 kV: 13.8 HU, 140 kV: 13.9 HU). At the newborn size and 70 keV VMI, the image noise from different kV options is comparable (9.4 HU for 70 kV, 8.9 HU for 90 kV, 9.7 HU for 120 kV, 10.2 HU for 140 kV). For APE of VMI, high kV (120 or 140 kV) performed overall better than low kV (70 or 90 kV). At the 5-year-old size, APE of 90 kV (median: 3.6%) is significantly higher (P < 0.001, Kruskal-Wallis rank sum test with Bonferroni correction) than 140 kV (median: 1.6%). At adult size, APE of 70 kV (median: 18.0%) is significantly higher (P < 0.0001, Kruskal-Wallis rank sum test with Bonferroni correction) than 120 kV (median: 1.4%) or 140 kV (median: 0.8%). The high kV also demonstrated lower RMSE and bias than the low kV across all controlled conditions. At 10-year-old size, RMSE and bias of 120 kV are 1.4 and 0.2 mg I/mL, whereas those from 70 kV are 1.9 and 0.8 mg I/mL. CONCLUSIONS The high kV options (120 or 140 kV) on the PCCT unit demonstrated overall better performance than the low kV options (70 or 90 kV), in terms of image quality of VMIs and IMs. Our results recommend the use of high kV for general body imaging on the PCCT.
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Affiliation(s)
- Wei Zhou
- From the Department of Radiology, University of Colorado, Anschutz Medical Campus, Aurora, CO (W.Z., D.H., L.P.B., J.P.W.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX (A.A., L.R.); Department of Radiology, Children's Hospital Colorado, Aurora, CO (L.P.B., J.P.W.); Department of Bioinformatics and Computational Biology, University of Minnesota, St Paul, MN (X.Z.); and Department of Pathology, University of Colorado, Anschutz Medical Campus, Aurora, CO (X.Z.)
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Stein T, Rau A, Russe MF, Arnold P, Faby S, Ulzheimer S, Weis M, Froelich MF, Overhoff D, Horger M, Hagen F, Bongers M, Nikolaou K, Schönberg SO, Bamberg F, Weiß J. Photon-Counting Computed Tomography - Basic Principles, Potenzial Benefits, and Initial Clinical Experience. ROFO-FORTSCHR RONTG 2023; 195:691-698. [PMID: 36863367 DOI: 10.1055/a-2018-3396] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
BACKGROUND Photon-counting computed tomography (PCCT) is a promising new technology with the potential to fundamentally change today's workflows in the daily routine and to provide new quantitative imaging information to improve clinical decision-making and patient management. METHOD The content of this review is based on an unrestricted literature search on PubMed and Google Scholar using the search terms "Photon-Counting CT", "Photon-Counting detector", "spectral CT", "Computed Tomography" as well as on the authors' experience. RESULTS The fundamental difference with respect to the currently established energy-integrating CT detectors is that PCCT allows counting of every single photon at the detector level. Based on the identified literature, PCCT phantom measurements and initial clinical studies have demonstrated that the new technology allows improved spatial resolution, reduced image noise, and new possibilities for advanced quantitative image postprocessing. CONCLUSION For clinical practice, the potential benefits include fewer beam hardening artifacts, radiation dose reduction, and the use of new contrast agents. In this review, we will discuss basic technical principles and potential clinical benefits and demonstrate first clinical use cases. KEY POINTS · Photon-counting computed tomography (PCCT) has been implemented in the clinical routine. · Compared to energy-integrating detector CT, PCCT allows the reduction of electronic image noise. · PCCT provides increased spatial resolution and a higher contrast-to-noise ratio. · The novel detector technology allows the quantification of spectral information. CITATION FORMAT · Stein T, Rau A, Russe MF et al. Photon-Counting Computed Tomography - Basic Principles, Potenzial Benefits, and Initial Clinical Experience. Fortschr Röntgenstr 2023; 195: 691 - 698.
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Affiliation(s)
- Thomas Stein
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Germany
| | - Alexander Rau
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Germany
| | - Maximilian Frederik Russe
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Germany
| | - Philipp Arnold
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Germany
| | - Sebastian Faby
- Computed Tomography, Siemens Healthcare GmbH, Forchheim, Germany
| | - Stefan Ulzheimer
- Computed Tomography, Siemens Healthcare GmbH, Forchheim, Germany
| | - Meike Weis
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Matthias F Froelich
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Daniel Overhoff
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Marius Horger
- Department of Radiology, University Hospitals Tübingen, Germany
| | - Florian Hagen
- Department of Radiology, University Hospitals Tübingen, Germany
| | - Malte Bongers
- Department of Radiology, University Hospitals Tübingen, Germany
| | | | - Stefan O Schönberg
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Germany
| | - Jakob Weiß
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Germany
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Abel F, Schubert T, Winklhofer S. Advanced Neuroimaging With Photon-Counting Detector CT. Invest Radiol 2023; 58:472-481. [PMID: 37158466 DOI: 10.1097/rli.0000000000000984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
ABSTRACT Photon-counting detector computed tomography (PCD-CT) is an emerging technology and promises the next step in CT evolution. Photon-counting detectors count the number of individual incoming photons and assess the energy level of each of them. These mechanisms differ substantially from conventional energy-integrating detectors. The new technique has several advantages, including lower radiation exposure, higher spatial resolution, reconstruction of images with less beam-hardening artifacts, and advanced opportunities for spectral imaging. Research PCD-CT systems have already demonstrated promising results, and recently, the first whole-body full field-of-view PCD-CT scanners became clinically available. Based on published studies of preclinical systems and the first experience with clinically approved scanners, the performance can be translated to valuable neuroimaging applications, including brain imaging, intracranial and extracranial CT angiographies, or head and neck imaging with detailed assessment of the temporal bone. In this review, we will provide an overview of the current status in neuroimaging with upcoming and potential clinical applications.
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Affiliation(s)
- Frederik Abel
- From the Department of Diagnostic and Interventional Radiology
| | - Tilman Schubert
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Tang X, Ren Y, Xie H. Noise correlation and its impact on the performance of multi-material decomposition-based spectral imaging in photon-counting CT. J Appl Clin Med Phys 2022; 24:e13830. [PMID: 36397280 PMCID: PMC9860003 DOI: 10.1002/acm2.13830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 07/31/2022] [Accepted: 10/05/2022] [Indexed: 11/21/2022] Open
Abstract
PURPOSE It has been known that noise correlation plays an important role in the determination of the performance of spectral imaging based on two-material decomposition (2-MD). To further understand the basics of spectral imaging in photon-counting CT toward optimal design and implementation, we study the noise correlation in multi-MD (m-MD) and its impact on the performance of spectral imaging. METHOD We derive the equations that characterize the noise and noise correlation in the material-specific (basis) images in m-MD, followed by a simulation study to verify the derived equations and study the noise correlation's impact on the performance of spectral imaging. Using a specially designed digital phantom, the study of noise correlation runs over the cases of two-, three-, and four-MD (2-MD, 3-MD, and 4-MD). Then, the noise correlation's impact on the performance of spectral imaging in photon-counting CT is investigated, using a modified Shepp-Logan phantom. RESULTS The results in 2-MD show that, in-line with what has been reported in the literature, the noise correlation coefficient between the material-specific images corresponding to the basis materials approaches -1. The results in m-MD (m ≥ 3) are more complicated and interesting, as the noise correlation coefficients between a pair of the material-specific images alternate between ±1, and so do in the case of 4-MD. The m-MD data show that the noise in virtual monochromatic imaging (a form of spectral imaging) is moderate even though the noises in material-specific (basis) images vary drastically. CONCLUSIONS The observation of noise correlation in 3-MD, 4-MD, and beyond (i.e., m-MD) is informative to the community. The relationship between noise correlation and the performance of spectral imaging revealed in this work may help clinical medical physicists understand the fundamentals of spectral imaging based on MD and optimize the performance of spectral imaging in photon-counting CT and other X-ray imaging modalities.
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Affiliation(s)
- Xiangyang Tang
- Imaging and Medical Physics, Department of Radiology and Imaging SciencesEmory University School of MedicineAtlantaGeorgiaUSA
| | - Yan Ren
- Imaging and Medical Physics, Department of Radiology and Imaging SciencesEmory University School of MedicineAtlantaGeorgiaUSA
| | - Huiqiao Xie
- Imaging and Medical Physics, Department of Radiology and Imaging SciencesEmory University School of MedicineAtlantaGeorgiaUSA
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Tang X, Ren Y, Xie H. Photon-counting CT via interleaved/gapped spectral channels: Feasibility and imaging performance. Med Phys 2021; 49:1445-1457. [PMID: 34914108 DOI: 10.1002/mp.15416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 11/18/2021] [Accepted: 12/03/2021] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Compared to energy-integration, photon-counting x-ray detection facilitates the spectral channelization (energy binning) in spectral CT and thus offers the opportunity of implementing data acquisition via sophisticated schemes, e.g., gapping or interleaving in spectral channels. In this article, we report our investigation of the performance of material decomposition based spectral imaging in photon-counting CT implemented in such data acquisition schemes, and their comparison with the benchmark scheme and other schemes without spectral gapping or interleaving. MATERIALS AND METHODS Using a deliberately designed anthropomorphic head phantom that mimics the intracranial soft tissues and bony structures, a simulation study is carried out with the focus on two-material decomposition-based spectral imaging in photon-counting CT, under both ideal and realistic detector spectral responses. The projection data are acquired in four spectral channels, and then are sorted to implement the schemes of gapping ((ch1 , ch3 ); (ch2 , ch4 ); (ch1 , ch4 )) and interleaving ((ch1 , ch3 )+(ch2 , ch4 ); (ch1 , ch4 )+(ch2 , ch3 ); ((ch1 +ch3 ), (ch2 +ch4 )); ((ch1 +ch4 ), (ch2 +ch3 ))) in spectral channels, in addition to the benchmark scheme ((ch1 +ch2 ), (ch3 +ch4 )) and other conventional schemes (ch1 , ch2 ), (ch2 , ch3 ) and (ch3 , ch4 ), where 'ch' denotes channel, '+' denote addition, and (·,·) the operation of material decomposition and image reconstruction. Using the contrast-to-noise ratio between targeted regions of interest as the figure of merit, we study the performance of spectral imaging (material specific and virtual monochromatic) associated with these spectral channelization schemes. RESULTS Under ideal detector spectral response, the scheme (ch1 , ch4 ) outperforms the benchmark scheme ((ch1 +ch2 ), (ch3 +ch4 )) and others in gapped and/or interleaved spectral channelization in material specific imaging, while the interleaved scheme (ch1 , ch4 )+(ch2 , ch3 ) performs the best in virtual monochromatic imaging. Notably, only about half x-ray dose is utilized in the scheme (ch1 , ch4 ) for image formation. Under realistic detector spectral response, the difference in imaging performance over all spectral channelization schemes diminishes, along with degradation in each scheme's individual performance. The results suggest that (i) different strategy in spectral channelization may have to be exercised in material specific imaging and virtual monochromatic imaging, respectively, and (ii) the spectral distortion in realistic detector's response due to charge-sharing, Compton scattering and fluorescent escaping should be mitigated as much as possible. CONCLUSION The spectral channelization schemes and associated imaging performance reported herein are novel and thus informative to the community, which may further the understanding of physical fundamentals and design principles for material decomposition based spectral imaging in photon-counting CT and other x-ray related imaging modalities. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Xiangyang Tang
- Imaging and Medical Physics, Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Yan Ren
- Imaging and Medical Physics, Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Huiqiao Xie
- Imaging and Medical Physics, Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
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Ren Y, Xie H, Long W, Yang X, Tang X. On the Conditioning of Spectral Channelization (Energy Binning) and Its Impact on Multi-Material Decomposition Based Spectral Imaging in Photon-Counting CT. IEEE Trans Biomed Eng 2021; 68:2678-2688. [DOI: 10.1109/tbme.2020.3048661] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Feng M, Ji X, Zhang R, Treb K, Dingle AM, Li K. An experimental method to correct low-frequency concentric artifacts in photon counting CT. Phys Med Biol 2021; 66. [PMID: 34315142 DOI: 10.1088/1361-6560/ac1833] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/27/2021] [Indexed: 11/12/2022]
Abstract
Large-area photon counting detectors (PCDs) are usually built by tiling multiple semiconductor panels that often have slightly different spectral responses to input x-rays. As a result of this spectral inconsistency, experimental PCD-CT images of large, human-sized objects may show high-frequency ring artifacts and low-frequency band artifacts. Due to the much larger width of the bands compared with the rings, the concentric artifact problem in PCD-CT images of human-sized objects cannot be adequately addressed by conventional CT ring correction methods. This work presents an experimental method to correct the concentric artifacts in PCD-CT. The method is applicable to not only energy-discriminating PCDs with multiple bins but also PCDs with only a single threshold controller. Its principle is similar to the two-step beam hardening correction method, except that the proposed method uses pixel-specific polynomial functions to address the spectral inconsistency problem across the detector plane. The pixel-specific polynomial coefficients were experimentally calibrated using 15 acrylic sheets and 6 aluminum sheets of known thicknesses. The pixel-specific polynomial functions were used to convert the measured PCD-CT projection data to acrylic- and aluminum-equivalent thicknesses that are energy-independent. The proposed method was experimentally evaluated using a human cadaver head and multiple physical phantoms: two of them contain iodine and one phantom contains dual K-edge contrast materials (gadolinium and iodine). The results show that the proposed method can effectively remove the low-frequency concentric artifacts in PCD-CT images while reducing beam hardening artifacts. In contrast, the conventional CT ring correction algorithm did not adequately address the low-frequency band artifacts. Compared with the direct material decomposition-based correction method, the proposed method not only relaxes the requirement of multi-energy bins but also generates images with lower noise and fewer concentric artifacts.
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Affiliation(s)
- Mang Feng
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States of America
| | - Xu Ji
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States of America
| | - Ran Zhang
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States of America
| | - Kevin Treb
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States of America
| | - Aaron M Dingle
- Department of Surgery, University of Wisconsin-Madison, WI 53792, United States of America
| | - Ke Li
- Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, WI 53705, United States of America.,Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792, United States of America
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Wang AS, Pelc NJ. Spectral Photon Counting CT: Imaging Algorithms and Performance Assessment. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2021; 5:453-464. [PMID: 35419500 PMCID: PMC9000208 DOI: 10.1109/trpms.2020.3007380] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
Photon counting x-ray detectors (PCDs) with spectral capabilities have the potential to revolutionize computed tomography (CT) for medical imaging. The ideal PCD provides accurate energy information for each incident x-ray, and at high spatial resolution. This information enables material-specific imaging, enhanced radiation dose efficiency, and improved spatial resolution in CT images. In practice, PCDs are affected by non-idealities, including limited energy resolution, pulse pileup, and cross talk due to charge sharing, K-fluorescence, and Compton scattering. In order to maximize their performance, PCDs must be carefully designed to reduce these effects and then later account for them during correction and post-acquisition steps. This review article examines algorithms for using PCDs in spectral CT applications, including how non-idealities impact image quality. Performance assessment metrics that account for spatial resolution and noise such as the detective quantum efficiency (DQE) can be used to compare different PCD designs, as well as compare PCDs with conventional energy integrating detectors (EIDs). These methods play an important role in enhancing spectral CT images and assessing the overall performance of PCDs.
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Affiliation(s)
- Adam S Wang
- Departments of Radiology and, by courtesy, Electrical Engineering, Stanford University, Stanford, CA 94305 USA
| | - Norbert J Pelc
- Department of Radiology, Stanford University, Stanford, CA 94305 USA
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Abstract
The introduction of photon-counting detectors is expected to be the next major breakthrough in clinical x-ray computed tomography (CT). During the last decade, there has been considerable research activity in the field of photon-counting CT, in terms of both hardware development and theoretical understanding of the factors affecting image quality. In this article, we review the recent progress in this field with the intent of highlighting the relationship between detector design considerations and the resulting image quality. We discuss detector design choices such as converter material, pixel size, and readout electronics design, and then elucidate their impact on detector performance in terms of dose efficiency, spatial resolution, and energy resolution. Furthermore, we give an overview of data processing, reconstruction methods and metrics of imaging performance; outline clinical applications; and discuss potential future developments.
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Affiliation(s)
- Mats Danielsson
- Department of Physics, KTH Royal Institute of Technology, AlbaNova University Center, SE-106 91 Stockholm, Sweden. Prismatic Sensors AB, AlbaNova University Center, SE-106 91 Stockholm, Sweden
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Jacobsen MC, Thrower SL. Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement. Med Phys 2020; 47:3752-3771. [PMID: 32453879 PMCID: PMC8495770 DOI: 10.1002/mp.14241] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 04/20/2020] [Accepted: 05/07/2020] [Indexed: 12/21/2022] Open
Abstract
Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.
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Affiliation(s)
- Megan C. Jacobsen
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sara L. Thrower
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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Persson M, Wang A, Pelc NJ. Detective quantum efficiency of photon-counting CdTe and Si detectors for computed tomography: a simulation study. J Med Imaging (Bellingham) 2020; 7:043501. [PMID: 32715022 DOI: 10.1117/1.jmi.7.4.043501] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 06/30/2020] [Indexed: 11/14/2022] Open
Abstract
Purpose: Developing photon-counting CT detectors requires understanding the impact of parameters, such as converter material, thickness, and pixel size. We apply a linear-systems framework, incorporating spatial and energy resolution, to study realistic silicon (Si) and cadmium telluride (CdTe) detectors at a low count rate. Approach: We compared CdTe detector designs with 0.5 × 0.5 mm 2 and 0.225 × 0.225 mm 2 pixels and Si detector designs with 0.5 × 0.5 mm 2 pixels of 30 and 60 mm active thickness, with and without tungsten scatter blockers. Monte-Carlo simulations of photon transport were used together with Gaussian charge sharing models fitted to published data. Results: For detection in a 300-mm-thick object at 120 kVp, the 0.5- and 0.225-mm pixel CdTe systems have 28% to 41% and 5% to 29% higher detective quantum efficiency (DQE), respectively, than the 60-mm Si system with tungsten, whereas the corresponding numbers for two-material decomposition are 2% lower to 11% higher DQE and 31% to 54% lower DQE compared to Si. We also show that combining these detectors with dual-spectrum acquisition is beneficial. Conclusions: In the low-count-rate regime, CdTe detector systems outperform the Si systems for detection tasks, whereas silicon outperforms one or both of the CdTe systems for material decomposition.
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Affiliation(s)
- Mats Persson
- Stanford University, Department of Bioengineering, Stanford, California, United States.,Stanford University, Department of Radiology, Stanford, California, United States
| | - Adam Wang
- Stanford University, Department of Radiology, Stanford, California, United States
| | - Norbert J Pelc
- Stanford University, Department of Bioengineering, Stanford, California, United States.,Stanford University, Department of Radiology, Stanford, California, United States.,Stanford University, Department of Electrical Engineering, Stanford, California, United States
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Persson M, Rajbhandary PL, Pelc NJ. A framework for performance characterization of energy-resolving photon-counting detectors. Med Phys 2018; 45:4897-4915. [PMID: 30191571 DOI: 10.1002/mp.13172] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Revised: 07/19/2018] [Accepted: 08/29/2018] [Indexed: 01/12/2023] Open
Abstract
PURPOSE Photon-counting, energy-resolving detectors are subject to intense research interest, and there is a need for a general framework for performance assessment of these detectors. The commonly used linear-systems theory framework, which measures detector performance in terms of noise-equivalent quanta (NEQ) and detective quantum efficiency (DQE) is widely used for characterizing conventional x-ray detectors but does not take energy-resolving capabilities into account. The purpose of this work is to extend this framework to encompass energy-resolving photon-counting detectors and elucidate how the imperfect energy response and other imperfections in real-world detectors affect imaging performance, both for feature detection and for material quantification tasks. METHOD We generalize NEQ and DQE to matrix-valued quantities as functions of spatial frequency, and show how these matrices can be calculated from simple Monte Carlo simulations. To demonstrate how the new metrics can be interpreted, we compute them for simplified models of fluorescence and Compton scatter in a photon-counting detector and for a Monte Carlo model of a CdTe detector with 0.5 × 0.5 mm 2 pixels. RESULTS Our results show that the ideal-linear-observer performance for any detection or material quantification task can be calculated from the proposed generalized NEQ and DQE metrics. We also demonstrate that the proposed NEQ metric is closely related to a generalized version of the Cramér-Rao lower bound commonly used for assessing material quantification performance. Off-diagonal elements in the NEQ and DQE matrices are shown to be related to loss of energy information due to imperfect energy resolution. The Monte Carlo model of the CdTe detector predicts a zero-frequency dose efficiency relative to an ideal detector of 0.86 and 0.65 for detecting water and bone, respectively. When the task instead is to quantify these materials, the corresponding values are 0.34 for water and 0.26 for bone. CONCLUSIONS We have developed a framework for assessing the performance of photon-counting energy-resolving detectors and shown that the matrix-valued NEQ and DQE metrics contain sufficient information for calculating the dose efficiency for both detection and quantification tasks, the task having any spatial and energy dependence. This framework will be beneficial for the development and optimization of photon-counting x-ray detectors.
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Affiliation(s)
- Mats Persson
- Departments of Bioengineering and Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Paurakh L Rajbhandary
- Departments of Electrical Engineering and Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Norbert J Pelc
- Departments of Bioengineering, Radiology and Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
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Willemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D. Photon-counting CT: Technical Principles and Clinical Prospects. Radiology 2018; 289:293-312. [PMID: 30179101 DOI: 10.1148/radiol.2018172656] [Citation(s) in RCA: 577] [Impact Index Per Article: 96.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Photon-counting CT is an emerging technology with the potential to dramatically change clinical CT. Photon-counting CT uses new energy-resolving x-ray detectors, with mechanisms that differ substantially from those of conventional energy-integrating detectors. Photon-counting CT detectors count the number of incoming photons and measure photon energy. This technique results in higher contrast-to-noise ratio, improved spatial resolution, and optimized spectral imaging. Photon-counting CT can reduce radiation exposure, reconstruct images at a higher resolution, correct beam-hardening artifacts, optimize the use of contrast agents, and create opportunities for quantitative imaging relative to current CT technology. In this review, the authors will explain the technical principles of photon-counting CT in nonmathematical terms for radiologists and clinicians. Following a general overview of the current status of photon-counting CT, they will explain potential clinical applications of this technology.
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Affiliation(s)
- Martin J Willemink
- From the Department of Radiology (M.J.W., M.P., N.J.P., D.F.) and Stanford Cardiovascular Institute (D.F.), Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands (M.J.W.); Departments of Bioengineering (M.P., N.J.P.) and Electrical Engineering (N.J.P.), Stanford University, Stanford, Calif; Department of Radiology and Department of Imaging Sciences and Biomedical Informatics, Emory University School of Medicine, Atlanta, Ga (A.P.)
| | - Mats Persson
- From the Department of Radiology (M.J.W., M.P., N.J.P., D.F.) and Stanford Cardiovascular Institute (D.F.), Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands (M.J.W.); Departments of Bioengineering (M.P., N.J.P.) and Electrical Engineering (N.J.P.), Stanford University, Stanford, Calif; Department of Radiology and Department of Imaging Sciences and Biomedical Informatics, Emory University School of Medicine, Atlanta, Ga (A.P.)
| | - Amir Pourmorteza
- From the Department of Radiology (M.J.W., M.P., N.J.P., D.F.) and Stanford Cardiovascular Institute (D.F.), Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands (M.J.W.); Departments of Bioengineering (M.P., N.J.P.) and Electrical Engineering (N.J.P.), Stanford University, Stanford, Calif; Department of Radiology and Department of Imaging Sciences and Biomedical Informatics, Emory University School of Medicine, Atlanta, Ga (A.P.)
| | - Norbert J Pelc
- From the Department of Radiology (M.J.W., M.P., N.J.P., D.F.) and Stanford Cardiovascular Institute (D.F.), Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands (M.J.W.); Departments of Bioengineering (M.P., N.J.P.) and Electrical Engineering (N.J.P.), Stanford University, Stanford, Calif; Department of Radiology and Department of Imaging Sciences and Biomedical Informatics, Emory University School of Medicine, Atlanta, Ga (A.P.)
| | - Dominik Fleischmann
- From the Department of Radiology (M.J.W., M.P., N.J.P., D.F.) and Stanford Cardiovascular Institute (D.F.), Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands (M.J.W.); Departments of Bioengineering (M.P., N.J.P.) and Electrical Engineering (N.J.P.), Stanford University, Stanford, Calif; Department of Radiology and Department of Imaging Sciences and Biomedical Informatics, Emory University School of Medicine, Atlanta, Ga (A.P.)
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Li Z, Leng S, Yu Z, Kappler S, McCollough CH. Estimation of signal and noise for a whole-body research photon-counting CT system. J Med Imaging (Bellingham) 2017; 4:023505. [PMID: 28653013 DOI: 10.1117/1.jmi.4.2.023505] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 05/30/2017] [Indexed: 11/14/2022] Open
Abstract
Photon-counting detector CT has a large number of acquisition parameters that require optimization, particularly the energy threshold configurations. Fast and accurate estimation of both signal and noise in photon-counting CT (PCCT) images can facilitate such optimization. Using the detector response function of a research PCCT system, we derived mathematical models for both signal and noise estimation, taking into account beam spectrum and filtration, object attenuation, water beam hardening, detector response, radiation dose, energy thresholds, and the propagation of noise. To determine the absolute noise value, a noise lookup table (LUT) for all available energy thresholds was acquired using a number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuations. Validation of the estimation algorithms was performed on a whole-body research PCCT system using semianthropomorphic water phantoms and solutions of calcium and iodine. Clinical feasibility of noise estimation was assessed with scans of a cadaver head and a living swine. The algorithms achieved accurate estimation of both signal and noise for a variety of scanning parameter combinations. Maximum discrepancies were below 15%, while most errors were below 5%.
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Affiliation(s)
- Zhoubo Li
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States.,Mayo Graduate School, Biomedical Engineering and Physiology Graduate Program, Rochester, Minnesota, United States
| | - Shuai Leng
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States
| | - Zhicong Yu
- Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States
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Hernandez AM, Seibert JA, Nosratieh A, Boone JM. Generation and analysis of clinically relevant breast imaging x-ray spectra. Med Phys 2017; 44:2148-2160. [PMID: 28303582 DOI: 10.1002/mp.12222] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Revised: 12/27/2016] [Accepted: 02/03/2017] [Indexed: 11/05/2022] Open
Abstract
PURPOSE The purpose of this work was to develop and make available x-ray spectra for some of the most widely used digital mammography (DM), breast tomosynthesis (BT), and breast CT (bCT) systems in North America. METHODS The Monte Carlo code MCNP6 was used to simulate minimally filtered (only beryllium) x-ray spectra at 8 tube potentials from 20 to 49 kV for DM/BT, and 9 tube potentials from 35 to 70 kV for bCT. Vendor-specific anode compositions, effective anode angles, focal spot sizes, source-to-detector distances, and beryllium filtration were simulated. For each 0.5 keV energy bin in all simulated spectra, the fluence was interpolated using cubic splines across the range of simulated tube potentials to produce spectra in 1 kV increments from 20 to 49 kV for DM/BT and from 35 to 70 kV for bCT. The HVL of simulated spectra with conventional filtration (at 35 kV for DM/BT and 49 kV for bCT) was used to assess spectral differences resulting from variations in: (a) focal spot size (0.1 and 0.3 mm IEC), (b) solid angle at the detector (i.e., small and large FOV size), and (c) geometrical specifications for vendors that employ the same anode composition. RESULTS Averaged across all DM/BT vendors, variations in focal spot and FOV size resulted in HVL differences of 2.2% and 0.9%, respectively. Comparing anode compositions separately, the HVL differences for Mo (GE, Siemens) and W (Hologic, Philips, and Siemens) spectra were 0.3% and 0.6%, respectively. Both the commercial Koning and prototype "Doheny" (UC Davis) bCT systems utilize W anodes with a 0.3 mm focal spot. Averaged across both bCT systems, variations in FOV size resulted in a 2.2% difference in HVL. In addition, the Koning spectrum was slightly harder than Doheny with a 4.2% difference in HVL. Therefore to reduce redundancy, a generic DM/BT system and a generic bCT system were used to generate the new spectra reported herein. The spectral models for application to DM/BT were dubbed the Molybdenum, Rhodium, and Tungsten Anode Spectral Models using Interpolating Cubic Splines (MASMICSM-T , RASMICSM-T , and TASMICSM-T ; subscript "M-T" indicating mammography and tomosynthesis). When compared against reference models (MASMIPM , RASMIPM , and TASMIPM ; subscript "M" indicating mammography), the new spectral models were in close agreement with mean differences of 1.3%, -1.3%, and -3.3%, respectively, across tube potential comparisons of 20, 30, and 40 kV with conventional filtration. TASMICSbCT -generated bCT spectra were also in close agreement with the reference TASMIP model with a mean difference of -0.8%, across tube potential comparisons of 35, 49, and 70 kV with 1.5 mm Al filtration. CONCLUSIONS The Mo, Rh, and W anode spectra for application in DM and BT (MASMICSM-T , RASMICSM-T , and TASMICSM-T ) and the W anode spectra for bCT (TASMICSbCT ) as described in this study should be useful for individuals interested in modeling the performance of modern breast x-ray imaging systems including dual-energy mammography which extends to 49 kV. These new spectra are tabulated in spreadsheet form and are made available to any interested party.
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Affiliation(s)
- Andrew M Hernandez
- Department of Radiology, Biomedical Engineering Graduate Group, University of California Davis, Sacramento, CA, 95817, USA
| | - J Anthony Seibert
- Department of Radiology and Biomedical Engineering, Biomedical Engineering Graduate Group, University of California Davis, Sacramento, CA, 95817, USA
| | - Anita Nosratieh
- Department of Radiology, Biomedical Engineering Graduate Group, University of California Davis, Sacramento, CA, 95817, USA
| | - John M Boone
- Department of Radiology and Biomedical Engineering, Biomedical Engineering Graduate Group, University of California Davis, Sacramento, CA, 95817, USA
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