Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT

Albrecht, Moritz H.; Vogl, Thomas J.; Martin, Simon S.; Nance, John W.; Duguay, Taylor M.; Wichmann, Julian L.; Cecco, Carlo N. De; Varga-Szemes, Ákos; Assen, Marly van; Tesche, Christian; Schoepf, U. Joseph

doi:10.1148/radiol.2019182297

Cited by 172 publications

(119 citation statements)

References 93 publications

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“…Dual-energy CT has been widely used recently [6]. Quantitative parameters derived from dual-energy CT data have proven to be useful for the diagnosis and nodal staging in several types of tumors [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement

Fang

Zhu

et al. 2020

Cancer Imaging

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Background: To explore the relationship between the lymph node status and preoperative computed tomography images texture features in pancreatic cancer. Methods: A total of 155 operable pancreatic cancer patients (104 men, 51 women; mean age 63.8 ± 9.6 years), who had undergone contrast-enhanced computed tomography in the arterial and portal venous phases, were enrolled in this retrospective study. There were 73 patients with lymph node metastases and 82 patients without nodal involvement. Four different data sets, with thin (1.25 mm) and thick (5 mm) slices (at arterial phase and portal venous phase) were analysed. Texture analysis was performed by using MaZda software. A combination of feature selection algorithms was used to determine 30 texture features with the optimal discriminative performance for differentiation between lymph node positive and negative groups. The prediction performance of the selected feature was evaluated by receiver operating characteristic (ROC) curve analysis. Results: There were 10 texture features with significant differences between two groups and significance in ROC analysis were identified. They were WavEnLH_s-2(wavelet energy with rows and columns are filtered with low pass and high pass frequency bands with scale factors 2) from wavelet-based features, 135dr_LngREmph (long run emphasis in 135 direction) and 135dr_Fraction (fraction of image in runs in 135 direction) from run length matrix-based features, and seven variables of sum average from coocurrence matrix-based features (SumAverg). The ideal cutoff value for predicting lymph node metastases was 270 for WavEnLH_s-2 (positive likelihood ratio 2.08). In addition, 135dr_ LngREmph and 135dr_Fraction were correlated with the ratio of metastatic to examined lymph nodes. Conclusions:Preoperative computed tomography high order texture features provide a useful imaging signature for the prediction of nodal involvement in pancreatic cancer.

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Section: Introductionmentioning

confidence: 99%

Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement

Fang

Zhu

et al. 2020

Cancer Imaging

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“…As such, virtual monoenergetic images can reduce metal artifacts. 115 Reduction or elimination of metal artifacts has been demonstrated for a large number of metallic objects, including hip arthroplasty/prosthesis, dental metallic implants, aortic repair stents, aneurysm clips, and more ( Fig. 23).…”

Section: C2 Metal Artifact Reductionmentioning

confidence: 99%

Principles and applications of multienergy CT: Report of AAPM Task Group 291

McCollough

Boedeker

Cody³

et al. 2020

Medical Physics

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In x-ray computed tomography (CT), materials with different elemental compositions can have identical CT number values, depending on the mass density of each material and the energy of the detected x-ray beam. Differentiating and classifying different tissue types and contrast agents can thus be extremely challenging. In multienergy CT, one or more additional attenuation measurements are obtained at a second, third or more energy. This allows the differentiation of at least two materials. Commercial dual-energy CT systems (only two energy measurements) are now available either using sequential acquisitions of low-and high-tube potential scans, fast tube-potential switching, beam filtration combined with spiral scanning, dual-source, or dual-layer detector approaches. The use of energy-resolving, photon-counting detectors is now being evaluated on research systems. Irrespective of the technological approach to data acquisition, all commercial multienergy CT systems circa 2020 provide dual-energy data. Material decomposition algorithms are then used to identify specific materials according to their effective atomic number and/or to quantitate mass density. These algorithms are applied to either projection or image data. Since 2006, a number of clinical applications have been developed for commercial release, including those that automatically (a) remove the calcium signal from bony anatomy and/or calcified plaque; (b) create iodine concentration maps from contrast-enhanced CT data and/or quantify absolute iodine concentration; (c) create virtual noncontrast-enhanced images from contrast-enhanced scans; (d) identify perfused blood volume in lung parenchyma or the myocardium; and (e) characterize materials according to their elemental compositions, which can allow in vivo differentiation between uric-acid and non-uric-acid urinary stones or uric acid (gout) or non-uric-acid (calcium pyrophosphate) deposits in articulating joints and surrounding tissues. In this report, the underlying physical principles of multienergy CT are reviewed and each of the current technical approaches are described. In addition, current and evolving clinical applications are introduced. Finally, the impact of multienergy CT technology on patient radiation dose is summarized.

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“…Besides conventional single energy imaging based on the integrated information from a single x-ray spectrum, dual-energy CT (DECT) techniques have been introduced to clinical practice extending diagnostic capabilities even further. Popular applications include the computation of virtual monochromatic (VMI) and virtual non-contrast (VNC) images or material characterization and decomposition [1][2][3]. Various techniques have been proposed and are currently used in clinical CT systems to realize DECT.…”

Section: Introductionmentioning

confidence: 99%

Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

et al. 2021

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Objective To evaluate the dual-energy (DE) performance and spectral separation with respect to iodine imaging in a photon-counting CT (PCCT) and compare it to dual-source CT (DSCT) DE imaging. Methods A semi-anthropomorphic phantom extendable with fat rings equipped with iodine vials is measured in an experimental PCCT. The system comprises a PC detector with two energy bins (20 keV, T) and (T, eU) with threshold T and tube voltage U. Measurements using the PCCT are performed at all available tube voltages (80 to 140 kV) and threshold settings (50–90 keV). Further measurements are performed using a conventional energy-integrating DSCT. Spectral separation is quantified as the relative contrast media ratio R between the energy bins and low/high images. Image noise and dose-normalized contrast-to-noise ratio (CNRD) are evaluated in resulting iodine images. All results are validated in a post-mortem angiography study. Results R of the PC detector varies between 1.2 and 2.6 and increases with higher thresholds and higher tube voltage. Reference R of the EI DSCT is found as 2.20 on average overall phantoms. Maximum CNRD in iodine images is found for T = 60/65/70/70 keV for 80/100/120/140 kV. The highest CNRD of the PCCT is obtained using 140 kV and is decreasing with decreasing tube voltage. All results could be confirmed in the post-mortem angiography study. Conclusion Intrinsically acquired DE data are able to provide iodine images similar to conventional DSCT. However, PCCT thresholds should be chosen with respect to tube voltage to maximize image quality in retrospectively derived image sets. Key Points • Photon-counting CT allows for the computation of iodine images with similar quality compared to conventional dual-source dual-energy CT. • Thresholds should be chosen as a function of the tube voltage to maximize iodine contrast-to-noise ratio in derived image sets. • Image quality of retrospectively computed image sets can be maximized using optimized threshold settings.

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Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT

Cited by 172 publications

References 93 publications

Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement

Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement

Principles and applications of multienergy CT: Report of AAPM Task Group 291

Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

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