Standardizing technical parameters and terms for abdominopelvic photon-counting CT: laying the groundwork for innovation and evidence sharing.

Photon-counting detector CT (PCD-CT) is a new technology that has multiple diagnostic benefits including increased spatial resolution, iodine signal, and radiation dose efficiency, as well as multi-energy imaging capability, but which also has unique challenges in abdominal imaging. The purpose of this work is to summarize key features, technical parameters, and terms, which are common amongst current abdominopelvic PCD-CT systems and to propose standardized terminology (where none exists). In addition, user-selectable protocol parameters are highlighted to facilitate both scientific evaluation and early clinical adoption. Unique features of PCD-CT systems include photon-counting detectors themselves, energy thresholds and bins, and tube potential considerations for preserved spectral separation. Key parameters for describing different PCD-CT systems are reviewed and explained. While PCD-CT can generate multi-energy images like dual-energy CT, there are new types of images such as threshold images, energy bin images, and special spectral images. The standardized terms and concepts herein build upon prior interdisciplinary consensus and have been endorsed by the newly created Society of Abdominal Radiology Photon-counting CT Emerging Technology Commission.

Perceptual thresholds for differences in CT noise texture.

Purpose: The average (fav) or peak (fpeak) noise power spectrum (NPS) frequency is often used as a one-parameter descriptor of the CT noise texture. Our study develops a more complete two-parameter model of the CT NPS and investigates the sensitivity of human observers to changes in it. Approach: A model of CT NPS was created based on its fpeak and a half-Gaussian fit (σ) to the downslope. Two-alternative forced-choice staircase studies were used to determine perceptual thresholds for noise texture, defined as parameter differences with a predetermined level of discrimination performance (80% correct). Five imaging scientist observers performed the forced-choice studies for eight directions in the fpeak/σ-space, for two reference NPSs (corresponding to body and lung kernels). The experiment was repeated with 32 radiologists, each evaluating a single direction in the fpeak/σ-space. NPS differences were quantified by the noise texture contrast (Ctexture), the integral of the absolute NPS difference. Results: The two-parameter NPS model was found to be a good representation of various clinical CT reconstructions. Perception thresholds for fpeak alone are 0.2 lp/cm for body and 0.4 lp/cm for lung NPSs. For σ, these values are 0.15 and 2 lp/cm, respectively. Thresholds change if the other parameter also changes. Different NPSs with the same fpeak or fav can be discriminated. Nonradiologist observers did not need more Ctexture than radiologists. Conclusions: fpeak or fav is insufficient to describe noise texture completely. The discrimination of noise texture changes depending on its frequency content. Radiologists do not discriminate noise texture changes better than nonradiologists.

Notice of Removal: Fourier Diffusion Models: A Method to Control MTF and NPS in Score-Based Stochastic Image Generation.

Removed.

Technical performance of a dual-energy CT system with a novel deep-learning based reconstruction process: Evaluation using an abdomen protocol.

BACKGROUND: A new tube voltage-switching dual-energy (DE) CT system using a novel deep-learning based reconstruction process has been introduced. Characterizing the performance of this DE approach can help demonstrate its benefits and potential drawbacks. PURPOSE: To evaluate the technical performance of a novel DECT system and compare it to that of standard single-kV CT and a rotate/rotate DECT, for abdominal imaging. METHODS: DE and single-kV images of four different phantoms were acquired on a kV-switching DECT system, and on a rotate/rotate DECT. The dose for the acquisitions of each phantom was set to that selected for the kV-switching DE mode by the automatic tube current modulation (ATCM) at manufacturer-recommended settings. The dose that the ATCM would have selected in single-kV mode was also recorded. Virtual monochromatic images (VMIs) from 40 to 130 keV, as well as iodine maps, were reconstructed from the DE data. Single-kV images, acquired at 120 kV, were reconstructed using body hybrid iterative reconstruction. All reconstructions were made at 0.5 mm section thickness. Task transfer functions (TTFs) were determined for a Teflon and LDPE rod. Noise magnitude (SD), and noise power spectrum (NPS) were calculated using 240 and 320 mm diameter water phantoms. Iodine quantification accuracy and contrast-to-noise ratios (CNRs) relative to water for 2, 5, 10, and 15 mg I/ml were determined using a multi-energy CT (MECT) phantom. Low-contrast visibility was determined and the presence of beam-hardening artifacts and inhomogeneities were evaluated. RESULTS: The TTFs of the kV-switching DE VMIs were higher than that of the single-kV images for Teflon (20% TTF: 6.8 lp/cm at 40 keV, 6.2 lp/cm for single-kV), while for LDPE the DE TTFs at 70 keV and above were equivalent or higher than the single-kV TTF. All TTFs of the kV-switching DECT were higher than for the rotate/rotate DECT. The SD was lowest in the 70 keV VMI (12.0 HU), which was lower than that of single-kV (18.3 HU). The average NPS frequency varied between 2.3 lp/cm and 4.2 lp/cm for the kV-switching VMIs and was 2.2 lp/cm for single-kV. The error in iodine quantification was at maximum 1 mg I/ml (at 5 mg I/ml). The highest CNR for all iodine concentrations was at 60 keV, 2.5 times higher than the CNR for single-kV. At 70-90 keV, the number of visible low contrast objects was comparable to that in single-kV, while other VMIs showed fewer objects. At manufacturer-recommended ATCM settings, the CTDIvol for the DE acquisitions of the water and MECT phantoms were 12.6 and 15.4 mGy, respectively, and higher than that for single-kV. The 70 keV VMI had less severe beam hardening artifacts than single-kV images. Hyper- and hypo-dense blotches may appear in VMIs when object attenuation exceeds manufacturer recommended limits. CONCLUSIONS: At manufacturer-recommended ATCM settings for abdominal imaging, this DE implementation results in higher CTDIvol compared to single-kV acquisitions. However, it can create sharper, lower noise VMIs with up to 2.5 times higher iodine CNR compared to single-kV images acquired at the same dose.

Task-Driven CT Image Quality Optimization for Low-Contrast Lesion Detectability with Tunable Neural Networks.

Low-contrast lesions are difficult to detect in noisy low-dose CT images. Improving CT image quality for this detection task has the potential to improve diagnostic accuracy and patient outcomes. In this work, we use tunable neural networks for CT image restoration with a hyperparameter to control the variance/bias tradeoff. We use clinical images from a super-high-resolution normal-dose CT scan to synthesize low-contrast low-dose CT images for supervised training of deep learning CT reconstruction models. Those models are trained using with multiple noise realizations so that variance and bias can be penalized separately. We use a training loss function with one hyperparameter called the denoising level, which controls the variance/bias tradeoff. Finally, we evaluate the CT image quality to find the optimal denoising level for low-contrast lesion detectability. We evaluate performance using a shallow neural network model classification model to represent a suboptimal image observer. Our results indicate that the optimal networks for low-contrast lesion detectability are those that prioritize bias reduction rather than mean-squared error, which demonstrates the potential clinical benefit of our proposed tunable neural networks.

CT imaging with ultra-high-resolution: Opportunities for cardiovascular imaging in clinical practice.

Cardiovascular computed tomography (CT) angiography has become an established alternative to invasive catheter angiography. However, imaging artifacts due to partial volume effects with current systems hinder accurate evaluation of calcified or stented segments. Increased spatial resolution may allow to overcome these barriers to precise delineation of vascular disease. Recent developments in CT hardware and reconstruction have enabled CT angiography with ultra-high spatial resolution (UHRCT). In this review we aim to describe the methods to achieve greater spatial resolution in CT that are either in clinical or preclinical stage. In addition, we provide an overview of the available clinical evidence including diagnostic accuracy studies supporting improved vascular assessment with this technology. The benefits that can be gleaned from the initial experiences with UHRCT are promising. Using UHRCT, more patients may receive non-invasive characterization of coronary atherosclerosis by overcoming the limitations of current CT spatial resolution in visualizing and quantifying calcified, stented or small diameter segments. UHRCT may potentially impact existing management pathways as well as contribute to better understanding of the underlying pathophysiology of both macro- and microvascular disease.

Validation of synthesized normal-resolution image data generated from high-resolution acquisitions on a commercial CT scanner.

PURPOSE: To validate a normal-resolution (NR) simulation (NRsim) algorithm that uses high-resolution (HR) or super-high resolution (SHR) acquisitions on a commercial HR computed tomography (CT) scanner by comparing image quality between NRsim-generated images and actual NR images. NRsim is intended to allow direct comparison between normal-resolution CT and HR/SHR reconstructions in clinical investigations, without repeating exams. METHODS: The Aquilion Precision CT (Canon Medical Systems Corporation) HR CT scanner has three resolution modes resulting from detector binning in the channel (x-y) and row (z) directions. For NR, each detector element is 0.5 mm × 0.5 mm along the channel and row directions, 0.25 mm × 0.5 mm for HR, and 0.25 mm × 0.25 mm for SHR. The NRsim algorithm simulates NR acquisitions from HR or SHR acquisitions (termed NRHR and NRSHR , respectively) by downsampling the pre-log raw data in the channel direction for the HR acquisitions and in the channel and row direction for the SHR acquisition. The downsampled data are then reconstructed using the same process as NR. The axial modulation transfer function (MTF), slice sensitivity profile (SSP), and CT number accuracy were measured using the Catphan 600 phantom, and the three-dimensional noise power spectrum (NPS) was measured in water-equivalent phantoms for standard protocols across a range of size-specific dose estimates (SSDE): head (6.2-29.8 mGy), lung (2.2-18.2 mGy), and body (5.6-19.4 mGy). The MTF and NPS measurements were combined to estimate low-contrast detectability (LCD) using a non-prewhitening model observer with an eye filter for a 5-mm disk with 10 HU contrast. All metrics were compared for NR, NRHR , and NRSHR images reconstructed using filtered back projection (FBP) and an iterative reconstruction algorithm (AIDR3D). We chose a 15% error threshold as a reasonable definition of success for NRsim when compared against actual NR based on published studies showing that a just-noticeable difference in image noise level for human observers is typically <15%. RESULTS: The axial MTF and SSPs for NRsim were in good agreement with NR demonstrated by a maximum difference of 5.1% for the MTF at 10% and 50% across materials (air, Teflon, LDPE, and polystyrene) and a maximum SSP difference of 2.2%. Noise magnitude differences were within 15% across the SSDE levels with the exception of below 4.5 mGy for the lung protocol with FBP. The relative RMSE of normalized NPS comparisons were all <15%. Differences in CT numbers for NRsim reconstructions were within 2 HU of NR. LCD for NRsim was within 15% of NR with the exception of NRSHR for the lung protocol SSDE levels below 3.7 mGy with FBP. CONCLUSIONS: NRsim, an algorithm for simulating NR acquisitions using HR and SHR raw data, was introduced and shown to generate images with spatial resolution, noise, HU accuracy, and LCD largely equivalent to scans acquired using an actual NR acquisition. At SSDE levels below ~5 mGy for the lung protocol, differences in noise magnitude and LCD for NRSHR were >15% which defines a region where NRsim degrades due to contributions from electronic noise.

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

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 non-contrast-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.

Correction to: Physical evaluation of an ultra-high-resolution CT scanner.

The original version of this article, published on 10 February 2019, unfortunately contained a mistake. The axes of the graphs in Fig. 3 are incorrect. The correct figure is given below. Therefore, the last two sentences in "Results," section "Noise," should read: "The peak frequency of the HR and SHR was 0.21 lp/mm. For the NR mode and the MDCT, the peak frequencies were 0.17 lp/mm and 0.21 lp/mm, respectively."

Physical evaluation of an ultra-high-resolution CT scanner.

OBJECTIVES: To evaluate the technical performance of an ultra-high-resolution CT (UHRCT) system. METHODS: The physico-technical capabilities of a novel commercial UHRCT system were assessed and compared with those of a current-generation multi-detector (MDCT) system. The super-high-resolution (SHR) mode of the system uses 0.25 mm (at isocentre) detector elements (dels) in the in-plane and longitudinal directions, while the high-resolution (HR) mode bins two dels in the longitudinal direction. The normal-resolution (NR) mode bins dels 2 × 2, resulting in a del-size equivalent to that of the MDCT system. In general, standard procedures and phantoms were used to perform these assessments. RESULTS: The UHRCT MTF (10% MTF 4.1 lp/mm) is twice as high as that of the MDCT (10% MTF 1.9 lp/mm), which is comparable to the MTF in the NR mode (10% MTF 1.7 lp/mm). The width of the slice sensitivity profile in the SHR mode (FWHM 0.45 mm) is about 60% of that of the MDCT (FWHM 0.77 mm). Uniformity and CT numbers are within the expected range. Noise in the high-resolution modes has a higher magnitude and higher frequency components compared with MDCT. Low-contrast visibility is lower for the NR, HR and SHR modes compared with MDCT, but about a 14%, for NR, and 23%, for HR and SHR, dose increase gives the same results. CONCLUSIONS: HR and SHR mode scanning results in double the spatial resolution, with about a 23% increase in dose required to achieve the same low-contrast detectability. KEY POINTS: • Resolution on UHRCT is up to twice as high as for the tested MDCT. • With abdominal settings, UHRCT needs higher dose for the same low-contrast detectability as MDCT, but dose is still below achievable levels as defined by current diagnostic reference levels. • The UHRCT system used in normal-resolution mode yields comparable resolution and noise characteristics as the MDCT system.

Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233.

BACKGROUND: The rapid development and complexity of new x-ray computed tomography (CT) technologies and the need for evidence-based optimization of image quality with respect to radiation and contrast media dose call for an updated approach towards CT performance evaluation. AIMS: This report offers updated testing guidelines for testing CT systems with an enhanced focus on the operational performance including iterative reconstructions and automatic exposure control (AEC) techniques. MATERIALS AND METHODS: The report was developed based on a comprehensive review of best methods and practices in the scientific literature. The detailed methods include the assessment of 1) CT noise (magnitude, texture, nonuniformity, inhomogeneity), 2) resolution (task transfer function under varying conditions and its scalar reflections), 3) task-based performance (detectability, estimability), and 4) AEC performance (spatial, noise, and mA concordance of attenuation and exposure modulation). The methods include varying reconstruction and tube current modulation conditions, standardized testing protocols, and standardized quantities and metrology to facilitate tracking, benchmarking, and quantitative comparisons. RESULTS: The methods, implemented in cited publications, are robust to provide a representative reflection of CT system performance as used operationally in a clinical facility. The methods include recommendations for phantoms and phantom image analysis. DISCUSSION: In line with the current professional trajectory of the field toward quantitation and operational engagement, the stated methods offer quantitation that is more predictive of clinical performance than specification-based approaches. They can pave the way to approach performance testing of new CT systems not only in terms of acceptance testing (i.e., verifying a device meets predefined specifications), but also system commissioning (i.e., determining how the system can be used most effectively in clinical practice). CONCLUSION: We offer a set of common testing procedures that can be utilized towards the optimal clinical utilization of CT imaging devices, benchmarking across varying systems and times, and a basis to develop future performance-based criteria for CT imaging.

Battlefield tracheal intubation training using virtual simulation: a multi center operational assessment of video laryngoscope technology.

Airway management is an essential skill in providing care in trauma situations. The video laryngoscope is a tool which offers improvement in teaching airway management skills and in managing airways of trauma patients on the far forward battlefield. An Operational Assessment (OA) of videolaryngoscope technology for medical training and airway management was conducted by the Center for Advanced Technology and Telemedicine (at the University of Nebraska Medical Center, Omaha, NE) for the US Air Force Modernization Command to validate this technology in the provision of Out of OR airway management and airway management training in military simulation centers. The value for both the training and performance of intubations was highly rated and the majority of respondents indicated interest in having a video laryngoscope in their facility.

Intubation success rates and perceived user satisfaction using the video laryngoscope to train deploying far forward combat medical personnel.

Studies show the video laryngoscope enhances intubation training by facilitating visualization of airway anatomy. We examined the performance and training of military healthcare providers in a brief intubation training course which included both direct and indirect (video) laryngoscopy. This training format with the video laryngoscope improved airway visualization and intubation performance, promoting increased trainee confidence levels for successful intubation. Web-based training paired with hands-on instruction with the video laryngoscope should be considered as a model for military basic airway management training.

Emphysema: effect of reconstruction algorithm on CT imaging measures.

In the current study, the effects of reconstruction algorithms on quantitative measures derived from computed tomographic (CT) lung images were assessed in patients with emphysema. CT image data sets were reconstructed with a standard algorithm and alternative algorithm(s) for 42 subjects. Algorithms were grouped as overenhancing, sharp, standard, or smooth. Density mask and volume measurements from the alternative algorithm data sets were compared with standard algorithm data sets. The overenhancing category yielded an average shift of 9.4% (ie, a shift in average score from 35.5% to 44.9%); the sharp category, a shift of 2.4%; and the smooth category, a shift of -1.0%. Differences in total lung volume measurements were less than 1%. In conclusion, the CT reconstruction algorithm may strongly affect density mask results, especially for certain reconstruction algorithms.

An analysis of MCNP cross-sections and tally methods for low-energy photon emitters.

Monte Carlo calculations are frequently used to analyse a variety of radiological science applications using low-energy (10-1000 keV) photon sources. This study seeks to create a low-energy benchmark for the MCNP Monte Carlo code by simulating the absolute dose rate in water and the air-kerma rate for monoenergetic point sources with energies between 10 keV and 1 MeV. The analysis compares four cross-section datasets as well as the tally method for collision kerma versus absorbed dose. The total photon attenuation coefficient cross-section for low atomic number elements has changed significantly as cross-section data have changed between 1967 and 1989. Differences of up to 10% are observed in the photoelectric cross-section for water at 30 keV between the standard MCNP cross-section dataset (DLC-200) and the most recent XCOM/NIST tabulation. At 30 keV, the absolute dose rate in water at 1.0 cm from the source increases by 7.8% after replacing the DLC-200 photoelectric cross-sections for water with those from the XCOM/NIST tabulation. The differences in the absolute dose rate are analysed when calculated with either the MCNP absorbed dose tally or the collision kerma tally. Significant differences between the collision kerma tally and the absorbed dose tally can occur when using the DLC-200 attenuation coefficients in conjunction with a modern tabulation of mass energy-absorption coefficients.