Impact of scatter radiation on spectral quantification performance of first- and second-generation dual-layer spectral computed tomography.

OBJECTIVE: To assess the impact of scatter radiation on quantitative performance of first and second-generation dual-layer spectral computed tomography (DLCT) systems. METHOD: A phantom with two iodine inserts (1 and 2 mg/mL) configured to intentionally introduce high scattering conditions was scanned with a first- and second-generation DLCT. Collimation widths (maximum of 4 cm for first generation and 8 cm for second generation) and radiation dose levels were varied. To evaluate the performance of both systems, the mean CT numbers of virtual monoenergetic images (MonoEs) at different energies were calculated and compared to expected values. MonoEs at 50  versus 150 keV were plotted to assess material characterization of both DLCTs. Additionally, iodine concentrations were determined, plotted, and compared against expected values. For each experimental scenario, absolute errors were reported. RESULTS: An experimental setup, including a phantom design, was successfully implemented to simulate high scatter radiation imaging conditions. Both CT scanners illustrated high spectral accuracy for small collimation widths (1 and 2 cm). With increased collimation (4 cm), the second-generation DLCT outperformed the earlier DLCT system. Further, the spectral performance of the second-generation DLCT at an 8 cm collimation width was comparable to a 4 cm collimation on the first-generation DLCT. A comparison of the absolute errors between both systems at lower energy MonoEs illustrates that, for the same acquisition parameters, the second-generation DLCT generated results with decreased errors. Similarly, the maximum error in iodine quantification was less with second-generation DLCT (0.45  and 0.33 mg/mL for the first and second-generation DLCT, respectively). CONCLUSION: The implementation of a two-dimensional anti-scatter grid in the second-generation DLCT improves the spectral quantification performance. In the clinical routine, this improvement may enable additional clinical benefits, for example, in lung imaging.

Spectral performance evaluation of a second-generation spectral detector CT.

PURPOSE: The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities. METHODS: A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70 keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150 keV, and root mean square error (RMSE) for adipose and iron content was reported. RESULTS: Measured inserts exhibited quantitative accuracy across a wide range of MonoE levels. MonoE 70 keV images demonstrated reduced dependence compared to conventional images for phantom size (1 vs. 27 HU) and acquisition parameters, particularly tube voltage (4 vs. 37 HU). Iodine density quantification was successful with errors ranging from -0.58 to 0.44 mg/mL. Similarly, inserts with different amounts of adipose and iron were differentiated, and the small deviation in values within inserts corresponded to a RMSE of 3.49 ± 1.76% and 1.67 ± 0.84 mg/mL for adipose and iron content, respectively. CONCLUSION: The second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.

Consistency of spectral results in cardiac dual-source photon-counting CT.

We evaluate stability of spectral results at different heart rates, acquisition modes, and cardiac phases in first-generation clinical dual-source photon-counting CT (PCCT). A cardiac motion simulator with a coronary stenosis mimicking a 50% eccentric calcium plaque was scanned at five different heart rates (0, 60-100 bpm) with the three available cardiac scan modes (high pitch prospectively ECG-triggered spiral, prospectively ECG-triggered axial, retrospectively ECG-gated spiral). Subsequently, full width half max (FWHM) of the stenosis, Dice score (DSC) for the stenosed region, and eccentricity of the non-stenosed region were calculated for virtual monoenergetic images (VMI) at 50, 70, and 150 keV and iodine density maps at both diastole and systole. FWHM averaged differences of - 0.20, - 0.28, and - 0.15 mm relative to static FWHM at VMI 150 keV across acquisition parameters for high pitch prospectively ECG-triggered spiral, prospectively ECG-triggered axial, and retrospectively ECG-gated spiral scans, respectively. Additionally, there was no effect of heart rate and acquisition mode on FWHM at diastole (p-values < 0.001). DSC demonstrated similarity among parameters with standard deviations of 0.08, 0.09, 0.11, and 0.08 for VMI 50, 70, and 150 keV, and iodine density maps, respectively, with insignificant differences at diastole (p-values < 0.01). Similarly, eccentricity illustrated small differences across heart rate and acquisition mode for each spectral result. Consistency of spectral results at different heart rates and acquisition modes for different cardiac phase demonstrates the added benefit of spectral results from PCCT to dual-source CT to further increase confidence in quantification and advance cardiovascular diagnostics.

Reduction in Radiologist Interpretation Time of Serial CT and MR Imaging Findings with Deep Learning Identification of Relevant Priors, Series and Finding Locations.

RATIONALE AND OBJECTIVES: Finding comparison to relevant prior studies is a requisite component of the radiology workflow. The purpose of this study was to evaluate the impact of a deep learning tool simplifying this time-consuming task by automatically identifying and displaying the finding in relevant prior studies. MATERIALS AND METHODS: The algorithm pipeline used in this retrospective study, TimeLens (TL), is based on natural language processing and descriptor-based image-matching algorithms. The dataset used for testing comprised 3872 series of 246 radiology examinations from 75 patients (189 CTs, 95 MRIs). To ensure a comprehensive testing, five finding types frequently encountered in radiology practice were included: aortic aneurysm, intracranial aneurysm, kidney lesion, meningioma, and pulmonary nodule. After a standardized training session, nine radiologists from three university hospitals performed two reading sessions on a cloud-based evaluation platform resembling a standard RIS/PACS. The task was to measure the diameter of the finding-of-interest on two or more exams (a most recent and at least one prior exam): first without use of TL, and a second session at an interval of at least 21 days with the use of TL. All user actions were logged for each round, including time needed to measure the finding at all timepoints, number of mouse clicks, and mouse distance traveled. The effect of TL was evaluated in total, per finding type, per reader, per experience (resident vs. board-certified radiologist), and per modality. Mouse movement patterns were analyzed with heatmaps. To assess the effect of habituation to the cases, a third round of readings was performed without TL. RESULTS: Across scenarios, TL reduced the average time needed to assess a finding at all timepoints by 40.1% (107 vs. 65 seconds; p < 0.001). Largest accelerations were demonstrated for assessment of pulmonary nodules (-47.0%; p < 0.001). Less mouse clicks (-17.2%) were needed for finding evaluation with TL, and mouse distance traveled was reduced by 38.0%. Time needed to assess the findings increased from round 2 to round 3 (+27.6%; p < 0.001). Readers were able to measure a given finding in 94.4% of cases on the series initially proposed by TL as most relevant series for comparison. The heatmaps showed consistently simplified mouse movement patterns with TL. CONCLUSION: A deep learning tool significantly reduced both the amount of user interactions with the radiology image viewer and the time needed to assess findings of interest on cross-sectional imaging with relevant prior exams.

Three-dimensional printing of patient-specific computed tomography lung phantoms: a reader study.

In modern clinical decision-support algorithms, heterogeneity in image characteristics due to variations in imaging systems and protocols hinders the development of reproducible quantitative measures including for feature extraction pipelines. With the help of a reader study, we investigate the ability to provide consistent ground-truth targets by using patient-specific 3D-printed lung phantoms. PixelPrint was developed for 3D-printing lifelike computed tomography (CT) lung phantoms by directly translating clinical images into printer instructions that control density on a voxel-by-voxel basis. Data sets of three COVID-19 patients served as input for 3D-printing lung phantoms. Five radiologists rated patient and phantom images for imaging characteristics and diagnostic confidence in a blinded reader study. Effect sizes of evaluating phantom as opposed to patient images were assessed using linear mixed models. Finally, PixelPrint's production reproducibility was evaluated. Images of patients and phantoms had little variation in the estimated mean (0.03-0.29, using a 1-5 scale). When comparing phantom images to patient images, effect size analysis revealed that the difference was within one-third of the inter- and intrareader variabilities. High correspondence between the four phantoms created using the same patient images was demonstrated by PixelPrint's production repeatability tests, with greater similarity scores between high-dose acquisitions of the phantoms than between clinical-dose acquisitions of a single phantom. We demonstrated PixelPrint's ability to produce lifelike CT lung phantoms reliably. These phantoms have the potential to provide ground-truth targets for validating the generalizability of inference-based decision-support algorithms between different health centers and imaging protocols and for optimizing examination protocols with realistic patient-based phantoms. Classification: CT lung phantoms, reader study.

Phantom-based quantification of the spectral accuracy in dual-layer spectral CT for pediatric imaging at 100 kVp.

Background: To determine the spectral accuracy in detector-based dual-energy CT (DECT) at 100 kVp and wide (8 cm) collimation width for dose levels and object sizes relevant to pediatric imaging. Methods: A spectral CT phantom containing tissue-equivalent materials and iodine inserts of varying concentrations was scanned on the latest generation detector-based DECT system. Two 3D-printed extension rings were used to mimic varying pediatric patient sizes. Scans were performed at 100 and 120 kVp, 4 and 8 cm collimation widths, and progressively reduced radiation dose levels, down to 0.9 mGy CTDIvol. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were quantified and compared to their expected values for all acquisition settings and phantom sizes. Results: DECT scans at 100 kVp provided highly accurate spectral results; however, a size dependence was observed for iodine quantification. For the medium phantom configuration (15 cm diameter), measurement errors in iodine density, effective atomic number, and electron density (ED) were below 0.3 mg/mL, 0.2 and 1.8 %EDwater, respectively. The average accuracy was slightly different from scans at 120 kVp; however, not statistically significant for all configurations. Collimation width had no substantial impact. Spectral results were accurate and reliable for radiation exposures down to 0.9 mGy CTDIvol. Conclusions: Detector-based DECT at 100 kVp can provide on-demand or retrospective spectral information with high accuracy even at extremely low doses, thereby making it an attractive solution for pediatric imaging.

Mitral Annular Disjunction: Review of an Increasingly Recognized Mitral Valve Entity.

Mitral annular disjunction (MAD) refers to atrial displacement of the hinge point of the mitral valve annulus from the ventricular myocardium. MAD leads to paradoxical expansion of the annulus in systole and may often be associated with mitral valve prolapse (MVP), leaflet degeneration, myocardial and papillary muscle fibrosis, and, potentially, malignant cardiac arrhythmias. Patients with MAD and MVP may present similarly, and MAD is potentially the missing link in explaining why some patients with MVP experience adverse outcomes. Patients with a 5 mm or longer MAD distance have an elevated risk of malignant cardiac arrhythmia compared with those with a shorter MAD distance. Evaluation for MAD is an important component of cardiac imaging, especially in patients with MVP and unexplained cardiac arrhythmias. Cardiac MRI is an important diagnostic tool that aids in recognizing and quantifying MAD, MVP, and fibrosis in the papillary muscle and myocardium, which may predict and help improve outcomes following electrophysiology procedures and mitral valve surgery. This article reviews the history, pathophysiology, controversy, prevalence, clinical implications, and imaging considerations of MAD, focusing on cardiac MRI. Keywords: MR-Dynamic Contrast Enhanced, Cardiac, Mitral Valve, Mitral Annular Disjunction, Mitral Valve Prolapse, Floppy Mitral Valve, Cardiac MRI, Arrhythmia, Sudden Cardiac Death, Barlow Valve © RSNA, 2023.

PixelPrint: Three-dimensional printing of realistic patient-specific lung phantoms for CT imaging.

Phantoms are essential tools for assessing and verifying performance in computed tomography (CT). Realistic patient-based lung phantoms that accurately represent textures and densities are essential in developing and evaluating novel CT hardware and software. This study introduces PixelPrint, a 3D-printing solution to create patient-specific lung phantoms with accurate contrast and textures. PixelPrint converts patient images directly into printer instructions, where density is modeled as the ratio of filament to voxel volume to emulate local attenuation values. For evaluation of PixelPrint, phantoms based on four COVID-19 pneumonia patients were manufactured and scanned with the original (clinical) CT scanners and protocols. Density and geometrical accuracies between phantom and patient images were evaluated for various anatomical features in the lung, and a radiomic feature comparison was performed for mild, moderate, and severe COVID-19 pneumonia patient-based phantoms. Qualitatively, CT images of the patient-based phantoms closely resemble the original CT images, both in texture and contrast levels, with clearly visible vascular and parenchymal structures. Regions-of-interest (ROIs) comparing attenuation demonstrated differences below 15 HU. Manual size measurements performed by an experienced thoracic radiologist revealed a high degree of geometrical correlation between identical patient and phantom features, with differences smaller than the intrinsic spatial resolution of the images. Radiomic feature analysis revealed high correspondence, with correlations of 0.95-0.99 between patient and phantom images. Our study demonstrates the feasibility of 3D-printed patient-based lung phantoms with accurate geometry, texture, and contrast that will enable protocol optimization, CT research and development advancements, and generation of ground-truth datasets for radiomic evaluations.

First-generation clinical dual-source photon-counting CT: ultra-low-dose quantitative spectral imaging.

OBJECTIVE: Evaluation of image characteristics at ultra-low radiation dose levels of a first-generation dual-source photon-counting computed tomography (PCCT) compared to a dual-source dual-energy CT (DECT) scanner. METHODS: A multi-energy CT phantom was imaged with and without an extension ring on both scanners over a range of radiation dose levels (CTDIvol 0.4-15.0 mGy). Scans were performed in different modes of acquisition for PCCT with 120 kVp and DECT with 70/Sn150 kVp and 100/Sn150 kVp. Various tissue inserts were used to characterize the precision and repeatability of Hounsfield units (HUs) on virtual mono-energetic images between 40 and 190 keV. Image noise was additionally investigated at an ultra-low radiation dose to illustrate PCCT's ability to remove electronic background noise. RESULTS: Our results demonstrate the high precision of HU measurements for a wide range of inserts and radiation exposure levels with PCCT. We report high performance for both scanners across a wide range of radiation exposure levels, with PCCT outperforming at low exposures compared to DECT. PCCT scans at the lowest radiation exposures illustrate significant reduction in electronic background noise, with a mean percent reduction of 74% (p value ~ 10-8) compared to DECT 70/Sn150 kVp and 60% (p value ~ 10-6) compared to DECT 100/Sn150 kVp. CONCLUSIONS: This paper reports the first experiences with a clinical dual-source PCCT. PCCT provides reliable HUs without disruption from electronic background noise for a wide range of dose values. Diagnostic benefits are not only for quantification at an ultra-low dose but also for imaging of obese patients. KEY POINTS: PCCT scanners provide precise and reliable Hounsfield units at ultra-low dose levels. The influence of electronic background noise can be removed at ultra-low-dose acquisitions with PCCT. Both spectral platforms have high performance along a wide range of radiation exposure levels, with PCCT outperforming at low radiation exposures.

Three-dimensional printing of patient-specific lung phantoms for CT imaging: Emulating lung tissue with accurate attenuation profiles and textures.

PURPOSE: Phantoms are a basic tool for assessing and verifying performance in CT research and clinical practice. Patient-based realistic lung phantoms accurately representing textures and densities are essential in developing and evaluating novel CT hardware and software. This study introduces PixelPrint, a 3D printing solution to create patient-based lung phantoms with accurate attenuation profiles and textures. METHODS: PixelPrint, a software tool, was developed to convert patient digital imaging and communications in medicine (DICOM) images directly into FDM printer instructions (G-code). Density was modeled as the ratio of filament to voxel volume to emulate attenuation profiles for each voxel, with the filament ratio controlled through continuous modification of the printing speed. A calibration phantom was designed to determine the mapping between filament line width and Hounsfield units (HU) within the range of human lungs. For evaluation of PixelPrint, a phantom based on a single human lung slice was manufactured and scanned with the same CT scanner and protocol used for the patient scan. Density and geometrical accuracy between phantom and patient CT data were evaluated for various anatomical features in the lung. RESULTS: For the calibration phantom, measured mean HU show a very high level of linear correlation with respect to the utilized filament line widths, (r > 0.999). Qualitatively, the CT image of the patient-based phantom closely resembles the original CT image both in texture and contrast levels (from -800 to 0 HU), with clearly visible vascular and parenchymal structures. Regions of interest comparing attenuation illustrated differences below 15 HU. Manual size measurements performed by an experienced thoracic radiologist reveal a high degree of geometrical correlation of details between identical patient and phantom features, with differences smaller than the intrinsic spatial resolution of the scans. CONCLUSION: The present study demonstrates the feasibility of 3D-printed patient-based lung phantoms with accurate organ geometry, image texture, and attenuation profiles. PixelPrint will enable applications in the research and development of CT technology, including further development in radiomics.

Dual-source photon-counting CT: consistency in spectral results at different acquisition modes and heart rates.

Cardiac CT is a useful tool for cardiovascular diagnostics that offers different acquisition modes, each with its advantages. The development of direct converting detector technology has resulted in the clinical translation of dual-source photon-counting CT. This takes advantage of the improved image quality at high heart rates from dual-source CT while making available spectral results for more precise material characterization and quantification. To evaluate the stability of spectral results among different acquisition modes and heart rates, a cardiac motion phantom with a rod mimicking a 50% coronary stenosis was scanned with a dual-source photon-counting CT in three different acquisition modes (retrospective dual-source spiral, prospective dual-source step-and-shoot, dual-source flash spiral) and at different heart rates (60, 80, 100 bpm). Dice scores of stenosed regions relative to a static scan, eccentricity of non-stenosed regions, full width half max, and normalized area under the curve of line profiles were calculated for iodine density maps, and virtual mono-energetic images at 40 and 70 keV. Dice scores and eccentricity were consistent and not significantly affected by acquisition mode or heart rate for spectral results. Full width half max and normalized area under the curve similarly illustrated minor differences between acquisition modes and heart rates. The consistency in these metrics demonstrate preserved image structure and allows for the use of spectral results with high confidence. Dual-source photon-counting CT will enable cardiovascular diagnostics with better material characterization and differentiation.

Risks and Options With Gadolinium-Based Contrast Agents in Patients With CKD: A Review.

Gadolinium-based contrast agents (GBCAs) improve the diagnostic capabilities of magnetic resonance imaging. Although initially believed to be without major adverse effects, GBCA use in patients with severe chronic kidney disease (CKD) was demonstrated to cause nephrogenic systemic fibrosis (NSF). Restrictive policies of GBCA use in CKD and selective use of GBCAs that bind free gadolinium more strongly have resulted in the virtual elimination of NSF cases. Contemporary studies of the use of GBCAs with high binding affinity for free gadolinium in severe CKD demonstrate an absence of NSF. Despite these observations and the limitations of contemporary studies, physicians remain concerned about GBCA use in severe CKD. Concerns of GBCA use in severe CKD are magnified by recent observations demonstrating gadolinium deposition in brain and a possible systemic syndrome attributed to GBCAs. Radiologic advances have resulted in several new imaging modalities that can be used in the severe CKD population and that do not require GBCA administration. In this article, we critically review GBCA use in patients with severe CKD and provide recommendations regarding GBCA use in this population.

Surveillance Imaging following Endovascular Aneurysm Repair: State of the Art.

Endovascular aneurysmal repair (EVAR) has become a prominent modality for the treatment of abdominal aortic aneurysm. Surveillance imaging is important for the detection of device-related complications, which include endoleak, structural abnormalities, and infection. Currently used modalities include ultrasound, X-ray, computed tomography, magnetic resonance imaging, and angiography. Understanding the advantages and drawbacks of each modality, as well available guidelines, can guide selection of the appropriate technique for individual patients. We review complications following EVAR and advances in surveillance imaging modalities.

The Controversy of Contrast-Induced Nephropathy With Intravenous Contrast: What Is the Risk?

Contrast-induced nephropathy (CIN) has long been observed in both experimental and clinical studies. However, recent observational studies have questioned the prevalence and severity of CIN following intravenous contrast exposure. Initial studies of acute kidney injury following intravenous contrast were limited by the absence of control groups or contained control groups that did not adjust for additional acute kidney injury risk factors, including prevalent chronic kidney disease, as well as accepted prophylactic strategies. More contemporary use of propensity score-adjusted models have attempted to minimize the risk for selection bias, although bias cannot be completely eliminated without a prospective randomized trial. Based on existing data, we recommend the following CIN risk classification: patients with estimated glomerular filtration rates (eGFRs) ≥ 45mL/min/1.73m2 are at negligible risk for CIN, while patients with eGFRs<30mL/min/1.73m2 are at high risk for CIN. Patients with eGFRs between 30 and 44mL/min/1.73m2 are at an intermediate risk for CIN unless diabetes mellitus is present, which would further increase the risk. In all patients at any increased risk for CIN, the risk for CIN needs to be balanced by the risk of not performing an intravenous contrast-enhanced study.

Effect of Gold Nanoparticle Size on Their Properties as Contrast Agents for Computed Tomography.

Computed tomography (CT) is one of the most commonly used clinical imaging modalities. There have recently been many reports of novel contrast agents for CT imaging. In particular, the development of gold nanoparticles (AuNP) as CT contrast agents is a topic of intense interest. AuNP have favorable characteristics for this application such as high payloads of contrast generating material, strong X-ray attenuation, excellent biocompatibility, tailorable surface chemistry, and tunable sizes and shapes. However, there have been conflicting reports on the role of AuNP size on their contrast generation for CT. We therefore sought to extensively investigate the AuNP size-CT contrast relationship. In order to do this, we synthesized AuNP with sizes ranging from 4 to 152 nm and capped them with 5 kDa m-PEG. The contrast generation of AuNP of different sizes was investigated with three clinical CT, a spectral photon counting CT (SPCCT) and two micro CT systems. X-ray attenuation was quantified as attenuation rate in Hounsfield units per unit concentration (HU/mM). No statistically significant difference in CT contrast generation was found among different AuNP sizes via phantom imaging with any of the systems tested. Furthermore, in vivo imaging was performed in mice to provide insight into the effect of AuNP size on animal biodistribution at CT dose levels, which has not previously been explored. Both in vivo imaging and ex vivo analysis with inductively coupled plasma optical emission spectroscopy (ICP-OES) indicated that AuNP that are 15 nm or smaller have long blood circulation times, while larger AuNP accumulated in the liver and spleen more rapidly. Therefore, while we observed no AuNP size effect on CT contrast generation, there is a significant effect of size on AuNP diagnostic utility.

Reduced Order Models for Transstenotic Pressure Drop in the Coronary Arteries.

The efficacy of reduced order modeling for transstenotic pressure drop in the coronary arteries is presented. Coronary artery disease is a leading cause of death worldwide and the computation of pressure drop in the coronary arteries has become a standard for evaluating the functional significance of a coronary stenosis. Comprehensive models typically employ three-dimensional (3D) computational fluid dynamics (CFD) to simulate coronary blood flow in order to compute transstenotic pressure drop at the arterial stenosis. In this study, we evaluate the capability of different hydrodynamic models to compute transstenotic pressure drop. Models range from algebraic formulae to one-dimensional (1D), two-dimensional (2D), and 3D time-dependent CFD simulations. Although several algebraic pressure-drop formulae have been proposed in the literature, these models were found to exhibit wide variation in predictions. Nonetheless, we demonstrate an algebraic formula that provides consistent predictions with 3D CFD results for various changes in stenosis severity, morphology, location, and flow rate. The accounting of viscous dissipation and flow separation were found to be significant contributions to accurate reduce order modeling of transstenotic coronary hemodynamics.