Tungsten-Based Contrast Agent for Photon-Counting Detector CT Angiography in Calcified Coronaries: Comparison to Iodine in a Cardiovascular Phantom.

OBJECTIVES: Calcified plaques induce blooming artifacts in coronary computed tomography angiography (CCTA) potentially leading to inaccurate stenosis evaluation. Tungsten represents a high atomic number, experimental contrast agent with different physical properties than iodine. We explored the potential of a tungsten-based contrast agent for photon-counting detector (PCD) CCTA in heavily calcified coronary vessels. MATERIALS AND METHODS: A cardiovascular phantom exhibiting coronaries with calcified plaques was imaged on a first-generation dual-source PCD-CT. The coronaries with 3 different calcified plaques were filled with iodine and tungsten contrast media solutions equating to iodine and tungsten delivery rates (IDR and TDR) of 0.3, 0.5, 0.7, 1.0, 1.5, 2.0, 2.5, and 3.0 g/s, respectively. Electrocardiogram-triggered sequential acquisitions were performed in the spectral mode (QuantumPlus). Virtual monoenergetic images (VMIs) were reconstructed from 40 to 190 keV in 1 keV increments. Blooming artifacts and percentage error stenoses from calcified plaques were quantified, and attenuation characteristics of both contrast media were recorded. RESULTS: Blooming artifacts from calcified plaques were most pronounced at 40 keV (78%) and least pronounced at 190 keV (58%). Similarly, percentage error stenoses were highest at 40 keV (48%) and lowest at 190 keV (2%), respectively. Attenuation of iodine decreased monotonically in VMIs from low to high keV, with the strongest decrease from 40 keV to 100 keV (IDR of 2.5 g/s: 1279 HU at 40 keV, 187 HU at 100 kV, and 35 HU at 190 keV). The attenuation of tungsten, on the other hand, increased monotonically as a function of VMI energy, with the strongest increase between 40 and 100 keV (TDR of 2.5 g/s: 202 HU at 40 keV, 661 HU at 100 kV, and 717 HU at 190 keV). For each keV level, the relationship between attenuation and IDR/TDR could be described by linear regressions (R2 ≥ 0.88, P < 0.001). Specifically, attenuation increased linearly when increasing the delivery rate irrespective of keV level or contrast medium. Iodine exhibited the highest relative increase in attenuation values at lower keV levels when increasing the IDR. Conversely, for tungsten, the greatest relative increase in attenuation values occurred at higher keV levels when increasing the TDR. When high keV imaging is desirable to reduce blooming artifacts from calcified plaques, IDR has to be increased at higher keV levels to maintain diagnostic vessel attenuation (ie, 300 HU), whereas for tungsten, TDR can be kept constant or can be even reduced at high keV energy levels. CONCLUSIONS: Tungsten's attenuation characteristics in relation to VMI energy levels are reversed to those of iodine, with tungsten exhibiting high attenuation values at high keV levels and vice versa. Thus, tungsten shows promise for high keV imaging CCTA with PCD-CT as-in distinction to iodine-both high vessel attenuation and low blooming artifacts from calcified plaques can be achieved.

Virtual monoenergetic imaging in photon-counting CT of the head and neck.

PURPOSE: Advantages of virtual monoenergetic images (VMI) have been reported for dual energy CT of the head and neck, and more recently VMIs derived from photon-counting (PCCT) angiography of the head and neck. We report image quality metrics of VMI in a PCCT angiography dataset, expanding the anatomical regions evaluated and extending observer-based qualitative methods further than previously reported. METHODS: In a prospective study, asymptomatic subjects underwent contrast enhanced PCCT of the head and neck using an investigational scanner. Image sets of low, high, and full spectrum (Threshold-1) energies; linear mix of low and high energies (Mix); and 23 VMIs (40-150 keV, 5 keV increments) were generated. In 8 anatomical locations, SNR and radiologists' preferences for VMI energy levels were measured using a forced-choice rank method (4 observers) and ratings of image quality using visual grading characteristic (VGC) analysis (2 observers) comparing VMI to Mix and Threshold-1 images. RESULTS: Fifteen subjects were included (7 men, 8 women, mean 57 years, range 46-75). Among all VMIs, SNRs varied by anatomic location. The highest SNRs were observed in VMIs. Radiologists preferred 50-60 keV VMIs for vascular structures and 75-85 keV for all other structures. Cumulative ratings of image quality averaged across all locations were higher for VMIs with areas under the curve of VMI vs Mix and VMI vs Threshold-1 of 0.67 and 0.68 for the first reader and 0.72 and 0.76 for the second, respectively. CONCLUSION: Preferred keV level and quality ratings of VMI compared to mixed and Threshold-1 images varied by anatomical location.

Reducing the risk of hallucinations with interpretable deep learning models for low-dose CT denoising: comparative performance analysis.

Objective.Reducing CT radiation dose is an often proposed measure to enhance patient safety, which, however results in increased image noise, translating into degradation of clinical image quality. Several deep learning methods have been proposed for low-dose CT (LDCT) denoising. The high risks posed by possible hallucinations in clinical images necessitate methods which aid the interpretation of deep learning networks. In this study, we aim to use qualitative reader studies and quantitative radiomics studies to assess the perceived quality, signal preservation and statistical feature preservation of LDCT volumes denoised by deep learning. We aim to compare interpretable deep learning methods with classical deep neural networks in clinical denoising performance.Approach.We conducted an image quality analysis study to assess the image quality of the denoised volumes based on four criteria to assess the perceived image quality. We subsequently conduct a lesion detection/segmentation study to assess the impact of denoising on signal detectability. Finally, a radiomic analysis study was performed to observe the quantitative and statistical similarity of the denoised images to standard dose CT (SDCT) images.Main results.The use of specific deep learning based algorithms generate denoised volumes which are qualitatively inferior to SDCT volumes(p< 0.05). Contrary to previous literature, denoising the volumes did not reduce the accuracy of the segmentation (p> 0.05). The denoised volumes, in most cases, generated radiomics features which were statistically similar to those generated from SDCT volumes (p> 0.05).Significance.Our results show that the denoised volumes have a lower perceived quality than SDCT volumes. Noise and denoising do not significantly affect detectability of the abdominal lesions. Denoised volumes also contain statistically identical features to SDCT volumes.

Patient-specific post-trigger delay in coronary CT angiography: A prospective study comparing with fixed delay.

OBJECTIVES: To validate the peak enhancement timing of a patient-specific post-trigger delay (PTD) in Coronary CT angiography (CCTA) and compare its image quality against a fixed PTD. METHODS: In this prospective study, 204 consecutive participants were randomly divided into two groups to perform CCTA in bolus tracking with either a fixed 5-second PTD (Group A) or a patient-specific PTD (Group B). Test bolus was also performed in Group B to determine the reference peak enhancement timing. One reader evaluated objective image quality, while two readers rated subjective image quality. The predicted PTD was validated through correlation and agreement analysis with the reference measurement. Objective image quality was compared between groups via two-sample t-test and linear regression, while the subjective ratings were compared with chi-square analysis. RESULTS: The two groups each had 102 participants with comparable characteristics (52.9 ± 11.3 versus 52.1 ± 11.3 years of age, and 53 versus 52 males). The scan timing from patient-specific PTD demonstrated strong correlation (R = 0.77) and consistency (ICC = 0.618) with the reference peak timing. Both readers rated better subjective image quality for the Group B (p < 0.001). The mean vessel enhancement was significantly higher in Group B in all coronary vessels (all p < 0.05). After adjusting for the participant variation, the patient-specific PTD strategy was associated with an average of 33.5 HU higher enhancement compared to the fixed PTD. CONCLUSIONS: Patient-specific delay could achieve reliable scan timing, optimize vessel opacification and obtain better image quality in CCTA.

New Contrast Media for K-Edge Imaging With Photon-Counting Detector CT.

ABSTRACT: The recent technological developments in photon-counting detector computed tomography (PCD-CT) and the introduction of the first commercially available clinical PCD-CT unit open up new exciting opportunities for contrast media research. With PCD-CT, the efficacy of available iodine-based contrast media improves, allowing for a reduction of iodine dosage or, on the other hand, an improvement of image quality in low contrast indications. Virtual monoenergetic image reconstructions are routinely available and enable the virtual monoenergetic image energy to be adapted to the diagnostic task.A key property of PCD-CT is the ability of spectral separation in combination with improved material decomposition. Thus, the discrimination of contrast media from intrinsic or pathological tissues and the discrimination of 2 or more contrasting elements that characterize different tissues are attractive fields for contrast media research. For these approaches, K-edge imaging in combination with high atomic number elements such as the lanthanides, tungsten, tantalum, or bismuth plays a central role.The purpose of this article is to present an overview of innovative contrast media concepts that use high atomic number elements. The emphasis is on improving contrast enhancement for cardiovascular plaque imaging, stent visualization, and exploring new approaches using 2 contrasting elements. Along with the published research, new experimental findings with a contrast medium that incorporates tungsten are included.Both the literature review and the new experimental data demonstrate the great potential and feasibility for new contrast media to significantly increase diagnostic performance and to enable new clinical fields and indications in combination with PCD-CT.

Radiation Dose Reduction in Contrast-Enhanced Abdominal CT: Comparison of Photon-Counting Detector CT with 2nd Generation Dual-Source Dual-Energy CT in an oncologic cohort.

RATIONAL AND OBJECTIVES: Comparison of radiation dose and image quality in routine abdominal and pelvic contrast-enhanced computed tomography (CECT) between a photon-counting detector CT (PCD-CT) and a dual energy dual source CT (DSCT). MATERIALS AND METHODS: 70 oncologic patients (mean age 66 ± 12 years, 29 females) were prospectively enrolled between November 2021 and February 2022. Abdominal CECT were clinically indicated and performed first on a 2nd-generation DSCT and at follow-up on a 1st-generation dual-source PCD-CT. The same contrast media (Imeron 350, Bracco imaging) and pump protocol was used for both scans. For both scanners, polychromatic images were reconstructed with 3mm slice thickness and comparable kernel (I30f[DSCT] and Br40f[PCD-CT]); for PCD-CT data from all counted events above the lowest energy threshold at 20 keV ("T3D") were used. Results were compared in terms of radiation dose metrics of CT dose index (CTDIvol), dose length product (DLP) and size-specific dose estimation (SSDE), objective and subjective measurements of image quality were scored by two emergency radiologists including lesion conspicuity. RESULTS: Median time interval between the scans was 4 months (IQR: 3-6). CNRvessel and SNRvessel of T3D reconstructions from PCD-CT were significantly higher than those of DSCT (all, p < 0.05). Qualitative image noise analysis from PCD-CT and DSCT yielded a mean of 4 each. Lesion conspicuity was rated significantly higher in PCD-CT (Q3 strength) compared to DSCT images. CTDI, DLP and SSDE mean values for PCD-CT and DSCT were 7.98 ± 2.56 mGy vs. 14.11 ± 2.92 mGy, 393.13 ± 153.55 mGy*cm vs. 693.61 ± 185.76 mGy*cm and 9.98 ± 2.41 vs. 14.63 ± 1.63, respectively, translating to a dose reduction of around 32% (SSDE). CONCLUSION: PCD-CT enables oncologic abdominal CT with a significantly reduced dose while keeping image quality similar to 2nd-generation DSCT.

Myeloma bone disease imaging on a 1st-generation clinical photon-counting detector CT vs. 2nd-generation dual-source dual-energy CT.

OBJECTIVE: Subjective and objective image quality comparison of bone microstructure and disease-related abnormalities in multiple myeloma patients using a 1st-generation dual-source photon-counting detector CT(DS-PCD-CT) and a 2nd-generation dual-source dual-energy (energy-integrating detector) CT (DS-EID-CT). METHODS: Fifty multiple myeloma patients (mean age 67.7 ± 10.9 years,16 females) were prospectively enrolled. Unenhanced whole-body CTs were clinically indicated and performed on DS-EID-CT and DS-PCD-CT (median time difference: 12 months). DS-PCD-CT was performed in Quantumplus UHR mode and DS-EID-CT was performed using dual-energy mode. DS-PCD-CT kernel was set at Br64 with Quantum iterative reconstruction strength Q1; for DS-EID-CT a comparable I70f kernel with SAFIRE iterative reconstruction strength 1 was used. Two independent radiologists assessed image quality subjectively using a 5-point Likert scale considering delineation and sharpness of trabecular bone and lytic bone lesions in the spine and pelvic bones. Additionally, ImageJ was used for quantification of bony septa inside the cancellous bone and through or the edges of osteolysis. RESULTS: Overall quality as well as detectability and sharpness in the delineation of lytic bone lesions were superior for DS-PCD-CT compared with DS-EID-CT (p < 0.0001). The inter-reader agreement for subjective image quality readings showed excellent consistency(α = 94.2-98.8). CTDI and DLP mean values for DS-PCD-CT and DS-EID-CT were 1107.4 ± 247.6 mGy*cm and 8.2 ± 1.8 mGy vs. 1344.3 ± 204.6 mGy*cm and 10.1 ± 1.9 mGy. The quantitative metric for bone microstructure in the femoral head showed significantly better visualization of trabeculae in DS-PCD-CT compared with DS-EID-CT (p < 0.0001). Quantitative analyses of edge sharpness of osteolysis showed significant steeper edges for DS-PCD-CT (p < 0.0001). CONCLUSION: DS-PCD-CT significantly improves spatial resolution of bony microstructure and lytic bone lesions compared to DS-EID-CT. KEY POINTS: • Application of photon-counting detector CT is superior to dual-source dual-energy integrating detector in clinical workup of multiple myeloma patients. • Compared to energy integrating detectors, photon-counting detectors significantly increase the spatial resolution of bone microstructure including disease-related lytic bone lesions in patients with multiple myeloma.

Image Quality and Radiation Dose of Contrast-Enhanced Chest-CT Acquired on a Clinical Photon-Counting Detector CT vs. Second-Generation Dual-Source CT in an Oncologic Cohort: Preliminary Results.

Our aim was to compare the image quality and patient dose of contrast-enhanced oncologic chest-CT of a first-generation photon-counting detector (PCD-CT) and a second-generation dual-source dual-energy CT (DSCT). For this reason, one hundred consecutive oncologic patients (63 male, 65 ± 11 years, BMI: 16−42 kg/m2) were prospectively enrolled and evaluated. Clinically indicated contrast-enhanced chest-CT were obtained with PCD-CT and compared to previously obtained chest-DSCT in the same individuals. The median time interval between the scans was three months. The same contrast media protocol was used for both scans. PCD-CT was performed in QuantumPlus mode (obtaining full spectral information) at 120 kVp. DSCT was performed using 100 kV for Tube A and 140 kV for Tube B. "T3D" PCD-CT images were evaluated, which emulate conventional 120 keV polychromatic images. For DSCT, the convolution algorithm was set at I31f with class 1 iterative reconstruction, whereas comparable Br40 kernel and iterative reconstruction strengths (Q1 and Q3) were applied for PCD-CT. Two radiologists assessed image quality using a five-point Likert scale and performed measurements of vessels and lung parenchyma for signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and in the case of pulmonary metastases tumor-to-lung parenchyma contrast ratio. PCD-CT CNRvessel was significantly higher than DSCT CNRvessel (all, p < 0.05). Readers rated image contrast of mediastinum, vessels, and lung parenchyma significantly higher in PCD-CT than DSCT images (p < 0.001). Q3 PCD-CT CNRlung_parenchyma was significantly higher than DSCT CNRlung_parenchyma and Q1 PCD-CT CNRlung_parenchyma (p < 0.01). The tumor-to-lung parenchyma contrast ratio was significantly higher on PCD-CT than DSCT images (0.08 ± 0.04 vs. 0.03 ± 0.02, p < 0.001). CTDI, DLP, SSDE mean values for PCD-CT and DSCT were 4.17 ± 1.29 mGy vs. 7.21 ± 0.49 mGy, 151.01 ± 48.56 mGy * cm vs. 288.64 ± 31.17 mGy * cm and 4.23 ± 0.97 vs. 7.48 ± 1.09, respectively. PCD-CT enables oncologic chest-CT with a significantly reduced dose while maintaining image quality similar to a second-generation DSCT for comparable protocol settings.

Image quality and dose exposure of contrast-enhanced abdominal CT on a 1st generation clinical dual-source photon-counting detector CT in obese patients vs. a 2nd generation dual-source dual energy integrating detector CT.

PURPOSE: To compare the radiation dose as well as the image quality of contrast-enhanced abdominal 1st-generation Photon-Counting Detector CT (PCD-CT) to a 2nd-generation Dual-Source Dual-Energy-Integrating-Detector CT (DSCT) in obese patients. METHOD: 51 overweight (BMI ≥ 25 kgm2) patients (median age: 67.00 years; IQR: 59.00-73.00, median BMI 32.15 kgm2; IQR: 28.70-35.76) who underwent clinically indicated, contrast-enhanced abdominal-CT in portal-venous phase on both 2nd-generation DSCT and on a commercially available 1st-generation PCD-CT were prospectively included the degree of obesity was defined by BMI-calculation (overweight, obesity grade I/30-34.9; obesity grade II/35-39.9; obesity grade III > 40) and by the absolute weight value. The same contrast media and pump protocol were used for both scans. PCD-CT was performed in Quantumplus mode at 120 kVp whereas DSCT used also 120 kVp in single energy mode. Comparable convolution algorithm between DSCT and PCD-CT were set. For both scanners, polychromatic images were reconstructed; for PCD-CT data from all counted events above the lowest energy threshold at 20 keV (termed T3D) were used. Two independent radiologists assessed subjective image quality using a 5-point Likert-scale and quantified the contrast-to-noise ratio of parenchymatous organs and vascular structures. RESULTS: Median time interval between the scans was 4 months (IQR 3-7 months). BMI was classified overweight (n = 18, 35.3%), grade I (n = 19, 37.3%), II (n = 9, 17.6%), III (n = 5, 9.8%). Mean CNRrenal_cortex (12.35 ± 3.77 vs. 14.16 ± 3.55) as well as median CNRvessels (9.88 vs. 12.40) and median CNRpancreas (2.81 vs. 4.04) of PCD-CT were significantly higher than those at DSCT (p < 0.05). The inter-reader agreement for all subjective image quality readings was moderate to substantial. Both radiologists independently rated the image quality higher for PCD-CT data sets (p < 0.05). Median CTDI and DLP values for PCD-CT and DSCT were 12.00 mGy (IQR: 10.20-13.50 mGy) vs. 16.05 mGy (IQR: 14.81-17.98) and 608 mGy * cm (IQR: 521.00-748.00 mGy * cm) vs. and 821.90 mGy * cm (IQR: 709.30-954.00 mGy * cm) (p < 0.001). CONCLUSION: Significant dose reduction by similar or even improved image quality was obtained with abdominal contrast-enhanced CT using PCD-CT in obese patients as compared to 2nd-generation DSCT.

Limited parameter denoising for low-dose X-ray computed tomography using deep reinforcement learning.

BACKGROUND: The use of deep learning has successfully solved several problems in the field of medical imaging. Deep learning has been applied to the CT denoising problem successfully. However, the use of deep learning requires large amounts of data to train deep convolutional networks (CNNs). Moreover, due to the large parameter count, such deep CNNs may cause unexpected results. PURPOSE: In this study, we introduce a novel CT denoising framework, which has interpretable behavior and provides useful results with limited data. METHODS: We employ bilateral filtering in both the projection and volume domains to remove noise. To account for nonstationary noise, we tune the σ parameters of the volume for every projection view and every volume pixel. The tuning is carried out by two deep CNNs. Due to the impracticality of labeling, the two-deep CNNs are trained via a Deep-Q reinforcement learning task. The reward for the task is generated by using a custom reward function represented by a neural network. Our experiments were carried out on abdominal scans for the Mayo Clinic the cancer imaging archive (TCIA) dataset and the American association of physicists in medicine (AAPM) Low Dose CT Grand Challenge. RESULTS: Our denoising framework has excellent denoising performance increasing the peak signal to noise ratio (PSNR) from 28.53 to 28.93 and increasing the structural similarity index (SSIM) from 0.8952 to 0.9204. We outperform several state-of-the-art deep CNNs, which have several orders of magnitude higher number of parameters (p-value [PSNR] = 0.000, p-value [SSIM] = 0.000). Our method does not introduce any blurring, which is introduced by mean squared error (MSE) loss-based methods, or any deep learning artifacts, which are introduced by wasserstein generative adversarial network (WGAN)-based models. Our ablation studies show that parameter tuning and using our reward network results in the best possible results. CONCLUSIONS: We present a novel CT denoising framework, which focuses on interpretability to deliver good denoising performance, especially with limited data. Our method outperforms state-of-the-art deep neural networks. Future work will be focused on accelerating our method and generalizing it to different geometries and body parts.

Optimize scan timing in abdominal multiphase CT: Bolus tracking with an individualized post-trigger delay.

PURPOSE: To conduct a head-to-head comparison in terms of image quality and diagnostic confidence between an individualized post-trigger delay and a conventional fixed post-trigger delay in bolus tracking abdominal multiphase CT. METHODS AND MATERIALS: Abdominal multiphase CT was performed in 104 patients with either of the two bolus tracking strategies: an individualized post-trigger delay (group A) and fixed post-trigger delay of 11 s (group B). All CT scan parameters and contrast media protocol parameters were consistent between the two groups. Quantitative parameters (organs and blood vessels enhancement, image noise, signal-to-noise ratios [SNRs] and contrast-to-noise ratios [CNRs]) and qualitative visual parameters (overall image quality and diagnostic confidence) were compared. Quantitative and qualitative image quality for the two groups were compared using the Mann-Whitney U and independent sample t test. Degrees of agreement between two radiologists were evaluated using the Kappa analysis. RESULTS: In the arterial phase (AP), images of group A provided higher attenuation (P ≤ 0.001). Although SNRs of liver, pancreas and aorta were similar in AP between the two groups, CNRs of liver, pancreas and portal vein in group A were significantly higher than those in group B (all P values ≤ 0.002). The overall subjective image quality and diagnostic confidence between the two groups were similar (P = 0.809; P = 0.768). CONCLUSION: Compared to a fixed post-trigger delay using bolus tracking, application of an individualized post-trigger delay can optimize the objective image quality in arterial phase without compromising diagnostic quality in abdominal multiphase CT.

Optimization of contrast material administration for coronary CT angiography using a software-based test-bolus evaluation algorithm.

OBJECTIVES: To evaluate the benefit of a prototype circulation time-based test bolus evaluation algorithm for the individualized optimal timing of contrast media (CM) delivery in patients undergoing coronary CT angiography (CCTA). METHODS: Thirty-two patients (62 ± 16 years) underwent CCTA using a prototype bolus evaluation tool to determine the optimal time-delay for CM administration. Contrast attenuation, signal-to-noise ratio (SNR), objective, and subjective image quality were evaluated by two independent radiologists. Results were compared to a control cohort (matched for age, sex, body mass index, and tube voltage) of patients who underwent CCTA using the generic test bolus peak attenuation +4 s protocol as scan delay. RESULTS: In the study group, the mean time delay to CCTA acquisition was significantly longer (26.0 ± 2.9 s) compared to the control group (23.1 ± 3.5 s; p < 0.01). In the study group, SNR improvement was seen in the right coronary artery (17.5 vs 13; p = 0.028), the left main (15.3 vs 12.3; p = 0.027), and the left anterior descending artery (18.5 vs 14.1; p = 0.048). Subjective image quality was rated higher in the study group (4.75 ± 0.7 vs 3.64 ± 0.5; p < 0.001). CONCLUSIONS: The prototype test bolus evaluation algorithm provided a reliable patient-specific scan delay for CCTA that ensured homogenous vascular attenuation, improvement in objective and subjective image quality, and avoidance of beam hardening artifacts. ADVANCES IN KNOWLEDGE: The prototype contrast bolus evaluation and optimization tool estimated circulation time-based time-delay improves the overall quality of CCTA.

Photon-Counting Multienergy Computed Tomography With Spectrally Optimized Contrast Media for Plaque Removal and Stenosis Assessment.

PURPOSE: The aim of this study was to systematically evaluate the potential to combine investigational contrast media with spectrally optimized energy-thresholding of photon-counting detector computed tomography (PCCT) for subtraction of calcified plaques in a coronary artery stenosis phantom. METHODS: A small vessel phantom containing 3 fillable tubes (diameter, 3 mm each) with calcified plaques was placed into an anthropomorphic chest phantom. The plaques had incremental thicknesses ranging from 0.3 to 2.7 mm, simulating vessel stenoses ranging from 10% to 90% of the lumen diameter. The phantom was filled with 5 different investigational contrast media (iodine, bismuth, hafnium, holmium, and tungsten) at equal mass concentrations (15 mg/mL) and was imaged on a prototype PCCT at 140 kVp using optimized, contrast media-dependent energy thresholds. Contrast maps (CMs) were reconstructed for each contrast medium by applying a linear 2-material decomposition algorithm. Image noise magnitude and noise texture of CM were compared among the contrast media using the noise power spectrum. Two blinded readers independently rated the vessel lumen visualization on short-axis and the overall subjective image quality on long-axis CM relative to iodine as the reference standard. Four readers determined the highest degree of stenosis that could be assessed with high diagnostic confidence on long-axis CM. RESULTS: Average image noise on CM was lower for tungsten (49 HU) and hafnium (62 HU) and higher for bismuth (81 HU) and holmium (165 HU) compared with iodine (78 HU). Noise texture of CM was similar among the contrast media. Interreader agreement for vessel lumen visualization on short-axis CM ranged from moderate to excellent (k = 0.567-0.814). Compared with iodine, lumen visualization of each reader was improved using tungsten (P < 0.001 for both readers), similar to improved using hafnium (P = 0.008, P = 0.29), similar using bismuth (P = 0.38, P = 0.69), and decreased using holmium (both, P < 0.001). Overall subjective image quality was similar for holmium and superior for tungsten, hafnium, and bismuth as compared with iodine. Higher-degree stenoses were evaluable with high confidence using tungsten (mean, 70%; interquartile range, 70%-70%), bismuth (70%; 60%-70%), and hafnium (75%; 70%-80%) compared with iodine (50%; 50%-60%) and holmium (50%; 50%-60%). CONCLUSIONS: Spectral optimization in PCCT combined with investigational contrast media can improve calcium subtraction and stenosis assessment in small vessels. Contrast maps of tungsten and, to a lesser extent, hafnium as contrast media yielded superior image noise properties and improved vessel lumen visualization, along with a higher subjective image quality compared with the reference standard iodine.

Computed Tomography Angiography of the Aorta-Optimization of Automatic Tube Voltage Selection Settings to Reduce Radiation Dose or Contrast Medium in a Prospective Randomized Trial.

OBJECTIVES: The aim of this study was to compare the image quality of low-kV protocols with optimized automatic tube voltage selection (ATVS) settings to reduce either radiation dose or contrast medium (CM) with that of a reference protocol for computed tomography angiography (CTA) of the thoracoabdominal aorta. MATERIALS AND METHODS: In this institutional review board-approved, single-center, prospective randomized controlled trial, 126 patients receiving CTA of the aorta were allocated to one of three computed tomography protocols: (A) reference protocol at 120 kVp and standard weight-adapted CM dose; (B) protocol at 90 kVp, reduced radiation and standard CM dose; and (C) protocol at 90 kVp, standard radiation and reduced CM dose. All three protocols were performed on a third-generation dual-source computed tomography scanner using the semimode of the ATVS system. The image-task-dependent optimization settings of the ATVS (slider level) were adjusted to level 11 (high-contrast task) for protocols A and B and level 3 (low-contrast task) for protocol C. Radiation dose parameters were assessed. The contrast-to-noise ratios (CNRs) of protocols B and C were tested for noninferiority compared with A. Subjective image quality was assessed using a 5-point Likert scale. RESULTS: Size-specific dose estimate was 34.3% lower for protocol B compared with A (P < 0.0001). Contrast medium was 20.2% lower for protocol C compared with A (P < 0.0001). Mean CNR in B and C was noninferior to protocol A (CNR of 30.2 ± 7, 33.4 ± 6.7, and 30.5 ± 8.9 for protocols A, B, and C, respectively). There was no significant difference in overall subjective image quality among protocols (4.09 ± 0.21, 4.03 ± 0.19, and 4.08 ± 0.17 for protocols A, B, and C, respectively; P = 0.4). CONCLUSIONS: The slider settings of an ATVS system can be adjusted to optimize either radiation dose or CM at noninferior image quality in low-kV CTA of the aorta. This optimization could be used to extend future ATVS algorithms to take clinical risk factors like kidney function of individual patients into account.

Quantitative dual-energy CT material decomposition of holmium microspheres: local concentration determination evaluated in phantoms and a rabbit tumor model.

OBJECTIVES: The purpose of this study was to assess the feasibility of dual-energy CT-based material decomposition using dual-X-ray spectra information to determine local concentrations of holmium microspheres in phantoms and in an animal model. MATERIALS AND METHODS: A spectral calibration phantom with a solution containing 10 mg/mL holmium and various tube settings was scanned using a third-generation dual-energy CT scanner to depict an energy-dependent and material-dependent enhancement vectors. A serial dilution of holmium (microspheres) was quantified by spectral material decomposition and compared with known holmium concentrations. Subsequently, the feasibility of the spectral material decomposition was demonstrated in situ in three euthanized rabbits with injected (radioactive) holmium microspheres. RESULTS: The measured CT values of the holmium solutions scale linearly to all measured concentrations and tube settings (R2 = 1.00). Material decomposition based on CT acquisitions using the tube voltage combinations of 80/150 Sn kV or 100/150 Sn kV allow the most accurate quantifications for concentrations down to 0.125 mg/mL holmium. CONCLUSION: Dual-energy CT facilitates image-based material decomposition to detect and quantify holmium microspheres in phantoms and rabbits. KEY POINTS: • Quantification of holmium concentrations based on dual-energy CT is obtained with good accuracy. • The optimal tube-voltage pairs for quantifying holmium were 80/150 Sn kV and 100/150 Sn kV using a third-generation dual-source CT system. • Quantification of accumulated holmium facilitates the assessment of local dosimetry for radiation therapies.

Individualized Delay for Abdominal Computed Tomography Angiography Bolus-Tracking Based on Sequential Monitoring: Increased Aortic Contrast Permits Decreased Injection Rate and Lower Iodine Dose.

OBJECTIVE: The aim of this study was to determine if computed tomography (CT) angiography using an individualized transition delay (CTA-ID) would facilitate reductions in injection rate and iodine dose. METHODS: The CTA-ID was performed in 20 patients with routine injection rate and iodine dose; 20 patients with injection rate lowered by 1 mL/s; and 40 patients with injection rate lowered by 1 mL/s with 29% less iodine. Routine CTAs in the same or size-matched patients served as controls. Diagnostic image quality and intra-arterial CT numbers were assessed. RESULTS: The median transition delay between aortic threshold and CTA-ID image acquisition was significantly longer than with conventional bolus tracking (mean increase, 13.3 seconds; P < 0.0001), with image quality being the same or better. Intra-arterial CT numbers were 200 Hounsfield units or greater for 80 of 80 CTA-ID, but not for 6 of 49 (12%) internal control or for 11 of 80 (14%) size-matched control patients. CONCLUSION: The CTA-ID bolus-tracking software alters transition delays to permit diagnostic CTA examinations despite slower injection rate and less iodine.

CT Angiography of the Aorta: Contrast Timing by Using a Fixed versus a Patient-specific Trigger Delay.

Background Optimal timing of the CT scan relative to the contrast media bolus remains a challenging task given the shorter scan durations of modern CT scanners, as well as interpatient variability. Purpose To compare contrast opacification in CT angiography of the aorta between a cohort with fixed trigger delay and a cohort with patient-specific individualized trigger delay for contrast media timing with bolus tracking. Materials and Methods In this prospective study (January-August 2018), CT angiography of the thoracoabdominal aorta with bolus tracking was performed in two different study cohorts: one with a fixed trigger delay of 4 seconds (fixed cohort) and one with a patient-specific trigger delay (individualized cohort). All CT and contrast media protocol parameters were kept identical among cohorts. Objective image quality was evaluated by one reader; two readers assessed subjective image quality. Student t test was used to test for differences in mean attenuation; the Wilcoxon-Mann-Whitney test was used to test for differences in noise, contrast-to-noise ratio, and subjective image quality. Results The fixed cohort had 108 study participants (16 women; mean age ± standard deviation, 72 years ± 10); the individualized cohort had 108 participants (16 women; mean age, 72 years ± 12). The trigger delay in the individualized cohort ranged from 6.4-11.3 seconds (mean, 9.2 seconds). There was higher overall attenuation in the individualized cohort than in the fixed cohort (486 HU ± 92 for individualized vs 438 HU ± 99 for fixed; P < .001), with increasing differences from the aortic arch (8 HU) to the iliac arteries (95 HU). The regression model indicated uniform attenuation in the individualized cohort and decreasing attenuation in the fixed cohort (decrease of 87 HU by the iliac arteries; P < .001). There was no difference between cohorts for image noise (20 vs 19; P = .41), but contrast-to-noise ratio (21 vs 19; P = .04) and subjective image quality were higher in the individualized cohort than in the fixed cohort (excellent or good image quality, 100% vs 67%; P < .001). Conclusion Compared with a fixed delay time after bolus tracking, a patient-specific individualized trigger delay improves image quality and provides uniform contrast attenuation for CT angiography of the aorta. ©RSNA, 2019.

Detection and Characterization of Renal Stones by Using Photon-Counting-based CT.

Purpose To compare a research photon-counting-detector (PCD) CT scanner to a dual-source, dual-energy CT scanner for the detection and characterization of renal stones in human participants with known stones. Materials and Methods Thirty study participants (median age, 61 years; 10 women) underwent a clinical renal stone characterization scan by using dual-energy CT and a subsequent research PCD CT scan by using the same radiation dose (as represented by volumetric CT dose index). Two radiologists were tasked with detection of stones, which were later characterized as uric acid or non-uric acid by using a commercial dual-energy CT analysis package. Stone size and contrast-to-noise ratio were additionally calculated. McNemar odds ratios and Cohen k were calculated separately for all stones and small stones (≤3 mm). Results One-hundred sixty renal stones (91 stones that were ≤ 3 mm in axial length) were visually detected. Compared with 1-mm-thick routine images from dual-energy CT, the odds of detecting a stone at PCD CT were 1.29 (95% confidence interval: 0.48, 3.45) for all stones. Stone segmentation and characterization were successful at PCD CT in 70.0% (112 of 160) of stones versus 54.4% (87 of 160) at dual-energy CT, and was superior for stones 3 mm or smaller at PCD CT (45 vs 25 stones, respectively; P = .002). Stone characterization agreement between scanners for stones of all sizes was substantial (k = 0.65). Conclusion Photon-counting-detector CT is similar to dual-energy CT for helping to detect renal stones and is better able to help characterize small renal stones. © RSNA, 2018.

Characterization of Urinary Stone Composition by Use of Whole-body, Photon-counting Detector CT.

RATIONAL AND OBJECTIVES: This study aims to investigate the performance of a whole-body, photon-counting detector (PCD) computed tomography (CT) system in differentiating urinary stone composition. MATERIALS AND METHODS: Eighty-seven human urinary stones with pure mineral composition were placed in four anthropomorphic water phantoms (35-50 cm lateral dimension) and scanned on a PCD-CT system at 100, 120, and 140 kV. For each phantom size, tube current was selected to match CTDIvol (volume CT dose index) to our clinical practice. Energy thresholds at [25, 65], [25, 70], and [25, 75] keV for 100, 120, and 140 kV, respectively, were used to generate dual-energy images. Each stone was automatically segmented using in-house software; CT number ratios were calculated and used to differentiate stone types in a receiver operating characteristic (ROC) analysis. A comparison with second- and third-generation dual-source, dual-energy CT scanners with conventional energy integrating detectors (EIDs) was performed under matching conditions. RESULTS: For all investigated settings and smaller phantoms, perfect separation between uric acid and non-uric acid stones was achieved (area under the ROC curve [AUC] = 1). For smaller phantoms, performance in differentiation of calcium oxalate and apatite stones was also similar between the three scanners: for the 35-cm phantom size, AUC values of 0.76, 0.79, and 0.80 were recorded for the second- and third-generation EID-CT and for the PCD-CT, respectively. For larger phantoms, PCD-CT and the third-generation EID-CT outperformed the second-generation EID-CT for both differentiation tasks: for a 50-cm phantom size and a uric acid/non-uric acid differentiating task, AUC values of 0.63, 0.95, and 0.99 were recorded for the second- and third-generation EID-CT and for the PCD-CT, respectively. CONCLUSION: PCD-CT provides comparable performance to state-of-the-art EID-CT in differentiating urinary stone composition.

Lung nodule volume quantification and shape differentiation with an ultra-high resolution technique on a photon-counting detector computed tomography system.

An ultra-high resolution (UHR) mode, with a detector pixel size of [Formula: see text] relative to isocenter, has been implemented on a whole body research photon-counting detector (PCD) computed tomography (CT) system. Twenty synthetic lung nodules were scanned using UHR and conventional resolution (macro) modes and reconstructed with medium and very sharp kernels. Linear regression was used to compare measured nodule volumes from CT images to reference volumes. The full-width-at-half-maximum of the calculated curvature histogram for each nodule was used as a shape index, and receiver operating characteristic analysis was performed to differentiate sphere- and star-shaped nodules. Results showed a strong linear relationship between measured nodule volumes and reference volumes for both modes. The overall volume estimation was more accurate using UHR mode and the very sharp kernel, having 4.8% error compared with 10.5% to 12.6% error in the macro mode. The improvement in volume measurements using the UHR mode was more evident for small nodule sizes or star-shaped nodules. Images from the UHR mode with the very sharp kernel consistently demonstrated the best performance [[Formula: see text]] for separating star- from sphere-shaped nodules, showing advantages of UHR mode on a PCD CT scanner for lung nodule characterization.