Quantification accuracy in photon-counting detector CT for coronary artery calcium score: a pilot study.

To validate the accuracy of coronary artery calcium score (CACS) using photon-counting detector (PCD) CT under various scanning settings and explore the optimized scanning settings considering both the accuracy and the radiation dose. A CACS phantom containing six hollow cylindrical hydroxyapatite calcifications of two sizes with three densities and 12 patients underwent CACS scans. For PCD-CT, two scanning modes (sequence and flash [high-pitch spiral mode]) and five tube voltages (90kV, 120kV, 140kV, Sn100kV, and Sn140kV) at different image quality (IQ) levels were set for phantom, and patients were scanned with 120kV at IQ19 using flash mode. All acquisitions from PCD-CT were reconstructed at 70keV. Acquisitions in sequence mode at 120kV on an energy-integrating detector CT (EID-CT) was used as the reference. Agatston, mass, and volume scores were calculated. The CACS from PCD-CT exhibited excellent agreements with the reference (all intraclass correlation coefficient [ICC] > 0.99). The root mean square error (RMSE) between the Agatston score acquired from PCD-CT and the reference (5.4-11.5) was small. A radiation dose reduction (16-75%) from PCD-CT compared with the reference was obtained in all protocols using flash mode, albeit with IQ20 only at sequence mode (22-44%). For the patients, ICC ( all ICC > 0.98) and Bland-Altman analysis of CACS all showed high agreements between PCD-CT and the reference, without reclassifying CACS categories(P = 0.317). PCD-CT yields repeatable and accurate CACS across diverse scanning protocols according to our pilot study. Sn100kV, 90kV, and 120kV using flash mode at IQ20 are recommended for clinical applications considering both accuracy and radiation dose.

Noise characterization analysis of dynamic dual-energy CT and its advantage in suppressing statistical noise.

OBJECTIVE: Multi-energy CT conducted by photon-counting detector has a wide range of applications, especially in multiple contrast agents imaging. However, static multi-energy (SME) CT imaging suffers from higher statistical noise because of increased energy bins with static energy thresholds. Our team has proposed a dynamic dual-energy (DDE) CT detector model and the corresponding iterative reconstruction algorithm to solve this problem. However, rigorous and detailed analysis of the statistical noise characterization in this DDE CT was lacked. APPROACH: Starting from the properties of the Poisson random variable, this paper analyzes the noise characterization of the DDE CT and compares it with the SME CT. It is proved that the multi-energy CT projections and reconstruction images calculated from the proposed DDE CT algorithm have less statistical noise than that of the SME CT. MAIN RESULTS: Simulations and experiments verify that the expectations of the multi-energy CT projections calculated from DDE CT are the same as those of the SME projections. Still, the variance of the former is smaller. We further analyze the convergence of the iterative DDE CT algorithm through simulations and prove that the derived noise characterization can be realized under different CT imaging configurations. SIGNIFICANCE: The low statistical noise characteristics demonstrate the value of DDE CT imaging technology.

Low-dose Ultra-high-resolution Photon-Counting Detector CT for Visceral Artery CT Angiography: A Preliminary Study.

RATIONALE AND OBJECTIVES: To validate the image quality of low-dose ultra-high-resolution (UHR) scanning mode of photon-counting detector CT (PCD-CT) for visceral artery computed tomography angiography (CTA). MATERIAL AND METHODS: We prospectively enrolled 57 patients each in the full dose (FD) and low-dose (LD) protocols, respectively, to undergo abdominal CT scans using the UHR mode on a PCD-CT system (NAEOTOM Alpha), between April 2023 and September 2023. Both the FD data and LD data were then reconstructed into two series of images: (a) 0.2 mm slice thickness, reconstruction kernel Bv48, quantum iterative reconstruction (QIR) 4; (b)1 mm slice thickness, Bv40, QIR 3. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of seven arteries were objectively measured. The image noise, vessel sharpness, overall quality, and visibility of nine arteries were subjectively assessed by three radiologists. RESULTS: The SNRs and CNRs of 0.2 mm reconstruction set was inferior to that of 1 mm reconstruction set (p < 0.001 for all the arteries and noise), however, the image quality of 0.2 mm reconstruction set was higher than that of 1 mm reconstruction set in qualitative evaluation especially for tiny arteries in Volume-rendered (VR) image (p < 0.001). The SNRs and CNRs were not significantly higher for FD group than LD group on the same slice thickness except for SNRs of common hepatic artery, splenic artery and bilateral renal arteries in 0.2 mm reconstruction set. In the comparison on image quality between normal weight and overweight patients within the same reconstruction set, the results showed that low-dose scan did not significantly impact the image quality in overweight patients. The ratings of visibility of nine visceral arteries were not significantly different among FD and LD at the same thickness reconstruction set except for superior mesenteric artery (p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in axial image; p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in coronal image, respectively) and left gastric artery (p = 0.002 and p < 0.001 for 0.2 mm and 1 mm reconstruction set in VR image, respectively). CONCLUSION: The low-dose UHR scanning mode of PCD-CT has proven to be adequate for the clinical evaluation of visceral arteries. Utilizing a reconstruction with a slice thickness of 0.2 mm could enhance arterial depiction, particularly for small vessels.

In vitro and in vivo optimized reconstruction for low-keV virtual monoenergetic photon-counting detector CT angiography of lower legs.

BACKGROUND: Lower extremity peripheral artery disease frequently presents with calcifications which reduces the accuracy of computed tomography (CT) angiography, especially below-the-knee. Photon-counting detector (PCD)-CT offers improved spatial resolution and less calcium blooming. We aimed to identify the optimal reconstruction parameters for PCD-CT angiography of the lower legs. METHODS: Tubes with different diameters (1-5 mm) were filled with different iodine concentrations and scanned in a water container. Images were reconstructed with 0.4 mm isotropic resolution using a quantitative kernel at all available sharpness levels (Qr36 to Qr76) and using different levels of quantum iterative reconstruction (QIR-2-4). Noise and image sharpness were determined for all reconstructions. Additionally, CT angiograms of 20 patients, reconstructed with a medium (Qr44), sharp (Qr60), and ultrasharp (Qr72) kernel at QIR-2-4, were evaluated by three readers assessing noise, delineation of plaques and vessel walls, and overall quality. RESULTS: In the phantom study, increased kernel sharpness led to higher image noise (e.g., 16, 38, 77 HU for Qr44, Qr60, Qr72, and QIR-3). Image sharpness increased with increasing kernel sharpness, reaching a plateau at the medium-high level 60. Higher QIR levels decreased image noise (e.g., 51, 38, 25 HU at QIR-2-4 and Qr60) without reducing vessel sharpness. The qualitative in vivo results confirmed these findings: the sharp kernel (Qr60) with the highest QIR yielded the best overall quality. CONCLUSION: The combination of a sharpness level optimized reconstruction kernel (Qr60) and the highest QIR level yield the best image quality for PCD-CT angiography of the lower legs when reconstructed at 0.4-mm resolution. RELEVANCE STATEMENT: Using high-resolution PCD-CT angiography with optimized reconstruction parameters might improve diagnostic accuracy and confidence in peripheral artery disease of the lower legs. KEY POINTS: Effective exploitation of the potential of PCD-CT angiography requires optimized reconstruction parameters. Too soft or too sharp reconstruction kernels reduce image quality. The highest level of quantum iterative reconstruction provides the best image quality.

Improved Detection of Small and Low-Density Plaques in Virtual Noncontrast Imaging-based Calcium Scoring at Photon-Counting Detector CT.

Purpose To investigate the impact of plaque size and density on virtual noncontrast (VNC)-based coronary artery calcium scoring (CACS) using photon-counting detector CT and to provide safety net reconstructions for improved detection of subtle plaques in patients whose VNC-based CACS would otherwise be erroneously zero when compared with true noncontrast (TNC)-based CACS. Materials and Methods In this prospective study, CACS was evaluated in a phantom containing calcifications with different diameters (5, 3, and 1 mm) and densities (800, 400, and 200 mg/cm3) and in participants who underwent TNC and contrast-enhanced cardiac photon-counting detector CT (July 2021-March 2022). VNC images were reconstructed at different virtual monoenergetic imaging (55-80 keV) and quantum iterative reconstruction (QIR) levels (QIR,1-4). TNC scans at 70 keV with QIR off served as the reference standard. In vitro CACS was analyzed using standard settings (3.0-mm sections, kernel Qr36, 130-HU threshold). Calcification detectability and CACS of small and low-density plaques were also evaluated using 1.0-mm sections, kernel Qr44, and 120- or 110-HU thresholds. Safety net reconstructions were defined based on background Agatston scores and evaluated in vivo in TNC plaques initially nondetectable using standard VNC reconstructions. Results The in vivo cohort included 63 participants (57.8 years ± 15.5 [SD]; 37 [59%] male, 26 [41%] female). Correlation and agreement between standard CACSVNC and CACSTNC were higher in large- and medium-sized and high- and medium-density than in low-density plaques (in vitro: intraclass correlation coefficient [ICC] ≥ 0.90; r > 0.9 vs ICC = 0.20-0.48; r = 0.5-0.6). Small plaques were not detectable using standard VNC reconstructions. Calcification detectability was highest using 1.0-mm sections, kernel Qr44, 120- and 110-HU thresholds, and QIR level of 2 or less VNC reconstructions. Compared with standard VNC, using safety net reconstructions (55 keV, QIR 2, 110-HU threshold) for in vivo subtle plaque detection led to higher detection (increased by 89% [50 of 56]) and improved correlation and agreement of CACSVNC with CACSTNC (in vivo: ICC = 0.51-0.61; r = 0.6). Conclusion Compared with TNC-based calcium scoring, VNC-based calcium scoring was limited for small and low-density plaques but improved using safety net reconstructions, which may be particularly useful in patients with low calcium scores who would otherwise be treated based on potentially false-negative results. Keywords: Coronary Artery Calcium CT, Photon-Counting Detector CT, Virtual Noncontrast, Plaque Size, Plaque Density Supplemental material is available for this article. © RSNA, 2024.

Revealing Detailed Cartilage Function Through Nanoparticle Diffusion Imaging: A Computed Tomography & Finite Element Study.

The ability of articular cartilage to withstand significant mechanical stresses during activities, such as walking or running, relies on its distinctive structure. Integrating detailed tissue properties into subject-specific biomechanical models is challenging due to the complexity of analyzing these characteristics. This limitation compromises the accuracy of models in replicating cartilage function and impacts predictive capabilities. To address this, methods revealing cartilage function at the constituent-specific level are essential. In this study, we demonstrated that computational modeling derived individual constituent-specific biomechanical properties could be predicted by a novel nanoparticle contrast-enhanced computer tomography (CECT) method. We imaged articular cartilage samples collected from the equine stifle joint (n = 60) using contrast-enhanced micro-computed tomography (µCECT) to determine contrast agents' intake within the samples, and compared those to cartilage functional properties, derived from a fibril-reinforced poroelastic finite element model. Two distinct imaging techniques were investigated: conventional energy-integrating µCECT employing a cationic tantalum oxide nanoparticle (Ta2O5-cNP) contrast agent and novel photon-counting µCECT utilizing a dual-contrast agent, comprising Ta2O5-cNP and neutral iodixanol. The results demonstrate the capacity to evaluate fibrillar and non-fibrillar functionality of cartilage, along with permeability-affected fluid flow in cartilage. This finding indicates the feasibility of incorporating these specific functional properties into biomechanical computational models, holding potential for personalized approaches to cartilage diagnostics and treatment.

Photon counting CT clinical adoption, integration, and workflow.

Photon counting CT was recently introduced into clinical practice [Rajendran K, Petersilka M, Henning A, Shanblatt ER, Schmidt B, Flohr TG, Ferrero A, Baffour F, Diehn FE, Yu L, Rajiah P, Fletcher JG, Leng S, McCollough CH. First Clinical Photon-counting Detector CT System: Technical Evaluation. Radiology 2022;303(1):130-138. doi: https://doi.org/10.1148/radiol.212579 ]. Photon counting detectors (PCD) afford better spatial resolution, radiation dose efficiency, and iodine contrast-to-noise than EID-CT [Leng S, Bruesewitz M, Tao S, Rajendran K, Halaweish AF, Campeau NG, Fletcher JG, McCollough CH. Photon-counting Detector CT: System Design and Clinical Applications of an Emerging Technology. Radiographics 2019;39(3):729-743. doi: https://doi.org/10.1148/rg.2019180115 ); (Leng S, Rajendran K, Gong H, Zhou W, Halaweish AF, Henning A, Kappler S, Baer M, Fletcher JG, McCollough CH. 150-mum Spatial Resolution Using Photon-Counting Detector Computed Tomography Technology: Technical Performance and First Patient Images. Invest Radiol 2018;53(11):655-662. doi: https://doi.org/10.1097/RLI.0000000000000488 )(Booij R, van der Werf NR, Dijkshoorn ML, van der Lugt A, van Straten M. Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data. Diagnostics (Basel) 2022;12(6). doi: https://doi.org/10.3390/diagnostics12061467 ); (Sawall S, Klein L, Amato C, Wehrse E, Dorn S, Maier J, Heinze S, Schlemmer HP, Ziener CH, Uhrig M, Kachelriess M. Iodine contrast-to-noise ratio improvement at unit dose and contrast media volume reduction in whole-body photon-counting CT. Eur J Radiol 2020;126:108909. doi: https://doi.org/10.1016/j.ejrad.2020.108909 ] while also maintaining multienergy CT (MECT) capabilities[Flohr T, Petersilka M, Henning A, Ulzheimer S, Ferda J, Schmidt B. Photon-counting CT review. Phys Med 2020;79:126-136. doi: https://doi.org/10.1016/j.ejmp.2020.10.030 ]. This article will review the clinical adoption of PCD-CT including protocol development, clinical applications, clinical integration and workflow considerations. Protocol development is institution specific and involves collaborative decision-making among radiologists, physicists, and technologists. Key PCD clinical applications include radiation exposure reduction, intravenous contrast volume reduction, and improved lesion conspicuity. Patients who would most benefit from these improvements may preferentially be scanned with PCD CT. With numerous available reconstructions, radiologists should be strategic in the series sent to PACS for interpretation and routinely sending spectral series to PACS can facilitate integration with clinical workflow. The Society of Abdominal Radiology PCD Emerging Technology Commission endorsed this article.

The Best of Both Worlds: Ultra-high-pitch Pulmonary Angiography with Free-Breathing Technique by Means of Photon-Counting Detector CT for Diagnosis of Acute Pulmonary Embolism.

RATIONALE AND OBJECTIVES: To assess image quality and radiation dose of ultra-high-pitch CT pulmonary angiography (CTPA) with free-breathing technique for diagnosis of pulmonary embolism using a photon-counting detector (PCD) CT compared to matched energy-integrating detector (EID)-based single-energy CTPA. MATERIALS AND METHODS: Fifty-one PCD-CTPAs were prospectively compared to 51 CTPAs on a third-generation dual-source EID-CT. CTPAs were acquired with an ultra-high-pitch protocol with free-breathing technique (40 mL contrast medium, pitch 3.2) at 140 kV (PCD) and 70-100 kV (EID). Iodine maps were reconstructed from spectral PCD-CTPAs. Image quality of CTPAs and iodine maps was assessed independently by three radiologists. Additionally, CT attenuation numbers within pulmonary arteries as well as signal-to-noise and contrast-to-noise ratios (SNR, CNR) were compared. Administered radiation dose was compared. RESULTS: CT attenuation was higher in the PCD-group (all P < 0.05). CNR and SNR were higher in lobar pulmonary arteries in PCD-CTPAs (P < 0.05), whereas no difference was ascertained within the pulmonary trunk (P > 0.05). Image quality of PCD-CTPA was rated best by all readers (excellent/good image quality in 96.1% of PCD-CTPAs vs. 50.9% of EID-CTPAs). PCD-CT produced no non-diagnostic scans vs. three non-diagnostic (5.9%) EID-CTPAs. Radiation dose was lower with PCD-CT than with EID-CT (effective dose 1.33 ± 0.47 vs. 1.80 ± 0.82 mSv; all P < 0.05). CONCLUSION: Ultra-high-pitch CTPA with free-breathing technique with PCD-CT allows for superior image quality with significantly reduced radiation dose and full spectral information. With the ultra-high pitch, only PCD-CTPA enables reconstruction of iodine maps containing additional functional information.

Prior image-based generative adversarial learning for multi-material decomposition in photon counting computed tomography.

BACKGROUND: Photon counting detector computed tomography (PCD-CT) is a novel promising technique providing higher spatial resolution, lower radiation dose and greater energy spectrum differentiation, which create more possibilities to improve image quality. Multi-material decomposition is an attractive application for PCD-CT to identify complicated materials and provide accurate quantitative analysis. However, limited by the finite photon counting rate in each energy window of photon counting detector, the noise problem hinders the decomposition of high-quality basis material images. METHODS: To address this issue, an end-to-end multi-material decomposition network based on prior images is proposed in this paper. First, the reconstructed images corresponding to the full spectrum with less noise are introduced as prior information to improve the overall signal-to-noise ratio of the data. Then, a generative adversarial network is designed to mine the relationship between reconstructed images and basis material images based on the information interaction of material decomposition. Furthermore, a weighted edge loss is introduced to adapt to the structural differences of different basis material images. RESULTS: To verify the performance of the proposed method, simulation and real studies are carried out. In simulation study of structured fibro-glandular tissue model, the results show that the proposed method decreased the root mean square error by 67 % and 26 % on adipose, 66 % and 28 % on fibroglandular, 52 % and 8 % on calcification, compared to butterfly network and dual interactive Wasserstein generative adversarial network. CONCLUSION: Experimentally, the proposed method shows certain advantages over other methods on noise suppression effect, detail retention ability and decomposition accuracy.

Polyenergetic reconstruction mitigates streak artifacts by dual source imaging in chest photon counting detector computed tomography.

OBJECTIVE: This study aims to assess the efficacy of polyenergetic reconstruction methods in reducing streak artifacts caused by dual source imaging in Photon Counting Detector Computed Tomography (PCD-CT) imaging, thereby improving image quality and diagnostic accuracy. METHODS: A retrospective cohort study was conducted, involving 50 patients who underwent chest Computed Tomography Angiography with PCD-CT, focusing on those with streak artifacts. Quantitative and qualitative analyses were performed on images reconstructed using monoenergetic and polyenergetic techniques. Quantitative evaluations measured the attenuation of tracheal air density in regions affected by streak artifacts, while qualitative assessments employed a modified Likert scale to rate image quality. Statistical analyses included Wilcoxon's signed-rank tests and Spearman's correlation, alongside assessments of inter-rater reliability. RESULTS: There was significantly lower attenuation of tracheal air density on the polyenergetic reconstructions (Median - 1010 ± 62 HU vs -930 ± 110 HU; P < 0.001), and significantly decreased variation on the polyenergetic reconstructions (Median 65.2 ± 79.5 HU vs 38.8 ± 33.9 HU; P < 0.001). The median modified-Likert scale were significantly better for the polyenergetic reconstructions (median modified-Likert 4 ± 0.5 vs 2.5 ± 1; P < 0.001). The inter-rater agreement was substantial and not significantly different between reconstructions (Gwet's ACPolyenergetic = 0.78 vs Gwet's ACVMI = 0.775). CONCLUSION: Polyenergetic reconstruction significantly mitigates streak artifacts in PCD-CT imaging, enhancing quantitative and qualitative image quality. This advancement addresses a known limitation of current PCD-CT reconstruction techniques, offering a promising approach to improving diagnostic reliability and accuracy in clinical practice. We demonstrate that future software implementations can resolve this artifact.

A Novel and Reliable Pixel Response Correction Method (DAC-Shifting) for Spectral Photon-Counting CT Imaging.

Spectral photon-counting cone-beam computed tomography (CT) imaging is challenged by individual pixel response behaviours, which lead to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform a post-processing ring artefact correction of sinogram data or scan reconstructions without taking the pixel response explicitly into account. Here, we present a novel post-processing method (digital-to-analogue converter (DAC)-shifting) which explicitly measures the current pixel response using flat-field images and subsequently corrects the projection data. The DAC-shifting method was evaluated using a repeat series of the spectral photon-counting imaging (Medipix3) of a phantom with different density inserts and iodine K-edge imaging. The method was also compared against polymethyl methacrylate (PMMA)-based STC. The DAC-shifting method was shown to be effective in correcting individual pixel responses and was robust against detector instability; it led to a 47.4% average reduction in CT-number variation in homogeneous materials, with a range of 40.7-55.6%. On the contrary, the STC correction showed varying results; a 13.7% average reduction in CT-number variation, ranging from a 43.7% increase to a 45.5% reduction. In K-edge imaging, DAC-shifting provides a sharper attenuation peak and more uniform CT values, which are expected to benefit iodine concentration quantifications.

Improving Visualization of In-stent Lumen Using Prototype Photon-counting Detector Computed Tomography with High-resolution Plaque Kernel.

The study aimed to compare the performance of photon-counting detector computed tomography (PCD CT) with high-resolution (HR)-plaque kernel with that of the energy-integrating detector CT (EID CT) in terms of the visualization of the lumen size and the in-stent stenotic portion at different coronary vessel angles. The lumen sizes in PCD CT and EID CT images were 2.13 and 1.80 mm at 0°, 2.20 and 1.77 mm at 45°, and 2.27 mm and 1.67 mm at 90°, respectively. The lumen sizes in PCD CT with HR-plaque kernel were wider than those in EID CT. The mean degree of the in-stent stenotic portion at 50% was 69.7% for PCD CT and 90.4% for EID CT. PCD CT images with HR-plaque kernel enable improved visualization of lumen size and accurate measurements of the in-stent stenotic portion compared to conventional EID CT images regardless of the stent direction.

An Image-Based Prior Knowledge-Free Approach for a Multi-Material Decomposition in Photon-Counting Computed Tomography.

Photon-counting CT systems generally allow for acquiring multiple spectral datasets and thus for decomposing CT images into multiple materials. We introduce a prior knowledge-free deterministic material decomposition approach for quantifying three material concentrations on a commercial photon-counting CT system based on a single CT scan. We acquired two phantom measurement series: one to calibrate and one to test the algorithm. For evaluation, we used an anthropomorphic abdominal phantom with inserts of either aqueous iodine solution, aqueous tungsten solution, or water. Material CT numbers were predicted based on a polynomial in the following parameters: Water-equivalent object diameter, object center-to-isocenter distance, voxel-to-isocenter distance, voxel-to-object center distance, and X-ray tube current. The material decomposition was performed as a generalized least-squares estimation. The algorithm provided material maps of iodine, tungsten, and water with average estimation errors of 4% in the contrast agent maps and 1% in the water map with respect to the material concentrations in the inserts. The contrast-to-noise ratio in the iodine and tungsten map was 36% and 16% compared to the noise-minimal threshold image. We were able to decompose four spectral images into iodine, tungsten, and water.

Synthetic hematocrit from virtual non-contrast images for myocardial extracellular volume evaluation with photon-counting detector CT.

OBJECTIVES: To assess the accuracy of a synthetic hematocrit derived from virtual non-contrast (VNC) and virtual non-iodine images (VNI) for myocardial extracellular volume (ECV) computation with photon-counting detector computed tomography (PCD-CT). MATERIALS AND METHODS: Consecutive patients undergoing PCD-CT including a coronary CT angiography (CCTA) and a late enhancement (LE) scan and having a blood hematocrit were retrospectively included. In the first 75 patients (derivation cohort), CCTA and LE scans were reconstructed as VNI at 60, 70, and 80 keV and as VNC with quantum iterative reconstruction (QIR) strengths 2, 3, and 4. Blood pool attenuation (BPmean) was correlated to blood hematocrit. In the next 50 patients (validation cohort), synthetic hematocrit was calculated using BPmean. Myocardial ECV was computed using the synthetic hematocrit and compared with the ECV using the blood hematocrit as a reference. RESULTS: In the derivation cohort (49 men, mean age 79 ± 8 years), a correlation between BPmean and blood hematocrit ranged from poor for VNI of CCTA at 80 keV, QIR2 (R2 = 0.12) to moderate for VNI of LE at 60 keV, QIR4; 70 keV, QIR3 and 4; and VNC of LE, QIR3 and 4 (all, R2 = 0.58). In the validation cohort (29 men, age 75 ± 14 years), synthetic hematocrit was calculated from VNC of the LE scan, QIR3. Median ECV was 26.9% (interquartile range (IQR), 25.5%, 28.8%) using the blood hematocrit and 26.8% (IQR, 25.4%, 29.7%) using synthetic hematocrit (VNC, QIR3; mean difference, -0.2%; limits of agreement, -2.4%, 2.0%; p = 0.33). CONCLUSION: Synthetic hematocrit calculated from VNC images enables an accurate computation of myocardial ECV with PCD-CT. CLINICAL RELEVANCE STATEMENT: Virtual non-contrast images from cardiac late enhancement scans with photon-counting detector CT allow the calculation of a synthetic hematocrit, which enables accurate computation of myocardial extracellular volume. KEY POINTS: Blood hematocrit is mandatory for conventional myocardial extracellular volume computation. Synthetic hematocrit can be calculated from virtual non-iodine and non-contrast photon-counting detector CT images. Synthetic hematocrit from virtual non-contrast images enables computation of the myocardial extracellular volume.

Photon-Counting Computed Tomography in Atherosclerotic Plaque Characterization.

Atherosclerotic plaque buildup in the coronary and carotid arteries is pivotal in the onset of acute myocardial infarctions or cerebrovascular events, leading to heightened levels of illness and death. Atherosclerosis is a complex and multistep disease, beginning with the deposition of low-density lipoproteins in the arterial intima and culminating in plaque rupture. Modern technology favors non-invasive imaging techniques to assess atherosclerotic plaque and offer insights beyond mere artery stenosis. Among these, computed tomography stands out for its widespread clinical adoption and is prized for its speed and accessibility. Nonetheless, some limitations persist. The introduction of photon-counting computed tomography (PCCT), with its multi-energy capabilities, enhanced spatial resolution, and superior soft tissue contrast with minimal electronic noise, brings significant advantages to carotid and coronary artery imaging, enabling a more comprehensive examination of atherosclerotic plaque composition. This narrative review aims to provide a comprehensive overview of the main concepts related to PCCT. Additionally, we aim to explore the existing literature on the clinical application of PCCT in assessing atherosclerotic plaque. Finally, we will examine the advantages and limitations of this recently introduced technology.

Stability and accuracy of fat quantification on photon-counting detector CT with various scan settings: A phantom study.

OBJECTIVE: Fat deposition is an important marker of many metabolic diseases. As a noninvasive and convenient examination method, CT has been widely used for fat quantification. With the clinical application of photon-counting detector (PCD)-CT, we aimed to investigate the accuracy, stability, and dose level of PCD-CT using various scan settings for fat quantification. MATERIALS AND METHODS: Eleven agar-based lipid-containing phantoms (vials with different fat fractions [FFs]; range: 0 %-100 %) were scanned using PCD-CT. Three scanning types (sequence scan, regular spiral scan with a pitch of 0.8, and high-pitch spiral scan with a pitch of 3.2), four tube voltages (90, 120, 140, and 100 kV with a tin filter), and three image quality (IQ) levels (IQ levels of 20, 40, and 80) were alternated, and each scan setting was used twice. For each scan, a 70-keV image was generated using the same reconstruction parameters. A regular spiral scan at 120 kV with IQ80 was used to transfer the CT numbers of all scans to the FF. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were implemented for accuracy and agreement evaluation, and group differences were compared using analysis of variance. RESULTS: Excellent agreement and accuracy of FF derived by PCD-CT with all scan settings was demonstrated by high ICCs (>0.9; range: 0.929-0.998, p < 0.017) and low bias (<5% range: -2.9 %-5%). The root mean square error (RMSE) between the PCD-CT-acquired FF and the reference standard ranged from 1.0 % to 5.0 %, among which the high-pitch scan at 120 kV with IQ20 accounted for the lowest RMSE (1.0 %). The spiral scan at 120 kV with IQ20 and IQ80 yielded the lowest bias (mean value: 1.19 % and 1.23 %, respectively). CONCLUSION: Fat quantification using PCD-CT reconstructed at 70 keV was accurate and stable under various scan settings. PCD-CT has great potential for fat quantification using ultralow radiation doses.

Update on Renal Cell Carcinoma Diagnosis with Novel Imaging Approaches.

This review highlights recent advances in renal cell carcinoma (RCC) imaging. It begins with dual-energy computed tomography (DECT), which has demonstrated a high diagnostic accuracy in the evaluation of renal masses. Several studies have suggested the potential benefits of iodine quantification, particularly for distinguishing low-attenuation, true enhancing solid masses from hyperdense cysts. By determining whether or not a renal mass is present, DECT could avoid the need for additional imaging studies, thereby reducing healthcare costs. DECT can also provide virtual unenhanced images, helping to reduce radiation exposure. The review then provides an update focusing on the advantages of multiparametric magnetic resonance (MR) imaging performance in the histological subtyping of RCC and in the differentiation of benign from malignant renal masses. A proposed standardized stepwise reading of images helps to identify clear cell RCC and papillary RCC with a high accuracy. Contrast-enhanced ultrasound may represent a promising diagnostic tool for the characterization of solid and cystic renal masses. Several combined pharmaceutical imaging strategies using both sestamibi and PSMA offer new opportunities in the diagnosis and staging of RCC, but their role in risk stratification needs to be evaluated. Although radiomics and tumor texture analysis are hampered by poor reproducibility and need standardization, they show promise in identifying new biomarkers for predicting tumor histology, clinical outcomes, overall survival, and the response to therapy. They have a wide range of potential applications but are still in the research phase. Artificial intelligence (AI) has shown encouraging results in tumor classification, grade, and prognosis. It is expected to play an important role in assessing the treatment response and advancing personalized medicine. The review then focuses on recently updated algorithms and guidelines. The Bosniak classification version 2019 incorporates MRI, precisely defines previously vague imaging terms, and allows a greater proportion of masses to be placed in lower-risk classes. Recent studies have reported an improved specificity of the higher-risk categories and better inter-reader agreement. The clear cell likelihood score, which adds standardization to the characterization of solid renal masses on MRI, has been validated in recent studies with high interobserver agreement. Finally, the review discusses the key imaging implications of the 2017 AUA guidelines for renal masses and localized renal cancer.

Improved noise reduction in photon-counting detector CT using prior knowledge-aware iterative denoising neural network.

Purpose: We aim to reduce image noise in high-resolution (HR) virtual monoenergetic images (VMIs) from photon-counting detector (PCD) CT scans by developing a prior knowledge-aware iterative denoising neural network (PKAID-Net) that efficiently exploits the unique noise characteristics of VMIs at different energy (keV) levels. Approach: PKAID-Net offers two major features: first, it utilizes a lower-noise VMI (e.g., 70 keV) as a prior input; second, it iteratively constructs a refined training dataset to improve the neural network's denoising performance. In each iteration, the denoised image from the previous module serves as an updated target image, which is included in the dataset for the subsequent training iteration. Our study includes 10 patient coronary CT angiography exams acquired on a clinical dual-source PCD-CT (NAEOTOM Alpha, Siemens Healthineers). The HR VMIs were reconstructed at 50, 70, and 100 keV, using a sharp vascular kernel (Bv68) and thin (0.6 mm) slice thickness (0.3 mm increment). PKAID-Net's performance was evaluated in terms of image noise, spatial detail preservation, and quantitative accuracy. Results: PKAID-Net achieved a noise reduction of 96% compared to filtered back projection and 65% relative to iterative reconstruction, all while preserving spatial and spectral fidelity and maintaining a natural noise texture. The iterative refinement of PCD-CT data during the training process substantially enhanced the robustness of deep learning-based denoising compared to the original method, which resulted in some spatial detail loss. Conclusions: The PKAID-Net provides substantial noise reduction while maintaining spatial and spectral fidelity of the HR VMIs from PCD-CT.

Low-contrast detectability of photon-counting-detector CT at different scan modes and image types in comparison with energy-integrating-detector CT.

Purpose: We aim to compare the low-contrast detectability of a clinical whole-body photon-counting-detector (PCD)-CT at different scan modes and image types with an energy-integrating-detector (EID)-CT. Approach: We used a channelized Hotelling observer (CHO) previously optimized for quality control purposes. An American College of Radiology CT accreditation phantom was scanned on both PCD-CT and EID-CT with 10 phantom positionings. For PCD-CT, images were generated using two scan modes, standard resolution (SR) and ultra-high-resolution (UHR); two image types, virtual monochromatic images at 70 keV and low-energy threshold (T3D); both filtered-back-projection (FBP) and iterative reconstruction (IR) reconstruction methods; and three reconstruction kernels. For each positioning, three repeated scans were acquired for each scan mode, image type, and CTDIvol of 6, 12, and 24 mGy. For EID-CT, images acquired from scans (10 positionings × 3 repeats × 3 doses) were reconstructed using the closest counterpart FBP and IR kernels. CHO was applied to calculate the index of detectability (d') on both scanners. Results: With the smooth Br44 kernel, the d' of UHR was mostly comparable with that of the SR mode (difference: -11.4% to 8.3%, p=0.020 to 0.956), and the T3D images had a higher d' (difference: 0.7% to 25.6%) than 70 keV images on PCD-CT. Compared with the EID-CT, UHR-T3D of PCD-CT had non-inferior d' (difference: -2.7% to 12.9%) with IR and non-superior d' (difference: 0.8% to 11.2%) with FBP using the Br44 kernel. PCD-CT produced higher d' than EID-CT by 61.8% to 247.1% with the sharper reconstruction kernels. Conclusions: The comparison between PCD-CT and EID-CT was significantly influenced by the reconstruction method and kernel. With a smooth kernel that is typically used in low-contrast detection tasks, the PCD-CT demonstrated low-contrast detectability that was comparable to EID-CT with IR and showed no superiority when using FBP. With the use of sharper kernels, the PCD-CT significantly outperformed EID-CT in low-contrast detectability.

Ultra-high resolution coronary CT angiography on photon-counting detector CT: bi-centre study on the impact of quantum iterative reconstruction on image quality and accuracy of stenosis measurements.

PURPOSE: To assess the impact of different quantum iterative reconstruction (QIR) levels on objective and subjective image quality of ultra-high resolution (UHR) coronary CT angiography (CCTA) images and to determine the effect of strength levels on stenosis quantification using photon-counting detector (PCD)-CT. METHOD: A dynamic vessel phantom containing two calcified lesions (25 % and 50 % stenosis) was scanned at heart rates of 60, 80 and 100 beats per minute with a PCD-CT system. In vivo CCTA examinations were performed in 102 patients. All scans were acquired in UHR mode (slice thickness0.2 mm) and reconstructed with four different QIR levels (1-4) using a sharp vascular kernel (Bv64). Image noise, signal-to-noise ratio (SNR), sharpness, and percent diameter stenosis (PDS) were quantified in the phantom, while noise, SNR, contrast-to-noise ratio (CNR), sharpness, and subjective quality metrics (noise, sharpness, overall image quality) were assessed in patient scans. RESULTS: Increasing QIR levels resulted in significantly lower objective image noise (in vitro and in vivo: both p < 0.001), higher SNR (both p < 0.001) and CNR (both p < 0.001). Sharpness and PDS values did not differ significantly among QIRs (all pairwise p > 0.008). Subjective noise of in vivo images significantly decreased with increasing QIR levels, resulting in significantly higher image quality scores at increasing QIR levels (all pairwise p < 0.001). Qualitative sharpness, on the other hand, did not differ across different levels of QIR (p = 0.15). CONCLUSIONS: The QIR algorithm may enhance the image quality of CCTA datasets without compromising image sharpness or accurate stenosis measurements, with the most prominent benefits at the highest strength level.