Photon-counting CT Research Articles

Assessment of quantitative information for radiation therapy at a first-generation clinical photon-counting computed tomography scanner.

As one of the latest developments in X-ray computed tomography (CT), photon-counting technology allows spectral detection, demonstrating considerable advantages as compared to conventional CT. In this study, we investigated the use of a first-generation clinical photon-counting computed tomography (PCCT) scanner and estimated proton relative (to water) stopping power (RSP) of tissue-equivalent materials from virtual monoenergetic reconstructions provided by the scanner. A set of calibration and evaluation tissue-equivalent inserts were scanned at 120 kVp. Maps of relative electron density (RED) and effective atomic number (EAN) were estimated from the reconstructed virtual monoenergetic images (VMI) using an approach previously applied to a spectral CT scanner with dual-layer detector technology, which allows direct calculation of RSP using the Bethe-Bloch formula. The accuracy of RED, EAN, and RSP was evaluated by root-mean-square errors (RMSE) averaged over the phantom inserts. The reference RSP values were obtained experimentally using a water column in an ion beam. For RED and EAN, the reference values were calculated based on the mass density and the chemical composition of the inserts. Different combinations of low- and high-energy VMIs were investigated in this study, ranging from 40 to 190 keV. The overall lowest error was achieved using VMIs at 60 and 180 keV, with an RSP accuracy of 1.27% and 0.71% for the calibration and the evaluation phantom, respectively.

Photon-Counting Detector CT With Quantum Iterative Reconstruction: Impact on Liver Lesion Detection and Radiation Dose Reduction.

To assess image noise, diagnostic performance, and potential for radiation dose reduction of photon-counting detector (PCD) computed tomography (CT) with quantum iterative reconstruction (QIR) in the detection of hypoattenuating and hyperattenuating focal liver lesions compared with energy-integrating detector (EID) CT. A medium-sized anthropomorphic abdominal phantom with liver parenchyma and lesions (diameter, 5-10 mm; hypoattenuating and hyperattenuating from -30 HU to +90 HU at 120 kVp) was used. The phantom was imaged on ( a ) a third-generation dual-source EID-CT (SOMATOM Force, Siemens Healthineers) in the dual-energy mode at 100 and 150 kVp with tin filtration and ( b ) a clinical dual-source PCD-CT at 120 kVp (NAEOTOM Alpha, Siemens). Scans were repeated 10 times for each of 3 different radiation doses of 5, 2.5, and 1.25 mGy. Datasets were reconstructed as virtual monoenergetic images (VMIs) at 60 keV for both scanners and as linear-blended images (LBIs) for EID-CT. For PCD-CT, VMIs were reconstructed with different strength levels of QIR (QIR 1-4) and without QIR (QIR-off). For EID-CT, VMIs and LBIs were reconstructed using advanced modeled iterative reconstruction at a strength level of 3. Noise power spectrum was measured to compare image noise magnitude and texture. A channelized Hotelling model observer was used to assess diagnostic accuracy for lesion detection. The potential for radiation dose reduction using PCD-CT was estimated for the QIR strength level with the highest area under the curve compared with EID-CT for each radiation dose. Image noise decreased with increasing QIR level at all radiation doses. Using QIR-4, noise reduction was 41%, 45%, and 59% compared with EID-CT VMIs and 12%, 18%, and 33% compared with EID-CT LBIs at 5, 2.5, and 1.25 mGy, respectively. The peak spatial frequency shifted slightly to lower frequencies at higher QIR levels. Lesion detection accuracy increased at higher QIR levels and was higher for PCD-CT compared with EID-CT VMIs. The improvement in detection with PCD-CT was strongest at the lowest radiation dose, with an area under the receiver operating curve of 0.917 for QIR-4 versus 0.677 for EID-CT VMIs for hyperattenuating lesions, and 0.900 for QIR-4 versus 0.726 for EID-CT VMIs for hypoattenuating lesions. Compared with EID-CT LBIs, detection was higher for QIR 1-4 at 2.5 mGy and for QIR 2-4 at 1.25 mGy (eg, 0.900 for QIR-4 compared with 0.854 for EID-CT LBIs at 1.25 mGy). Radiation dose reduction potential of PCD-CT with QIR-4 was 54% at 5 mGy compared with VMIs and 39% at 2.5 mGy compared with LBIs. Compared with EID-CT, PCD-CT with QIR substantially improved focal liver lesion detection, especially at low radiation dose. This enables substantial radiation dose reduction while maintaining diagnostic accuracy.

Photon-counting detector CT improves quality of arterial phase abdominal scans: A head-to-head comparison with energy-integrating CT

PurposePhoton-counting detector (PCD)-CT is expected to have a substantial impact on oncologic abdominal imaging. We compared subjective and objective image quality between PCD-CT and conventional energy-integrating detector (EID-)CT arterial phase abdominal scans. MethodsThis study included 84 patients undergoing both types of abdominal CT. EID-CT scans were acquired with a tube voltage of 100 kVp. With PCD-CT, acquired with 120-kVp, we reconstructed polychromatic T3D images and virtual monoenergetic images (VMIs) in 10-keV intervals from 40 to 90 keV. Quantitative image analysis included noise and contrast-to-noise ratio (CNR) of hepatic vessels, kidney cortex, and hypervascular liver lesions to liver parenchyma. Three raters used a 5-point Likert scale for qualitative image analysis of image noise and contrast, lesion conspicuity, and overall image quality. Radiation dose exposure (CT dose index) was compared between the two CT types. ResultsMean CT dose index and effective dose were respectively 18 % and 26 % lower with PCD-CT versus EID-CT. Compared with EID-CT, CNRs of kidney cortex and vessel to liver parenchyma were significantly higher in PCD-CT VMIs at energies ≤ 60 keV and in polychromatic T3D images (p < 0.004). Overall image quality of PCD-CT VMIs at 50 and 60 keV was rated as significantly better (p < 0.01) than the EID-CT images (inter-reader agreement alpha = 0.80). Lesion conspicuity was significantly better in low-keV VMIs (p < 0.03) and worse in > 70-keV VMIs. ConclusionsWith low-keV VMI, PCD-CT yields significantly improved objective and subjective quality of arterial phase oncological imaging compared with EID-CT. This advantage may translate into higher diagnostic confidence and lower radiation dose protocols.

Photon-counting Detector CT with Deep Learning Noise Reduction to Detect Multiple Myeloma.

Background Photon-counting detector (PCD) CT and deep learning noise reduction may improve spatial resolution at lower radiation doses compared with energy-integrating detector (EID) CT. Purpose To demonstrate the diagnostic impact of improved spatial resolution in whole-body low-dose CT scans for viewing multiple myeloma by using PCD CT with deep learning denoising compared with conventional EID CT. Materials and Methods Between April and July 2021, adult participants who underwent a whole-body EID CT scan were prospectively enrolled and scanned with a PCD CT system in ultra-high-resolution mode at matched radiation dose (8 mSv for an average adult) at an academic medical center. EID CT and PCD CT images were reconstructed with Br44 and Br64 kernels at 2-mm section thickness. PCD CT images were also reconstructed with Br44 and Br76 kernels at 0.6-mm section thickness. The thinner PCD CT images were denoised by using a convolutional neural network. Image quality was objectively quantified in two phantoms and a randomly selected subset of participants (10 participants; median age, 63.5 years; five men). Two radiologists scored PCD CT images relative to EID CT by using a five-point Likert scale to detect findings reflecting multiple myeloma. The scoring for the matched reconstruction series was blinded to scanner type. Reader-averaged scores were tested with the null hypothesis of equivalent visualization between EID and PCD. Results Twenty-seven participants (median age, 68 years; IQR, 61-72 years; 16 men) were included. The blinded assessment of 2-mm images demonstrated improvement in viewing lytic lesions, intramedullary lesions, fatty metamorphosis, and pathologic fractures for PCD CT versus EID CT (P < .05 for all comparisons). The 0.6-mm PCD CT images with convolutional neural network denoising also demonstrated improvement in viewing all four pathologic abnormalities and detected one or more lytic lesions in 21 of 27 participants compared with the 2-mm EID CT images (P < .001). Conclusion Ultra-high-resolution photon-counting detector CT improved the visibility of multiple myeloma lesions relative to energy-integrating detector CT. © RSNA, 2022 Online supplemental material is available for this article.

First in-human quantitative plaque characterization with ultra-high resolution coronary photon-counting CT angiography.

PurposeTo assess the effect of ultra-high-resolution coronary CT angiography (CCTA) with photon-counting detector (PCD) CT on quantitative coronary plaque characterization.Materials and methodsIn this IRB-approved study, 22 plaques of 20 patients (7 women; mean age 77 ± 8 years, mean body mass index 26.1 ± 3.6 kg/m2) undergoing electrocardiography (ECG)-gated ultra-high-resolution CCTA with PCD-CT were included. Images were reconstructed with a smooth (Bv40) and a sharp (Bv64) vascular kernel, with quantum iterative reconstruction (strength level 4), and using a slice thickness of 0.6, 0.4, and 0.2 mm, respectively (field-of-view 200 mm × 200 mm, matrix size 512 × 512 pixels). Reconstructions with the Bv40 kernel and slice thickness of 0.6 mm served as the reference standard. After identification of a plaque in coronary arteries with a vessel diameter ≥2 mm, plaque composition was determined using a dedicated, semi-automated plaque quantification software. Total plaque, calcified, fibrotic, and lipid-rich plaque components were quantified in all datasets.ResultsMedian plaque volume was highest (23.5 mm3, interquartiles 17.9–34.3 mm3) for reconstructions with the reference standard and lowest for ultra-high-resolution reconstructions with a slice thickness of 0.2 mm and the Bv64 kernel (18.1 mm3, interquartiles 14.1–25.8 mm3, p < 0.001). Reconstructions with the reference standard showed largest calcified (85.1%, interquartiles 76.4–91.1%) and smallest lipid-rich plaque components (0.5%, interquartiles 0.0–1.5%). Smallest calcified plaque components (75.2%, interquartiles 69.9–80.8%) and largest lipid-rich components (6.7%, interquartiles 5.1–8.4%) were found for ultra-high-resolution reconstructions with a slice thickness of 0.2 mm and the Bv64 kernel. At an identical slice thickness, volume of calcified components was always lower, and volume of lipid-rich components was always higher for reconstructions with the Bv64 kernel compared with reconstructions with the Bv40 kernel (all, p < 0.001).ConclusionThis patient study indicates significant differences of ultra-high-resolution scanning with PCD-CT on quantitative coronary plaque characterization. Reduced blooming artifacts may allow improved visualization of fibrotic and lipid-rich plaque components with the ultra-high-resolution mode of PCD-CT.

Photon-counting CT Material Decomposition: Initial Experience in Assessing Adrenal Adenoma.

See also the editorial by Pourmorteza in this issue.

Metal artifacts and artifact reduction of neurovascular coils in photon-counting detector CT versus energy-integrating detector CT — in vitro comparison of a standard brain imaging protocol

ObjectivesPhoton-counting detector computed tomography (PCD-CT) is a promising new technique for CT imaging. The aim of the present study was the in vitro comparison of coil-related artifacts in PCD-CT and conventional energy-integrating detector CT (EID-CT) using a comparable standard brain imaging protocol before and after metal artifact reduction (MAR).MethodsA nidus-shaped rubber latex, resembling an aneurysm of the cerebral arteries, was filled with neurovascular platinum coils and inserted into a brain imaging phantom. Image acquisition and reconstruction were repeatedly performed for PCD-CT and EID-CT (n = 10, respectively) using a standard brain imaging protocol. Moreover, linear interpolation MAR was performed for PCD-CT and EID-CT images. The degree of artifacts was analyzed quantitatively (standard deviation in a donut-shaped region of interest) and qualitatively (5-point scale analysis).ResultsQuantitative and qualitative analysis demonstrated a lower degree of metal artifacts in the EID-CT images compared to the total-energy PCD-CT images (e.g., 82.99 ± 7.89 Hounsfield units (HU) versus 90.35 ± 6.28 HU; p < 0.001) with no qualitative difference between the high-energy bin PCD-CT images and the EID-CT images (4.18 ± 0.37 and 3.70 ± 0.64; p = 0.575). After MAR, artifacts were more profoundly reduced in the PCD-CT images compared to the EID-CT images in both analyses (e.g., 2.35 ± 0.43 and 3.18 ± 0.34; p < 0.001).ConclusionPCD-CT in combination with MAR have the potential to provide an improved option for reduction of coil-related artifacts in cerebral imaging in this in vitro study.Key Points• Photon-counting detector CT produces more artifacts compared to energy-integrating detector CT without metal artifact reduction in cerebral in vitro imaging after neurovascular coil-embolization.• Spectral information of PCD-CT provides the potential for new post-processing techniques, since the coil-related artifacts were lower in PCD-CT images compared to EID-CT images after linear interpolation metal artifact reduction in this in vitro study.

Ytterbium Nanoparticle Contrast Agents for Conventional and Spectral Photon-Counting CT and Their Applications for Hydrogel Imaging.

Significant work has been done to develop nanoparticle contrast agents for computed tomography (CT), with a focus on identifying safer and more effective formulations. Contrast agents for spectral photon-counting computed tomography (SPCCT), a fast-growing imaging modality derived from conventional CT, have also recently gained considerable attention. In this study, we explored the synthesis of ultrasmall ytterbium nanoparticles (YbNP) and demonstrated that, potentially, they can be used as conventional CT and SPCCT contrast agents. These nanoparticles were tested in vitro for their cytotoxicity and contrast-generating properties with a variety of imaging systems. When scanned with conventional CT and SPCCT at clinically relevant energies, YbNP are significantly more attenuating than gold nanoparticles (AuNP), the contrast agents that have been most well studied. Furthermore, YbNP were studied for their potential application for labeling and monitoring hydrogels. The presence of the YbNP payload in hydrogels allowed for hydrogel localization and tracking in vivo. Additionally, the in vivo imaging results revealed that YbNP generate higher contrast when compared to AuNP used as a label. In summary, this is the first research study to examine ultrasmall YbNP as conventional CT and SPCCT contrast agents, as well as using them in a hydrogel system to make it radiopaque. These findings underscore YbNP's utility as CT and SPCCT contrast agents, as well as their potential for tracking hydrogels in vivo.

Photon-counting detector CT and energy-integrating detector CT for trabecular bone microstructure analysis of cubic specimens from human radius

BackgroundAs bone microstructure is known to impact bone strength, the aim of this in vitro study was to evaluate if the emerging photon-counting detector computed tomography (PCD-CT) technique may be used for measurements of trabecular bone structures like thickness, separation, nodes, spacing and bone volume fraction.MethodsFourteen cubic sections of human radius were scanned with two multislice CT devices, one PCD-CT and one energy-integrating detector CT (EID-CT), using micro-CT as a reference standard. The protocols for PCD-CT and EID-CT were those recommended for inner- and middle-ear structures, although at higher mAs values: PCD-CT at 450 mAs and EID-CT at 600 (dose equivalent to PCD-CT) and 1000 mAs. Average measurements of the five bone parameters as well as dispersion measurements of thickness, separation and spacing were calculated using a three-dimensional automated region growing (ARG) algorithm. Spearman correlations with micro-CT were computed.ResultsCorrelations with micro-CT, for PCD-CT and EID-CT, ranged from 0.64 to 0.98 for all parameters except for dispersion of thickness, which did not show a significant correlation (p = 0.078 to 0.892). PCD-CT had seven of the eight parameters with correlations ρ > 0.7 and three ρ > 0.9. The dose-equivalent EID-CT instead had four parameters with correlations ρ > 0.7 and only one ρ > 0.9.ConclusionsIn this in vitro study of radius specimens, strong correlations were found between trabecular bone structure parameters computed from PCD-CT data when compared to micro-CT. This suggests that PCD-CT might be useful for analysing bone microstructure in the peripheral human skeleton.

Anemia Detection by Hemoglobin Quantification on Contrast-enhanced Photon-counting CT Data Sets.

See also the editorial by Dodd and MacDermott in this issue.

Can Photon-Counting CT Improve Estimation Accuracy of Morphological Radiomics Features? A Simulation Study for Assessing the Quantitative Benefits from Improved Spatial Resolution in Deep Silicon-Based Photon-Counting CT

Deep silicon-based photon-counting CT (Si-PCCT) is an emerging detector technology that provides improved spatial resolution by virtue of its reduced pixel sizes. This article reports the outcomes of the first simulation study evaluating the impact of this advantage over energy-integrating CT (ECT) for estimation of morphological radiomics features in lung lesions. A dynamic nutrient-access-based stochastic model was utilized to generate three distinct morphologies for lung lesions. The lesions were inserted into the lung parenchyma of an anthropomorphic phantom (XCAT - 50th percentile BMI) at 50, 70, and 90 mm from isocenter. The phantom was virtually imaged with an imaging simulator (DukeSim) modeling a Si-PCCT and a conventional ECT system using varying imaging conditions (dose, reconstruction kernel, and pixel size). The imaged lesions were segmented using a commercial segmentation tool (AutoContour, Advantage Workstation Server 3.2, GE Healthcare) followed by extraction of morphological radiomics features using an open-source radiomics package (pyradiomics). The estimation errors for both systems were computed as percent differences from corresponding feature values estimated for the ground-truth lesions. Compared to ECT, the mean estimation error was lower for Si-PCCT (independent features: 35.9% vs. 54.0%, all features: 54.5% vs. 68.1%) with statistically significant reductions in errors for 8/14 features. For both systems, the estimation accuracy was minimally affected by dose and distance from the isocenter while reconstruction kernel and pixel size were observed to have a relatively stronger effect. For all lesions and imaging conditions considered, Si-PCCT exhibited improved estimation accuracy for morphological radiomics features over a conventional ECT system, demonstrating the potential of this technology for improved quantitative imaging.

Ultrahigh resolution whole body photon counting computed tomography as a novel versatile tool for translational research from mouse to man

X-ray computed tomography (CT) is a cardinal tool in clinical practice. It provides cross-sectional images within seconds. The recent introduction of clinical photon-counting CT allowed for an increase in spatial resolution by more than a factor of two resulting in a pixel size in the center of rotation of about 150 µm. This level of spatial resolution is in the order of dedicated preclinical micro-CT systems. However so far, the need for different dedicated clinical and preclinical systems often hinders the rapid translation of early research results to applications in men. This drawback might be overcome by ultra-high resolution (UHR) clinical photon-counting CT unifying preclinical and clinical research capabilities in a single machine. Herein, the prototype of a clinical UHR PCD CT (SOMATOM CounT, Siemens Healthineers, Forchheim, Germany) was used. The system comprises a conventional energy-integrating detector (EID) and a novel photon-counting detector (PCD). While the EID provides a pixel size of 0.6 mm in the centre of rotation, the PCD provides a pixel size of 0.25 mm. Additionally, it provides a quantification of photon energies by sorting them into up to four distinct energy bins. This acquisition of multi-energy data allows for a multitude of applications, e.g. pseudo-monochromatic imaging. In particular, we examine the relation between spatial resolution, image noise and administered radiation dose for a multitude of use-cases. These cases include ultra-high resolution and multi-energy acquisitions of mice administered with a prototype bismuth-based contrast agent (nanoPET Pharma, Berlin, Germany) as well as larger animals and actual patients. The clinical EID provides a spatial resolution of about 9 lp/cm (modulation transfer function at 10%, MTF10%) while UHR allows for the acquisition of images with up to 16 lp/cm allowing for the visualization of all relevant anatomical structures in preclinical and clinical specimen. The spectral capabilities of the system enable a variety of applications previously not available in preclinical research such as pseudo-monochromatic images. Clinical ultra-high resolution photon-counting CT has the potential to unify preclinical and clinical research on a single system enabling versatile imaging of specimens and individuals ranging from mice to man.

Material decomposition from photon-counting CT using a convolutional neural network and energy-integrating CT training labels

Objective. Photon-counting CT (PCCT) has better dose efficiency and spectral resolution than energy-integrating CT, which is advantageous for material decomposition. Unfortunately, the accuracy of PCCT-based material decomposition is limited due to spectral distortions in the photon-counting detector (PCD). Approach. In this work, we demonstrate a deep learning (DL) approach that compensates for spectral distortions in the PCD and improves accuracy in material decomposition by using decomposition maps provided by high-dose multi-energy-integrating detector (EID) data as training labels. We use a 3D U-net architecture and compare networks with PCD filtered back projection (FBP) reconstruction (FBP2Decomp), PCD iterative reconstruction (Iter2Decomp), and PCD decomposition (Decomp2Decomp) as the input. Main results. We found that our Iter2Decomp approach performs best, but DL outperforms matrix inversion decomposition regardless of the input. Compared to PCD matrix inversion decomposition, Iter2Decomp gives 27.50% lower root mean squared error (RMSE) in the iodine (I) map and 59.87% lower RMSE in the photoelectric effect (PE) map. In addition, it increases the structural similarity (SSIM) by 1.92%, 6.05%, and 9.33% in the I, Compton scattering (CS), and PE maps, respectively. When taking measurements from iodine and calcium vials, Iter2Decomp provides excellent agreement with multi-EID decomposition. One limitation is some blurring caused by our DL approach, with a decrease from 1.98 line pairs/mm at 50% modulation transfer function (MTF) with PCD matrix inversion decomposition to 1.75 line pairs/mm at 50% MTF when using Iter2Decomp. Significance. Overall, this work demonstrates that our DL approach with high-dose multi-EID derived decomposition labels is effective at generating more accurate material maps from PCD data. More accurate preclinical spectral PCCT imaging such as this could serve for developing nanoparticles that show promise in the field of theranostics (therapy and diagnostics).

Improved visualization of the wrist at lower radiation dose with photon-counting-detector CT.

To compare the image quality of ultra-high-resolution wrist CTs acquired on photon-counting detector CT versus conventional energy-integrating-detector CT systems. Participants were scanned on a photon-counting-detector CT systemafter clinical energy-integrating detector CTs. Energy-integrating-detector CT scan parameters: comb filter-based ultra-high-resolution mode, 120kV, 250 mAs, Ur70 or Ur73 kernel, 0.4- or 0.6-mm section thickness. Photon-counting-detector CT scan parameters: non-comb-based ultra-high-resolution mode, 120kV, 120 mAs, Br84 kernel, 0.4-mm section thickness. Two musculoskeletal radiologists blinded to CT system, scored specific osseous structures using a 5-point Likert scale (1 to 5). The Wilcoxon rank-sum test was used for statistical analysis of reader scores. Paired t-test was used to compare volume CT dose index, bone CT number, and image noise between CT systems. P-value < 0.05 was considered statistically significant. Twelve wrists (mean participant age 55.3 ± 17.8, 6 females, 6 males) were included. The mean volume CT dose index was lower for photon-counting detector CT (9.6 ± 0.1mGy versus 19.0 ± 6.7mGy, p < .001). Photon-counting-detector CT images had higher Likert scores for visualization of osseous structures (median score = 4, p < 0.001). The mean bone CT number was higher in photon-counting-detector CT images (1946 ± 77 HU versus 1727 ± 49 HU, p < 0.001). Conversely, there was no difference in the mean image noise of the two CT systems (63 ± 6 HU versus 61 ± 6 HU, p = 0.13). Ultra-high-resolution imaging with photon-counting-detector CT depicted wrist structures more clearly than conventional energy-integrating-detector CT despite a 49% radiation dose reduction.

Assessment of image quality in photon-counting detector computed tomography of the wrist – An ex vivo study

PurposeThe aim of this study was to evaluate the effect of reconstruction parameters on image quality in wrist imaging using photon-counting detector CT (PCD-CT) and to compare the results with images from an energy-integrating detector CT (EID-CT). MethodsTwelve cadaveric wrist specimens were examined using a prototype PCD-CT and a clinical EID-CT using similar radiation dose. Reconstruction parameters were matched between scanners. Also, sharper reconstruction kernels, a larger matrix size, and smaller slice thicknesses were evaluated for PCD-CT. Image noise, contrast-to-noise ratio (CNR) and image sharpness in trabecular structures were quantitatively measured. Image quality with respect to the visibility of cortical and trabecular bone structures was assessed by six radiologists using visual grading methods. ResultsImages obtained with PCD-CT had lower noise (42.6 ± 3.9 HU vs 75.1 ± 6.3 HU), higher CNR (38.9 ± 4.5 vs 19.0 ± 2.4) and higher trabecular sharpness (63.5 ± 6.0 vs 53.7 ± 8.5) than those obtained with EID-CT using similar scan and reconstruction parameters (p < 0.001). The image sharpness in trabecular structures was further improved by using sharper kernels, despite higher noise levels. Radiologists had a strong preference for PCD-CT images both in terms of spatial resolution and suitability for bone imaging. Visual grading analysis showed an improved visibility of cortical bone, trabeculae and nutritive canals (p < 0.005). ConclusionPCD-CT offers improved image quality regarding bone structures in the wrist relative to EID-CT systems, particularly when sharper reconstruction kernels, smaller slice thickness and a larger image matrix size are used.

Performance demonstration of a novel photon-counting CT for preclinical application

Photon-counting computed tomography (PC-CT) has attracted attention over the last few years as the next-generation CT technique that solves the problems encountered in clinical CT. In PC-CT, dark current and electronic noise can be reduced by setting the energy threshold to exceed the noise level, which leads to a low-dose scan. Furthermore, multiple energy thresholds realize multicolor CT imaging, which is not possible with clinical CT. Recently, we proposed a novel PC-CT system consisting of a multipixel photon counter (MPPC) coupled with a high-speed scintillator, performing simultaneous imaging of multiple contrast agents and estimate concentration. However, the PC-CT images obtained by our PC-CT system faces some limitations, such as degradation of image quality due to the lack of photon statistics and/or image resolution loss due to the pixel size of the detectors. In this study, the signal-to-noise ratio (SNR) of the PC-CT images was improved by applying machine-learning models, that is, U-Net and Noise2Noise, to the PC-CT images. In addition, a new imaging method was developed to acquire the high-resolution CT images required for clinical use. As a result, the resolution of the CT images improved from 1.04 mm to 0.77 mm. Finally, the visualization of contrast agents in plants was set as a challenge for the next step towards the clinical application of MPPC-based PC-CT. The results demonstrate that our PC-CT system can provide color imaging not only in phantom-based experiments, but also in plants close to an organism.

Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score-First Results of a Photon-Counting CT.

The coronary artery calcium score is an independent risk factor of the development of adverse cardiac events. The severity of coronary artery calcification may influence the myocardial texture. Due to higher spatial resolution and signal-to-noise ratio, new CT technologies such as PCCT may improve the detection of texture alterations depending on the severity of coronary artery calcification. In this retrospective, single-center, IRB-approved study, left ventricular myocardium was segmented and radiomics features were extracted using pyradiomics. The mean and standard deviation with the Pearson correlation coefficient for correlations of features were calculated and visualized as boxplots and heatmaps. Random forest feature selection was performed. Thirty patients (26.7% women, median age 58 years) were enrolled in the study. Patients were divided into two subgroups depending on the severity of coronary artery calcification (Agatston score 0 and Agatston score ≥ 100). Through random forest feature selection, a set of four higher-order features could be defined to discriminate myocardial texture between the two groups. When including the additional Agatston 1–99 groups as a validation, a severity-associated change in feature intensity was detected. A subset of radiomics features texture alterations of the left ventricular myocardium was associated with the severity of coronary artery calcification estimated by the Agatston score.

Photon-Counting Detectors in Computed Tomography: A Review

AbstractPhoton-counting computed tomography (CT) is a new technique that has the potential to revolutionize clinical CT and is predicted to be the next significant advancement. In recent years, tremendous research has been conducted to demonstrate the developments in hardware assembly and its working principles. The articles in this review were obtained by conducting a search of the MEDLINE database. Photon-counting detectors (PCDs) provide excellent quality diagnostic images with high spatial resolution, reduced noise, artifacts, increased contrast-to-noise ratio, and multienergy data acquisition as compared with conventionally used energy-integrating detector (EID). The search covered articles published between 2011 and 2021. The title and abstract of each article were reviewed as determined by the search strategy. From these, eligible studies and articles that provided the working and clinical application of PCDs were selected. This article aims to provide a systematic review of the basic working principles of PCDs, emphasize the uses and clinical applications of PCDs, and compare it to EIDs. It provides a nonmathematical explanation and understanding of photon-counting CT systems for radiologists as well as clinicians.

428 The Impact Of Virtual Monoenergetic Image Energy Levels On Pericoronary Adipose Tissue Attenuation Using Dual-source Photon-counting Detector Computed Tomography

Introduction: Increased pericoronary adipose tissue (PCAT) attenuation based on CT angiography (CTA) is a surrogate marker of perivascular inflammation and was shown to be associated with plaque development and vulnerability. The first-generation photon-counting detector CT (PCD-CT) has excellent temporal and spatial resolution and might allow for a more precise assessment of PCAT. PCD-CT allows tissue assessment in multiple energy ranges by providing virtual monoenergetic images (VMI). The aim of our study was to evaluate PCAT at different monoenergetic energy levels using a dual-source PCD-CT as compared with polychromatic images at 120 kV (T3D).

429 The Effect Of Quantum Iterative Reconstruction Levels On Coronary Calcium Scores Using Dual-source Photon-counting Detector Computed Tomography: In Vivo Experience

Introduction: Coronary calcium score is a well-established risk factor of adverse cardiac events. Novel dual-source photon-counting detector CT (PCD-CT) technology has been introduced in clinical practice recently, however data are limited regarding the impact of quantum iterative reconstruction (QIR) algorithm on coronary calcium score (CACS). We therefore aimed to assess the difference in CACS using images without QIR and QIR levels of 1 to 4.