Diagnostic performance of photon-counting detector CT for differentiation between adrenal adenomas and metastases.

OBJECTIVES: Aim of this study was to assess the value of virtual non-contrast (VNC) reconstructions in differentiating between adrenal adenomas and metastases on a photon-counting detector CT (PCD-CT). MATERIAL AND METHODS: Patients with adrenal masses and contrast-enhanced CT scans in portal venous phase were included. Image reconstructions were performed, including conventional VNC (VNCConv) and PureCalcium VNC (VNCPC), as well as virtual monochromatic images (VMI, 40-90 keV) and iodine maps. We analyzed images using semi-automatic segmentation of adrenal lesions and extracted quantitative data. Logistic regression models, non-parametric tests, Bland-Altman plots, and a random forest classifier were used for statistical analyses. RESULTS: The final study cohort consisted of 90 patients (36 female, mean age 67.8 years [range 39-87]) with adrenal lesions (45 adenomas, 45 metastases). Compared to metastases, adrenal adenomas showed significantly lower CT-values in VNCConv and VNCPC (p = 0.007). Mean difference between VNC and true non-contrast (TNC) was 17.67 for VNCConv and 14.85 for VNCPC. Random forest classifier and logistic regression models both identified VNCConv and VNCPC as the best discriminators. When using 26 HU as the threshold in VNCConv reconstructions, adenomas could be discriminated from metastases with a sensitivity of 86.7% and a specificity of 75.6%. CONCLUSION: VNC algorithms overestimate CT values compared to TNC in the assessment of adrenal lesions. However, they allow a reliable discrimination between adrenal adenomas and metastases and could be used in clinical routine in near future with an increased threshold (e.g., 26 HU). Further (multi-center) studies with larger patient cohorts and standardized protocols are required. CLINICAL RELEVANCE STATEMENT: VNC reconstructions overestimate CT values compared to TNC. Using a different threshold (e.g., 26 HU compared to the established 10 HU), VNC has a high diagnostic accuracy for the discrimination between adrenal adenomas and metastases. KEY POINTS: • Virtual non-contrast reconstructions may be promising tools to differentiate adrenal lesions and might save further diagnostic tests. • The conventional and a new calcium-preserving virtual non-contrast algorithm tend to systematically overestimate CT-values compared to true non-contrast images. • Therefore, increasing the established threshold for true non-contrast images (e.g., 10HU) may help to differentiate between adrenal adenomas and metastases on contrast-enhanced CT.

Heart rate sensitivity of virtual non-contrast calcium scores derived from photon counting detector CT data: a phantom study.

PURPOSE: To assess the reliability of virtual non-contrast (VNC) derived coronary artery calcium quantities in relation to heart rate and the VNC algorithm used compared to reference true non-contrast (TNC), considering several clinically established acquisition modes. MATERIAL AND METHODS: An ad hoc built coronary phantom containing four calcified lesions and an iodinated lumen was scanned using three cardiac acquisition modes three times within an anthropomorphic cardiac motion phantom simulating different heart rates (0, 60, 80, 100 bpm) and reconstructed with a conventional (VNCconv) and a calcium-sensitive (VNCpc) VNC algorithm. TNC reference was scanned at 0 bpm with non-iodinated lumen. Calcium scores were assessed in terms of number of lesions detected, Agatston and volume scores and global noise was measured. Paired t-test and Wilcoxon test were performed to test measurements for significant difference. RESULTS: For both VNC algorithms used, calcium levels or noise were not significantly affected by heart rate. Measurements on VNCpc reconstructions best reproduced TNC results, but with increased variability (Agatston scores at 0 bpm for TNC, VNCconv, and VNCpc were 47.1 ± 1.1, 6.7 ± 2.8 (p < 0.001), and 45.3 ± 7.6 (p > 0.05), respectively). VNC reconstructions showed lower noise levels compared to TNC, especially for VNCpc (noiseheart on TNC, VNCconv and VNCpc at 0 bpm was 5.0 ± 0.4, 4.5 ± 0.2, 4.2 ± 0.2). CONCLUSION: No significant heart rate dependence of VNC-based calcium scores was observed in an intra-reconstruction comparison. VNCpc reproduces TNC scores better than VNCconv without significant differences and decreased noise, however, with an increasing average deviation with rising heart rates. VNC-based CACS should be used with caution as the measures show higher variability compared to reference TNC and therefore hold the potential of incorrect risk categorization.

Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets.

OBJECTIVES: To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series. METHODS: Consecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNCConv) and a novel calcium-preserving (VNCPC) algorithm. EAT was segmented on TNC, VNCConv, VNCPC, and CCTA (CTA-30) series using thresholds of -190 to -30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA0). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data. RESULTS: EAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R2 > 0.9). Measurements on the novel VNCPC series showed the best correlation (R2 = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were -12%, -3%, -13%, and +10% for VNCConv, VNCPC, CTA-30, and CTA0 compared to TNC. Distribution of CT values on VNCPC showed less difference to TNC than on VNCConv (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016). CONCLUSIONS: VNCPC-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient's radiation dose. KEY POINTS: • Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R2>0.9). • Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values. • A novel VNC algorithm (VNCPC) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series.

Stent imaging on a clinical dual-source photon-counting detector CT system-impact of luminal attenuation and sharp kernels on lumen visibility.

OBJECTIVES: To assess the impact of scan modes and reconstruction kernels using a novel dual-source photon-counting detector CT (PCD-CT) on lumen visibility and sharpness of different stent sizes. METHODS: A phantom containing six balloon-expandable stents (2.5 to 9 mm diameter) in silicone tubing was scanned on a PCD-CT with standard (0.6 mm and 0.4 mm thicknesses) and ultra-high-resolution (0.2 mm thickness) modes. With the use of increasing contrast medium concentrations, densities of 0, 200, 400, and 600 HU were achieved. Standard-resolution scans were reconstructed using increasing sharpness kernels, using both polyenergetic quantitative soft tissue "conventional" ((Qr40c(0.6 mm), Qr40c(0.4 mm), Qr72c(0.2 mm)) and vascular (Bv) virtual monoenergetic reconstructions (Bv44m(0.4 mm), Bv60m(0.4 mm)) at 70 keV. In-stent lumen visibility, sharpness (max. ΔHU of the stent measured in profile plots), and in-stent noise (standard deviation of HU) were measured. RESULTS: In-stent lumen visibility was highest for Qr72c(0.2 mm) (86.5 ± 2.8% to 88.3 ± 2.6%) and in Bv60m(0.4 mm) reconstructions (77.3 ± 2.9 to 82.7 ± 2.5%). Lumen visibility was lowest in the smallest stent (2.5 mm) ranging from 54.1% in Qr40c(0.6 mm) to 74.1% in Qr72c(0.2 mm) and highest in the largest stent (9 mm) ranging from 93.8% in Qr40c(0.6 mm) to 99.1% in the Qr72c(0.2 mm) series. Lumen visibility decreased by 2.1% for every 200-HU increase in lumen attenuation. Max. ΔHU between stents and stent lumen was highest in Qr72c(0.2 mm) (ΔHU 892 ± 504 to 1526 ± 517) and Bv60m(0.4 mm) series (ΔHU 480 ± 357 to 1030 ± 344). Improvement of lumen visibility and sharpness in UHR and Bv60m(0.4 mm) series was strongest in smaller stent sizes. CONCLUSION: UHR acquisition mode and sharp reconstruction kernels on a novel PCD-CT system significantly improve in-stent lumen visibility and sharpness-especially for smaller stent sizes. KEY POINTS: • In-stent lumen visibility and sharpness of stents significantly improve using sharp reconstruction kernels (Bv60) and ultra-high-resolution mode in photon-counting detector computed tomography. • The observed improvement of stent-lumen visibility was highest in smaller stent sizes.

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

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

Discrimination of Hemorrhage and Contrast Media in a Head Phantom on Photon-Counting Detector CT Data.

In this anthropomorphic head phantom study, samples containing blood and contrast agent with concentrations ranging from 0 to 6 mg iodine per milliliter and another set of samples without blood for reference were scanned with a photon-counting detector CT using a standard cranial protocol. It was demonstrated that photon-counting detector CT can reliably distinguish hemorrhage and contrast media, including density determination of the latter. The technology promises to add value in several neuroimaging applications.

Optimal conspicuity of pancreatic ductal adenocarcinoma in virtual monochromatic imaging reconstructions on a photon-counting detector CT: comparison to conventional MDCT.

PURPOSE: To analyze the conspicuity of pancreatic ductal adenocarcinoma (PDAC) in virtual monoenergetic images (VMI) on a novel photon-counting detector CT (PCD-CT) in comparison to energy-integrating CT (EID-CT). METHODS: Inclusion criteria comprised initial diagnosis of PDAC (reference standard: histopathological analysis) and standardized contrast-enhanced CT imaging either on an EID-CT or a PCD-CT. Patients were excluded due to different histopathological diagnosis or missing tumor delineation on CT. On the PCD-CT, 40-190 keV VMI reconstructions were generated. Image noise, tumor-to-pancreas ratio (TPR) and contrast-to-noise ratio (CNR) were analyzed by ROI-based measurements in arterial and portal venous contrast phase. Two board-certified radiologist evaluated image quality and tumor delineation at both, EID-CT and PCD-CT (40 and 70 keV). RESULTS: Thirty-eight patients (mean age 70.4 years ± 10.3 [range 45-91], 27 males; PCD-CT: n=19, EID-CT: n=19) were retrospectively included. On the PCD-CT, tumor conspicuity (reflected by low TPR and high CNR) was significantly improved at low-energy VMI series (≤ 70 keV compared to > 70 keV), both in arterial and in portal venous contrast phase (P < 0.001), reaching the maximum at 40 keV. Comparison between PCD-CT and EID-CT showed significantly higher CNR on the PCD-CT in portal venous contrast phase at < 70 keV (P < 0.016). On the PCD-CT, tumor conspicuity was improved in portal venous contrast phase compared to arterial contrast phase especially at the lower end of the VMI spectrum (≤ 70 keV). Qualitative analysis revealed that tumor delineation is improved in 40 keV reconstructions compared to 70 keV reconstructions on a PCD-CT. CONCLUSION: PCD-CT VMI reconstructions (≤ 70 keV) showed significantly improved conspicuity of PDAC in quantitative and qualitative analysis in both, arterial and portal venous contrast phase, compared to EID-CT, which may be important for early detection of tumor tissue in clinical routine. Tumor delineation was superior in portal venous contrast phase compared to arterial contrast phase.

Photon-counting detector CT - first experiences in the field of musculoskeletal radiology.

The introduction of photon-counting detector CT (PCD-CT) marks a remarkable leap in innovation in CT imaging. The new detector technology allows X-rays to be converted directly into an electrical signal without an intermediate step via a scintillation layer and allows the energy of individual photons to be measured. Initial data show high spatial resolution, complete elimination of electronic noise, and steady availability of spectral image data sets. In particular, the new technology shows promise with respect to the imaging of osseous structures. Recently, PCD-CT was implemented in the clinical routine. The aim of this review was to summarize recent studies and to show our first experiences with photon-counting detector technology in the field of musculoskeletal radiology.We performed a literature search using Medline and included a total of 90 articles and reviews that covered recent experimental and clinical experiences with the new technology.In this review, we focus on (1) spatial resolution and delineation of fine anatomic structures, (2) reduction of radiation dose, (3) electronic noise, (4) techniques for metal artifact reduction, and (5) possibilities of spectral imaging. This article provides insight into our first experiences with photon-counting detector technology and shows results and images from experimental and clinical studies. · This review summarizes recent experimental and clinical studies in the field of photon-counting detector CT and musculoskeletal radiology.. · The potential of photon-counting detector technology in the field of musculoskeletal radiology includes improved spatial resolution, reduction in radiation dose, metal artifact reduction, and spectral imaging.. · PCD-CT enables imaging at lower radiation doses while maintaining or even enhancing spatial resolution, crucial for reducing patient exposure, especially in repeated or prolonged imaging scenarios.. · It offers promising results in reducing metal artifacts commonly encountered in orthopedic or dental implants, enhancing the interpretability of adjacent structures in postoperative and follow-up imaging.. · With its ability to routinely acquire spectral data, PCD-CT scans allow for material classification, such as detecting urate crystals in suspected gout or visualizing bone marrow edema, potentially reducing reliance on MRI in certain cases.. Bette S, Risch F, Becker J et al. Photon-counting detector CT - first experiences in the field of musculoskeletal radiology. Fortschr Röntgenstr 2024; DOI 10.1055/a-2312-6914.

Radiomics-Based Machine Learning Model for Diagnosis of Acute Pancreatitis Using Computed Tomography.

In the early diagnostic workup of acute pancreatitis (AP), the role of contrast-enhanced CT is to establish the diagnosis in uncertain cases, assess severity, and detect potential complications like necrosis, fluid collections, bleeding or portal vein thrombosis. The value of texture analysis/radiomics of medical images has rapidly increased during the past decade, and the main focus has been on oncological imaging and tumor classification. Previous studies assessed the value of radiomics for differentiating between malignancies and inflammatory diseases of the pancreas as well as for prediction of AP severity. The aim of our study was to evaluate an automatic machine learning model for AP detection using radiomics analysis. Patients with abdominal pain and contrast-enhanced CT of the abdomen in an emergency setting were retrospectively included in this single-center study. The pancreas was automatically segmented using TotalSegmentator and radiomics features were extracted using PyRadiomics. We performed unsupervised hierarchical clustering and applied the random-forest based Boruta model to select the most important radiomics features. Important features and lipase levels were included in a logistic regression model with AP as the dependent variable. The model was established in a training cohort using fivefold cross-validation and applied to the test cohort (80/20 split). From a total of 1012 patients, 137 patients with AP and 138 patients without AP were included in the final study cohort. Feature selection confirmed 28 important features (mainly shape and first-order features) for the differentiation between AP and controls. The logistic regression model showed excellent diagnostic accuracy of radiomics features for the detection of AP, with an area under the curve (AUC) of 0.932. Using lipase levels only, an AUC of 0.946 was observed. Using both radiomics features and lipase levels, we showed an excellent AUC of 0.933 for the detection of AP. Automated segmentation of the pancreas and consecutive radiomics analysis almost achieved the high diagnostic accuracy of lipase levels, a well-established predictor of AP, and might be considered an additional diagnostic tool in unclear cases. This study provides scientific evidence that automated image analysis of the pancreas achieves comparable diagnostic accuracy to lipase levels and might therefore be used in the future in the rapidly growing era of AI-based image analysis.

Virtual non-contrast series of photon-counting detector computed tomography angiography for aortic valve calcium scoring.

The aim of our study was to evaluate two different virtual non-contrast (VNC) algorithms applied to photon counting detector (PCD)-CT data in terms of noise, effectiveness of contrast media subtraction and aortic valve calcium (AVC) scoring compared to reference true non-contrast (TNC)-based results. Consecutive patients underwent TAVR planning examination comprising a TNC scan, followed by a CTA of the heart. VNC series were reconstructed using a conventional (VNCconv) and a calcium-preserving (VNCpc) algorithm. Noise was analyzed by means of the standard deviation of CT-values within the left ventricle. To assess the effectiveness of contrast media removal, heart volumes were segmented and the proportion of their histograms > 130HU was taken. AVC was measured by Agatston and volume score. 41 patients were included. Comparable noise levels to TNC were achieved with all VNC reconstructions. Contrast media was effectively virtually removed (proportions > 130HU from 81% to < 1%). Median calcium scores derived from VNCconv underestimated TNC-based scores (up to 74%). Results with smallest absolute difference to TNC were obtained with VNCpc reconstructions (0.4 mm, Br36, QIR 4), but with persistent significant underestimation (median 29%). Both VNC algorithms showed near-perfect (r²>0.9) correlation with TNC. Thin-slice VNC reconstructions provide equivalent noise levels to standard thick-slice TNC series and effective virtual removal of iodinated contrast. AVC scoring was feasible on both VNC series, showing near-perfect correlation, but with significant underestimation. VNCpc with 0.4 mm slices and Br36 kernel at QIR 4 gave the most comparable results and, with further advances, could be a promising replacement for additional TNC.

A direct comparison of multi-energy x-ray and proton CT for imaging and relative stopping power estimation of plastic andex-vivophantoms.

Objective.Proton therapy administers a highly conformal dose to the tumour region, necessitating accurate prediction of the patient's 3D map of proton relative stopping power (RSP) compared to water. This remains challenging due to inaccuracies inherent in single-energy computed tomography (SECT) calibration. Recent advancements in spectral x-ray CT (xCT) and proton CT (pCT) have shown improved RSP estimation compared to traditional SECT methods. This study aims to provide the first comparison of the imaging and RSP estimation performance among dual-energy CT (DECT) and photon-counting CT (PCCT) scanners, and a pCT system prototype.Approach.Two phantoms were scanned with the three systems for their performance characterisation: a plastic phantom, filled with water and containing four plastic inserts and a wood insert, and a heterogeneous biological phantom, containing a formalin-stabilised bovine specimen. RSP maps were generated by converting CT numbers to RSP using a calibration based on low- and high-energy xCT images, while pCT utilised a distance-driven filtered back projection algorithm for RSP reconstruction. Spatial resolution, noise, and RSP accuracy were compared across the resulting images.Main results.All three systems exhibited similar spatial resolution of around 0.54 lp/mm for the plastic phantom. The PCCT images were less noisy than the DECT images at the same dose level. The lowest mean absolute percentage error (MAPE) of RSP,(0.28±0.07)%, was obtained with the pCT system, compared to MAPE values of(0.51±0.08)%and(0.80±0.08)%for the DECT- and PCCT-based methods, respectively. For the biological phantom, the xCT-based methods resulted in higher RSP values in most of the voxels compared to pCT.Significance.The pCT system yielded the most accurate estimation of RSP values for the plastic materials, and was thus used to benchmark the xCT calibration performance on the biological phantom. This study underlined the potential benefits and constraints of utilising such a novelex-vivophantom for inter-centre surveys in future.

Radiomics signature for automatic hydronephrosis detection in unenhanced Low-Dose CT.

PURPOSE: To investigate the diagnostic performance of an automatic pipeline for detection of hydronephrosis on kidney's parenchyma on unenhanced low-dose CT of the abdomen. METHODS: This retrospective study included 95 patients with confirmed unilateral hydronephrosis in an unenhanced low-dose CT of the abdomen. Data were split into training (n = 67) and test (n = 28) cohorts. Both kidneys for each case were included in further analyses, whereas the kidney without hydronephrosis was used as control. Using the training cohort, we developed a pipeline consisting of a deep-learning model for automatic segmentation (a Convolutional Neural Network based on nnU-Net architecture) of the kidney's parenchyma and a radiomics classifier to detect hydronephrosis. The models were assessed using standard classification metrics, such as area under the ROC curve (AUC), sensitivity and specificity, as well as semantic segmentation metrics, including Dice coefficient and Jaccard index. RESULTS: Using manual segmentation of the kidney's parenchyma, hydronephrosis can be detected with an AUC of 0.84, a sensitivity of 75% and a specificity of 82%, a PPV of 81% and a NPV of 77%. Automatic kidney segmentation achieved a mean Dice score of 0.87 and 0.91 for the right and left kidney, respectively. Additionally, automatic segmentation achieved an AUC of 0.83, a sensitivity of 86%, specificity of 64%, PPV of 71%, and NPV of 82%. CONCLUSION: Our proposed radiomics signature using automatic kidney's parenchyma segmentation allows for accurate hydronephrosis detection on unenhanced low-dose CT scans of the abdomen independently of widened renal pelvis. This method could be used in clinical routine to highlight hydronephrosis to radiologists as well as clinicians, especially in patients with concurrent parapelvic cysts and might reduce time and costs associated with diagnosing hydronephrosis.

Multiphase photon counting detector CT data sets - Which combination of contrast phase and virtual non-contrast algorithm is best suited to replace true non-contrast series in the assessment of active bleeding?

PURPOSE: Aim of this study was to determine which virtual non-contrast (VNC) reconstruction algorithm, applied to which contrast phase of computed tomography angiography, best matches true non-contrast (TNC) images in the assessment of active bleeding. METHOD: Patients who underwent a triphasic scan (pre-contrast, arterial, portal venous contrast) on a photon-counting detector CT (PCD-CT) (120 kV, image quality level 68) with suspected active (tumor, postoperative, spontaneous or other) bleeding were retrospectively included in this study. Conventional (VNCConv) and a calcium-preserving VNC algorithm (VNCPC) were derived from both arterial (art) and portal venous (pv) contrast scans, and analyzed quantitatively and qualitatively by two independent and blinded raters. RESULTS: 40 patients (22 female, mean age 76 years) were included. Measurements of CT values showed significant albeit small differences between TNC and VNC for most analyzed tissue regions without clear superiority of a VNC algorithm or contrast phase (e.g. ΔHU fat TNC to VNCPCpv 3.1 HU). However, qualitative analysis showed a preference to VNCPCpv in terms of image quality (on a 5-point Likert scale VNCConvart = 3.5 ± 0.8, VNCPCart = 3.7 ± 0.7, VNCConvpv = 3.7 ± 0.7, VNCPCpv = 3.8 ± 0.7) and residual calcium contrast (VNCConvart = 3.0 ± 0.8, VNCPCart = 3.5 ± 0.7, VNCConvpv = 3.6 ± 0.7, VNCPCpv = 3.9 ± 0.6). CONCLUSIONS: When multiple post-contrast phases are available, VNCPC series based on portal venous phase are the most suitable replacement for an additional pre-contrast scan, with the prospect of a significant reduction in patient radiation dose.

Improved Thermal Sensitivity Using Virtual Monochromatic Imaging Derived from Photon Counting Detector CT Data Sets: Ex Vivo Results of CT-Guided Cryoablation in Porcine Liver.

PURPOSE: To investigate differences in thermal sensitivity of virtual monoenergetic imaging (VMI) series generated from photon-counting detector (PCD) CT data sets, regarding their use to improve discrimination of the ablation zone during percutaneous cryoablation. MATERIALS AND METHODS: CT-guided cryoablation was performed using an ex vivo model of porcine liver on a PCD-CT system. The ablation zone was imaged continuously for 8 min by acquiring a CT scan every 5 s. Tissue temperature was measured using fiberoptic temperature probes placed parallel to the cryoprobe. CT-values and noise were measured at the tip of the temperature probes on each scan and on VMI series from 40 to 130 keV. Correlation of CT-values and temperature was assessed using linear regression analyses. RESULTS: For the whole temperature range of [- 40, + 20] °C, we observed a linear correlation between CT-values and temperature in reference 70 keV images (R2 = 0.60, p < 0.001) with a thermal sensitivity of 1.4HU/°C. For the most dynamic range of [- 15, + 20] °C, the sensitivity increased to 2.4HU/°C (R2 = 0.50, p < 0.001). Using VMI reconstructions, the thermal sensitivity increased from 1.4 HU/°C at 70 keV to 1.5, 1.7 and 2.0HU/°C at 60, 50 and 40 keV, respectively (range [- 40, + 20] °C). For [- 15, + 20]°C, the thermal sensitivity increased from 2.4HU/°C at 70 keV to 2.5, 2.6 and 2.7HU/°C at 60, 50 and 40 keV, respectively. Both CT-values and noise also increased with decreasing VMI keV-levels. CONCLUSION: During CT-guided cryoablation of porcine liver, low-keV VMI reconstructions derived from PCD-CT data sets exhibit improved thermal sensitivity being highest between + 20 and - 15 °C.

Image Characteristics of Virtual Non-Contrast Series Derived from Photon-Counting Detector Coronary CT Angiography-Prerequisites for and Feasibility of Calcium Quantification.

In photon-counting detector CT (PCD-CT), coronary artery calcium scoring (CACS) can be performed using virtual non-contrast (VNC) series derived from coronary CT angiography (CCTA) datasets. Our study analyzed image characteristics of VNC series in terms of the efficacy of virtual iodine "removal" and image noise to determine whether the prerequisites for calcium quantification were satisfied. We analyzed 38 patients who had undergone non-enhanced CT followed by CCTA on a PCD-CT. VNC reconstructions were performed at different settings and algorithms (conventional VNCConv; PureCalcium VNCPC). Virtual iodine "removal" was investigated by comparing histograms of heart volumes. Noise was assessed within the left ventricular cavity. Calcium was quantified on the true non-contrast (TNC) and all VNC series. The histograms were comparable for TNC and all VNC. Image noise between TNC and all VNC differed slightly but significantly. VNCConv CACS showed a significant underestimation regardless of the reconstruction setting, while VNCPC CACS were comparable to TNC. Correlations between TNC and VNC were excellent, with a higher predictive accuracy for VNCPC. In conclusion, the iodine contrast can be effectively subtracted from CCTA datasets. The remaining VNC series satisfy the requirements for CACS, yielding results with excellent correlation compared to TNC-based CACS and high predicting accuracy.

Spectral metal artifact reduction after posterior spinal fixation in photon-counting detector CT datasets.

PURPOSE: To investigate the usefulness of virtual monoenergetic image (VMI) reconstructions derived from scans on a novel photon-counting detector CT (PCD-CT) for artifact reduction in patients after posterior spinal fixation. METHODS: This retrospective cohort study included 23 patients status post posterior spinal fixation. Subjects were scanned on a novel PCD-CT (NAEOTOM Alpha, Siemens Healthineers, Erlangen, Germany) as part of routine clinical care. 14 sets of VMI reconstructions were derived in 10 keV increments for the interval 60-190 keV. The mean and the standard deviation (SD) of CT-values in 12 defined locations around a pair of pedicle screws on one vertebral level and the SD of homogenous fat were measured and used to calculate an artifact index (AIx). RESULTS: Averaged over all regions, the lowest AIx was observed at VMI levels of 110 keV (32.5 (27.8-37.9)) which was significantly different from those of VMIs ≤ 90 keV (p < 0.001) or ≥160 keV (p < 0.015), respectively. Overall AIx values increased in both lower- and higher-keV levels. Regarding individual locations, either a monotonous AIx-decrease for increasing keV values or an AIx-minimum in intermediate-keV levels (100-140 keV) was found. In locations adjacent to larger metal parts, the increase of AIx values at the high-end of the keV spectrum was mainly explained by a reappearance of streak artifacts. CONCLUSION: Our findings suggest that 110 keV is the optimal VMI setting for overall artifact suppression. In specific anatomical regions, however, slight adjustments towards higher-keV levels may provide better results.

Artifact Reduction From Dental Material in Photon-Counting Detector Computed Tomography Data Sets Based on High-keV Monoenergetic Imaging and Iterative Metal Artifact Reduction Reconstructions-Can We Combine the Best of Two Worlds?

OBJECTIVE: The aim of this study was to compare the effectiveness of common strategies for artifact reduction of dental material in photon-counting detector computed tomography data sets. MATERIALS AND METHODS: Patients with dental material who underwent clinically indicated CT of the neck were enrolled. Image series were reconstructed using a standard and sharp kernel, with and without iterative metal artifact reduction (IMAR) (Qr40, Qr40 IMAR , Qr60, Qr60 IMAR ) at different virtual monoenergetic imaging (VMI) levels (40-190 keV). On representative slice positions with and without dental artifacts, mean and standard deviation of CT values were measured in all series at identical locations. The mean absolute error of CT values ( ) and the artifact index (AIX) were calculated and analyzed focusing on 3 main comparisons: ( a ) different VMI levels versus 70 keV, ( b ) standard versus sharp kernel, and ( c ) nonuse or use of IMAR reconstruction. The Wilcoxon test was used to assess differences for nonparametric data. RESULTS: The final cohort comprised 50 patients. Artifact measures decreased for VMI levels >70 keV, yet only significantly so for reconstructions using IMAR (maximum reduction, 25%). The higher image noise of the sharp versus standard kernel is reflected in higher AIX values and is more pronounced in IMAR series (maximum increase, 38%). The most profound artifact reduction was observed for IMAR reconstructions (maximum reduction : 84%; AIX: 90%). CONCLUSIONS: Metal artifacts caused by large amounts of dental material can be substantially reduced by IMAR, regardless of kernel choice or VMI settings. Increasing the keV level of VMI series, on the other hand, only slightly reduces dental artifacts; this effect, however, is additive to the benefit conferred by IMAR reconstructions.

Anemia detection and quantification in contrast-enhanced CT scans on a novel photon-counting detector CT: A prospective proof-of-concept study.

PURPOSE: To correlate CT values of the blood pool on VNC series with serum hemoglobin values for the detection of anemia in oncologic patients undergoing contrast-enhanced PCD-CT scans. METHODS: This prospective study (NCT04989192) included consecutive oncologic patients undergoing contrast-enhanced CT on a novel PCD-CT system between 08/2021 and 01/2022. The interval between complete blood count (CBC) and CT scan acquisition had to be no more than seven days. CT-values of the blood pool were measured on 70 keV VMI series (CT-values(BP)70keV) and on VNC series (CT-values(BP)VNC) at five anatomic positions (left atrium, left ventricle, main pulmonary artery, ascending and descending aorta) and averaged per patient. Pearson correlation analyses and ROC analyses were performed to identify relations between CT-values(BP)VNC, CBC parameters, and degrees of anemia as defined by the WHO (no anemia, mild, moderate, severe anemia). RESULTS: A total of 329 patients (age 68 ± 12 years; 200 men) were included. CT-values(BP)VNC showed a strong linear correlation to serum hemoglobin (r2 = 0.80, p <.001) and hematocrit (r2 = 0.76, p <.001) and were significantly different between anemia subgroups in both women and men (ΔHU: 3.5-11.4; all p <.01). ROC analyses yielded high diagnostic performance for the identification of patients without anemia, patients without and with mild anemia, and patients with severe anemia using gender-specific cutoffs for CT-value(BP)VNC (all AUC's > 0.90). CONCLUSIONS: The spectral information inherent in PCD-CT acquisitions allows the detection and quantification of anemia in contrast-enhanced CT acquisitions of oncologic patients with high diagnostic accuracy.

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.

Low-dose CT of the abdomen: Initial experience on a novel photon-counting detector CT and comparison with energy-integrating detector CT.

PURPOSE: To analyze the quantitative and qualitative image quality of low-dose CT scans of the abdomen on a novel photon-counting detector CT (PCD-CT) in comparison with a traditional energy-integrating detector CT (EID-CT). METHODS: Consecutive patients with clinically indicated low-dose CT were scanned on a PCD-CT and compared with a BMI-matched EID-CT-cohort scanned during the same timeframe. Radiation dose, image noise, and signal-to-noise ratio (SNR) were measured for each patient. Furthermore, image quality and conspicuity of abdominal structures (adrenal glands, mesenteric vessels, ureters, and renal pelvis) were assessed on 5-point Likert-scales (1 = very poor quality/not detectable; 5 = excellent quality/differentiability). RESULTS: Twenty patients (mean age 46.2 [range: 19-77]; 13 men) were included. Image noise was significantly lower (24.9 ± 3.3 vs. 31.4 ± 5.6 SD HU, p < 0.001) and SNR significantly higher (2.1 ± 0.3 vs. 1.5 ± 0.4; p < 0.001) on the PCD-CT. Subjective image quality was substantially higher (4.0 ± 0.3 vs. 3.1 ± 0.6; p < 0.001) and conspicuity better for the renal pelvis, ureters, and mesenteric vessels on the PCD-CT. There was no significant difference in the conspicuity of the adrenal glands. With increasing BMI (1st-4th BMI quartile), noise increased, and SNR decreased more strongly on the EID-CT than on the PCD-CT (ΔNoise: 39% vs. 2%, ΔSNR: -33% vs. -7% for EID-CT vs. PCD-CT, respectively) while radiation dose increased comparably (70 vs. 59%). CONCLUSIONS: Low-dose CT scans of the abdomen performed on a novel PCD-CT exhibit reduced noise, higher SNR, increased subjective image quality, and superior conspicuity of abdominal fine structures compared to scans in comparable patients on an EID-CT.