Photon-Counting Detector CT for Kidney Stone Detection in Excretory Phase CT-Comparison Between Virtual Non-contrast and Virtual Non-iodine Reconstructions in a 3D Printed Kidney Phantom.

RATIONALE AND OBJECTIVES: To evaluate and compare the effectiveness of contrast media subtraction and kidney stone detection between a virtual non-iodine reconstruction algorithm (VNI; PureCalcium) and a virtual non-contrast (VNC) algorithm in excretory phase photon-counting detector computed tomography (PCD-CT), using a 3D printed kidney phantom under various tube voltages and radiation doses. MATERIALS AND METHODS: A 3D-printed kidney phantom, holding Calcium Oxalate (CaOx) and uric acid stones within contrast-enhanced calyces, was created. The calyx density mirrored the average density observed in 200 excretory phase patients (916 HU at 110 kV). Imaging was conducted on a clinical dual-source PCD-CT at 120 kV and 140 kV, with radiation doses set at 5, 10, and 15 mGy. VNI and VNC algorithms were applied. Two blinded readers evaluated the image quality, along with the degree of contrast media and kidney stone subtraction, using visual scales. Krippendorff's alpha was calculated to determine inter-reader agreement, and the Chi-squared test was employed for comparing ordinal data. RESULTS: Reader 2 rated overall image quality higher for VNI than VNC (4.90 vs. 4.00; P < .05), while Reader 1 found no significant difference (4.96 vs. 5.00; P > .05). Substantial agreement was observed between readers for contrast media subtraction in both VNC and VNI (Krippendorff's alpha range: 0.628-0.748). Incomplete contrast media subtraction occurred more frequently with VNI for both readers (Reader 1: 29% vs. 15%; P < .05; Reader 2: 24% vs. 20%; P > .05). Uric acid and smaller stones (<5 mm) were more likely to be subtracted than CaOx and larger stones in both VNC and VNI. Overall, a higher rate of stone subtraction was noted with VNI compared to VNC (Reader 1: 22% vs. 16%; Reader 2: 25% vs. 10%; P < .05). Neither radiation dose nor tube voltage significantly influenced stone subtraction (P > .05). CONCLUSION: VNC demonstrated greater accuracy than VNI for contrast media subtraction and kidney stone visibility. Radiation dose and tube voltage had no significant impact. Nonetheless, both algorithms still exhibited frequent incomplete contrast media subtraction and partial kidney stone subtraction.

Multi-Energy Low-Kiloelectron Volt versus Single-Energy Low-Kilovolt Images for Endoleak Detection at CT Angiography of the Aorta.

Purpose To compare image quality, diagnostic performance, and conspicuity between single-energy and multi-energy images for endoleak detection at CT angiography (CTA) after endovascular aortic repair (EVAR). Materials and Methods In this single-center prospective randomized controlled trial, individuals undergoing CTA after EVAR between August 2020 and May 2022 were allocated to imaging using either low-kilovolt single-energy images (SEI; 80 kV, group A) or low-kiloelectron volt virtual monoenergetic images (VMI) at 40 and 50 keV from multi-energy CT (80/Sn150 kV, group B). Scan protocols were dose matched (volume CT dose index: mean, 4.5 mGy ± 1.8 [SD] vs 4.7 mGy ± 1.3, P = .41). Contrast-to-noise ratio (CNR) was measured. Two expert radiologists established the reference standard for the presence of endoleaks. Detection and conspicuity of endoleaks and subjective image quality were assessed by two different blinded radiologists. Interreader agreement was calculated. Nonparametric statistical tests were used. Results A total of 125 participants (mean age, 76 years ± 8; 103 men) were allocated to groups A (n = 64) and B (n = 61). CNR was significantly lower for 40-keV VMI (mean, 19.1; P = .048) and 50-keV VMI (mean, 16.8; P < .001) as compared with SEI (mean, 22.2). In total, 45 endoleaks were present (A: 23 vs B: 22). Sensitivity for endoleak detection was higher for SEI (82.6%, 19 of 23; P = .88) and 50-keV VMI (81.8%, 18 of 22; P = .90) as compared with 40-keV VMI (77.3%, 17 of 22). Specificity was comparable among groups (SEI: 92.7%, 38 of 41; both VMI energies: 92.3%, 35 of 38; P = .99), with an interreader agreement of 1. Conspicuity of endoleaks was comparable between SEI (median, 2.99) and VMI (both energies: median, 2.87; P = .04). Overall subjective image quality was rated significantly higher for SEI (median, 4 [IQR, 4-4) as compared with 40 and 50 keV (both energies: median, 4 [IQR, 3-4]; P < .001). Conclusion SEI demonstrated higher image quality and comparable diagnostic accuracy as compared with 50-keV VMI for endoleak detection at CTA after EVAR. Keywords: Aneurysms, CT, CT Angiography, Vascular, Aorta, Technology Assessment, Multidetector CT, Abdominal Aortic Aneurysms, Endoleaks, Perigraft Leak Supplemental material is available for this article. © RSNA, 2024.

Photon-Counting Detector CT for Liver Lesion Detection-Optimal Virtual Monoenergetic Energy for Different Simulated Patient Sizes and Radiation Doses.

OBJECTIVES: The aim of this study was to evaluate the optimal energy level of virtual monoenergetic images (VMIs) from photon-counting detector computed tomography (CT) for the detection of liver lesions as a function of phantom size and radiation dose. MATERIALS AND METHODS: An anthropomorphic abdominal phantom with liver parenchyma and lesions was imaged on a dual-source photon-counting detector CT at 120 kVp. Five hypoattenuating lesions with a lesion-to-background contrast difference of -30 HU and -45 HU and 3 hyperattenuating lesions with +30 HU and +90 HU were used. The lesion diameter was 5-10 mm. Rings of fat-equivalent material were added to emulate medium- or large-sized patients. The medium size was imaged at a volume CT dose index of 5, 2.5, and 1.25 mGy and the large size at 5 and 2.5 mGy, respectively. Each setup was imaged 10 times. For each setup, VMIs from 40 to 80 keV at 5 keV increments were reconstructed with quantum iterative reconstruction at a strength level of 4 (QIR-4). Lesion detectability was measured as area under the receiver operating curve (AUC) using a channelized Hotelling model observer with 10 dense differences of Gaussian channels. RESULTS: Overall, highest detectability was found at 65 and 70 keV for both hypoattenuating and hyperattenuating lesions in the medium and large phantom independent of radiation dose (AUC range, 0.91-1.0 for the medium and 0.94-0.99 for the large phantom, respectively). The lowest detectability was found at 40 keV irrespective of the radiation dose and phantom size (AUC range, 0.78-0.99). A more pronounced reduction in detectability was apparent at 40-50 keV as compared with 65-75 keV when radiation dose was decreased. At equal radiation dose, detection as a function of VMI energy differed stronger for the large size as compared with the medium-sized phantom (12% vs 6%). CONCLUSIONS: Detectability of hypoattenuating and hyperattenuating liver lesions differed between VMI energies for different phantom sizes and radiation doses. Virtual monoenergetic images at 65 and 70 keV yielded highest detectability independent of phantom size and radiation dose.

Fully automated computational measurement of noise in positron emission tomography.

OBJECTIVES: To introduce an automated computational algorithm that estimates the global noise level across the whole imaging volume of PET datasets. METHODS: [18F]FDG PET images of 38 patients were reconstructed with simulated decreasing acquisition times (15-120 s) resulting in increasing noise levels, and with block sequential regularized expectation maximization with beta values of 450 and 600 (Q.Clear 450 and 600). One reader performed manual volume-of-interest (VOI) based noise measurements in liver and lung parenchyma and two readers graded subjective image quality as sufficient or insufficient. An automated computational noise measurement algorithm was developed and deployed on the whole imaging volume of each reconstruction, delivering a single value representing the global image noise (Global Noise Index, GNI). Manual noise measurement values and subjective image quality gradings were compared with the GNI. RESULTS: Irrespective of the absolute noise values, there was no significant difference between the GNI and manual liver measurements in terms of the distribution of noise values (p = 0.84 for Q.Clear 450, and p = 0.51 for Q.Clear 600). The GNI showed a fair to moderately strong correlation with manual noise measurements in liver parenchyma (r = 0.6 in Q.Clear 450, r = 0.54 in Q.Clear 600, all p < 0.001), and a fair correlation with manual noise measurements in lung parenchyma (r = 0.52 in Q.Clear 450, r = 0.33 in Q.Clear 600, all p < 0.001). Classification performance of the GNI for subjective image quality was AUC 0.898 for Q.Clear 450 and 0.919 for Q.Clear 600. CONCLUSION: An algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. CLINICAL RELEVANCE STATEMENT: An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking of clinical PET imaging within and across institutions. KEY POINTS: • Noise is an important quantitative marker that strongly impacts image quality of PET images. • An automated computational noise measurement algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets. • An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking as well as protocol harmonization.

Metal Artifact Reduction in Photon-Counting Detector CT: Quantitative Evaluation of Artifact Reduction Techniques.

OBJECTIVES: With the introduction of clinical photon-counting detector computed tomography (PCD-CT) and its novel reconstruction techniques, a quantitative investigation of different acquisition and reconstruction settings is necessary to optimize clinical acquisition protocols for metal artifact reduction. MATERIALS AND METHODS: A multienergy phantom was scanned on a clinical dual-source PCD-CT (NAEOTOM Alpha; Siemens Healthcare GmbH) with 4 different central inserts: water-equivalent plastic, aluminum, steel, and titanium. Acquisitions were performed at 120 kVp and 140 kVp (CTDIvol 10 mGy) and reconstructed as virtual monoenergetic images (VMIs; 110-150 keV), as T3D, and with the standard reconstruction "none" (70 keV VMI) using different reconstruction kernels (Br36, Br56) and with as well as without iterative metal artifact reduction (iMAR). Metal artifacts were quantified, calculating relative percentages of metal artifacts. Mean CT numbers of an adjacent water-equivalent insert and different tissue-equivalent inserts were evaluated, and eccentricity of metal rods was measured. Repeated-measures analysis of variance was performed for statistical analysis. RESULTS: Metal artifacts were most prevalent for the steel insert (12.6% average artifacts), followed by titanium (4.2%) and aluminum (1.0%). The strongest metal artifact reduction was noted for iMAR (with iMAR: 1.4%, without iMAR: 10.5%; P < 0.001) or VMI (VMI: 110 keV 2.6% to 150 keV 3.3%, T3D: 11.0%, and none: 16.0%; P < 0.001) individually, with best results when combining iMAR and VMI at 110 keV (1.2%). Changing acquisition tube potential (120 kV: 6.6%, 140 kV: 5.2%; P = 0.33) or reconstruction kernel (Br36: 5.5%, Br56: 6.4%; P = 0.17) was less effective. Mean CT numbers and standard deviations were significantly affected by iMAR (with iMAR: -3.0 ± 21.5 HU, without iMAR: -8.5 ± 24.3 HU; P < 0.001), VMI (VMI: 110 keV -3.6 ± 21.6 HU to 150 keV -1.4 ± 21.2 HU, T3D: -11.7 ± 23.8 HU, and none: -16.9 ± 29.8 HU; P < 0.001), tube potential (120 kV: -4.7 ± 22.8 HU, 140 kV: -6.8 ± 23.0 HU; P = 0.03), and reconstruction kernel (Br36: -5.5 ± 14.2 HU, Br56: -6.8 ± 23.0 HU; P < 0.001). Both iMAR and VMI improved quantitative CT number accuracy and metal rod eccentricity for the steel rod, but iMAR was of limited effectiveness for the aluminum rod. CONCLUSIONS: For metal artifact reduction in PCD-CT, a combination of iMAR and VMI at 110 keV demonstrated the strongest artifact reduction of the evaluated options, whereas the impact of reconstruction kernel and tube potential was limited.

Cardiac Virtual Noncontrast Images for Calcium Quantification with Photon-counting Detector CT.

Purpose: To assess the accuracy of aortic valve calcium (AVC), mitral annular calcium (MAC), and coronary artery calcium (CAC) quantification and risk stratification using virtual noncontrast (VNC) images from late enhancement photon-counting detector CT as compared with true noncontrast images. Materials and Methods: This retrospective, institutional review board-approved study evaluated patients undergoing photon-counting detector CT between January and September 2022. VNC images were reconstructed from late enhancement cardiac scans at 60, 70, 80, and 90 keV using quantum iterative reconstruction (QIR) strengths of 2-4. AVC, MAC, and CAC were quantified on VNC images and compared with quantification of AVC, MAC, and CAC on true noncontrast images using Bland-Altman analyses, regression models, intraclass correlation coefficients (ICC), and Wilcoxon tests. Agreement between severe aortic stenosis likelihood categories and CAC risk categories determined from VNC and true noncontrast images was assessed by weighted κ analysis. Results: Ninety patients were included (mean age, 80 years ± 8 [SD]; 49 male patients). Scores were similar on true noncontrast images and VNC images at 80 keV for AVC and MAC, regardless of QIR strengths, and VNC images at 70 keV with QIR 4 for CAC (all P > .05). The best results were achieved using VNC images at 80 keV with QIR 4 for AVC (mean difference, 3; ICC = 0.992; r = 0.98) and MAC (mean difference, 6; ICC = 0.998; r = 0.99), and VNC images at 70 keV with QIR 4 for CAC (mean difference, 28; ICC = 0.996; r = 0.99). Agreement between calcification categories was excellent on VNC images at 80 keV for AVC (κ = 0.974) and on VNC images at 70 keV for CAC (κ = 0.967). Conclusion: VNC images from cardiac photon-counting detector CT enables patient risk stratification and accurate quantification of AVC, MAC, and CAC.Keywords: Coronary Arteries, Aortic Valve, Mitral Valve, Aortic Stenosis, Calcifications, Photon-counting Detector CT Supplemental material is available for this article © RSNA, 2023.

Impact of radiation dose on the detection of interstitial lung changes and image quality in low-dose chest CT - Assessment in multiple dose levels from a single patient scan.

PURPOSE: To assess image quality and detectability of interstitial lung changes using multiple radiation doses from the same chest CT scan of patients with suspected interstitial lung disease (ILD). METHOD: Retrospective study of consecutive adult patients with suspected ILD receiving unenhanced chest CT as single-energy dual-source acquisition at 100 kVp (Dual-split mode). 67% and 33% of the overall tube current time product were assigned to tube A and B, respectively. 100%-dose was 2.34 ± 0.97 mGy. Five different radiation doses (100%, 67%, 45%, 39%, 33%) were reconstructed from this single acquisition using linear-blending technique. Two blinded radiologists assessed reticulations, ground-glass opacities (GGO) and honeycombing as well as subjective image noise. Percentage agreement (PA) as compared to 100%-dose were calculated. Non-parametric statistical tests were used. RESULTS: A total of 228 patients were included (61.2 ± 14.6 years,146 female). PA was highest for honeycombing (>96%) and independent of dose reduction (P > 0.8). PA for reticulations and GGO decreased when reducing the radiation dose from 100% to 67% for both readers (reticulations: 83.3% and 93.9%; GGO: 87.7% and 79.8% for reader 1 and 2, respectively). Additional dose reduction did not significantly change PA for both readers (all P > 0.05). Subjective image noise increased with decreasing radiation dose (Spearman Rho of ρ = 0.34 and ρ = 0.53 for reader 1 and 2, respectively, P < 0.001). CONCLUSIONS: Radiation dose reduction had a stronger impact on subtle interstitial lung changes. Detectability decreased with initial dose reduction indicating that a minimum dose is needed to maintain diagnostic accuracy in chest CT for suspected ILD.

Photon-Counting Detector CT Angiography for Endoleak Detection After Endovascular Aortic Repair: Triphasic CT With True Noncontrast Versus Biphasic CT With Virtual Noniodine Imaging.

OBJECTIVES: The aim of this study was to compare image quality and endoleak detection after endovascular abdominal aortic aneurysm repair between a triphasic computed tomography (CT) with true noncontrast (TNC) and a biphasic CT with virtual noniodine (VNI) images on photon-counting detector CT (PCD-CT). MATERIALS AND METHODS: Adult patients after endovascular abdominal aortic aneurysm repair who received a triphasic examination (TNC, arterial, venous phase) on a PCD-CT between August 2021 and July 2022 were retrospectively included. Endoleak detection was evaluated by 2 blinded radiologists on 2 different readout sets (triphasic CT with TNC-arterial-venous vs biphasic CT with VNI-arterial-venous). Virtual noniodine images were reconstructed from the venous phase. The radiologic report with additional confirmation by an expert reader served as reference standard for endoleak presence. Sensitivity, specificity, and interreader agreement (Krippendorf α) were calculated. Image noise was assessed subjectively in patients using a 5-point scale and objectively calculating the noise power spectrum in a phantom. RESULTS: One hundred ten patients (7 women; age, 76 ± 8 years) with 41 endoleaks were included. Endoleak detection was comparable between both readout sets with a sensitivity and specificity of 0.95/0.84 (TNC) versus 0.95/0.86 (VNI) for reader 1 and 0.88/0.98 (TNC) versus 0.88/0.94 (VNI) for reader 2. Interreader agreement for endoleak detection was substantial (TNC: 0.716, VNI: 0.756). Subjective image noise was comparable between TNC and VNI (4; IQR [4, 5] vs 4; IQR [4, 5], P = 0.44). In the phantom, noise power spectrum peak spatial frequency was similar between TNC and VNI (both f peak = 0.16 mm -1 ). Objective image noise was higher in TNC (12.7 HU) as compared with VNI (11.5 HU). CONCLUSIONS: Endoleak detection and image quality were comparable using VNI images in biphasic CT as compared with TNC images in triphasic CT offering the possibility to reduce scan phases and radiation exposure.

Pseudoenhancement in Cystic Renal Lesions - Impact of Virtual Monoenergetic Images of Photon-Counting Detector CT on Lesion Classification.

RATIONALE AND OBJECTIVES: To investigate the impact of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) on the enhancement and classification of renal cysts. MATERIALS AND METHODS: Adults with renal cysts (≥7 mm) who received a triphasic examination on a clinical PCD-CT (120 kVp; IQ level 68) between July 2021 and March 2022 were retrospectively identified. Only non-enhancing cysts (enhancement<10 HU between unenhanced and venous phase at 70 keV) were included. VMI from 40 to 190 keV with increments of 10 keV were reconstructed from the venous phase. Enhancement was measured to classify each lesion as non-enhancing (<10 HU), equivocally enhancing (10-19 HU), and definitely enhancing (≥20 HU). Classification changes as a function of VMI were assessed. Pearson correlation coefficient, the Kruskal-Wallis and the Chi-square test were used. RESULTS: A total of 86 patients (mean age, 74 ± 9 years; 74 male) with 160 non-enhancing renal cysts (17.6 ± 10 mm) were included. CT attenuation of the cysts increased from higher to lower VMI levels with a mean attenuation of 4 ± 11 HU at 190 keV to 36 ± 17 HU at 40 keV. Mean attenuation of the renal parenchyma was 43 ± 4 HU at 190 keV and 414 ± 71 HU at 40 keV. No cyst exhibited enhancement from 70 keV to 190 keV. At 40, 50, and 60 keV, 35% (56/160), 29% (47/160) and 9% (15/160) of cysts showed equivocal and 46% (74/160), 10% (16/160), and 0% (0/160) definite enhancement, respectively. There was no significant influence of size (P=.13), cyst location (P=.9) and BMI (P=.19) on enhancement classification. CONCLUSION: VMI has a relevant impact on enhancement and classification of renal cysts with misclassification in a large number of cases at energy levels below 70 keV.

Evaluation of Image Quality of Overweight and Obese Patients in CT Using High Data Rate Detectors.

BACKGROUND/AIM: To evaluate the impact of high data rate and sampling frequency detector technology compared to standard scan equipment on the image quality in abdominal computed tomography (CT) of overweight and obese patients. PATIENTS AND METHODS: A total of 173 patients were retrospectively included in this study. Objective image quality in abdominal CT was evaluated using comparative analysis with new detector technology prior to market launch and standard CT equipment. Contrast noise ratio (CNR), image noise, volumetric computed tomography dose index (CTDIVol), and figures of merit (Q and Q1) were assessed for all patients. RESULTS: Image quality was superior in the new detector technology for all parameters evaluated. The dose dependent parameters Q and Q1 showed a significant difference (p<0.001). CONCLUSION: A significant increase in objective image quality could be demonstrated using a new generation detector setup with increased frequency transfer in abdominal CT of overweight patients.

CT Angiography of the Aorta Using Photon-counting Detector CT with Reduced Contrast Media Volume.

Purpose: To develop and evaluate a low-volume contrast media protocol for thoracoabdominal CT angiography (CTA) with photon-counting detector (PCD) CT. Materials and Methods: This prospective study included consecutive participants (April-September 2021) who underwent CTA with PCD CT of the thoracoabdominal aorta and previous CTA with energy-integrating detector (EID) CT at equal radiation doses. In PCD CT, virtual monoenergetic images (VMI) were reconstructed in 5-keV intervals from 40 to 60 keV. Attenuation of the aorta, image noise, and contrast-to-noise ratio (CNR) were measured, and subjective image quality was rated by two independent readers. In the first group of participants, the same contrast media protocol was used for both scans. CNR gain in PCD CT compared with EID CT served as the reference for contrast media volume reduction in the second group. Noninferiority analysis was used to test noninferior image quality of the low-volume contrast media protocol with PCD CT. Results: The study included 100 participants (mean age, 75 years ± 8 [SD]; 83 men). In the first group (n = 40), VMI at 50 keV provided the best trade-off between objective and subjective image quality, achieving 25% higher CNR compared with EID CT. Contrast media volume in the second group (n = 60) was reduced by 25% (52.5 mL). Mean differences in CNR and subjective image quality between EID CT and PCD CT at 50 keV were above the predefined boundaries of noninferiority (-0.54 [95% CI: -1.71, 0.62] and -0.36 [95% CI: -0.41, -0.31], respectively). Conclusion: CTA of the aorta with PCD CT was associated with higher CNR, which was translated into a low-volume contrast media protocol demonstrating noninferior image quality compared with EID CT at the same radiation dose.Keywords: CT Angiography, CT-Spectral, Vascular, Aorta, Contrast Agents-Intravenous, Technology Assessment© RSNA, 2023See also the commentary by Dundas and Leipsic in this issue.

Dual-energy CT kidney stone characterization-can diagnostic accuracy be achieved at low radiation dose?

OBJECTIVES: To assess the accuracy of low-dose dual-energy computed tomography (DECT) to differentiate uric acid from non-uric acid kidney stones in two generations of dual-source DECT with stone composition analysis as the reference standard. METHODS: Patients who received a low-dose unenhanced DECT for the detection or follow-up of urolithiasis and stone extraction with stone composition analysis between January 2020 and January 2022 were retrospectively included. Collected stones were characterized using X-ray diffraction. Size, volume, CT attenuation, and stone characterization were assessed using DECT post-processing software. Characterization as uric acid or non-uric acid stones was compared to stone composition analysis as the reference standard. Sensitivity, specificity, and accuracy of stone classification were computed. Dose length product (DLP) and effective dose served as radiation dose estimates. RESULTS: A total of 227 stones in 203 patients were analyzed. Stone composition analysis identified 15 uric acid and 212 non-uric acid stones. Mean size and volume were 4.7 mm × 2.8 mm and 114 mm3, respectively. CT attenuation of uric acid stones was significantly lower as compared to non-uric acid stones (p < 0.001). Two hundred twenty-five of 227 kidney stones were correctly classified by DECT. Pooled sensitivity, specificity, and accuracy were 1.0 (95%CI: 0.97, 1.00), 0.93 (95%CI: 0.68, 1.00), and 0.99 (95%CI: 0.97, 1.00), respectively. Eighty-two of 84 stones with a diameter of ≤ 3 mm were correctly classified. Mean DLP was 162 ± 57 mGy*cm and effective dose was 2.43 ± 0.86 mSv. CONCLUSIONS: Low-dose dual-source DECT demonstrated high accuracy to discriminate uric acid from non-uric acid stones even at small stone sizes. KEY POINTS: • Two hundred twenty-five of 227 stones were correctly classified as uric acid vs. non-uric acid stones by low-dose dual-energy CT with stone composition analysis as the reference standard. • Pooled sensitivity, specificity, and accuracy for stone characterization were 1.0, 0.93, and 0.99, respectively. • Low-dose dual-energy CT for stone characterization was feasible in the majority of small stones < 3 mm.

Photon-counting detector coronary CT angiography: impact of virtual monoenergetic imaging and iterative reconstruction on image quality.

OBJECTIVES: To assess the impact of low kilo-electronvolt (keV) virtual monoenergetic image (VMI) energies and iterative reconstruction on image quality of clinical photon-counting detector coronary CT angiography (CCTA). METHODS: CCTA with PCD-CT (prospective ECG-triggering, 120 kVp, automatic tube current modulation) was performed in a high-end cardiovascular phantom with dynamic flow, pulsatile heart motion, and including different calcified plaques with various stenosis grades and in 10 consecutive patients. VMI at 40,50,60 and 70 keV were reconstructed without (QIR-off) and with all quantum iterative reconstruction (QIR) levels (QIR-1 to 4). In the phantom, noise power spectrum, vessel attenuation, contrast-to-noise-ratio (CNR), and vessel sharpness were measured. Two readers graded stenoses in the phantom and graded overall image quality, subjective noise, vessel sharpness, vascular contrast, and coronary artery plaque delineation on 5-point Likert scales in patients. RESULTS: In the phantom, noise texture was only slightly affected by keV and QIR while noise increased by 69% from 70 keV QIR-4 to 40 keV QIR-off. Reconstructions at 40 keV QIR-4 exhibited the highest CNR (46.1 ± 1.8), vessel sharpness (425 ± 42 ∆HU/mm), and vessel attenuation (1098 ± 14 HU). Stenosis measurements were not affected by keV or QIR level (p > 0.12) with an average error of 3%/6% for reader 1/reader 2, respectively. In patients, across all subjective categories and both readers, 40 keV QIR-3 and QIR-4 images received the best scores (p < 0.001). CONCLUSION: Forty keV VMI with QIR-4 significantly improved image quality of CCTA with PCD-CT. ADVANCES IN KNOWLEDGE: PCD-CT at 40 keV and QIR-4 improves image quality of CCTA.

Assessment of Image Quality in Chest CT With Precision Matrix and Increased Framing Rate Using Single Source CT: A Phantom Study.

BACKGROUND/AIM: The aim was to evaluate the effect of a combined precision matrix and high sampling rate on the delineation of anatomical structures and objective image quality in single source CT in a qualitative approach. MATERIALS AND METHODS: An anthropomorphic thoracic phantom was used to evaluate the objective image quality parameters, including image noise, noise power spectrum, image stepness and Q for different CT scanners including high/standard matrix and framing frequency setups. Scan parameters were standardized over all scanners. Additional subjective quality assessment was also performed. RESULTS: A linear mixed effects model was used to determine the effect of sampling rate and image matrix on objective image quality parameters. Noise power spectrum and image noise were significantly influenced by both framing frequency and image matrix. There were significant differences between high and standard frequency/matrix acquisitions. CONCLUSION: Higher framing frequency and image matrix allows for improved image noise texture and objective image quality in CT.

Impact of photon counting detector CT derived virtual monoenergetic images and iodine maps on the diagnosis of pleural empyema.

PURPOSE: The purpose of this study was to evaluate the impact of virtual monoenergetic image (VMI) energies and iodine maps on the diagnosis of pleural empyema with photon counting detector computed tomography (PCD-CT). MATERIALS AND METHODS: In this IRB-approved retrospective study, consecutive patients with non-infectious pleural effusion or histopathology-proven empyema were included. PCD-CT examinations were performed on a dual-source PCD-CT in the multi-energy (QuantumPlus) mode at 120 kV with weight-adjusted intravenous contrast-agent. VMIs from 40-70 keV obtained in 10 keV intervals and an iodine map was reconstructed for each scan. CT attenuation was measured in the aorta, the pleura and the peripleural fat (between autochthonous dorsal muscles and dorsal ribs). Contrast-to-noise (CNR) and signal-to-noise (SNR) ratios were calculated. Two blinded radiologists evaluated if empyema was present (yes/no), and rated diagnostic confidence (1 to 4; not confident to fully confident, respectively) with and without using the iodine map. Sensitivity, specificity and diagnostic confidence were estimated. Interobserver agreement was estimated using an unweighted Cohen kappa test. A one-way ANOVA was used to compare variables. Differences in sensitivity and specificity between the different levels of energy were searched using McNemar test. RESULTS: Sixty patients (median age, 60 years; 26 women) were included. A strong negative correlation was found between image noise and VMI energies (r = -0.98; P = 0.001) and CNR increased with lower VMI energies (r = -0.98; P = 0.002). Diagnostic accuracy (96%; 95% CI: 82-100) as well as diagnostic confidence (3.4 ± 0.75 [SD]) were highest at 40 keV. Diagnostic accuracy and confidence at higher VMI energies improved with the addition of iodine maps (P ≤0.001). Overall, no difference in CT attenuation of peripleural fat between patients with empyema and those with pleural effusion was found (P = 0.07). CONCLUSION: Low VMI energies lead to a higher diagnostic accuracy and diagnostic confidence in the diagnosis of pleural empyema. Iodine maps help in diagnosing empyema only at high VMI energies.

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

OBJECTIVES: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Liver Iodine Quantification With Photon-Counting Detector CT: Accuracy in an Abdominal Phantom and Feasibility in Patients.

RATIONALE AND OBJECTIVES: To compare the accuracy of iodine quantification in liver parenchyma and lesions between dual-source photon-counting detector CT (PCD-CT) and dual-source energy-integrating detector CT (EID-CT) in a phantom and to demonstrate the feasibility of iodine quantification with PCD-CT in liver parenchyma and lesions in patients. MATERIALS AND METHODS: An anthropomorphic abdominal phantom with a liver insert containing parenchyma and lesions was imaged on a clinical PCD-CT at 120kV and in the dual-energy mode on an EID-CT with kV-combinations of 80/Sn150kV, 90/Sn150kV, and 100/Sn150kV. Three patient sizes were imaged at three different radiation doses (CTDIvol: 5, 10, 15mGy). Thirty patients with liver cysts, hemangiomas or metastases imaged with PCD-CT were retrospectively included. Iodine maps were reconstructed and iodine concentrations were measured in liver parenchyma and lesions. For the phantom, iodine error was quantified as the absolute difference to the vendor's specifications as reference. RESULTS: Overall iodine error was 0.33 ± 0.29, 0.34 ± 0.32, 0.39 ± 0.37, 0.35 ± 0.39 mgI/mL for 80/Sn150kV, 90/Sn150kV, 100/Sn150kV of EID-CT, and PCD-CT, respectively, without significant differences between PCD-CT and EID-CT (p > 0.05). Radiation dose did not significantly influence error of PCD-CT (p > 0.05) nor EID-CT (p > 0.05). For both scanners, smaller patient sizes were associated with lower errors (p < 0.05). Iodine concentration and base material attenuation significantly influenced quantification for EID-CT (p < 0.05) but not PCD-CT (p > 0.05). In patients, iodine quantification was feasible in liver parenchyma, cysts, hemangiomas, and metastases. CONCLUSION: Iodine quantification with PCD-CT is accurate in simulated liver parenchyma and lesions irrespective of radiation dose, iodine concentration, and base attenuation and is feasible in common liver lesions in patients.

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

Purpose: To assess the effect of ultra-high-resolution coronary CT angiography (CCTA) with photon-counting detector (PCD) CT on quantitative coronary plaque characterization. Materials and methods: In 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. Results: Median 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). Conclusion: This 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.