Objectives: The aim of this study was to evaluate the feasibility and accuracy of cardiac late enhancement (LE) scanning for extracellular volume (ECV) quantification with dual-source photon-counting detector computed tomography (PCD-CT). Materials and Methods: In this institutional review board–approved study, 30 patients (mean age, 79 years; 12 women; mean body mass index, 28 kg/m²) with severe aortic stenosis undergoing PCD-CT as part of their preprocedural workup for transcatheter aortic valve replacement were included. The scan protocol consisted of a nonenhanced calcium-scoring scan, coronary CT angiography (CTA) followed by CTA of the thoracoabdominal aorta, and a low-dose LE scan 5 minutes after the administration of 100 mL contrast media (all scans electrocardiogram-gated). Virtual monoenergetic (65 keV) and dual-energy (DE) iodine images were reconstructed from the LE scan. Extracellular volume was calculated using the iodine ratios of myocardium and blood-pool of the LE scan, and additionally based on single-energy (SE) subtraction of the nonenhanced scan from the LE scan. Three-dimensional analysis was performed automatically for the whole-heart myocardial volume by matching a heart model generated from the respective coronary CTA data. Bland-Altman and correlation analysis were used to compare the ECV values determined by both methods. Results: The median dose length product for the LE scan was 84 mGy·cm (interquartile range, 69; 125 mGy·cm). Extracellular volume quantification was feasible in all patients. The median ECV value was 30.5% (interquartile range, 28.4%–33.6%). Two focal ECV elevations matched known prior myocardial infarction. The DE- and SE-based ECV quantification correlated well (r = 0.87, P < 0.001). Bland-Altman analysis showed small mean errors between DE- and SE-based ECV quantification (0.9%; 95% confidence interval, 0.1%–1.6%) with narrow limits of agreement (−3.3% to 5.0%). Conclusions: Dual-source PCD-CT enables accurate ECV quantification using an LE cardiac DE scan at low radiation dose. Extracellular volume calculation from iodine ratios of the LE scan obviates the need for acquisition of a true nonenhanced scan and is not affected by potential misregistration between 2 separate scans.

To develop and evaluate a low-volume contrast media protocol for thoracoabdominal CT angiography (CTA) with photon-counting detector (PCD) CT. 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. 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). 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.

Objective: The aim of this study was to determine the potential of photon-counting detector computed tomography (PCD-CT) for radiation dose reduction compared with conventional energy-integrated detector CT (EID-CT) in the assessment of interstitial lung disease (ILD) in systemic sclerosis (SSc) patients. Methods: In this retrospective study, SSc patients receiving a follow-up noncontrast chest examination on a PCD-CT were included between May 2021 and December 2021. Baseline scans were generated on a dual-source EID-CT by selecting the tube current-time product for each of the 2 x-ray tubes to obtain a 100% (D₁₀₀), a 66% (D₆₆), and a 33% dose image (D₃₃) from the same data set. Slice thickness and kernel were adjusted between the 2 scans. Image noise was assessed by placing a fixed region of interest in the subcutaneous fat. Two independent readers rated subjective image quality (5-point Likert scale), presence, extent, diagnostic confidence, and accuracy of SSc-ILD. D₁₀₀ interpreted by a radiologist with 22 years of experience served as reference standard. Interobserver agreement was calculated with Cohen κ, and mean variables were compared by a paired t test. Results: Eighty patients (mean 56 ± 14; 64 women) were included. Although CTDI_vol of PCD-CT was comparable to D₃₃ (0.72 vs 0.76 mGy, P = 0.091), mean image noise of PCD-CT was comparable to D₁₀₀ (131 ± 15 vs 113 ± 12, P > 0.05). Overall subjective image quality of PCD-CT was comparable to D₁₀₀ (4.72 vs 4.71; P = 0.874). Diagnostic accuracy was higher in PCD-CT compared with D₃₃/D₆₆ (97.6% and 92.5%/96.3%, respectively) and comparable to D₁₀₀ (98.1%). Conclusions: With PCD-CT, a radiation dose reduction of 66% compared with EID-CT is feasible, without penalty in image quality and diagnostic performance for the evaluation of ILD.

The aim of this study was to characterize image quality and to determine the optimal strength levels of a novel iterative reconstruction algorithm (quantum iterative reconstruction, QIR) for low-dose, ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) of the lung. Images were acquired on a clinical dual-source PCD-CT in the UHR mode and reconstructed with a sharp lung reconstruction kernel at different strength levels of QIR (QIR-1 to QIR-4) and without QIR (QIR-off). Noise power spectrum (NPS) and target transfer function (TTF) were analyzed in a cylindrical phantom. 52 consecutive patients referred for low-dose UHR chest PCD-CT were included (CTDI_vol: 1 ± 0.6 mGy). Quantitative image quality analysis was performed computationally which included the calculation of the global noise index (GNI) and the global signal-to-noise ratio index (GSNRI). The mean attenuation of the lung parenchyma was measured. Two readers graded images qualitatively in terms of overall image quality, image sharpness, and subjective image noise using 5-point Likert scales. In the phantom, an increase in the QIR level slightly decreased spatial resolution and considerably decreased noise amplitude without affecting the frequency content. In patients, GNI decreased from QIR-off (202 ± 34 HU) to QIR-4 (106 ± 18 HU) (p < 0.001) by 48%. GSNRI increased from QIR-off (4.4 ± 0.8) to QIR-4 (8.2 ± 1.6) (p < 0.001) by 87%. Attenuation of lung parenchyma was highly comparable among reconstructions (QIR-off: −849 ± 53 HU to QIR-4: −853 ± 52 HU, p < 0.001). Subjective noise was best in QIR-4 (p < 0.001), while QIR-3 was best for sharpness and overall image quality (p < 0.001). Thus, our phantom and patient study indicates that QIR-3 provides the optimal iterative reconstruction level for low-dose, UHR PCD-CT of the lungs.

Objective: To evaluate the performance of virtual non-contrast images (VNC) compared to true non-contrast (TNC) images in photon-counting detector computed tomography (PCD-CT) for the evaluation of lung parenchyma and emphysema quantification. Methods: 65 (mean age 73 years; 48 male) consecutive patients who underwent a three-phase (non-contrast, arterial and venous) chest/abdomen CT on a first-generation dual-source PCD-CT were retrospectively included. Scans were performed in the multienergy (QuantumPlus) mode at 120 kV with 70 ml intravenous contrast agent at an injection rate of 4 ml s⁻¹. VNC were reconstructed from the arterial (VNC_art) and venous phase (VNC_ven). TNC and VNC images of the lung were assessed quantitatively by calculating the global noise index (GNI) and qualitatively by two independent, blinded readers (overall image quality and emphysema assessment). Emphysema quantification was performed using a commercially available software tool at a threshold of −950 HU for all data sets. TNC images served as reference standard for emphysema quantification. Low attenuation values (LAV) were compared in a Bland–Altman plot. Results: GNI was similar in VNC_art (103.0 ± 30.1) and VNC_ven (98.2 ± 22.2) as compared to TNC (100.9 ± 19.0, p = 0.546 and p = 0.272, respectively). Subjective image quality (emphysema assessment and overall image quality) was highest for TNC (p = 0.001), followed by VNC_ven and VNC_art. Both, VNC_art and VNC_ven showed no significant difference in emphysema quantification as compared to TNC (p = 0.409 vs. p = 0.093; respectively). Conclusion: Emphysema evaluation is feasible using virtual non-contrast images from PCD-CT. Advances in knowledge: Emphysema quantification is feasible and accurate using VNC images in PCD-CT. Based on these findings, additional TNC scans for emphysema quantification could be omitted in the future.

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). 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. 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). 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.