PurposeThe aim of this study was to evaluate coronary computed tomography angiography (CCTA)-based in vitro and in vivo coronary artery calcium scoring (CACS) using a novel virtual noniodine reconstruction (PureCalcium) on a clinical first-generation photon-counting detector–computed tomography system compared with virtual noncontrast (VNC) reconstructions and true noncontrast (TNC) acquisitions.Materials and MethodsAlthough CACS and CCTA are well-established techniques for the assessment of coronary artery disease, they are complementary acquisitions, translating into increased scan time and patient radiation dose. Hence, accurate CACS derived from a single CCTA acquisition would be highly desirable. In this study, CACS based on PureCalcium, VNC, and TNC, reconstructions was evaluated in a CACS phantom and in 67 patients (70 [59/80] years, 58.2% male) undergoing CCTA on a first-generation photon counting detector–computed tomography system. Coronary artery calcium scores were quantified for the 3 reconstructions and compared using Wilcoxon test. Agreement was evaluated by Pearson and Spearman correlation and Bland-Altman analysis. Classification of coronary artery calcium score categories (0, 1–10, 11–100, 101–400, and >400) was compared using Cohen κ.ResultsPhantom studies demonstrated strong agreement between CACSPureCalcium and CACSTNC (60.7 ± 90.6 vs 67.3 ± 88.3, P = 0.01, r = 0.98, intraclass correlation [ICC] = 0.98; mean bias, 6.6; limits of agreement [LoA], −39.8/26.6), whereas CACSVNC showed a significant underestimation (42.4 ± 75.3 vs 67.3 ± 88.3, P < 0.001, r = 0.94, ICC = 0.89; mean bias, 24.9; LoA, −87.1/37.2). In vivo comparison confirmed a high correlation but revealed an underestimation of CACSPureCalcium (169.3 [0.7/969.4] vs 232.2 [26.5/1112.2], P < 0.001, r = 0.97, ICC = 0.98; mean bias, −113.5; LoA, −470.2/243.2). In comparison, CACSVNC showed a similarly high correlation, but a substantially larger underestimation (24.3 [0/272.3] vs 232.2 [26.5/1112.2], P < 0.001, r = 0.97, ICC = 0.54; mean bias, −551.6; LoA, −2037.5/934.4). CACSPureCalcium showed superior agreement of CACS classification (κ = 0.88) than CACSVNC (κ = 0.60).ConclusionsThe accuracy of CACS quantification and classification based on PureCalcium reconstructions of CCTA outperforms CACS derived from VNC reconstructions.

Background Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be demonstrated in the context of current screening modalities. Here, we present findings on the performance of an AI convolutional neural network (CNN) prototype (AI-RAD Companion, Siemens Healthineers) that automatically detects pulmonary nodules and quantifies coronary artery calcium volume (CACV) on low-dose chest CT (LDCT), and compare results to expert radiologists. We also correlate AI findings with adverse cardiopulmonary outcomes in a retrospective cohort of 117 patients who underwent LDCT. Methods A total of 117 patients were enrolled in this study. Two CNNs were used to identify lung nodules and CACV on LDCT scans. All subjects were used for lung nodule analysis, and 96 subjects met the criteria for coronary artery calcium volume analysis. Interobserver concordance was measured using ICC and Cohen’s kappa. Multivariate logistic regression and partial least squares regression were used for outcomes analysis. Results Agreement of the AI findings with experts was excellent (CACV ICC = 0.904, lung nodules Cohen’s kappa = 0.846) with high sensitivity and specificity (CACV: sensitivity = .929, specificity = .960; lung nodules: sensitivity = 1, specificity = 0.708). The AI findings improved the prediction of major cardiopulmonary outcomes at 1-year follow-up including major adverse cardiac events and lung cancer (AUCMACE = 0.911, AUCLung Cancer = 0.942). Conclusion We conclude the AI prototype rapidly and accurately identifies significant risk factors for cardiopulmonary disease on standard screening low-dose chest CT. This information can be used to improve diagnostic ability, facilitate intervention, improve morbidity and mortality, and decrease healthcare costs. There is also potential application in countries with limited numbers of cardiothoracic radiologists.

PurposeThe aim of this study was to evaluate strategies to reduce contrast media volumes for coronary computed tomography (CT) angiography on a clinical first-generation dual-source photon-counting detector (PCD)-CT system using a dynamic circulation phantom.Materials and MethodsCoronary CT angiograph is an established method for the assessment of coronary artery disease that relies on the administration of iodinated contrast media. Reduction of contrast media volumes while maintaining diagnostic image quality is desirable. In this study, a dynamic phantom containing a 3-dimensional-printed model of the thoracic aorta and coronary arteries was evaluated using a clinical contrast injection protocol with stepwise reduced contrast agent concentrations (100%, 75%, 50%, 40%, 30%, and 20% contrast media content of the same 50 mL bolus, resulting in iodine delivery rates of 1.5, 1.1, 0.7, 0.6, 0.4 and 0.3 gl/s) on a first-generation, dual-source PCD-CT. Polychromatic images (T3D) and virtual monoenergetic images were reconstructed in the range of 40 to 70 keV in 5-keV steps. Attenuation and noise were measured in the coronary arteries and background material and the contrast-to-noise ratio (CNR) were calculated. Attenuation of 350 HU and a CNR of the reference protocol at 70 keV were regarded as sufficient for simulation of diagnostic purposes. Vessel sharpness and noise power spectra were analyzed for the aforementioned reconstructions.ResultsThe standard clinical contrast protocol (bolus with 100% contrast) yielded diagnostic coronary artery attenuation for all tested reconstructions (>398 HU). A 50% reduction in contrast media concentration demonstrated sufficient attenuation of the coronary arteries at 40 to 55 keV (>366 HU). Virtual monoenergetic image reconstructions of 40 to 45 and 40 keV allowed satisfactory attenuation of the coronary arteries for contrast concentrations of 40% and 30% of the original protocol. A reduction of contrast agent concentration to 20% of the initial concentration provided insufficient attenuation in the target vessels for all reconstructions. The highest CNR was found for virtual monoenergetic reconstructions at 40 keV for all contrast media injection protocols, yielding a sufficient CNR at a 50% reduction of contrast agent concentration.ConclusionsUsing virtual monoenergetic image reconstructions at 40 keV on a dual-source PCD-CT system, contrast media concentration could be reduced by 50% to obtain diagnostic attenuation and objective image quality for coronary CT angiography in a dynamic vessel phantom. These initial feasibility study results have to be validated in clinical studies.

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