Ultra-high-resolution photon-counting detector computed tomography of the lungs: Phantom and clinical assessment of radiation dose and image quality.

PURPOSE: Photon-counting-detector computed tomography (PCD-CT) offers enhanced noise reduction, spatial resolution, and image quality in comparison to energy-integrated-detectors CT (EID-CT). These hypothesized improvements were compared using PCD-CT ultra-high (UHR) and standard-resolution (SR) scan-modes. METHODS: Phantom scans were obtained with both EID-CT and PCD-CT (UHR, SR) on an adult body-phantom. Radiation dose was measured and noise levels were compared at a minimum achievable slice thickness of 0.5 mm for EID-CT, 0.2 mm for PCD-CT-UHR and 0.4 mm for PCD-CT-SR. Signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNR) were calculated for five tissue densities. Additionally, data from 25 patients who had PCD-CT of chest were reconstructed at 1 mm and 0.2 mm (UHR) slice-thickness and compared quantitatively (SNR) and qualitatively (noise, quality, sharpness, bone details). RESULTS: Phantom PCD-CT-UHR and PCD-CT-SR scans had similar measured radiation dose (16.0mGy vs 15.8 mGy). Phantom PCD-CT-SR (0.4 mm) had lower noise level in comparison to EID-CT (0.5 mm) (9.0HU vs 9.6HU). PCD-CT-UHR (0.2 mm) had slightly higher noise level (11.1HU). Phantom PCD-CT-SR (0.4 mm) had higher SNR in comparison to EID-CT (0.5 mm) while achieving higher resolution (Bone 115 vs 96, Acrylic 14 vs 14, Polyethylene 11 vs 10). SNR was slightly lower across all densities for PCD-CT UHR (0.2 mm). Interestingly, CNR was highest in the 0.2 mm PCD-CT group; PCD-CT CNR was 2.45 and 2.88 times the CNR for 0.5 mm EID-CT for acrylic and poly densities. Clinical comparison of SNR showed predictably higher SNR for 1 mm (30.3 ± 10.7 vs 14.2 ± 7, p = 0.02). Median subjective ratings were higher for 0.2 mm UHR vs 1 mm PCD-CT for nodule contour (4.6 ± 0.3 vs 3.6 ± 0.1, p = 0.02), bone detail (5 ± 0 vs 4 ± 0.1, p = 0.001), image quality (5 ± 0.1 vs 4.6 ± 0.4, p = 0.001), and sharpness (5 ± 0.1 vs 4 ± 0.2). CONCLUSION: Both UHR and SR PCD-CT result in similar radiation dose levels. PCD-CT can achieve higher resolution with lower noise level in comparison to EID-CT.

Substrate Imaging Before Catheter Ablation of Ventricular Tachycardia: Risk Prediction for Acute Hemodynamic Decompensation.

BACKGROUND: The PAINESD (Pulmonary disease, Age, Ischemic cardiomyopathy, NYHA functional class, Ejection fraction, Storm, Diabetes mellitus) risk score has been validated as a predictor of periprocedural acute hemodynamic decompensation (AHD) in patients undergoing ventricular tachycardia (VT) ablation. Whether the addition of total scar volume (TSV) determined by preprocedure computed tomography imaging provides additional risk stratification has not been previously investigated. OBJECTIVES: The purpose of this study was to evaluate the impact of TSV on the risk of AHD and its adjunctive benefit to the PAINESD score newly modified as Pulmonary disease, Age, Ischemic cardiomyopathy, NYHA class, Ejection fraction, Storm, Scar volume, Diabetes mellitus (PAINES2D) based on the addition of scar volumes. METHODS: This was a retrospective analysis of all index VT ablations at a quaternary care center from 2017 to 2022. Associations between TSV and AHD were evaluated among patients with structural heart disease. RESULTS: Among 61 patients with TSV data, 13 (21%) had periprocedural AHD. TSV and PAINESD were independently associated with AHD risk. Both TSV and PAINESD were associated with AHD (P = 0.016 vs P = 0.053, respectively). The highest TSV tertile (≥37.30 mL) showed significant association with AHD (P = 0.018; OR: 4.80) compared to the other tertiles. The PAINESD and PAINES2D scores had significant impact on AHD (P = 0.046 and P = 0.010, respectively). The PAINES2D score had a greater impact on AHD compared to PAINESD (area under the curve: 0.73; P = 0.011; 95% CI: 0.56-0.91 and area under the curve: 0.67; P = 0.058; 95% CI: 0.49-0.85, respectively). CONCLUSIONS: Addition of TSV to a modified PAINESD score, PAINES2D, enhances risk prediction of AHD. Further prospective study is needed to assess benefit in various cardiomyopathy populations undergoing VT ablation.

Radiation Dose Reduction for Coronary Artery Calcium Scoring Using a Virtual Noniodine Algorithm on Photon-Counting Detector Computed-Tomography Phantom Data.

Background: On the basis of the hypothesis that virtual noniodine (VNI)-based coronary artery calcium scoring (CACS) is feasible at reduced radiation doses, this study assesses the impact of radiation dose reduction on the accuracy of this VNI algorithm on a photon-counting detector (PCD)-CT. Methods: In a systematic in vitro setting, a phantom for CACS simulating three chest sizes was scanned on a clinical PCD-CT. The standard radiation dose was chosen at volumetric CT dose indices (CTDIVol) of 1.5, 3.3, 7.0 mGy for small, medium-sized, and large phantoms, and was gradually reduced by adjusting the tube current resulting in 100, 75, 50, and 25%, respectively. VNI images were reconstructed at 55 keV, quantum iterative reconstruction (QIR)1, and at 60 keV/QIR4, and evaluated regarding image quality (image noise (IN), contrast-to-noise ratio (CNR)), and CACS. All VNI results were compared to true noncontrast (TNC)-based CACS at 70 keV and standard radiation dose (reference). Results: INTNC was significantly higher than INVNI, and INVNI at 55 keV/QIR1 higher than at 60 keV/QIR4 (100% dose: 16.7 ± 1.9 vs. 12.8 ± 1.7 vs. 7.7 ± 0.9; p < 0.001 for every radiation dose). CNRTNC was higher than CNRVNI, but it was better to use 60 keV/QIR4 (p < 0.001). CACSVNI showed strong correlation and agreement at every radiation dose (p < 0.001, r > 0.9, intraclass correlation coefficient > 0.9). The coefficients of the variation in root-mean squared error were less than 10% and thus clinically nonrelevant for the CACSVNI of every radiation dose. Conclusion: This phantom study suggests that CACSVNI is feasible on PCD-CT, even at reduced radiation dose while maintaining image quality and CACS accuracy.

Comparison of First-generation and Third-generation Dual-source Computed Tomography for Detecting Coronary Artery Disease in Patients Evaluated for Transcatheter Aortic Valve Replacement.

PURPOSE: This study compared image quality and evaluability of coronary artery disease (CAD) in routine preparatory imaging for transcatheter aortic valve replacement using 64-slice (first-generation) to 192-slice (third-generation) dual-source computed tomography(DSCT). MATERIALS AND METHODS: The CT data sets of 192 patients (122 women, median age 82 y) without severe renal dysfunction or known CAD were analyzed retrospectively. Half were examined using first-generation DSCT (June 2014 to February 2016) and the other half with third-generation DSCT (April 2016 to April 2017). Per protocol, contrast material (110 [110 to 120] vs. 70 [70 to 70] mL, P <0.001) and radiation dose of multiphasic retrospectively gated thoracic CT angiography (dose-length-product, 1001 [707 to 1312] vs. 727 [474 to 1369] mGy×cm, P <0.001) were significantly lower with third-generation DSCT. Significant CAD was defined as CAD-RADS ≥4 by CT. Invasive coronary angiography served as the reference standard (CAD is defined as ≥70% stenosis or fractional flow reserve ≤0.80). RESULTS: In comparison with first-generation DSCT, third-generation DSCT showed significantly better subjective (3 [interquartile range 2 to 3] vs. 4 [3 to 4.25] on a 5-point scale, P <0.001) and objective image quality (signal-to-noise ratio of left coronary artery 12.8 [9.9 to 16.4] vs. 15.2 [12.4 to 19.0], P <0.001). Accuracy (72.9% vs. 91.7%, P =0.001), specificity (59.7% vs. 88.3%, P <0.001), positive (61.0% vs. 83.3%, P <0.001), and negative predictive value (91.9% vs. 98.2%, P =0.045) for detecting CAD per-patient were significantly better using third-generation DSCT, while sensitivity was similar (92.3% vs. 97.2%, P =0.129). CONCLUSIONS: Coronary artery evaluation with CT angiography before TAVI is feasible in selected patients. Compared with first-generation DSCT, state-of-the-art third-generation DSCT technology is superior for this purpose, allowing for less contrast medium and radiation dose while providing better image quality and improved diagnostic performance.

Left atrial strain correlates with severity of cardiac involvement in Anderson-Fabry disease.

OBJECTIVES: Cardiac involvement in Anderson-Fabry disease (AFD) results in myocardial lipid depositions. An early diagnosis can maximize therapeutic benefit. Thus, this study aims to investigate the potential of cardiac MRI (CMR) based parameters of left atrial (LA) function and strain to detect early stages of AFD. METHODS: Patients (n = 58, age 40 (29-51) years, 31 female) with genetically proven AFD had undergone CMR including left ventricular (LV) volumetry, mass index (LVMi), T1, and late gadolinium enhancement, complemented by LA and LV strain measurements and atrial emptying fractions. Patients were stratified into three disease phases and compared to age and sex-matched healthy controls (HC, n = 58, age 41 [26-56] years, 31 female). RESULTS: A total of 19 early-, 20 intermediate-, and 19 advanced-phase patients were included. LV and LA reservoir strain was significantly impaired in all AFD phases, including early disease (both p < 0.001). In contrast, LA volumetry, T1, and LVMi showed no significant differences between the early phase and HC (p > 0.05). In the intermediate phase, LVMi and T1 demonstrated significant differences. In advanced phase, all parameters except active emptying fractions differed significantly from HC. ROC curve analyses of early disease phases revealed superior diagnostic confidence for the LA reservoir strain (AUC 0.88, sensitivity 89%, specificity 75%) over the LV strain (AUC 0.82). CONCLUSIONS: LA reservoir strain showed impairment in early AFD and significantly correlated with disease severity. The novel approach performed better in identifying early disease than the established approach using LVMi and T1. Further studies are needed to evaluate whether these results justify earlier initiation of therapy and help minimize cardiac complications. KEY POINTS: • Parameters of left atrial function and deformation showed impairments in the early stages of Anderson-Fabry disease and correlated significantly with the severity of Anderson-Fabry disease. • Left atrial reservoir strain performed superior to ventricular strain in detecting early myocardial involvement in Anderson-Fabry disease and improved diagnostic accuracies of approaches already using ventricular strain. • Further studies are needed to evaluate whether earlier initiation of enzyme replacement therapy based on these results can help minimize cardiac complications from Anderson-Fabry disease.

Biventricular strain assessment indicates progressive impairment of myocardial contractility in phenotypically negative patients with Fabry's disease.

PURPOSE: The accumulation of sphingolipids in Fabry's disease (FD) leads to left ventricular (LV) hypertrophy and shortened T1 in cardiac magnetic resonance (CMR). Early detection of myocardial involvement is essential for the timely initiation and efficacy of enzyme replacement therapy. However, there is a diagnostic gap between the onset of accumulation and detectable myocardial changes. This study aimed to evaluate the diagnostic value of biventricular strain assessment in early FD. METHODS: Genetically proven FD patients (n = 58) and healthy volunteers (HV, n = 62) who had undergone 3 T CMR were retrospectively identified and stratified into 3 groups according to disease severity. Biventricular volumetry, global longitudinal strains (GLS), indexed biventricular masses (RVMi/LVMi), and T1 were evaluated. Group comparisons were performed by ANOVA and diagnostic accuracy was evaluated by ROC-analysis. RESULTS: The study population included 19 group I, 20 group II and 19 group III patients. LV volumetry and T1 showed no significant difference between early FD patients and HV (all p > 0.760). However, RVMi was increased, while RV-GLS and LV-GLS were significantly impaired (p = 0.024 and < 0.001, respectively). Biventricular strains accurately discriminated early FD patients and HV with RV-GLS being non-inferior to LV-GLS (AUC for both 0.83, p > 0.05). Adding strains to the established approach using T1 and LVMi further increased diagnostic accuracy (AUC 0.99, p < 0.05). CONCLUSIONS: Biventricular strains may help detect altered myocardial deformation patterns in phenotypically negative FD patients. These findings may lead to an earlier initiation of therapy, which in turn may slow hypertrophy and the associated long-term risks.

Role of CTA Surveillance for Management of Endovascular Repair of Aortic Dissection.

OBJECTIVES: The aim of this study was to evaluate the effect of timing for post-interventional CT imaging on the rate of re-intervention and all-cause mortality in patients with endovascular treatment of type B aortic dissections (TBAD). MATERIAL AND METHODS: Data on 70 patients with endovascular repair of aortic dissection during a three-year period from a single institution retrospectively were collected. Study participants were stratified based on those who had a postoperative CTA in the first 30 days after index intervention (early) vs. those who did not (late). The re-intervention and all-cause mortality rates between the two groups were investigated using Kaplan-Meier and Cox regression analysis. RESULTS: During a median follow-up time of 230 days, the primary endpoint (additional operation) was reached in 24/70 patients (34.3%) with no statistically significant difference between the early and late CTA group (log-rank-test: P = 0.886). All-cause mortality was present in 14/70 (20%) patients, with no statistically significant difference between both groups (log-rank-test: P = 0.440). Additionally, both groups had no significant differences in time to additional operation and death. Cox regression analysis revealed the presence of a chronic TBAD and underlying connective tissue disease as relevant risk factors for the need for an additional operation and obesity as a protective and renal failure as a negative factor for all-cause mortality. CONCLUSION: CTA surveillance within 30 days of the index operation did not significantly modify mortality or rate of re-intervention after endovascular treatment for TBAD. Surveillance recommendations should be tailored to individualized factors.

Unstable plaques hide in heavily calcified coronary arteries.

Background: The napkin-ring sign (NRS) was accepted as unstable plaques at coronary computed tomography angiography (CCTA). However, the incidence is relatively low. We sought to assess whether the newly defined diamond-attenuation-sign [DAS, defined as a qualitative plaque feature in a mixed plaque (MP) on CCTA cross-section images by the presence of two features: a visual calcification (in the shape of a diamond) accompanied by an annular-shape lower attenuation plaque tissue surrounding the lumen like a ring], could be accurately identified as unstable atherosclerotic plaques. Methods: Eight heart transplant recipients (8 male; mean age, 48.5±11.6 years; range, 37-65 years) underwent CCTA exams prior to heart transplant surgery. Segment-based CCTA sections were independently evaluated for various plaque patterns including non-calcified plaque (NCP) with NRS (NCP-NRS), NCP without NRS (NCP-non-NRS), MP with DAS (MP-DAS), MP without DAS sign (MP-non-DAS), and calcified plaque (CP). Results: NCP-NRS plaques in 6.4% (23/358), NCP-non-NRS plaques in 24.0% (86/358), MP-DAS plaques in 18.2% (65/358), MP-non-DAS plaques in 20.1% (72/358), and calcified-plaques in 7.0% (25/358) of all cases. The specificity and positive predictive values of the MP-DAS and NCP-NRS signs to identify unstable plaque features were excellent (97.1% vs. 98.6%, 90.8% vs. 87.0%, respectively). DAS plaques were more frequently seen on CCTA exams than that of NRS (39.3% vs. 13.3%, respectively, P=0.001). The diagnostic performance of MP-DAS to identify unstable coronary lesions was superior compared to NCP-NRS [area under the receiver operating characteristic curve (ROC), 0.756; 95% CI: 0.717-0.791 vs. 0.558; 95% CI: 0.514-0.600, respectively, P<0.001]. Conclusions: Both the DAS and NRS had a high specificity and positive predictive value for the presence of unstable lesions. DAS was a better identification of unstable atherosclerotic plaques in the assessment of plaque-calcification-pattern (PCP).

Tumor burden of lung metastases at initial staging in breast cancer patients detected by artificial intelligence as a prognostic tool for precision medicine.

BACKGROUND: Determination of the total number and size of all pulmonary metastases on chest CT is time-consuming and as such has been understudied as an independent metric for disease assessment. A novel artificial intelligence (AI) model may allow for automated detection, size determination, and quantification of the number of pulmonary metastases on chest CT. OBJECTIVE: To investigate the utility of a novel AI program applied to initial staging chest CT in breast cancer patients in risk assessment of mortality and survival. METHODS: Retrospective imaging data from a cohort of 226 subjects with breast cancer was assessed by the novel AI program and the results validated by blinded readers. Mean clinical follow-up was 2.5 years for outcomes including cancer-related death and development of extrapulmonary metastatic disease. AI measurements including total number of pulmonary metastases and maximum nodule size were assessed by Cox-proportional hazard modeling and adjusted survival. RESULTS: 752 lung nodules were identified by the AI program, 689 of which were identified in 168 subjects having confirmed lung metastases (Lmet+) and 63 were identified in 58 subjects without confirmed lung metastases (Lmet-). When compared to the reader assessment, AI had a per-patient sensitivity, specificity, PPV and NPV of 0.952, 0.639, 0.878, and 0.830. Mortality in the Lmet + group was four times greater compared to the Lmet-group (p = 0.002). In a multivariate analysis, total lung nodule count by AI had a high correlation with overall mortality (OR 1.11 (range 1.07-1.15), p < 0.001) with an AUC of 0.811 (R2 = 0.226, p < 0.0001). When total lung nodule count and maximum nodule diameter were combined there was an AUC of 0.826 (R2 = 0.243, p < 0.001). CONCLUSION: Automated AI-based detection of lung metastases in breast cancer patients at initial staging chest CT performed well at identifying pulmonary metastases and demonstrated strong correlation between the total number and maximum size of lung metastases with future mortality. CLINICAL IMPACT: As a component of precision medicine, AI-based measurements at the time of initial staging may improve prediction of which breast cancer patients will have negative future outcomes.

Tumorous tissue characterization using integrated 18F-FDG PET/dual-energy CT in lung cancer: Combining iodine enhancement and glycolytic activity.

Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (18F-FDG) has become the method of choice for tumor staging in lung cancer patients with improved diagnostic accuracy for the evaluation of lymph node involvement and distant metastasis. Due to its spectral capabilities, dual-energy CT (DECT) employs a material decomposition algorithm enabling precise quantification of iodine concentrations in distinct tissues. This technique enhances the characterization of tumor blood supply and has demonstrated promising results for the assessment of therapy response in patients with lung cancer. Several studies have demonstrated that DECT provides additional value to the PET-based evaluation of glycolytic activity, especially for the evaluation of therapy response and follow-up of patients with lung cancer. The combination of PET and DECT in a single scanner system enables the simultaneous assessment of glycolytic activity and iodine enhancement, offering further insight to the characterization of tumorous tissues. Recently a new approach of a novel integrated PET/DECT was investigated in a pilot study on patients with non-small cell lung cancer (NSCLC). The study showed a moderate correlation between PET-based standard uptake values (SUV) and DECT-based iodine densities in the evaluation of lung tumorous tissue but with limited assessment of lymph nodes. The following review on tumorous tissue characterization using PET and DECT imaging describes the strengths and limitations of this novel technique.

Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes.

BACKGROUND: Low-dose computed tomography (LDCT) are performed routinely for lung cancer screening. However, a large amount of nonpulmonary data from these scans remains unassessed. We aimed to validate a deep learning model to automatically segment and measure left atrial (LA) volumes from routine NCCT and evaluate prediction of cardiovascular outcomes. METHODS: We retrospectively evaluated 273 patients (median age 69 years, 55.5% male) who underwent LDCT for lung cancer screening. LA volumes were quantified by three expert cardiothoracic radiologists and a prototype AI algorithm. LA volumes were then indexed to the body surface area (BSA). Expert and AI LA volume index (LAVi) were compared and used to predict cardiovascular outcomes within five years. Logistic regression with appropriate univariate statistics were used for modelling outcomes. RESULTS: There was excellent correlation between AI and expert results with an LAV intraclass correlation of 0.950 (0.936-0.960). Bland-Altman plot demonstrated the AI underestimated LAVi by a mean 5.86 â€‹mL/m2. AI-LAVi was associated with new-onset atrial fibrillation (AUC 0.86; OR 1.12, 95% CI 1.08-1.18, p â€‹< â€‹0.001), HF hospitalization (AUC 0.90; OR 1.07, 95% CI 1.04-1.13, p â€‹< â€‹0.001), and MACCE (AUC 0.68; OR 1.04, 95% CI 1.01-1.07, p â€‹= â€‹0.01). CONCLUSION: This novel deep learning algorithm for automated measurement of LA volume on lung cancer screening scans had excellent agreement with manual quantification. AI-LAVi is significantly associated with increased risk of new-onset atrial fibrillation, HF hospitalization, and major adverse cardiac and cerebrovascular events within 5 years.

Diagnostic Accuracy and Performance of Artificial Intelligence in Detecting Lung Nodules in Patients With Complex Lung Disease: A Noninferiority Study.

OBJECTIVES: The aim of the study is to investigate the performance of artificial intelligence (AI) convolutional neural networks (CNN) in detecting lung nodules on chest computed tomography of patients with complex lung disease, and demonstrate its noninferiority when compared against an experienced radiologist through clinically relevant assessments. METHODS: A CNN prototype was used to retrospectively evaluate 103 complex lung disease cases and 40 control cases without reported nodules. Computed tomography scans were blindly evaluated by an expert thoracic radiologist; a month after initial analyses, 20 positive cases were re-evaluated with the assistance of AI. For clinically relevant applications: (1) AI was asked to classify each patient into nodules present or absent and (2) AI results were compared against standard radiology reports. Standard statistics were performed to determine detection performance. RESULTS: AI was, on average, 27 seconds faster than the expert and detected 8.4% of nodules that would have been missed. AI had a sensitivity of 67.7%, similar to an accuracy reported for experienced radiologists. AI correctly classified each patient (nodules present/absent) with a sensitivity of 96.1%. When matched against radiology reports, AI performed with a sensitivity of 89.4%. Control group assessment demonstrated an overall specificity of 82.5%. When aided by AI, the expert decreased the average assessment time per case from 2:44 minutes to 35.7 seconds, while reporting an overall increase in confidence. CONCLUSION: In a group of patients with complex lung disease, the sensitivity of AI is similar to an experienced radiologist and the tool helps detect previously missed nodules. AI also helps experts analyze for lung nodules faster and more confidently, a feature that is beneficial to patients and favorable to hospitals due to increased patient load and need for shorter turnaround times.

Prospective Evaluation of the First Integrated Positron Emission Tomography/Dual-Energy Computed Tomography System in Patients With Lung Cancer.

PURPOSE: The aim of this pilot study was to prospectively evaluate the first integrated positron emission tomography (PET)/dual-energy computed tomography (DECT) system performance in patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: In this single-center, prospective trial, consecutive patients with NSCLC referred for a PET study between May 2017 and June 2018 were enrolled. All patients received contrast-enhanced imaging on a clinical PET/DECT system. Data analysis included PET-based standard uptake values (SUVmax) and DECT-based iodine densities of tumor masses, lymph nodes, and distant metastases. Results were analyzed using correlation tests and receiver operating characteristics curves. RESULTS: The study population was composed of 21 patients (median age 62 y, 14 male patients). A moderate positive correlation was found between iodine density values (2.2 mg/mL) and SUVmax (10.5) in tumor masses (ρ=0.53, P<0.01). Iodine density values (2.3 mg/mL) and SUVmax (5.4) of lymph node metastases showed a weak positive correlation (ρ=0.23, P=0.14). In addition, iodine quantification analysis provided no added value in differentiating between pathologic and nonpathologic lymph nodes with an area under the curve (AUC) of 0.55 using PET-based SUVmax as the reference standard. A weak positive correlation was observed between iodine density (2.2 mg/mL) and SUVmax in distant metastases (14.9, ρ=0.23, P=0.52). CONCLUSIONS: The application of an integrated PET/DECT system in lung cancer might provide additional insights in the assessment of tumor masses. However, the added value of iodine density quantification for the evaluation of lymph nodes and distant metastases seems limited.

Compressed sensing acceleration of cardiac cine imaging allows reliable and reproducible assessment of volumetric and functional parameters of the left and right atrium.

OBJECTIVES: To compare volumetric and functional parameters of the atria derived from highly accelerated compressed sensing (CS)-based cine sequences in comparison to conventional (Conv) cine imaging. METHODS: CS and Conv cine sequences were acquired in 101 subjects (82 healthy volunteers (HV) and 19 patients with heart failure with reduced ejection fraction (HFrEF)) using a 3T MR scanner in this single-center study. Time-volume analysis of the left (LA) and right atria (RA) were performed in both sequences to evaluate atrial volumes and function (total, passive, and active emptying fraction). Inter-sequence and inter- and intra-reader agreement were analyzed using correlation, intraclass correlation (ICC), and Bland-Altman analysis. RESULTS: CS-based cine imaging led to a 69% reduction of acquisition time. There was significant difference in atrial parameters between CS and Conv cine, e.g., LA minimal volume (LAVmin) (Conv 24.0 ml (16.7-32.7), CS 25.7 ml (19.2-35.2), p < 0.0001) or passive emptying fraction (PEF) (Conv 53.9% (46.7-58.4), CS 49.0% (42.0-54.1), p < 0.0001). However, there was high correlation between the techniques, yielding good to excellent ICC (0.76-0.99) and small mean of differences in Bland-Altman analysis (e.g. LAVmin - 2.0 ml, PEF 3.3%). Measurements showed high inter- (ICC > 0.958) and intra-rater (ICC > 0.934) agreement for both techniques. CS-based parameters (PEF AUC = 0.965, LAVmin AUC = 0.864) showed equivalent diagnostic ability compared to Conv cine imaging (PEF AUC = 0.989, LAVmin AUC = 0.859) to differentiate between HV and HFrEF. CONCLUSION: Atrial volumetric and functional evaluation using CS cine imaging is feasible with relevant reduction of acquisition time, therefore strengthening the role of CS in clinical CMR for atrial imaging. KEY POINTS: • Reliable assessment of atrial volumes and function based on compressed sensing cine imaging is feasible. • Compressed sensing reduces scan time and has the potential to overcome obstacles of conventional cine imaging. • No significant differences for subjective image quality, inter- and intra-rater agreement, and ability to differentiate healthy volunteers and heart failure patients were detected between conventional and compressed sensing cine imaging.

Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.

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.

Predictive Value of Cardiac CTA, Cardiac MRI, and Transthoracic Echocardiography for Cardioembolic Stroke Recurrence.

BACKGROUND. Transthoracic echocardiography (TTE) is the standard of care for initial evaluation of patients with suspected cardioembolic stroke. Although TTE is useful for assessing certain sources of cardiac emboli, its diagnostic capability is limited in the detection of other sources, including left atrial thrombus and aortic plaques. OBJECTIVE. The purpose of this article was to investigate sensitivity, specificity, and predictive value of cardiac CTA (CCTA), cardiac MRI (CMRI), and TTE for recurrence in patients with suspected cardioembolic stroke. METHODS. We retrospectively included 151 patients with suspected cardioembolic stroke who underwent TTE and either CMRI (n = 75) or CCTA (n = 76) between January 2013 and May 2017. We evaluated for the presence of left atrial thrombus, left ventricular thrombus, vulnerable aortic plaque, cardiac tumors, and valvular vegetation as causes of cardioembolic stroke. The end point was stroke recurrence. Sensitivity, specificity, PPV, and NPV for recurrent stroke were calculated; the diagnostic accuracy of CMRI, CCTA, and TTE was compared between and within groups using AUC. RESULTS. Twelve and 14 recurrent strokes occurred in the CCTA and CMRI groups, respectively. Sensitivity, specificity, PPV, and NPV were 33.3%, 93.7%, 50.0%, and 88.2% for CCTA; 14.3%, 80.3%, 14.3%, and 80.3% for CMRI; 14.3%, 83.6%, 16.7%, and 80.9% for TTE in the CMRI group; and 8.3%, 93.7%, 20.0%, and 84.5% for TTE in the CCTA group. Accuracy was not different (p > .05) between CCTA (AUC = 0.63; 95% CI, 0.49-0.77), CMRI (0.53; 95% CI, 0.42-0.63), TTE in the CMRI group (0.51; 95% CI, 0.40-0.61), and TTE in the CCTA group (0.51; 95% CI, 0.42-0.59). In the CCTA group, atrial and ventricular thrombus were detected by CCTA in three patients and TTE in one patient; in the CMRI group, thrombus was detected by CMRI in one patient and TTE in two patients. CONCLUSION. CCTA, CMRI, and TTE showed comparably high specificity and NPV for cardioembolic stroke recurrence. CCTA and CMRI may be valid alternatives to TTE. CCTA may be preferred given potentially better detection of atrial and ventricular thrombus. CLINICAL IMPACT. CCTA and CMRI have similar clinical performance as TTE for predicting cardioembolic stroke recurrence. This observation may be especially important when TTE provides equivocal findings.

The Feasibility, Tolerability, Safety, and Accuracy of Low-radiation Dynamic Computed Tomography Myocardial Perfusion Imaging With Regadenoson Compared With Single-photon Emission Computed Tomography.

OBJECTIVES: Computed tomography (CT) myocardial perfusion imaging (CT-MPI) with hyperemia induced by regadenoson was evaluated for the detection of myocardial ischemia, safety, relative radiation exposure, and patient experience compared with single-photon emission computed tomography (SPECT) imaging. MATERIALS AND METHODS: Twenty-four patients (66.5 y, 29% male) who had undergone clinically indicated SPECT imaging and provided written informed consent were included in this phase II, IRB-approved, and FDA-approved clinical trial. All patients underwent coronary CT angiography and CT-MPI with hyperemia induced by the intravenous administration of regadenoson (0.4 mg/5 mL). Patient experience and findings on CT-MPI images were compared to SPECT imaging. RESULTS: Patient experience and safety were similar between CT-MPI and SPECT procedures and no serious adverse events due to the administration of regadenoson occurred. SPECT resulted in a higher number of mild adverse events than CT-MPI. Patient radiation exposure was similar during the combined coronary computed tomography angiography and CT-MPI (4.4 [2.7] mSv) and SPECT imaging (5.6 [1.7] mSv) (P-value 0.401) procedures. Using SPECT as the reference standard, CT-MPI analysis showed a sensitivity of 58.3% (95% confidence interval [CI]: 27.7-84.8), a specificity of 100% (95% CI: 73.5-100), and an accuracy of 79.1% (95% CI: 57.9-92.87). Low apparent sensitivity occurred when the SPECT defects were small and highly suspicious for artifacts. CONCLUSIONS: This study demonstrated that CT-MPI is safe, well tolerated, and can be performed with comparable radiation exposure to SPECT. CT-MPI has the benefit of providing both complete anatomic coronary evaluation and assessment of myocardial perfusion.

Artificial Intelligence-based Fully Automated Per Lobe Segmentation and Emphysema-quantification Based on Chest Computed Tomography Compared With Global Initiative for Chronic Obstructive Lung Disease Severity of Smokers.

OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for the fully automated per lobe segmentation and emphysema quantification (EQ) on chest-computed tomography as it compares to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity classification of chronic obstructive pulmonary disease (COPD) patients. METHODS: Patients (n=137) who underwent chest-computed tomography acquisition and spirometry within 6 months were retrospectively included in this Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant study. Patient-specific spirometry data, which included forced expiratory volume in 1 second, forced vital capacity, and the forced expiratory volume in 1 second/forced vital capacity ratio (Tiffeneau-Index), were used to assign patients to their respective GOLD stage I to IV. Lung lobe segmentation was carried out using AI-RAD Companion software prototype (Siemens Healthineers), a deep convolution image-to-image network and emphysema was quantified in each lung lobe to detect the low attenuation volume. RESULTS: A strong correlation between the whole-lung-EQ and the GOLD stages was found (ρ=0.88, P<0.0001). The most significant correlation was noted in the left upper lobe (ρ=0.85, P<0.0001), and the weakest in the left lower lobe (ρ=0.72, P<0.0001) and right middle lobe (ρ=0.72, P<0.0001). CONCLUSIONS: AI-based per lobe segmentation and its EQ demonstrate a very strong correlation with the GOLD severity stages of COPD patients. Furthermore, the low attenuation volume of the left upper lobe not only showed the strongest correlation to GOLD severity but was also able to most clearly distinguish mild and moderate forms of COPD. This is particularly relevant due to the fact that early disease processes often elude conventional pulmonary function diagnostics. Earlier detection of COPD is a crucial element for positively altering the course of disease progression through various therapeutic options.

Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT.

In this article, the authors discuss the technical background and summarize the current body of literature regarding virtual monoenergetic (VM) images derived from dual-energy CT data, which can be reconstructed between 40 and 200 keV. Substantially improved iodine attenuation at lower kiloelectron volt levels and reduced beam-hardening artifacts at higher kiloelectron volt levels have been demonstrated from all major manufacturers of dual-energy CT units. Improved contrast attenuation with VM imaging at lower kiloelectron volt levels enables better delineation and diagnostic accuracy in the detection of various vascular or oncologic abnormalities. Low-kiloelectron-volt VM imaging may be useful for salvaging CT studies with suboptimal contrast material delivery or providing additional information on the arterial vasculature obtained from venous phase acquisitions. For patients with renal impairment, substantial reductions in the use of iodinated contrast material can be achieved by using lower-energy VM imaging. The authors recommend routine reconstruction of VM images at 50 keV when using dual-energy CT to exploit the increased contrast properties. For reduction of beam-hardening artifacts, VM imaging at 120 keV is useful for the initial assessment.

Coronary CT angiography radiation dose trends: A 10-year analysis to develop institutional diagnostic reference levels.

PURPOSE: To develop institutional diagnostic reference levels (IDRL) for coronary CT angiography (CCTA) according to patient size by analyzing radiation dose changes over the past 10 years. MATERIALS AND METHODS: This IRB approved retrospective investigation analyzed radiation dose data from CCTA between 2007 and 2016 at our institution. Annual trends in radiation dose were described for each scanner type and scanning mode. Radiation levels were analyzed for normorhythmic patients, patients with prior coronary artery bypass grafting (CABG), arrhythmia, and according to patient size and tube voltage. Median, and quartile values for volume CT dose index (CTDIvol), dose-length product (DLP), and size-specific dose estimate (SSDE) were calculated. Wilcoxon rank-sum test and Kruskal Wallis test were performed to assess the significance of quantitative data. RESULTS: 35,375 examinations from 33,317 patients (median age, 58 [50-66] years; male patients, 21,087 [58.7%]) were analyzed. CTDIvol, DLP, and SSDE significantly decreased by 9.0%, 30.8%, and 40.1% (all P < 0.05) for all examinations, respectively. All radiation dose metrics progressively decreased across scanning modes (especially retrospectively ECG-gated spiral and prospectively ECG-triggered high-pitch spiral acquisition mode), but did not significantly change across scanners in the last 6 years. CTDIvol and DLP increased with patient size when water-equivalent diameters were >19 cm for normorhythmic and CABG patients. In arrhythmic patients, CTDIvol increased progressively with water-equivalent diameters across all groups. CONCLUSION: CCTA radiation dose has progressively decreased in the past decade except in patients with prior CABG and arrhythmia. Size-specific IDRLs may optimize radiation utilization in these patients going forward.