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Cardiac computed tomography (CT) and cardiac magnetic resonance imaging (MRI) are routine radiological examinations for diagnosis and prognosis of cardiac disease. The expected growth in cardiac radiology in the coming years will exceed the current scanner capacity and trained workforce. The European Society of Cardiovascular Radiology (ESCR) focuses on supporting and strengthening the role of cardiac cross-sectional imaging in Europe from a multi-modality perspective. Together with the European Society of Radiology (ESR), the ESCR has taken the initiative to describe the current status of, a vision for, and the required activities in cardiac radiology to sustain, increase and optimize the quality and availability of cardiac imaging and experienced radiologists across Europe. Key Points: • Providing adequate availability for performing and interpreting cardiac CT and MRI is essential, especially with expanding indications. • The radiologist has a central role in non-invasive cardiac imaging examinations which encompasses the entire process from selecting the best modality to answer the referring physician's clinical question to long-term image storage. • Optimal radiological education and training, knowledge of the imaging process, regular updating of diagnostic standards, and close collaboration with colleagues from other specialties are essential. [ABSTRACT FROM AUTHOR]

In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of 'non visual' markers that contribute to establishing diagnosis or prognosis. Important catalysts to these developments in thoracic imaging include new indications (like computed tomography [CT] lung cancer screening) and the COVID‐19 pandemic. This review focuses on developments in CT, radiomics, artificial intelligence (AI) and x‐ray velocimetry for imaging of the lungs. Recent developments in CT include the potential for ultra‐low‐dose CT imaging for lung nodules, and the advent of a new generation of CT systems based on photon‐counting detector technology. Radiomics has demonstrated potential towards predictive and prognostic tasks particularly in lung cancer, previously not achievable by visual inspection by radiologists, exploiting high dimensional patterns (mostly texture related) on medical imaging data. Deep learning technology has revolutionized the field of AI and as a result, performance of AI algorithms is approaching human performance for an increasing number of specific tasks. X‐ray velocimetry integrates x‐ray (fluoroscopic) imaging with unique image processing to produce quantitative four dimensional measurement of lung tissue motion, and accurate calculations of lung ventilation. See relatedEditorial [ABSTRACT FROM AUTHOR]

Background: Contained rupture of the ascending aorta is a rare condition, but the severity of this complication enforces strict guidelines for its prevention and a prompt diagnosis, once already occurred. Case presentation: A 66-year-old man with a history of type 2 diabetes, longstanding aortic valve stenosis and aortic root aneurysm of 47 mm was hospital admitted for elective surgery. A Bentall-De Bono procedure was performed in order to replace the stenotic bicuspid aortic valve and exclude the dilated portion of the aortic wall. Intraoperatively, a discontinuity of the aortic wall, just above the aortic annulus, at the non-coronary sinus of Valsalva was incidentally observed. The aortic wall discontinuity was none other than a contained aortic rupture. The preoperative CT-scan images were afterwards analyzed by the radiologist, in order to identify the contained aortic rupture. Indeed a false aneurysm of the non-coronary sinus of Valsalva of a maximum diameter of 15 mm was detected, thanks to a 3D reconstruction. Conclusions: The diagnosis of contained aortic rupture is certainly demanding, particularly in absence of signs or symptoms of rupture in a chamber of the heart or in the pericardium. Although this case represents a consensus of experts' opinion, the recognition of these specific cases in which the risk of dissection, rupture or death is at its highest, would allow to operate at the appropriate time, improving the outcomes. [ABSTRACT FROM AUTHOR]

Objectives: We sought to investigate if artificial medical images can blend with original ones and whether they adhere to the variable anatomical constraints provided. Methods: Artificial images were generated with a generative model trained on publicly available standard and low-dose chest CT images (805 scans; 39,803 2D images), of which 17% contained evidence of pathological formations (lung nodules). The test set (90 scans; 5121 2D images) was used to assess if artificial images (512 × 512 primary and control image sets) blended in with original images, using both quantitative metrics and expert opinion. We further assessed if pathology characteristics in the artificial images can be manipulated. Results: Primary and control artificial images attained an average objective similarity of 0.78 ± 0.04 (ranging from 0 [entirely dissimilar] to 1[identical]) and 0.76 ± 0.06, respectively. Five radiologists with experience in chest and thoracic imaging provided a subjective measure of image quality; they rated artificial images as 3.13 ± 0.46 (range of 1 [unrealistic] to 4 [almost indistinguishable to the original image]), close to their rating of the original images (3.73 ± 0.31). Radiologists clearly distinguished images in the control sets (2.32 ± 0.48 and 1.07 ± 0.19). In almost a quarter of the scenarios, they were not able to distinguish primary artificial images from the original ones. Conclusion: Artificial images can be generated in a way such that they blend in with original images and adhere to anatomical constraints, which can be manipulated to augment the variability of cases. Critical relevance statement: Artificial medical images can be used to enhance the availability and variety of medical training images by creating new but comparable images that can blend in with original images. Key points: • Artificial images, similar to original ones, can be created using generative networks. • Pathological features of artificial images can be adjusted through guiding the network. • Artificial images proved viable to augment the depth and broadening of diagnostic training. [ABSTRACT FROM AUTHOR]

Objectives Although exponential growth is assumed for lung cancer, this has never been quantified in vivo. Aim of this study was to evaluate and quantify growth patterns of lung cancers detected in the Dutch-Belgian low-dose computed tomography (CT) lung cancer screening trial (NELSON), in order to elucidate the development and progression of early lung cancer. Materials and methods Solid lung nodules found at ≥3 CT examinations before lung cancer diagnosis were included. Lung cancer volume ( V ) growth curves were fitted with a single exponential, expressed as V = V 1 exp( t / τ ), with t time from baseline (days), V 1 estimated baseline volume (mm 3 ), and τ estimated time constant. The R 2 coefficient of determination was used to evaluate goodness of fit. Overall volume-doubling time for the individual lung cancer is given by τ * log(2). Results Forty-seven lung cancers in 46 participants were included. Forty participants were male (87.0%); mean age was 61.7 years (standard deviation, 6.2 years). Median nodule size at baseline was 99.5 mm 3 (IQR: 46.8–261.8 mm 3 ). Nodules were followed for a median of 770 days (inter-quartile range: 383–1102 days) before lung cancer diagnosis. One cancer (2.1%) was diagnosed after six CT examinations, six cancers (12.8%) were diagnosed after five CTs, 14 (29.8%) after four CTs, and 26 cancers (55.3%) after three CTs. Lung cancer growth could be described by an exponential function with excellent goodness of fit ( R 2 0.98). Median overall volume-doubling time was 348 days (inter-quartile range: 222–492 days). Conclusion This study based on CT lung cancer screening provides in vivo evidence that growth of cancerous small-to-intermediate sized lung nodules detected at low-dose CT lung cancer screening can be described by an exponential function such as volume-doubling time. [ABSTRACT FROM AUTHOR]

Purpose: To determine which left atrial (LA) and left ventricular (LV) parameters are associated with future major adverse cardiac event (MACE) and whether these measurements have independent prognostic value beyond risk factors and computed tomography (CT)-derived coronary artery disease measures.Materials and Methods: This retrospective analysis was performed under an IRB waiver and in HIPAA compliance. Subjects underwent coronary CT angiography (CCTA) using a dual-source CT system for acute chest pain evaluation. LV mass, LV ejection fraction (EF), LV end-systolic volume (ESV) and LV end-diastolic volume (EDV), LA ESV and LA diameter, septal wall thickness and cardiac chamber diameters were measured. MACE was defined as cardiac death, non-fatal myocardial infarction, unstable angina, or late revascularization. The association between cardiac CT measures and the occurrence of MACE was quantified using Cox proportional hazard analysis.Results: 225 subjects (age, 56.2±11.2; 140 males) were analyzed, of whom 42 (18.7%) experienced a MACE during a median follow-up of 13 months. LA diameter (HR:1.07, 95%CI:1.01-1.13permm) and LV mass (HR:1.05, 95%CI:1.00-1.10perg) remained significant prognostic factor of MACE after controlling for Framingham risk score. LA diameter and LV mass were also found to have prognostic value independent of each other. The other morphologic and functional cardiac measures were no significant prognostic factors for MACE.Conclusion: CT-derived LA diameter and LV mass are associated with future MACE in patients undergoing evaluation for chest pain, and portend independent prognostic value beyond traditional risk factors, coronary calcium score, and obstructive coronary artery disease. [ABSTRACT FROM AUTHOR]

Blacks have higher mortality and hospitalization rates because of congestive heart failure compared with white counterparts. Differences in cardiac structure and function may contribute to the racial disparity in cardiovascular outcomes. Our aim was to compare computed tomography (CT)-derived cardiac measurements between black patients with acute chest pain and age- and gender-matched white patients. We performed a retrospective analysis under an institutional review board waiver and in Health Insurance Portability and Accountability Act compliance. We investigated patients who underwent cardiac dual-source CT for acute chest pain. Myocardial mass, left ventricular (LV) ejection fraction, LV end-systolic volume, and LV end-diastolic volume were quantified using an automated analysis algorithm. Septal wall thickness and cardiac chamber diameters were manually measured. Measurements were compared by independent t test and linear regression. The study population consisted of 300 patients (150 black-mean age 54 ± 12 years; 46% men; 150 white-mean age 55 ± 11 years; 46% men). Myocardial mass was larger for blacks compared with white (176.1 ± 58.4 vs 155.9 ± 51.7 g, p = 0.002), which remained significant after adjusting for age, gender, body mass index, and hypertension. Septal wall thickness was slightly greater (11.9 ± 2.7 vs 11.2 ± 3.1 mm, p = 0.036). The LV inner diameter was moderately larger in black patients in systole (32.3 ± 9.0 vs 30.1 ± 5.4 ml, p = 0.010) and in diastole (50.1 ± 7.8 vs 48.9 ± 5.2 ml, p = 0.137), as well as LV end-diastolic volume (134.5 ± 42.7 vs 128.2 ± 30.6 ml, p = 0.143). Ejection fraction was nonsignificantly lower in blacks (67.1 ± 13.5% vs 69.0 ± 9.6%, p = 0.169). In conclusion, CT-derived myocardial mass was larger in blacks compared with whites, whereas LV functional parameters were generally not statistically different, suggesting that LV mass might be a possible contributing factor to the higher rate of cardiac events in blacks. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to investigate the association of spirometry and pulmonary CT biomarkers with cardiovascular events. Methods: In this lung cancer screening trial 3,080 male participants without a prior cardiovascular event were analysed. Fatal and non-fatal cardiovascular events were included. Spirometry included forced expiratory volume measured in units of one-second percent predicted (FEV%predicted) and FEV divided by forced vital capacity (FVC; FEV/FVC). CT examinations were quantified for coronary artery calcium volume, pulmonary emphysema (perc15) and bronchial wall thickness (pi10). Data were analysed via a Cox proportional hazard analysis, net reclassification improvement (NRI) and C-indices. Results: 184 participants experienced a cardiovascular event during a median follow-up of 2.9 years. Age, pack-years and smoking status adjusted hazard ratios were 0.992 (95 % confidence interval (CI) 0.985-0.999) for FEV%predicted, 1.000 (95%CI 0.986-1.015) for FEV/FVC, 1.014 (95%CI 1.005-1.023) for perc15 per 10 HU, and 1.269 (95%CI 1.024-1.573) for pi10 per 1 mm. The incremental C-index (<0.015) and NRI (<2.8 %) were minimal. Coronary artery calcium volume had a hazard ratio of 1.046 (95%CI 1.034-1.058) per 100 mm, an increase in C-index of 0.076 and an NRI of 16.9 % ( P < 0.0001). Conclusions: Pulmonary CT biomarkers and spirometry measurements were significantly associated with cardiovascular events, but did not contain clinically relevant independent prognostic information for cardiovascular events. Key Points: • Pulmonary CT biomarkers and spirometry are associated with cardiovascular events • These pulmonary measurements do not contain clinically relevant independent prognostic information • Only coronary calcium score improved cardiovascular risk prediction above age and smoking [ABSTRACT FROM AUTHOR]

Purpose: To assess the accuracy of dual-energy CT (DECT) for the quantification of iodine concentrations in a thoracic phantom across various cardiac DECT protocols and simulated patient sizes. Materials and methods: Experiments were performed on first- and second-generation dual-source CT (DSCT) systems in DECT mode using various cardiac DECT protocols. An anthropomorphic thoracic phantom was equipped with tubular inserts containing known iodine concentrations (0-20 mg/mL) in the cardiac chamber and up to two fat-equivalent rings to simulate different patient sizes. DECT-derived iodine concentrations were measured using dedicated software and compared to true concentrations. General linear regression models were used to identify predictors of measurement accuracy Results: Correlation between measured and true iodine concentrations ( n = 72) across CT systems and protocols was excellent ( R = 0.994-0.997, P < 0.0001). Mean measurement errors were 3.0 ± 7.0 % and −2.9 ± 3.8 % for first- and second-generation DSCT, respectively. This error increased with simulated patient size. The second-generation DSCT showed the most stable measurements across a wide range of iodine concentrations and simulated patient sizes. Conclusion: Overall, DECT provides accurate measurements of iodine concentrations across cardiac CT protocols, strengthening the case for DECT-derived blood volume estimates as a surrogate of myocardial blood supply. Key Points: • Dual-energy CT provides new opportunities for quantitative assessment in cardiac imaging. • DECT can quantify myocardial iodine as a surrogate for myocardial perfusion. • DECT measurements of iodine concentrations are overall very accurate. • The accuracy of such measurements decreases as patient size increases. [ABSTRACT FROM AUTHOR]

Current multi-detector CT and electron beam tomography (EBT) technology enables the evaluation of coronary calcification. Multiple software packages are available to quantify calcification using several scoring algorithms implementing user-definable scoring parameters. We investigated the effect of scoring parameters on the calcium score outcome. Three parameters (four-connected or eight-connected, lesion size threshold and interpolation) are evaluated. Their theoretical influence on the scoring outcome is shown using simplified examples. To evaluate the effect in real data, we performed calcium scoring on randomly chosen EBT scans from 50 participants in an epidemiological study. Both the Agatston and volume scores were calculated. Changing from eight-connected to four-connected connectivity decreased both Agatston and volume scores (mean variability Agatston 3.15% and volume score -3.52%). Decreasing the threshold from 4 to 2 pixels increased the calcium scores because smaller lesions were also selected as calcified plaques (mean variability Agatston 16.23% and volume score 18.66%). Finally, the use of interpolation had a large negative effect on the volume score (mean variability -29.67%) and almost no effect on the Agatston score. Parameter settings in software for quantification for coronary calcification affect the calcium score outcome. Therefore, parameter settings for calcium scoring should be standardized. [ABSTRACT FROM AUTHOR]

Background A U- or J-shaped association exists between alcohol consumption and coronary heart disease. One of the proposed mechanisms for this association involves atherogenesis, but there are no data on the association between alcohol consumption and coronary atherosclerosis in asymptomatic subjects. Coronary calcification, a measure of coronary atherosclerosis, allows for the study of the association. Methods This cross-sectional study was performed using data from the population-based Rotterdam Coronary Calcification Study. Data on alcohol consumption were available for 1795 individuals without coronary heart disease. Mean ± SD age of the participants was 71 ± 5.7 years. Coronary calcification was detected on electron beam computed tomographic scans and quantified as a calcium score by the Agatston method. Extensive coronary calcification was defined as a calcium score above 400. Results In this population, 15.8% of individuals consumed no alcohol; 46.5% consumed 1 alcoholic drink or less per day; 16.9% consumed 1 to 2 drinks per day; and 20.9% consumed more than 2 drinks per day. A U-shaped association was found between alcohol consumption and coronary calcification. Compared with nondrinkers, the odds ratio of extensive coronary calcification was 0.60 (95% confidence interval [CI], 0.44-0.82) for those who consumed 1 drink or less daily; 0.51 (95% CI, 0.35-0.76) for those who consumed 1 to 2 drinks daily; and 0.90 (95% CI, 0.62-1.29) for those who consumed more than 2 drinks. The association remained after multivariate adjustment. Conclusions The consumption of 2 alcoholic drinks or fewer per day was inversely associated with extensive coronary calcification. The risk of extensive coronary calcification was 50% lower in individuals who consumed 1 to 2 alcoholic drinks per day than in nondrinkers. [ABSTRACT FROM AUTHOR]

Purpose: The Rose questionnaire is a standardized method of measuring angina pectoris in general populations. Electron-beam computed tomography (CT) is a non-invasive technique to quantify the amount of coronary calcification. In a population-based study, we investigated the association between Rose questionnaire angina pectoris and coronary calcification.Methods: The Rotterdam Coronary Calcification Study is embedded in the Rotterdam Study, a population-based study in subjects aged ⩾55 years. Participants of the Rotterdam Coronary Calcification Study underwent an electron-beam CT scan between 1997 and 2000. Coronary calcification was quantified in a calcium score according to Agatston''s method. Rose questionnaire angina pectoris was assessed during a home interview. The first 2013 participants were included in the present analyses.Results: In men, the presence of Rose questionnaire angina pectoris was associated with a 12.9-fold (95% confidence interval: 3.8–43.7) increased risk of a calcium score >1000 (reference: calcium score 0–100). The corresponding relative risk in women was 4.8 (2.0–11.3). Similar results were found when we computed sex-specific quartiles of the calcium score.Conclusions: Rose questionnaire angina pectoris is strongly associated with the amount of coronary calcification. Rose questionnaire angina pectoris corresponds better with the amount of coronary calcification in men than in women. [Copyright &y& Elsevier]

: ObjectivesThe present study was designed to examine the associations of coronary calcification assessed by electron beam computed tomography (CT) with measures of extracoronary atherosclerosis.: BackgroundAlthough measures of extracoronary atherosclerosis have been used to predict coronary events, it is not yet known to what extent those measures reflect coronary atherosclerosis.: MethodsThe Rotterdam Coronary Calcification Study is a population-based study in subjects age 55 years and over. Participants of the study underwent an electron beam CT scan. Coronary calcification was quantified according to the Agatston calcium score. Measures of extracoronary atherosclerosis included common carotid intima media thickness (IMT), carotid plaques, ankle-arm index (AAI) and aortic calcification. We used the first 2,013 participants for the present analyses. Age-adjusted geometric mean calcium scores were computed for categories of extracoronary measures using analyses of variance.: ResultsGraded associations with coronary calcification were found for the carotid and aortic measures. Associations were strongest for carotid plaques and aortic calcification; coronary calcification increased from the lowest category (no plaques) to the highest category 9-fold and 11-fold in men and 10-fold and 20-fold in women, respectively. A nonlinear association was found for AAI with an increase in coronary calcification only at lower levels of AAI.: ConclusionsIn this population-based study, graded associations were found between coronary calcification and common carotid IMT, carotid plaques and aortic calcification. A nonlinear association was found between coronary calcification and the AAI. [Copyright &y& Elsevier]

Background and objective: Bronchiectasis is a frequent incidental finding on chest computed tomography (CT), but its relevance in lung cancer screening is not fully understood. We investigated the association between bronchiectasis and respiratory symptoms, pulmonary function, and emphysema in lung cancer screening participants with and without chronic obstructive pulmonary disease (COPD). Methods: We included 3260 (ex-)smokers from the Dutch-Belgian lung cancer screening trial (NELSON). Bronchiectasis was scored by chest radiologists. The relationship with pulmonary function (FEV1%predicted, FEV1/FVC), respiratory complaints (cough, dyspnea, wheezing, mucus hypersecretion), and CT-quantified emphysema (15th percentile) was examined with independent t-tests and multivariate regression. Results: Bronchiectasis was present in 5.4% (n = 175/3260). There was no difference in prevalence between subjects with and without COPD (68/1121 [5.9%] vs. 109/2139 [5.1%]; p =.368). COPD subjects with bronchiectasis had a lower FEV1%predicted (76.2% vs. 85.0%; p <.001), lower FEV1/FVC (0.58 vs. 0.62; p <.001), and more emphysema (− 938 HU vs. − 930 HU; p =.001) than COPD subjects without bronchiectasis. In COPD subjects, bronchiectasis was independently associated with a lower FEV1%predicted (B = − 7.7; CI [− 12.3, − 3.3]), lower FEV1/FVC (B = − 2.5; CI [− 4.3, − 0.8]), more cough (OR 2.4; CI [1.3, 4.3]), more mucus hypersecretion (OR 1.8; CI [1.0, 3.1]) and more dyspnea (OR 2.3; CI [1.3, 3.9]). In those without COPD (n = 2139), bronchiectasis was associated with more cough, mucus hypersecretion, and wheezing, but not with deteriorating lung function. Conclusion: Bronchiectasis was present in 5.4% of our lung cancer screening participants and was associated with more respiratory symptoms and, in those with COPD, with lower lung function and more emphysema. Clinical relevance statement: In a lung cancer screening population, bronchiectasis has a prevalence of 5.4% with a mainly mild severity. This finding is of little clinical relevance unless mild COPD is also present. In those subjects, bronchiectasis was associated with a lower lung function, more respiratory symptoms, and more emphysema. Key Points: • Bronchiectasis was found in 5.4% of lung cancer screening participants, consisting of (ex-)smokers with and without mild COPD. • In those with mild COPD, bronchiectasis was associated with a lower lung function, more respiratory symptoms, and more emphysema. • Incidental findings of mild bronchiectasis are not very relevant in a lung cancer screening population, unless COPD is also present. [ABSTRACT FROM AUTHOR]

Objectives: Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its performance across different populations. This systematic review and meta-analysis aimed to evaluate the performance of Lung-RADS (versions 1.0 and 1.1) for detecting lung cancer in different populations. Methods: We performed literature searches in PubMed, Web of Science, Cochrane Library, and Embase databases on October 21, 2022, for studies that evaluated the accuracy of Lung-RADS in lung cancer screening. A bivariate random-effects model was used to estimate pooled sensitivity and specificity, and heterogeneity was explored in stratified and meta-regression analyses. Results: A total of 31 studies with 104,224 participants were included. For version 1.0 (27 studies, 95,413 individuals), pooled sensitivity was 0.96 (95% confidence interval [CI]: 0.90–0.99) and pooled specificity was 0.90 (95% CI: 0.87–0.92). Studies in high-risk populations showed higher sensitivity (0.98 [95% CI: 0.92–0.99] vs. 0.84 [95% CI: 0.50–0.96]) and lower specificity (0.87 [95% CI: 0.85–0.88] vs. 0.95 (95% CI: 0.92–0.97]) than studies in general populations. Non-Asian studies tended toward higher sensitivity (0.97 [95% CI: 0.91–0.99] vs. 0.91 [95% CI: 0.67–0.98]) and lower specificity (0.88 [95% CI: 0.85–0.90] vs. 0.93 [95% CI: 0.88–0.96]) than Asian studies. For version 1.1 (4 studies, 8811 individuals), pooled sensitivity was 0.91 (95% CI: 0.83–0.96) and specificity was 0.81 (95% CI: 0.67–0.90). Conclusion: Among studies using Lung-RADS version 1.0, considerable heterogeneity in sensitivity and specificity was noted, explained by population type (high risk vs. general), population area (Asia vs. non-Asia), and cancer prevalence. Clinical relevance statement: Meta-regression of lung cancer screening studies using Lung-RADS version 1.0 showed considerable heterogeneity in sensitivity and specificity, explained by the different target populations, including high-risk versus general populations, Asian versus non-Asian populations, and populations with different lung cancer prevalence. Key Points: • High-risk population studies showed higher sensitivity and lower specificity compared with studies performed in general populations by using Lung-RADS version 1.0. • In non-Asian studies, the diagnostic performance of Lung-RADS version 1.0 tended to be better than in Asian studies. • There are limited studies on the performance of Lung-RADS version 1.1, and evidence is lacking for Asian populations. [ABSTRACT FROM AUTHOR]

This article discusses the use of computed tomography (CT) in the diagnosis and treatment of coronary artery disease (CAD). The evidence suggests that CT can accurately detect CAD and improve patient outcomes compared to invasive procedures. Three fundamental changes are proposed for integrating CT into clinical pathways for CAD: better prevention of cardiovascular events, individual determination of treatment strategy, and improved procedural planning. However, there are limitations to the current evidence base, and further research is needed to assess the use of CT in different patient populations. Overall, multidisciplinary research has made important advancements in CAD diagnosis and treatment, and there is potential for further improvements in non-invasive cardiovascular imaging. [Extracted from the article]

Objectives: To present a framework to develop and implement a fast-track artificial intelligence (AI) curriculum into an existing radiology residency program, with the potential to prepare a new generation of AI conscious radiologists. Methods: The AI-curriculum framework comprises five sequential steps: (1) forming a team of AI experts, (2) assessing the residents' knowledge level and needs, (3) defining learning objectives, (4) matching these objectives with effective teaching strategies, and finally (5) implementing and evaluating the pilot. Following these steps, a multidisciplinary team of AI engineers, radiologists, and radiology residents designed a 3-day program, including didactic lectures, hands-on laboratory sessions, and group discussions with experts to enhance AI understanding. Pre- and post-curriculum surveys were conducted to assess participants' expectations and progress and were analyzed using a Wilcoxon rank-sum test. Results: There was 100% response rate to the pre- and post-curriculum survey (17 and 12 respondents, respectively). Participants' confidence in their knowledge and understanding of AI in radiology significantly increased after completing the program (pre-curriculum means 3.25 ± 1.48 (SD), post-curriculum means 6.5 ± 0.90 (SD), p-value = 0.002). A total of 75% confirmed that the course addressed topics that were applicable to their work in radiology. Lectures on the fundamentals of AI and group discussions with experts were deemed most useful. Conclusion: Designing an AI curriculum for radiology residents and implementing it into a radiology residency program is feasible using the framework presented. The 3-day AI curriculum effectively increased participants' perception of knowledge and skills about AI in radiology and can serve as a starting point for further customization. Critical relevance statement: The framework provides guidance for developing and implementing an AI curriculum in radiology residency programs, educating residents on the application of AI in radiology and ultimately contributing to future high-quality, safe, and effective patient care. Key points: • AI education is necessary to prepare a new generation of AI-conscious radiologists. • The AI curriculum increased participants' perception of AI knowledge and skills in radiology. • This five-step framework can assist integrating AI education into radiology residency programs. [ABSTRACT FROM AUTHOR]

The aim of this phantom study was to assess the detectability and volumetric accuracy of pulmonary nodules on photon-counting detector CT (PCD-CT) at different low-dose levels compared to conventional energy-integrating detector CT (EID-CT). In-house fabricated artificial nodules of different shapes (spherical, lobulated, spiculated), sizes (2.5–10 mm and 5–1222 mm3), and densities (−330 HU and 100 HU) were randomly inserted into an anthropomorphic thorax phantom. The phantom was scanned with a low-dose chest protocol with PCD-CT and EID-CT, in which the dose with PCD-CT was lowered from 100% to 10% with respect to the EID-CT reference dose. Two blinded observers independently assessed the CT examinations of the nodules. A third observer measured the nodule volumes using commercial software. The influence of the scanner type, dose, observer, physical nodule volume, shape, and density on the detectability and volumetric accuracy was assessed by a multivariable regression analysis. In 120 CT examinations, 642 nodules were present. Observer 1 and 2 detected 367 (57%) and 289 nodules (45%), respectively. With PCD-CT and EID-CT, the nodule detectability was similar. The physical nodule volumes were underestimated by 20% (range 8–52%) with PCD-CT and 24% (range 9–52%) with EID-CT. With PCD-CT, no significant decrease in the detectability and volumetric accuracy was found at dose reductions down to 10% of the reference dose (p > 0.05). The detectability and volumetric accuracy were significantly influenced by the observer, nodule volume, and a spiculated nodule shape (p < 0.05), but not by dose, CT scanner type, and nodule density (p > 0.05). Low-dose PCD-CT demonstrates potential to detect and assess the volumes of pulmonary nodules, even with a radiation dose reduction of up to 90%. [ABSTRACT FROM AUTHOR]

Objectives: Computed tomography (CT)–based bronchial parameters correlate with disease status. Segmentation and measurement of the bronchial lumen and walls usually require significant manpower. We evaluate the reproducibility of a deep learning and optimal-surface graph-cut method to automatically segment the airway lumen and wall, and calculate bronchial parameters. Methods: A deep-learning airway segmentation model was newly trained on 24 Imaging in Lifelines (ImaLife) low-dose chest CT scans. This model was combined with an optimal-surface graph-cut for airway wall segmentation. These tools were used to calculate bronchial parameters in CT scans of 188 ImaLife participants with two scans an average of 3 months apart. Bronchial parameters were compared for reproducibility assessment, assuming no change between scans. Results: Of 376 CT scans, 374 (99%) were successfully measured. Segmented airway trees contained a mean of 10 generations and 250 branches. The coefficient of determination (R2) for the luminal area (LA) ranged from 0.93 at the trachea to 0.68 at the 6th generation, decreasing to 0.51 at the 8th generation. Corresponding values for Wall Area Percentage (WAP) were 0.86, 0.67, and 0.42, respectively. Bland–Altman analysis of LA and WAP per generation demonstrated mean differences close to 0; limits of agreement (LoA) were narrow for WAP and Pi10 (± 3.7% of mean) and wider for LA (± 16.4–22.8% for 2–6th generations). From the 7th generation onwards, there was a sharp decrease in reproducibility and a widening LoA. Conclusion: The outlined approach for automatic bronchial parameter measurement on low-dose chest CT scans is a reliable way to assess the airway tree down to the 6th generation. Statement on clinical relevance: This reliable and fully automatic pipeline for bronchial parameter measurement on low-dose CT scans has potential applications in screening for early disease and clinical tasks such as virtual bronchoscopy or surgical planning, while also enabling the exploration of bronchial parameters in large datasets. Key Points: • Deep learning combined with optimal-surface graph-cut provides accurate airway lumen and wall segmentations on low-dose CT scans. • Analysis of repeat scans showed that the automated tools had moderate-to-good reproducibility of bronchial measurements down to the 6thgeneration airway. • Automated measurement of bronchial parameters enables the assessment of large datasets with less man-hours. [ABSTRACT FROM AUTHOR]

Objectives: To assess the incidence of acute adverse events (AAEs) in gadolinium-enhanced cardiac magnetic resonance (CMR) imaging.Methods: Gadolinium-based contrast agent (GBCA)-enhanced CMR data from the multinational, multicenter European Society of Cardiovascular Radiology MRCT Registry was included. AAE severity was classified according to the American College of Radiology Manual on Contrast Media (mild, moderate, severe). Multivariable generalized linear mixed effect models were used to assess the likelihood of AAEs in various GBCA, adjusting for pharmacological stressor, main indications (i.e., suspected or known coronary artery disease or myocarditis), age, sex, and submitting center as a random effect.Results: In the study population of 72,839 GBCA-enhanced CMRs, a total of 260 AAEs were reported (0.36%), with a minority of severe AAEs (n = 24, 0.033%). Allergic-like AAEs were less likely than physiologic AAEs (29% versus 71%). Patients without pharmacological stress imaging had a lower AAE rate (0.22%) compared to stress imaging (0.75%), with the highest AAE rates for regadenoson (2.95%). AAE rates also varied by GBCA subtype (overall p < 0.001). There was significant interaction between GBCA and pharmacological stressor (interaction p = 0.025), with AAE rates ranging between 0 and 10% for certain GBCA/stressor combinations. There was further marginal evidence that higher GBCA volume was associated with higher AAE incidence (OR = 1.02, p = 0.05).Conclusion: GBCA-enhanced CMR imaging demonstrates low AAE rates comparable to those of other body regions. AAE likelihood correlates with GBCA subtype, pharmacological stressor, and imaging indication. Intravenous fluid administration in patients with cardiac impairment might contribute to these findings.Key Points: • Acute adverse event rates in cardiac magnetic resonance (CMR) imaging with gadolinium-based contrast agents (GBCAs) are low (0.36%), especially for severe adverse events (0.033%). • Mild and moderate adverse events are more frequent during stress CMR imaging. • Physiologic AAEs are more common than allergic AAEs in CMR imaging. [ABSTRACT FROM AUTHOR]

This study describes the development and evaluation of an auto-segmentation tool for the left anterior descending coronary artery (LAD), on non-contrast planning computed tomography scans of breast cancer patients. The dosimetric parameters of the auto-segmented LAD contours are highly correlated with those of manual contours (R 2-values ≥0.89). [ABSTRACT FROM AUTHOR]

Background: Lung cancer screening can reduce cancer mortality. Most implementation studies focus only on low-dose computed tomography (LDCT) and clinical attributes of screening and do not include preferences of potential participants. In this study we evaluated the perceived value of screening programs based on LDCT, breath analysis (BA), or blood biomarkers (BB) according to the perspective of the target population.Methods: A multi-criteria decision analysis framework was adopted. The weights of seven attributes of screening (sensitivity, specificity, radiation burden, duration of screening process, waiting time until results are communicated, location of screening, and mode of screening) were obtained from an earlier study that included a broad sample from the Netherlands. Performance data for the screening modalities was obtained from clinical trials and expert opinion. Parameter uncertainty about clinical performances was incorporated probabilistically, while heterogeneity in preferences was analyzed through subgroup analyses.Results: The mean overall values were 0.58 (CI: 0.57 to 0.59), 0.57 (CI: 0.56 to 0.59), and 0.44 (CI: 0.43 to 0.45) for BB, BA, and LDCT, respectively. Seventy-seven per cent of respondents preferred BB or BA. For most subgroups, the overall values were similar to those of the entire sample. BA had the highest value for respondents who would have been eligible for earlier screening trials.Discussion: BB and BA seem valuable to participants because they can be applied in a primary care setting. Although LDCT still seems preferable given its strong and positive evidence base, it is important to take non-clinical attributes into account to maximize attendance. [ABSTRACT FROM AUTHOR]

To evaluate the influence of nodule margin on inter- and intrareader variability in manual diameter measurements and semi-automatic volume measurements of solid nodules detected in low-dose CT lung cancer screening. 25 nodules of each morphological category (smooth, lobulated, spiculated and irregular) were randomly selected from 93 participants of the Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON). Semi-automatic volume measurements were performed using Syngo LungCARE® software (Version Somaris/5 VB10A-W, Siemens, Forchheim, Germany). Three radiologists independently measured mean diameters manually. Impact of nodule margin on interreader variability was evaluated based on systematic error and 95% limits of agreement. Interreader variability was compared with the nodule growth cut-off as used in Lung CT Screening Reporting and Data System (LungRADS; +1.5-mm diameter) and the Dutch-Belgian Randomized Lung Cancer Screening Trial(acronym: NELSON) /British Thoracic Society (+25% volume). For manual diameter measurements, a significant systematic error (up to 1.2 mm) between readers was found in all morphological categories. For semi-automatic volume measurements, no statistically significant systematic error was found. The interreader variability in mean diameter measurements exceeded the 1.5-mm cut-off for nodule growth for all morphological categories [smooth: ±1.9 mm (+27%), lobulated: ±2.0 mm (+33%), spiculated: ±3.5 mm (+133%), irregular: ±4.5 mm (+200%)]. The 25% vol growth cut-off was exceeded slightly for spiculated [28% (+12%)] and irregular [27% (+8%)] nodules. Lung nodule sizing based on manual diameter measurement is affected by nodule margin. Interreader variability increases especially for nodules with spiculated and irregular margins, and causes substantial misclassification of nodule growth. This effect is almost neglectable for semi-automated volume measurements. Semi-automatic volume measurements are superior for both size and growth determination of pulmonary nodules. Nodule assessment based on manual diameter measurements is susceptible to nodule margin. This effect is almost neglectable for semi-automated volume measurements. The larger interreader variability for manual diameter measurement results in inaccurate lung nodule growth detection and size classification. [ABSTRACT FROM AUTHOR]

Objectives: To study the ratio of ablation zone volume to applied energy in computed tomography (CT)-guided radiofrequency ablation (RFA) and microwave ablation (MWA) in patients with hepatocellular carcinoma (HCC) in a cirrhotic liver and in patients with colorectal liver metastasis (CRLM).Methods: In total, 90 liver tumors, 45 HCCs in a cirrhotic liver and 45 CRLMs were treated with RFA or with one of two MWA devices (MWA_A and MWA_B), resulting in 15 procedures for each tumor type, per device. Device settings were recorded and the applied energy was calculated. Ablation volumes were segmented on the contrast-enhanced CT scans obtained 1 week after the procedure. The ratio of ablation zone volume in milliliters to applied energy in kilojoules was determined for each procedure and compared between HCC (RHCC) and CRLM (RCRLM), stratified according to ablation device.Results: With RFA, RHCC and RCRLM were 0.22 mL/kJ (0.14-0.45 mL/kJ) and 0.15 mL/kJ (0.14-0.22 mL/kJ; p = 0.110), respectively. With MWA_A, RHCC was 0.81 (0.61-1.07 mL/kJ) and RCRLM was 0.43 (0.35-0.61 mL/kJ; p = 0.001). With MWA_B, RHCC was 0.67 (0.41-0.85 mL/kJ) and RCRLM was 0.43 (0.35-0.61 mL/kJ; p = 0.040).Conclusions: With RFA, there was no significant difference in energy deposition ratio between tumor types. With both MWA devices, the ratios were higher for HCCs. Tailoring microwave ablation device protocols to tumor type might prevent incomplete ablations.Key Points: • HCCs and CRLMs respond differently to microwave ablation • For MWA, CRLMs required more energy to achieve a similar ablation volume • Tailoring ablation protocols to tumor type might prevent incomplete ablations. [ABSTRACT FROM AUTHOR]

Predicted lung volumes based on the Global Lung Function Initiative (GLI) model are used in pulmonary disease detection and monitoring. It is unknown how well the predicted lung volume corresponds with computed tomography (CT) derived total lung volume (TLV). The aim of this study was to compare the GLI-2021 model predictions of total lung capacity (TLC) with CT-derived TLV. 151 female and 139 male healthy participants (age 45–65 years) were consecutively selected from a Dutch general population cohort, the Imaging in Lifelines (ImaLife) cohort. In ImaLife, all participants underwent low-dose, inspiratory chest CT. TLV was measured by an automated analysis, and compared to predicted TLC based on the GLI-2021 model. Bland-Altman analysis was performed for analysis of systematic bias and range between limits of agreement. To further mimic the GLI-cohort all analyses were repeated in a subset of never-smokers (51% of the cohort). Mean±SD of TLV was 4.7±0.9 L in women and 6.2±1.2 L in men. TLC overestimated TLV, with systematic bias of 1.0 L in women and 1.6 L in men. Range between limits of agreement was 3.2 L for women and 4.2 L for men, indicating high variability. Performing the analysis with never-smokers yielded similar results. In conclusion, in a healthy cohort, predicted TLC substantially overestimates CT-derived TLV, with low precision and accuracy. In a clinical context where an accurate or precise lung volume is required, measurement of lung volume should be considered. [ABSTRACT FROM AUTHOR]

Background: Chest low-dose computed tomography (LDCT) is a promising technology for population-based screening because it is non-invasive, relatively inexpensive, associated with low radiation and highly sensitive to lung cancer. To improve the cost-effectiveness of lung cancer screening, simultaneous screening for other diseases could be considered. This systematic review was conducted to analyse studies that published evidence on the cost-effectiveness of chest LDCT screening programs for different diseases. Methods: Scopus and PubMed were searched for English publications (1 January 2011–22 July 2022) using search terms related to screening, computed tomography and cost-effectiveness. An additional search specifically searched for the cost-effectiveness of screening for lung cancer, chronic obstructive pulmonary disease or cardiovascular disease. Included publications should present a full health economic evaluation of population screening with chest LDCT. The extracted data included the disease screened for, model type, country context of screening, inclusion of comorbidities or incidental findings, incremental costs, incremental effects and the resulting cost-effectiveness ratio amongst others. Reporting quality was assessed using the 2022 Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Results: The search yielded 1799 unique papers, of which 43 were included. Most papers focused on lung cancer screening (n = 40), and three were on coronary calcium scoring. Microsimulation was the most commonly applied modelling type (n = 16), followed by life table analysis (n = 10) and Markov cohort models (n = 10). Studies reflected the healthcare context of the US (n = 15), Canada (n = 4), the UK (n = 3) and 13 other countries. The reported incremental cost-effectiveness ratio ranged from US$10,000 to US$90,000/quality-adjusted life year (QALY) for lung cancer screening compared to no screening and was US$15,900/QALY–US$45,300/QALY for coronary calcium scoring compared to no screening. Discussion: Almost all health economic evaluations of LDCT screening focused on lung cancer. Literature regarding the health economic benefits of simultaneous LDCT screening for multiple diseases is absent. Most studies suggest LDCT screening is cost-effective for current and former smokers aged 55–74 with a minimum of 30 pack-years of smoking history. Consequently, more evidence on LDCT is needed to support further cost-effectiveness analyses. Preferably evidence on simultaneous screening for multiple diseases is needed, but alternatively, on single-disease screening. Registration of systematic review: Prospective Register of Ongoing Systematic Reviews registration CRD42021290228 can be accessed https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=290228. [ABSTRACT FROM AUTHOR]

Lung cancer screening with low-dose CT can save lives. This European Union (EU) position statement presents the available evidence and the major issues that need to be addressed to ensure the successful implementation of low-dose CT lung cancer screening in Europe. This statement identified specific actions required by the European lung cancer screening community to adopt before the implementation of low-dose CT lung cancer screening. This position statement recommends the following actions: a risk stratification approach should be used for future lung cancer low-dose CT programmes; that individuals who enter screening programmes should be provided with information on the benefits and harms of screening, and smoking cessation should be offered to all current smokers; that management of detected solid nodules should use semi-automatically measured volume and volume-doubling time; that national quality assurance boards should be set up to oversee technical standards; that a lung nodule management pathway should be established and incorporated into clinical practice with a tailored screening approach; that non-calcified baseline lung nodules greater than 300 mm3, and new lung nodules greater than 200 mm3, should be managed in multidisciplinary teams according to this EU position statement recommendations to ensure that patients receive the most appropriate treatment; and planning for implementation of low-dose CT screening should start throughout Europe as soon as possible. European countries need to set a timeline for implementing lung cancer screening. [ABSTRACT FROM AUTHOR]

Background: Because early detection of lung cancer can substantially improve survival, there is increasing attention for lung cancer screening.Objectives: To estimate public preferences for lung cancer screening and to identify subgroups in preferences.Methods: Seven important attributes were selected using the literature, interviews, and a panel session. Preferences were elicited using a swing weighting questionnaire. The resulting attribute weights indicate the relative importance of swings from the worst to the best level between attributes. Hierarchical clustering was used to identify subgroups with different attribute weights.Results: One thousand thirty-four respondents from a representative Dutch panel aged between 40 and 80 years were included. The identified attributes were location of screening (weight = 0.18 ± 0.16), mode of screening (weight = 0.17 ± 0.14), sensitivity (weight = 0.16 ± 0.13) and specificity (weight = 0.13 ± 0.12) of the screening modality, waiting time until results (weight = 0.13 ± 0.12), radiation burden (weight = 0.13 ± 0.12), and duration of screening procedure (weight = 0.10 ± 0.09). Most respondents preferred breath analysis (45%) to giving blood samples (31%) or going through a scanner (24%) as screening modality; 59% preferred screening at the general practitioner's office instead of at the hospital. There was a significant difference in education between the five identified preference subgroups (P < 0.01).Conclusions: There is considerable variation in how people value attributes of lung cancer screening. Different screening policies and implementation strategies may be appropriate for particular preference subgroups. Our results indicate that people prefer breath analysis and that they are more likely to attend screening modalities that can be used at a primary care facility. [ABSTRACT FROM AUTHOR]

• Solitary pulmonary nodules to be evaluated is expected to increase over time. • Virtual bronchoscopy navigation with or without sheet tunnelling has a diagnostic yield of 77%. • Preventing futile invasive procedures or receiving treatment without histological confirmation of cancer. • Allows for treatment adaptation in two-third of the analyzed patient population. The number of solitary pulmonary nodules to be evaluated is expected to increase and therefore we need to improve diagnostic and therapeutic tools to approach these nodules. To prevent patients from futile invasive procedures and receiving treatment without histological confirmation of cancer, we evaluated the value of virtual bronchoscopy navigation to obtain a diagnosis of the solitary pulmonary nodule in a real-world clinical setting. In the NAVIGATOR single center, prospective, observational cohort study patients underwent a virtual bronchoscopy navigation procedure with or without guide sheet tunnelling to assess a solitary pulmonary nodule. Nodules were considered not accessible if a diagnosis could not be obtained by either by CT-guided transthoracic biopsy or conventional bronchoscopy. Between February 2021 and January 2022 35 patients underwent the virtual bronchoscopy navigation procedure. The overall diagnostic yield was 77% and was dependent on size of the nodule and chosen path, with highest yield in lesions with an airway path. Adverse events were few and manageable. Virtual bronchoscopy navigation with or without sheet tunnelling is a new technique with a good diagnostic yield, also in patients in whom previously performed procedures failed to establish a diagnosis and/or alternative procedures are considered not feasible based on expected yield and/or safety. Preventing futile or more invasive procedures like surgery or transthoracic punctures with a higher complication rate is beneficial for patients, and allowed treatment adaptation in two-third of the analyzed patient population. [ABSTRACT FROM AUTHOR]

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access. [ABSTRACT FROM AUTHOR]

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society's highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. We have produced a twin-papers consensus, indicated through the documents as respectively "Part I" and "Part II." The first document (Part I) begins with a discussion of features, role, indications, and evidence for CT and MR imaging-based diagnosis of carotid artery disease for risk stratification and prediction of stroke (Section I). It then provides an extensive overview and insight into imaging-derived biomarkers and their potential use in risk stratification (Section II). Finally, detailed recommendations about optimized imaging technique and imaging strategies are summarized (Section III). The second part of this consensus paper (Part II) is focused on structured reporting of carotid imaging studies with CT/MR. Key Points: • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • Imaging-derived biomarkers and their potential use in risk stratification are evolving; their correct interpretation and use in clinical practice must be well-understood. • A correct imaging strategy and scan protocol will produce the best possible results for disease evaluation. [ABSTRACT FROM AUTHOR]

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society's highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. The purpose of this second document is to discuss suggestions for standardized reporting based on the accompanying consensus document part I. Key Points: • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • The information in the report must cover vessel morphology, description of stenosis, and plaque imaging features. • A structured approach to reporting ensures that all essential information is delivered in a standardized and consistent way to the referring clinician. [ABSTRACT FROM AUTHOR]

Background: Chest computed tomography (CT) emphysema quantification is a vital diagnostic tool in patient evaluation for bronchoscopic lung volume reduction (BLVR). Smooth kernels for CT image reconstruction are generally recommended for quantitative analyses. This recommendation is not always followed, which may affect quantification of emphysema extent and eventually, treatment decisions. Objective: The main goal is to demonstrate the influence of CT reconstruction kernels on emphysema quantification in patients with severe COPD, considered for BLVR. Methods: Chest CT scans were acquired with one multi-detector CT system and reconstructed using three different kernels: smooth, medium smooth, and sharp. Other parameters were kept constant. Emphysema scores (ESs), meaning the percentage of voxels below −950 Hounsfield units, were calculated and compared to the smooth reference kernel using paired t tests. Bland-Altman plots were made to assess the biases and limits of agreement between kernels. Results: Ninety-eight COPD patient CT scans were analyzed. The sharp kernel had a systematic bias of 6.2% and limits of agreement of 16.6% to −4.2% compared to the smooth kernel. The medium smooth kernel had a systematic bias of 5.7% and limits of agreement of 9.2% and 2.2% compared to the smooth kernel. The ES differed, for a single patient, up to 18% for different kernels. Conclusions: Chest CT kernel reconstruction can lead to a significant difference in emphysema severity quantification. This may cause invalid treatment selection in COPD patients evaluated for BLVR. Standardization of a smooth CT kernel setting and/or normalization to a standard kernel is strongly recommended. [ABSTRACT FROM AUTHOR]

Objectives: Coronary motion artifacts affect the diagnostic accuracy of coronary CT angiography (CCTA), especially in the mid right coronary artery (mRCA). The purpose is to correct CCTA motion artifacts of the mRCA using a GAN (generative adversarial network). Methods: We included 313 patients with CCTA scans, who had paired motion-affected and motion-free reference images at different R-R interval phases in the same cardiac cycle and included another 53 CCTA cases with invasive coronary angiography (ICA) comparison. Pix2pix, an image-to-image conversion GAN, was trained by the motion-affected and motion-free reference pairs to generate motion-free images from the motion-affected images. Peak signal-to-noise ratio (PSNR), structural similarity (SSIM), Dice similarity coefficient (DSC), and Hausdorff distance (HD) were calculated to evaluate the image quality of GAN-generated images. Results: At the image level, the median of PSNR, SSIM, DSC, and HD of GAN-generated images were 26.1 (interquartile: 24.4–27.5), 0.860 (0.830–0.882), 0.783 (0.714–0.825), and 4.47 (3.00–4.47), respectively, significantly better than the motion-affected images (p < 0.001). At the patient level, the image quality results were similar. GAN-generated images improved the motion artifact alleviation score (4 vs. 1, p < 0.001) and overall image quality score (4 vs. 1, p < 0.001) than those of the motion-affected images. In patients with ICA comparison, GAN-generated images achieved accuracy of 81%, 85%, and 70% in identifying no, < 50%, and ≥ 50% stenosis, respectively, higher than 66%, 72%, and 68% for the motion-affected images. Conclusion: Generative adversarial network-generated CCTA images greatly improved the image quality and diagnostic accuracy compared to motion-affected images. Key Points: • A generative adversarial network greatly reduced motion artifacts in coronary CT angiography and improved image quality. • GAN-generated images improved diagnosis accuracy of identifying no, < 50%, and ≥ 50% stenosis. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to evaluate the association between visual emphysema and the presence of lung nodules, and Lung-RADS category with low-dose CT (LDCT). Methods: Baseline LDCT scans of 1162 participants from a lung cancer screening study (Nelcin-B3) performed in a Chinese general population were included. The presence, subtypes, and severity of emphysema (at least trace) were visually assessed by one radiologist. The presence, size, and classification of non-calcified lung nodules (≥ 30 mm3) and Lung-RADS category were independently assessed by another two radiologists. Multivariable logistic regression and stratified analyses were performed to estimate the association between emphysema and lung nodules, Lung-RADS category, after adjusting for age, sex, BMI, smoking status, pack-years, and passive smoking. Results: Emphysema and lung nodules were observed in 674 (58.0%) and 424 (36.5%) participants, respectively. Participants with emphysema had a 71% increased risk of having lung nodules (adjusted odds ratios, aOR: 1.71, 95% CI: 1.26–2.31) and 70% increased risk of positive Lung-RADS category (aOR: 1.70, 95% CI: 1.09–2.66) than those without emphysema. Participants with paraseptal emphysema (n = 47, 4.0%) were at a higher risk for lung nodules than those with centrilobular emphysema (CLE) (aOR: 2.43, 95% CI: 1.32–4.50 and aOR: 1.60, 95% CI: 1.23–2.09, respectively). Only CLE was associated with positive Lung-RADS category (p = 0.02). CLE severity was related to a higher risk of lung nodules (ranges aOR: 1.44–2.61, overall p < 0.01). Conclusion: In a Chinese general population, visual emphysema based on LDCT is independently related to the presence of lung nodules (≥ 30 mm3) and specifically CLE subtype is related to positive Lung-RADS category. The risk of lung nodules increases with CLE severity. Key Points: • Participants with emphysema had an increased risk of having lung nodules, especially smokers. • Participants with PSE were at a higher risk for lung nodules than those with CLE, but nodules in participants with CLE had a higher risk of positive Lung-RADS category. • The risk of lung nodules increases with CLE severity. [ABSTRACT FROM AUTHOR]

Simple Summary: Artificial Intelligence (AI) algorithms can assist clinicians in their daily tasks by automatically detecting and/or classifying nodules in chest CT scans. Bias of such algorithms is one of the reasons why implementation of them in clinical practice is still not widely adopted. There is no published review on the bias that these algorithms may contain. This review aims to present different types of bias in such algorithms and present possible ways to mitigate them. Only then it would be possible to ensure that these algorithms work as intended under many different clinical settings. Artificial Intelligence (AI) algorithms for automatic lung nodule detection and classification can assist radiologists in their daily routine of chest CT evaluation. Even though many AI algorithms for these tasks have already been developed, their implementation in the clinical workflow is still largely lacking. Apart from the significant number of false-positive findings, one of the reasons for that is the bias that these algorithms may contain. In this review, different types of biases that may exist in chest CT AI nodule detection and classification algorithms are listed and discussed. Examples from the literature in which each type of bias occurs are presented, along with ways to mitigate these biases. Different types of biases can occur in chest CT AI algorithms for lung nodule detection and classification. Mitigation of them can be very difficult, if not impossible to achieve completely. [ABSTRACT FROM AUTHOR]

Objectives: To compare the use of coronary computed tomography angiography (CCTA) between academic and non-academic sites across Europe over the last decade. Methods: We analyzed a large multicenter registry (ESCR MR/CT Registry) of stable symptomatic patients who received CCTA 01/2010–01/2020 at 47 (22%) academic and 165 (78%) non-academic sites across 19 European countries. We compared image quality, radiation dose, contrast-media-related adverse events, patient characteristics, CCTA findings, and downstream testing between academic and non-academic sites. Results: Among 64,317 included patients (41% female; 60 ± 13 years), academic sites accounted for most cases in 2010–2014 (52%), while non-academic sites dominated in 2015–2020 (71%). Despite less contemporary technology, non-academic sites maintained low radiation doses (4.76 [2.46–6.85] mSv) with a 30% decline of high-dose scans (> 7 mSv) over time. Academic and non-academic sites both reported diagnostic image quality in 98% of cases and low rate of scan-related adverse events (0.4%). Academic and non-academic sites examined similar patient populations (41% females both; age: 61 ± 14 vs. 60 ± 12 years; pretest probability for obstructive CAD: low 21% vs. 23%, intermediate 73% vs. 72%, high 6% both, CAD prevalence on CCTA: 40% vs. 41%). Nevertheless, non-academic sites referred more patients to non-invasive ischemia testing (6.5% vs. 4.2%) and invasive coronary angiography/surgery (8.5% vs. 5.6%). Conclusions: Non-academic and academic sites provide safe, high-quality CCTA across Europe, essential to successfully implement the recently updated guidelines for the diagnosis and management of chronic coronary syndromes. However, despite examining similar populations with comparable CAD prevalence, non-academic sites tend to refer more patients to downstream testing. Key Points: • Smaller non-academic providers increasingly use CCTA to rule out obstructive coronary artery disease. • Non-academic and academic sites provide comparably safe, high-quality CCTA across Europe. • Compared to academic sites, non-academic sites tend to refer more patients to downstream testing. [ABSTRACT FROM AUTHOR]

Objective: Research on computed tomography (CT) bronchial parameter measurements shows that there are conflicting results on the values for bronchial parameters in the never-smoking, smoking, asthma, and chronic obstructive pulmonary disease (COPD) populations. This review assesses the current CT methods for obtaining bronchial wall parameters and their comparison between populations. Methods: A systematic review of MEDLINE and Embase was conducted following PRISMA guidelines (last search date 25th October 2021). Methodology data was collected and summarised. Values of percentage wall area (WA%), wall thickness (WT), summary airway measure (Pi10), and luminal area (Ai) were pooled and compared between populations. Results: A total of 169 articles were included for methodologic review; 66 of these were included for meta-analysis. Most measurements were obtained from multiplanar reconstructions of segmented airways (93 of 169 articles), using various tools and algorithms; third generation airways in the upper and lower lobes were most frequently studied. COPD (12,746) and smoking (15,092) populations were largest across studies and mostly consisted of men (median 64.4%, IQR 61.5 – 66.1%). There were significant differences between populations; the largest WA% was found in COPD (mean SD 62.93 ± 7.41%, n = 6,045), and the asthma population had the largest Pi10 (4.03 ± 0.27 mm, n = 442). Ai normalised to body surface area (Ai/BSA) (12.46 ± 4 mm2, n = 134) was largest in the never-smoking population. Conclusions: Studies on CT-derived bronchial parameter measurements are heterogenous in methodology and population, resulting in challenges to compare outcomes between studies. Significant differences between populations exist for several parameters, most notably in the wall area percentage; however, there is a large overlap in their ranges. Key Points: • Diverse methodology in measuring airways contributes to overlap in ranges of bronchial parameters among the never-smoking, smoking, COPD, and asthma populations. • The combined number of never-smoking participants in studies is low, limiting insight into this population and the impact of participant characteristics on bronchial parameters. • Wall area percent of the right upper lobe apical segment is the most studied (87 articles) and differentiates all except smoking vs asthma populations. [ABSTRACT FROM AUTHOR]

The purpose is to establish and validate a machine-learning-derived radiomics approach to determine the existence of atrial fibrillation (AF) by analyzing epicardial adipose tissue (EAT) in CT images. Patients with AF based on electrocardiographic tracing who underwent contrast-enhanced (n = 200) or non-enhanced (n = 300) chest CT scans were analyzed retrospectively. After EAT segmentation and radiomics feature extraction, the segmented EAT yielded 1691 radiomics features. The most contributive features to AF were selected by the Boruta algorithm and machine-learning-based random forest algorithm, and combined to construct a radiomics signature (EAT-score). Multivariate logistic regression was used to build clinical factor and nested models. In the test cohort of contrast-enhanced scanning (n = 60/200), the AUC of EAT-score for identifying patients with AF was 0.92 (95%CI: 0.84–1.00), higher than 0.71 (0.58–0.85) of the clinical factor model (total cholesterol and body mass index) (DeLong's p = 0.01), and higher than 0.73 (0.61–0.86) of the EAT volume model (p = 0.01). In the test cohort of non-enhanced scanning (n = 100/300), the AUC of EAT-score was 0.85 (0.77–0.92), higher than that of the CT attenuation model (p < 0.001). The two nested models (EAT-score+volume and EAT-score+volume+clinical factors) for contrast-enhanced scan and one (EAT-score+CT attenuation) for non-enhanced scan showed similar AUCs with that of EAT-score (all p > 0.05). EAT-score generated by machine-learning-based radiomics achieved high performance in identifying patients with AF. A radiomics analysis based on machine learning allows for the identification of AF on the EAT in contrast-enhanced and non-enhanced chest CT. [ABSTRACT FROM AUTHOR]

Background: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans.In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI.For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853).In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial.Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Methods: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans.In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI.For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853).In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial.Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Results: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans.In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI.For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853).In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial.Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Conclusion: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans.In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI.For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853).In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial.Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Clinical relevance statement: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans.In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI.For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853).In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial.Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Key Points: The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans.In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60–75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI.For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671–0.853).In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial.Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates.Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed.Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT. [ABSTRACT FROM AUTHOR]

Stable chest pain is a common symptom with multiple potential causes. Non-invasive imaging has an important role in diagnosis and guiding management through the assessment of coronary stenoses, atherosclerotic plaque, myocardial ischaemia or infarction, and cardiac function. Computed tomography (CT) provides the anatomical evaluation of coronary artery disease (CAD) with the assessment of stenosis, plaque type and plaque burden, with additional functional information available from CT fractional flow reserve (FFR) or CT myocardial perfusion imaging. Stress magnetic resonance imaging, nuclear stress myocardial perfusion imaging, and stress echocardiography can assess myocardial ischaemia and other cardiac functional parameters. Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. Functional testing may be considered for patients with known CAD, where the clinical significance is uncertain based on anatomical testing, or in patients with high pre-test probability. This practice recommendations document can be used to guide the selection of non-invasive imaging for patients with stable chest pain and provides brief recommendations on how to perform and report these diagnostic tests.The selection of non-invasive imaging tests for patients with stable chest pain should be based on symptoms, pre-test probability, and previous history.Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability.Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability.The selection of non-invasive imaging tests for patients with stable chest pain should be based on symptoms, pre-test probability, and previous history.Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability.Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability.Non-invasive imaging is an important part of the assessment of patients with stable chest pain. The selection of non-invasive imaging test should be based on symptoms, pre-test probability, and previous history. (Level of evidence: High).Coronary CT angiography can be used as a first line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. CT provides information on stenoses, plaque type, plaque volume, and if required functional information with CT fractional flow reserve or CT perfusion. (Level of evidence: High).Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability. Stress MRI, SPECT, PET, and echocardiography can provide information on myocardial ischemia, along with cardiac functional and other information. (Level of evidence: Medium).Non-invasive imaging is an important part of the assessment of patients with stable chest pain. The selection of non-invasive imaging test should be based on symptoms, pre-test probability, and previous history. (Level of evidence: High).Coronary CT angiography can be used as a first line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. CT provides information on stenoses, plaque type, plaque volume, and if required functional information with CT fractional flow reserve or CT perfusion. (Level of evidence: High).Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability. Stress MRI, SPECT, PET, and echocardiography can provide information on myocardial ischemia, along with cardiac functional and other information. (Level of evidence: Medium).Key Points: Stable chest pain is a common symptom with multiple potential causes. Non-invasive imaging has an important role in diagnosis and guiding management through the assessment of coronary stenoses, atherosclerotic plaque, myocardial ischaemia or infarction, and cardiac function. Computed tomography (CT) provides the anatomical evaluation of coronary artery disease (CAD) with the assessment of stenosis, plaque type and plaque burden, with additional functional information available from CT fractional flow reserve (FFR) or CT myocardial perfusion imaging. Stress magnetic resonance imaging, nuclear stress myocardial perfusion imaging, and stress echocardiography can assess myocardial ischaemia and other cardiac functional parameters. Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. Functional testing may be considered for patients with known CAD, where the clinical significance is uncertain based on anatomical testing, or in patients with high pre-test probability. This practice recommendations document can be used to guide the selection of non-invasive imaging for patients with stable chest pain and provides brief recommendations on how to perform and report these diagnostic tests.The selection of non-invasive imaging tests for patients with stable chest pain should be based on symptoms, pre-test probability, and previous history.Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability.Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability.The selection of non-invasive imaging tests for patients with stable chest pain should be based on symptoms, pre-test probability, and previous history.Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability.Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability.Non-invasive imaging is an important part of the assessment of patients with stable chest pain. The selection of non-invasive imaging test should be based on symptoms, pre-test probability, and previous history. (Level of evidence: High).Coronary CT angiography can be used as a first line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. CT provides information on stenoses, plaque type, plaque volume, and if required functional information with CT fractional flow reserve or CT perfusion. (Level of evidence: High).Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability. Stress MRI, SPECT, PET, and echocardiography can provide information on myocardial ischemia, along with cardiac functional and other information. (Level of evidence: Medium).Non-invasive imaging is an important part of the assessment of patients with stable chest pain. The selection of non-invasive imaging test should be based on symptoms, pre-test probability, and previous history. (Level of evidence: High).Coronary CT angiography can be used as a first line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. CT provides information on stenoses, plaque type, plaque volume, and if required functional information with CT fractional flow reserve or CT perfusion. (Level of evidence: High).Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability. Stress MRI, SPECT, PET, and echocardiography can provide information on myocardial ischemia, along with cardiac functional and other information. (Level of evidence: Medium).Key recommendations: Stable chest pain is a common symptom with multiple potential causes. Non-invasive imaging has an important role in diagnosis and guiding management through the assessment of coronary stenoses, atherosclerotic plaque, myocardial ischaemia or infarction, and cardiac function. Computed tomography (CT) provides the anatomical evaluation of coronary artery disease (CAD) with the assessment of stenosis, plaque type and plaque burden, with additional functional information available from CT fractional flow reserve (FFR) or CT myocardial perfusion imaging. Stress magnetic resonance imaging, nuclear stress myocardial perfusion imaging, and stress echocardiography can assess myocardial ischaemia and other cardiac functional parameters. Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. Functional testing may be considered for patients with known CAD, where the clinical significance is uncertain based on anatomical testing, or in patients with high pre-test probability. This practice recommendations document can be used to guide the selection of non-invasive imaging for patients with stable chest pain and provides brief recommendations on how to perform and report these diagnostic tests.The selection of non-invasive imaging tests for patients with stable chest pain should be based on symptoms, pre-test probability, and previous history.Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability.Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability.The selection of non-invasive imaging tests for patients with stable chest pain should be based on symptoms, pre-test probability, and previous history.Coronary CT angiography can be used as a first-line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability.Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability.Non-invasive imaging is an important part of the assessment of patients with stable chest pain. The selection of non-invasive imaging test should be based on symptoms, pre-test probability, and previous history. (Level of evidence: High).Coronary CT angiography can be used as a first line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. CT provides information on stenoses, plaque type, plaque volume, and if required functional information with CT fractional flow reserve or CT perfusion. (Level of evidence: High).Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability. Stress MRI, SPECT, PET, and echocardiography can provide information on myocardial ischemia, along with cardiac functional and other information. (Level of evidence: Medium).Non-invasive imaging is an important part of the assessment of patients with stable chest pain. The selection of non-invasive imaging test should be based on symptoms, pre-test probability, and previous history. (Level of evidence: High).Coronary CT angiography can be used as a first line test for many patients with stable chest pain, particularly those with low to intermediate pre-test probability. CT provides information on stenoses, plaque type, plaque volume, and if required functional information with CT fractional flow reserve or CT perfusion. (Level of evidence: High).Functional testing can be considered for patients with known CAD, where the clinical significance of CAD is uncertain based on anatomical testing, or in patients with high pre-test probability. Stress MRI, SPECT, PET, and echocardiography can provide information on myocardial ischemia, along with cardiac functional and other information. (Level of evidence: Medium). [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) remains a leading cause of death and disability worldwide. Acute myocardial infarction (AMI) causes irreversible myocardial damage, heart failure, life-threatening arrythmias and sudden cardiac death (SCD), and is a main driver of CVD mortality and morbidity. To control the forecasted increase in CVD burden for both the individual and society, improved strategies for the prevention of AMI and SCD are required. Current prevention of AMI and SCD is directed towards risk-modifying interventions, guided by risk assessment using clinical risk prediction scores (CRPSs) and the coronary artery calcium score (CACS). Early detection of more advanced coronary artery disease (CAD), beyond risk assessment by CRPSs or CACS, is a promising strategy to allow personalized treatment for the improved prevention of AMI and SCD in the general population. We review evidence for further testing, beyond CRPSs and CACS, and therapies focusing on promising targets, including subclinical obstructive CAD, high-risk plaques, and silent myocardial ischemia. We also evaluate the potential of multi-modality imaging to enhance the conduction of adequately powered trials to provide high-quality evidence on the impact of add-on tests and therapies in the prevention of AMI and SCD in asymptomatic individuals. To conclude, we discuss the occurrence of AMI and SCD in individuals currently estimated to be at "low-risk" by the current strategy based on CRPSs, and methods to improve prevention of AMI and SCD in this "low-risk" population. [ABSTRACT FROM AUTHOR]

Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to establish deep convolutional neural network (CNN) models using these two imaging markers to diagnose and grade COPD. Subjects who underwent chest CT and pulmonary function test (PFT) from one hospital (n = 373) were retrospectively included as the training cohort, and subjects from another hospital (n = 226) were used as the external test cohort. According to the PFT results, all subjects were labeled as Global Initiative for Chronic Obstructive Lung Disease (GOLD) Grade 1, 2, 3, 4 or normal. Two DenseNet-201 CNNs were trained using CT images of lung parenchyma and bronchial wall to generate two corresponding confidence levels to indicate the possibility of COPD, then combined with logistic regression analysis. Quantitative CT was used for comparison. In the test cohort, CNN achieved an area under the curve of 0.899 (95%CI: 0.853–0.935) to determine the existence of COPD, and an accuracy of 81.7% (76.2–86.7%), which was significantly higher than the accuracy 68.1% (61.6%–74.2%) using quantitative CT method (p < 0.05). For three-way (normal, GOLD 1–2, and GOLD 3–4) and five-way (normal, GOLD 1, 2, 3, and 4) classifications, CNN reached accuracies of 77.4 and 67.9%, respectively. CNN can identify emphysema and airway wall remodeling on CT images to infer lung function and determine the existence and severity of COPD. It provides an alternative way to detect COPD using the extensively available chest CT. CNN can identify the main pathological changes of COPD (emphysema and airway wall remodeling) based on CT images, to infer lung function and determine the existence and severity of COPD. CNN reached an area under the curve of 0.853 to determine the existence of COPD in the external test cohort. The CNN approach provides an alternative and effective way for early detection of COPD using extensively used chest CT, as an important alternative to pulmonary function test. [ABSTRACT FROM AUTHOR]

Objectives: Estimating the maximum acceptable cost (MAC) per screened individual for low-dose computed tomography (LDCT) lung cancer (LC) screening, and determining the effect of additionally screening for chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), or both on the MAC. Methods: A model-based early health technology assessment (HTA) was conducted to estimate whether a new intervention could be cost-effective by calculating the MAC at a willingness-to-pay (WTP) of €20k/quality-adjusted life-year (QALY) and €80k/QALY, for a population of current and former smokers, aged 50–75 years in The Netherlands. The MAC was estimated based on incremental QALYs gained from a stage shift assuming screened individuals are detected in earlier disease stages. Data were obtained from literature and publicly available statistics and validated with experts. Results: The MAC per individual for implementing LC screening at a WTP of €20k/QALY was €113. If COPD, CVD, or both were included in screening, the MAC increased to €230, €895, or €971 respectively. Scenario analyses assessed whether screening-specific disease high-risk populations would improve cost-effectiveness, showing that high-risk CVD populations were more likely to improve economic viability compared to COPD. Conclusions: The economic viability of combined screening is substantially larger than for LC screening alone, primarily due to benefits from CVD screening, and is dependent on the target screening population, which is key to optimise the screening program. The total cost of breast and cervical cancer screening is lower (€420) than the MAC of Big-3, indicating that Big-3 screening may be acceptable from a health economic perspective. Key Points: • Once-off combined low-dose CT screening for lung cancer, COPD, and CVD in individuals aged 50–75 years is potentially cost-effective if screening would cost less than €971 per screened individual. • Multi-disease screening requires detailed insight into the co-occurrence of these diseases to identify the optimal target screening population. • With the same target screening population and WTP, lung cancer-only screening should cost less than €113 per screened individual to be cost-effective. [ABSTRACT FROM AUTHOR]

• Dose dependent myocardial fibrosis plays a central role in late cardiac toxicity. • An increased rate of atrial fibrillation was found in the irradiated patient group. • Atrial fibrillation has hemodynamic consequences and an effect on global health. • Patients showed lower scores on role functioning after neoadjuvant CRT. Although cure rates in esophageal cancer (EC) have improved since the introduction of neoadjuvant chemoradiation (nCRT), evidence for treatment-related cardiac toxicity is growing, of which the exact mechanisms remain unknown. The primary objective of this study was to identify (subclinical) cardiac dysfunction in EC patients after nCRT followed by surgical resection as compared to surgery alone. EC survivors followed for 5–15 years after curative resection with (n = 20) or without (n = 20) nCRT were enrolled in this prospective cross-sectional pilot study. All patients underwent several clinical and diagnostic tests in order to objectify (sub)clinical cardiac toxicity including cardiac CT and MRI, echocardiography, ECG, 6-minutes walking test, physical examination and EORTC questionnaires. We found an increased rate of myocardial fibrosis (Linear late gadolinium enhancement (LGE) 4 vs. 1; p = 0.13; mean extracellular volume (ECV) 28.4 vs. 24.0; p < 0.01), atrial fibrillation (AF) (6 vs. 2; p = 0.07) and conduction changes in ECG among patients treated with nCRT as compared to those treated with surgery alone. The results suggested an impact on quality of life in terms of worse role functioning for this patient group (95.0 vs. 88.8; p = 0.03). Based on our analyses we hypothesize that in EC patients, radiation-induced myocardial fibrosis plays a central role in cardiac toxicity leading to AF, conduction changes and ultimately to decreased role functioning. The results emphasize the need to verify these findings in larger cohorts of patients. [ABSTRACT FROM AUTHOR]

• The Chinese population has a higher prevalence of emphysema compared to the Dutch population, which was only seen in never smoker after stratification by smoking status. • Increasing age and male sex increased the odds of emphysema to similar magnitudes in both populations. • Factors other than smoking, age, and sex, for example, air pollution or ethnicity may play a key role in emphysema formation. Studies should now focus on elucidating other risk factors that contribute to the high prevalence of CT-defined emphysema in Chinese never smokers. We determine and compare the prevalence, subtypes, severity, and risk factors for emphysema assessed by low-dose CT(LDCT) in Chinese and Dutch general populations. This cross-sectional study included LDCT scans of 1143 participants between May and October 2017 from a Chinese Cohort study and 1200 participants with same age range and different smoking status between May and October 2019 from a Dutch population-based study. An experienced radiologist visually assessed the scans for emphysema presence (≥trace), subtype, and severity. Logistic regression analyses, overall and stratified by smoking status, were performed and adjusted for fume exposure, demographic and smoking data. The Chinese population had a comparable proportion of women to the Dutch population (54.9 % vs 58.9 %), was older (61.7 ± 6.3 vs 59.8 ± 8.1), included more never smokers (66.4 % vs 38.3 %), had a higher emphysema prevalence ([58.8 % vs 39.7 %], adjusted odds ratio, aOR = 2.06, 95 %CI = 1.68–2.53), and more often had centrilobular emphysema (54.8 % vs 32.8 %, p < 0.001), but no differences in emphysema severity. After stratification, only in never smokers an increased odds of emphysema was observed in the Chinese compared to the Dutch (aOR = 2.55, 95 %CI = 1.95–3.35). Never smokers in both populations shared older age (aOR = 1.59, 95 %CI = 1.25–2.02 vs 1.26, 95 %CI = 0.97–1.64) and male sex (aOR = 1.50, 95 %CI = 1.02–2.22 vs 1.93, 95 %CI = 1.26–2.96) as risk factors for emphysema. Only never smokers had a higher prevalence of mainly centrilobular emphysema in the Chinese general population compared to the Dutch after adjusting for confounders, indicating that factors other than smoking, age and sex contribute to presence of CT-defined emphysema. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty.The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group.The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance.Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction.• Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm.• Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse.• Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness.Methods and materials: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty.The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group.The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance.Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction.• Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm.• Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse.• Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness.Results: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty.The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group.The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance.Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction.• Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm.• Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse.• Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness.Conclusion: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty.The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group.The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance.Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction.• Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm.• Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse.• Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness.Clinical relevance statement: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty.The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group.The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance.Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction.• Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm.• Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse.• Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness.Key Points: To investigate the effect of uncertainty estimation on the performance of a Deep Learning (DL) algorithm for estimating malignancy risk of pulmonary nodules.In this retrospective study, we integrated an uncertainty estimation method into a previously developed DL algorithm for nodule malignancy risk estimation. Uncertainty thresholds were developed using CT data from the Danish Lung Cancer Screening Trial (DLCST), containing 883 nodules (65 malignant) collected between 2004 and 2010. We used thresholds on the 90th and 95th percentiles of the uncertainty score distribution to categorize nodules into certain and uncertain groups. External validation was performed on clinical CT data from a tertiary academic center containing 374 nodules (207 malignant) collected between 2004 and 2012. DL performance was measured using area under the ROC curve (AUC) for the full set of nodules, for the certain cases and for the uncertain cases. Additionally, nodule characteristics were compared to identify trends for inducing uncertainty.The DL algorithm performed significantly worse in the uncertain group compared to the certain group of DLCST (AUC 0.62 (95% CI: 0.49, 0.76) vs 0.93 (95% CI: 0.88, 0.97); p < .001) and the clinical dataset (AUC 0.62 (95% CI: 0.50, 0.73) vs 0.90 (95% CI: 0.86, 0.94); p < .001). The uncertain group included larger benign nodules as well as more part-solid and non-solid nodules than the certain group.The integrated uncertainty estimation showed excellent performance for identifying uncertain cases in which the DL-based nodule malignancy risk estimation algorithm had significantly worse performance.Deep Learning algorithms often lack the ability to gauge and communicate uncertainty. For safe clinical implementation, uncertainty estimation is of pivotal importance to identify cases where the deep learning algorithm harbors doubt in its prediction.• Deep learning (DL) algorithms often lack uncertainty estimation, which potentially reduce the risk of errors and improve safety during clinical adoption of the DL algorithm.• Uncertainty estimation identifies pulmonary nodules in which the discriminative performance of the DL algorithm is significantly worse.• Uncertainty estimation can further enhance the benefits of the DL algorithm and improve its safety and trustworthiness. [ABSTRACT FROM AUTHOR]

Rationale: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.Materials and methods: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.Results: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.Conclusions: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.Clinical relevance statement: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.Key Points: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile.Graphical Abstract: To provide an overview of the current status of cardiac multimodality imaging practices in Europe and radiologist involvement using data from the European Society of Cardiovascular Radiology (ESCR) MRCT-registry.Numbers on cardiac CT and MRI examinations were extracted from the MRCT-registry of the ESCR, entered between January 2011 and October 2023 (n = 432,265). Data collection included the total/annual numbers of examinations, indications, complications, and reporting habits.Thirty-two countries contributed to the MRCT-registry, including 29 European countries. Between 2011 and 2022, there was a 4.5-fold increase in annually submitted CT examinations, from 3368 to 15,267, and a 3.8-fold increase in MRI examinations, from 3445 to 13,183. The main indications for cardiac CT were suspected coronary artery disease (CAD) (59%) and transcatheter aortic valve replacement planning (21%). The number of patients with intermediate pretest probability who underwent CT for suspected CAD showed an increase from 61% in 2012 to 82% in 2022. The main MRI indications were suspected myocarditis (26%), CAD (21%), and suspected cardiomyopathy (19%). Adverse event rates were very low for CT (0.3%) and MRI (0.7%) examinations. Reporting of CT and MRI examinations was performed mainly by radiologists (respectively 76% and 71%) and, to a lesser degree, in consensus with non-radiologists (19% and 27%, respectively). The remaining examinations (4.9% CT and 1.7% MRI) were reported by non-radiological specialties or in separate readings of radiologists and non-radiologists.Real-life data on cardiac imaging in Europe using the largest available MRCT-registry demonstrate a considerable increase in examinations over the past years, the vast majority of which are read by radiologists. These findings indicate that radiologists contribute to meeting the increasing demands of competent and effective care in cardiac imaging to a relevant extent.The number of cardiac CT and MRI examinations has risen over the past years, and radiologists read the vast majority of these studies as recorded in the MRCT-registry.• The number of cardiac imaging examinations is constantly increasing.• Radiologists play a central role in providing cardiac CT and MR imaging services to a large volume of patients.• Cardiac CT and MR imaging examinations performed and read by radiologists show a good safety profile. [ABSTRACT FROM AUTHOR]

Objectives: The interpretability of convolutional neural networks (CNNs) for classifying subsolid nodules (SSNs) is insufficient for clinicians. Our purpose was to develop CNN models to classify SSNs on CT images and to investigate image features associated with the CNN classification. Methods: CT images containing SSNs with a diameter of ≤ 3 cm were retrospectively collected. We trained and validated CNNs by a 5-fold cross-validation method for classifying SSNs into three categories (benign and preinvasive lesions [PL], minimally invasive adenocarcinoma [MIA], and invasive adenocarcinoma [IA]) that were histologically confirmed or followed up for 6.4 years. The mechanism of CNNs on human-recognizable CT image features was investigated and visualized by gradient-weighted class activation map (Grad-CAM), separated activation channels and areas, and DeepDream algorithm. Results: The accuracy was 93% for classifying 586 SSNs from 569 patients into three categories (346 benign and PL, 144 MIA, and 96 IA in 5-fold cross-validation). The Grad-CAM successfully located the entire region of image features that determined the final classification. Activated areas in the benign and PL group were primarily smooth margins (p < 0.001) and ground-glass components (p = 0.033), whereas in the IA group, the activated areas were mainly part-solid (p < 0.001) and solid components (p < 0.001), lobulated shapes (p < 0.001), and air bronchograms (p < 0.001). However, the activated areas for MIA were variable. The DeepDream algorithm showed the image features in a human-recognizable pattern that the CNN learned from a training dataset. Conclusion: This study provides medical evidence to interpret the mechanism of CNNs that helps support the clinical application of artificial intelligence. Key Points: • CNN achieved high accuracy (93%) in classifying subsolid nodules on CT images into three categories: benign and preinvasive lesions, MIA, and IA. • The gradient-weighted class activation map (Grad-CAM) located the entire region of image features that determined the final classification, and the visualization of the separated activated areas was consistent with radiologists' expertise for diagnosing subsolid nodules. • DeepDream showed the image features that CNN learned from a training dataset in a human-recognizable pattern. [ABSTRACT FROM AUTHOR]