Impact of Significant Coronary Artery Calcification Reported on Low-Dose Computed Tomography Lung Cancer Screening

Prevalence and clinical implications of coronary artery calcium scoring on non-gated thoracic computed tomography: a systematic review and meta-analysis

OBJECTIVES

Coronary artery calcifications (CACs) indicate the presence of coronary artery disease. CAC can be found on thoracic computed tomography (CT) conducted for non-cardiac reasons. This systematic review and meta-analysis of non-gated thoracic CT aims to assess the clinical impact and prevalence of CAC.

METHODS

Online databases were searched for articles assessing prevalence, demographic characteristics, accuracy and prognosis of incidental CAC on non-gated thoracic CT. Meta-analysis was performed using a random effects model.

RESULTS

A total of 108 studies (113,406 patients) were included (38% female). Prevalence of CAC ranged from 2.7 to 100% (pooled prevalence 52%, 95% confidence interval [CI] 46-58%). Patients with CAC were older (pooled standardised mean difference 0.88, 95% CI 0.65-1.11, p < 0.001), and more likely to be male (pooled odds ratio [OR] 1.95, 95% CI 1.55-2.45, p < 0.001), with diabetes (pooled OR 2.63, 95% CI 1.95-3.54, p < 0.001), hypercholesterolaemia (pooled OR 2.28, 95% CI 1.33-3.93, p < 0.01) and hypertension (pooled OR 3.89, 95% CI 2.26-6.70, p < 0.001), but not higher body mass index or smoking. Non-gated CT assessment of CAC had excellent agreement with electrocardiogram-gated CT (pooled correlation coefficient 0.96, 95% CI 0.92-0.98, p < 0.001). In 51,582 patients, followed-up for 51.6 ± 27.4 months, patients with CAC had increased all cause mortality (pooled relative risk [RR] 2.13, 95% CI 1.57-2.90, p = 0.004) and major adverse cardiovascular events (pooled RR 2.91, 95% CI 2.26-3.93, p < 0.001). When CAC was present on CT, it was reported in between 18.6% and 93% of reports.

CONCLUSION

CAC is a common, but underreported, finding on non-gated CT with important prognostic implications.

CLINICAL RELEVANCE STATEMENT

Coronary artery calcium is an important prognostic indicator of cardiovascular disease. It can be assessed on non-gated thoracic CT and is a commonly underreported finding. This represents a significant population where there is a potential missed opportunity for lifestyle modification recommendations and preventative therapies. This study aims to highlight the importance of reporting incidental coronary artery calcium on non-gated thoracic CT.

KEY POINTS

• Coronary artery calcification is a common finding on non-gated thoracic CT and can be reliably identified compared to gated-CT. • Coronary artery calcification on thoracic CT is associated with an increased risk of all cause mortality and major adverse cardiovascsular events. • Coronary artery calcification is frequently not reported on non-gated thoracic CT.

Impact of Cardiovascular Imaging Results on Medication Use and Adherence: A Systematic Review and Meta-Analysis

INTRODUCTION

Cardiovascular imaging results offer valuable information that can guide health decisions, but their impact on medication use and adherence is unclear. This systematic review and meta-analysis aimed to determine the downstream impact of cardiovascular imaging results on medication use and adherence.

METHODS

Searches were conducted across databases, including MEDLINE, PsychINFO, EMBASE, and relevant references up to 2024. Data were extracted from studies comparing outcomes for individuals with diseased versus normal arteries and trials comparing outcomes for individuals who were provided imaging results versus those with no access to imaging results and analysed in 2023 and 2024. Pooled odds ratios (ORs) for outcomes were calculated.

RESULTS

The analysis included 29 studies with 24 contributing data points. Initiation (OR:2.77;95% CI:1.82-4.20) and continuation (OR:2.06;95% CI:1.28-3.30) of lipid-lowering medications (LLMs), antihypertensives (OR:2.02;95% CI:1.76-2.33), and antiplatelets (OR:2.47;95% CI:1.68-3.64) were significantly higher in individuals with diseased arteries. The proportion of individuals on LLM increased by 2.7-fold in those with diseased arteries and 1.5-fold in those with normal arteries post-screening. The proportion on LLM increased by 4.2 times in the imaging group and 2.2 times in the "no imaging group" post-screening. There was a significant increase in LLM initiation (OR:2.37;95% CI: 1.17-4.79) in the imaging group, but medication continuation did not significantly differ between the imaging and "no imaging group".

DISCUSSION

Cardiovascular imaging results can prompt initiation of medications, particularly lipid-lowering medications, reflecting a proactive response to identified risk factors. However, evidence regarding medication continuation is mixed, and further research is required.

Opportunistic Screening for Coronary Artery Disease: An Untapped Population Health Resource

BACKGROUND

Coronary artery disease is the leading cause of death in the United States. At-risk asymptomatic adults are eligible for screening with electrocardiogram-gated coronary artery calcium (CAC) CT, which aids in risk stratification and management decision-making. Incidental CAC (iCAC) is easily quantified on chest CT in patients imaged for noncardiac indications; however, radiologists do not routinely report the finding.

OBJECTIVE

To determine the clinical significance of CAC identified incidentally on routine chest CT performed for noncardiac indications.

DESIGN

An informationist developed search strategies in MEDLINE, Embase, and SCOPUS, and two reviewers independently screened results at both the abstract and full text levels. Data extracted from eligible articles included age, rate of iCAC identification, radiologist reporting frequency, impact on downstream medical management, and association of iCAC with patient outcomes.

RESULTS

From 359 unique citations, 83 research publications met inclusion criteria. The percentage of patients with iCAC ranged from 9% to 100%. Thirty-one investigations measured association(s) between iCAC and cardiovascular morbidity and mortality, and 29 identified significant correlations, including nonfatal myocardial infarction, fatal myocardial infarction, major adverse cardiovascular event, cardiovascular death, and all-cause death. iCAC was present in 20% to 100% of the patients in these cohorts, but when present, iCAC was reported by radiologists in only 31% to 44% of cases. Between 18% and 77% of patients with iCAC were not on preventive medications in studies that reported these data. Seven studies measured the effect of reporting on guideline directed medical therapy, and 5 (71%) reported an increase in medication prescriptions after diagnosis of iCAC, with one confirming reductions in low-density lipoprotein levels. Twelve investigations reported good concordance between CAC grade on noncardiac CT and Agatston score on electrocardiogram-gated cardiac CT, and 10 demonstrated that artificial intelligence tools can reliably calculate an Agatston score on noncardiac CT.

CONCLUSION

A body of evidence demonstrates that patients with iCAC on routine chest CT are at risk for cardiovascular disease events and death, but they are often undiagnosed. Uniform reporting of iCAC in the chest CT impression represents an opportunity for radiology to contribute to early identification of high-risk individuals and potentially reduce morbidity and mortality. AI tools have been validated to calculate Agatston score on routine chest CT and hold the best potential for facilitating broad adoption.

Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers

BACKGROUND

Heavy smokers are at increased risk for cardiovascular disease and may benefit from individualized risk quantification using routine lung cancer screening chest computed tomography. We investigated the prognostic value of deep learning-based automated epicardial adipose tissue quantification and compared it to established cardiovascular risk factors and coronary artery calcium.

METHODS

We investigated the prognostic value of automated epicardial adipose tissue quantification in heavy smokers enrolled in the National Lung Screening Trial and followed for 12.3 (11.9-12.8) years. The epicardial adipose tissue was segmented and quantified on non-ECG-synchronized, non-contrast low-dose chest computed tomography scans using a validated deep-learning algorithm. Multivariable survival regression analyses were then utilized to determine the associations of epicardial adipose tissue volume and density with all-cause and cardiovascular mortality (myocardial infarction and stroke).

RESULTS

Here we show in 24,090 adult heavy smokers (59% men; 61 ± 5 years) that epicardial adipose tissue volume and density are independently associated with all-cause (adjusted hazard ratios: 1.10 and 1.38; P < 0.001) and cardiovascular mortality (adjusted hazard ratios: 1.14 and 1.78; P < 0.001) beyond demographics, clinical risk factors, body habitus, level of education, and coronary artery calcium score.

CONCLUSIONS

Our findings suggest that automated assessment of epicardial adipose tissue from low-dose lung cancer screening images offers prognostic value in heavy smokers, with potential implications for cardiovascular risk stratification in this high-risk population.

The Role of Artificial Intelligence in Coronary Calcium Scoring in Standard Cardiac Computed Tomography and Chest Computed Tomography With Different Reconstruction Kernels

PURPOSE

To assess the correlation of coronary calcium score (CS) obtained by artificial intelligence (AI) with those obtained by electrocardiography gated standard cardiac computed tomography (CCT) and nongated chest computed tomography (ChCT) with different reconstruction kernels.

PATIENTS AND METHODS

Seventy-six patients received standard CCT and ChCT simultaneously. We compared CS obtained in 4 groups: CS CCT , by the traditional method from standard CCT, 25 cm field of view, 3 mm slice thickness, and kernel filter convolution 12 (FC12); CS AICCT , by AI from the standard CCT; CS ChCTsoft , by AI from the non-gated CCT, 40 cm field of view, 3 mm slice thickness, and a soft kernel FC02; and CS ChCTsharp , by AI from CCT image with same parameters for CS ChCTsoft except for using a sharp kernel FC56. Statistical analyses included Spearman rank correlation coefficient (ρ), intraclass correlation (ICC), Bland-Altman plots, and weighted kappa analysis (κ).

RESULTS

The CS AICCT was consistent with CS CCT (ρ = 0.994 and ICC of 1.00, P < 0.001) with excellent agreement with respect to cardiovascular (CV) risk categories of the Agatston score (κ = 1.000). The correlation between CS ChCTsoft and CS ChCTsharp was good (ρ = 0.912, 0.963 and ICC = 0.929, 0.948, respectively, P < 0.001) with a tendency of underestimation (Bland-Altman mean difference and 95% upper and lower limits of agreements were 329.1 [-798.9 to 1457] and 335.3 [-651.9 to 1322], respectively). The CV risk category agreement between CS ChCTsoft and CS ChCTsharp was moderate (κ = 0.556 and 0.537, respectively).

CONCLUSIONS

There was an excellent correlation between CS CCT and CS AICCT , with excellent agreement between CV risk categories. There was also a good correlation between CS CCT and CS obtained by ChCT albeit with a tendency for underestimation and moderate accuracy in terms of CV risk assessment.

Reporting and Outcomes of Coronary Calcification on Lung Cancer Screening CT

RATIONALE AND OBJECTIVES

To evaluate the accuracy and downstream testing and statin prescribing of real-world reporting of coronary calcification on lung cancer screening (LCS) CT.

MATERIALS AND METHODS

We retrospectively reviewed LCS CTs from January 2015 to November 2021 for reporting of coronary calcification; reports that denoted coronary calcification as a significant incidental finding ("S" modifier) were also noted. We evaluated calcium scoring accuracy in patients in whom a cardiac or calcium scoring CT was performed within 1 year of the LCS CT. For the first LCS CT in all patients, we evaluated whether a stress test was performed within 6 months and whether a new statin prescription was written within 90 days of the LCS CT. Patients were stratified by atherosclerotic cardiovascular disease (ASCVD) risk group, used in a multivariable regression analysis for new statin prescriptions.

RESULTS

Eight thousand nine hundred eighty-seven patients underwent screening. In 117 patients who had a paired cardiac CT, scores were concordant in 65 (56%), and LCS CTs did not mention or underestimated calcifications in 40 (34%). Reporting of coronary artery calcifications led to new statin prescriptions, with OR of 1.8 for calcifications without S modifier and 4.4 for calcifications with S modifier. Reporting of coronary artery calcification with S modifier led to subsequent stress testing in 141/1582 (9%) of patients.

CONCLUSION

Coronary calcifications are frequently not mentioned or underestimated at LCS CT. Reporting of coronary calcifications leads to new statin prescriptions, and radiologists should consider reporting these to allow for a risk-benefit discussion with the patient's physician.

Effect of stage shift and immunotherapy treatment on lung cancer survival outcomes

OBJECTIVES

Non-small-cell lung cancer mortality has declined at a faster rate than incidence due to multiple factors, including changes in smoking behaviour, early detection which shifts diagnosis, and novel therapies. Limited resources require that we quantify the contribution of early detection versus novel therapies in improving lung cancer survival outcomes.

METHODS

Non-small-cell lung cancer patients from the Surveillance, Epidemiology, and End Results-Medicare data were queried and divided into: (i) stage IV diagnosed in 2015 (n = 3774) and (ii) stage I-III diagnosed in 2010-2012 (n = 15 817). Multivariable Cox-proportional hazards models were performed to assess the independent association of immunotherapy or diagnosis at stage I/II versus III with survival.

RESULTS

Patients treated with immunotherapy had significantly better survival than those who did not (HRadj: 0.49, 95% confidence interval: 0.43-0.56), as did those diagnosed at stage I/II versus stage III (HRadj: 0.36, 95% confidence interval: 0.35-0.37). Patients on immunotherapy had a 10.7-month longer survival than those who were not. Stage I/II patients had an average survival benefit of 34 months, compared to stage III. If 25%% of stage IV patients not on immunotherapy received it, there would be a gain of 22 292 person-years survival per 100 000 diagnoses. A switch of only 25% from stage III to stage I/II would correspond to 70 833 person-years survival per 100 000 diagnoses.

CONCLUSIONS

In this cohort study, earlier stage at diagnosis contributed to life expectancy by almost 3 years, while gains from immunotherapy would contribute ½ year of survival. Given the relative affordability of early detection, risk reduction through increased screening should be optimized.

Using Recurrent Neural Networks to Extract High-Quality Information From Lung Cancer Screening Computerized Tomography Reports for Inter-Radiologist Audit and Feedback Quality Improvement

PURPOSE

Lung cancer screening programs generate a high volume of low-dose computed tomography (LDCT) reports that contain valuable information, typically in a free-text format. High-performance named-entity recognition (NER) models can extract relevant information from these reports automatically for inter-radiologist quality control.

METHODS

Using LDCT report data from a longitudinal lung cancer screening program (8,305 reports; 3,124 participants; 2006-2019), we trained a rule-based model and two bidirectional long short-term memory (Bi-LSTM) NER neural network models to detect clinically relevant information from LDCT reports. Model performance was tested using F1 scores and compared with a published open-source radiology NER model (Stanza) in an independent evaluation set of 150 reports. The top performing model was applied to a data set of 6,948 reports for an inter-radiologist quality control assessment.

RESULTS

The best performing model, a Bi-LSTM NER recurrent neural network model, had an overall F1 score of 0.950, which outperformed Stanza (F1 score = 0.872) and a rule-based NER model (F1 score = 0.809). Recall (sensitivity) for the best Bi-LSTM model ranged from 0.916 to 0.991 for different entity types; precision (positive predictive value) ranged from 0.892 to 0.997. Test performance remained stable across time periods. There was an average of a 2.86-fold difference in the number of identified entities between the most and the least detailed radiologists.

CONCLUSION

We built an open-source Bi-LSTM NER model that outperformed other open-source or rule-based radiology NER models. This model can efficiently extract clinically relevant information from lung cancer screening computerized tomography reports with high accuracy, enabling efficient audit and feedback to improve quality of patient care.

Clinical Scores, Biomarkers and IT Tools in Lung Cancer Screening-Can an Integrated Approach Overcome Current Challenges?

As most lung cancer (LC) cases are still detected at advanced and incurable stages, there are increasing efforts to foster detection at earlier stages by low dose computed tomography (LDCT) based LC screening. In this scoping review, we describe current advances in candidate selection for screening (selection phase), technical aspects (screening), and probability evaluation of malignancy of CT-detected pulmonary nodules (PN management). Literature was non-systematically assessed and reviewed for suitability by the authors. For the selection phase, we describe current eligibility criteria for screening, along with their limitations and potential refinements through advanced clinical scores and biomarker assessments. For LC screening, we discuss how the accuracy of computerized tomography (CT) scan reading might be augmented by IT tools, helping radiologists to cope with increasing workloads. For PN management, we evaluate the precision of follow-up scans by semi-automatic volume measurements of CT-detected PN. Moreover, we present an integrative approach to evaluate the probability of PN malignancy to enable safe decisions on further management. As a clear limitation, additional validation studies are required for most innovative diagnostic approaches presented in this article, but the integration of clinical risk models, current imaging techniques, and advancing biomarker research has the potential to improve the LC screening performance generally.

Cardiac computed tomographic imaging in cardio-oncology: An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT). Endorsed by the International Cardio-Oncology Society (ICOS)

Cardio-Oncology is a rapidly growing sub-specialty of medicine, however, there is very limited guidance on the use of cardiac CT (CCT) in the care of Cardio-Oncology patients. In order to fill in the existing gaps, this Expert Consensus statement comprised of a multidisciplinary collaboration of experts in Cardiology, Radiology, Cardiovascular Multimodality Imaging, Cardio-Oncology, Oncology and Radiation Oncology aims to summarize current evidence for CCT applications in Cardio-Oncology and provide practice recommendations for clinicians.

Are cardiovascular comorbidities always associated with a worse prognosis in patients with lung cancer?

Many factors contribute to mortality in lung cancer, including the presence of concomitant cardiovascular disease. In the treatment of early stage of lung cancer, the presence of comorbidities and occurence of cardiotoxicity may be prognostic. The effect of cardiotoxicity of radiotherapy and chemoradiotherapy on overall survival has been documented. Acute arterial and venous thromboembolic events seem to correlate with the degree of the histological malignancy, its clinical advancement, and even with optimal cardiac treatment, they may influence the survival time. In the case of high-grade and advanced lung cancer stage especially in an unresectable stadium, the prognosis depends primarily on the factors related to the histopathological and molecular diagnosis. Electrocardiographic and echocardiographic abnormalities may be prognostic factors, as they seem to correlate with the patient's performance status as well as tumor localization and size.

Frequency of Statin Prescription Among Individuals with Coronary Artery Calcifications Detected Through Lung Cancer Screening

Individuals eligible for lung cancer screening (LCS) are at risk for atherosclerotic cardiovascular disease (ASCVD) due to smoking history. Coronary artery calcifications (CAC), a common incidental finding on low-dose CT (LDCT) for LCS, is a predictor of cardiovascular events. Despite findings of high ASCVD risk and CAC, a substantial proportion of LCS patients are not prescribed primary preventive statin therapy for ASCVD. We assessed the frequency of statin prescription in LCS patients with moderate levels of CAC. Among 259 individuals with moderate CAC, 95% had ASCVD risk ≥ 7.5%. Despite this, 27% of patients were statin-free prior to LDCT and 21.2% remained statin-free after LDCT showing moderate CAC. Illustratively, while a substantial proportion of LCS patients are statin-eligible, many lack a statin prescription, even after findings of CAC burden. CAC reporting should be standardized, and interdisciplinary communication should be optimized to ensure that LCS patients are placed on appropriate preventive therapy.

Lung-RADS Category 3 and 4 Nodules on Lung Cancer Screening in Clinical Practice

Background: Lung-RADS category 3 and 4 nodules account for most cancers among screening-detected lung cancers and are considered actionable nodules with management implications. The cancer frequency among such nodules is estimated in the Lung-RADS recommendations and has been investigated primarily using retrospectively assigned Lung-RADS classifications. Objective: To assess the frequency of cancer among lung nodules assigned Lung-RADS category 3 or 4 at lung cancer screening (LCS) in clinical practice and factors that impact the cancer frequency within each category. Methods: This retrospective study was based on review of clinical radiology reports of 9148 consecutive low-dose CT LCS examinations performed in 4798 patients between June 2014 and January 2021 as part of an established LCS program. Unique nodules assigned Lung-RADS category 3 or 4 (4A, 4B, or 4X) that were clinically categorized as benign or malignant by a multidisciplinary conference, considering histologic analysis and follow-up imaging, were selected for further analysis; benign diagnoses based on stability required at least 12 months of follow-up imaging. Indeterminate nodules were excluded. Cancer frequencies were evaluated. Results: Of the 9148 LCS examinations, 857 (9.4%) were assigned Lung-RADS category 3, and 721 (7.9%) were assigned category 4. The final analysis included 1297 unique nodules in 1139 patients (598 men, 541 women; mean age, 66.0±6.3 years). A total of 1108/1297 (85.4%) nodules were deemed benign, and 189/1297 (14.6%) were deemed malignant. Frequencies of malignancy for category 3, 4A, 4B, and 4X nodules were 3.9%, 15.5%, 36.3%, and 76.8%, respectively. A total of 45/46 (97.8%) endobronchial nodules (all category 4A) were deemed benign based on resolution. Cancer frequency was 13.1%, 24.4%, and 13.5% for solid, part-solid, and ground-glass nodules, respectively. Conclusions: When applying Lung-RADS for LCS clinical practice, the frequency of Lung-RADS category 3 and 4 nodules, as well as cancer frequency in these categories, were higher than prevalence and cancer risk estimated for category 3 and 4 nodules in the Lung-RADS recommendations and reported in earlier studies using retrospective category assignments. Nearly all endobronchial category 4A nodules were benign. Clinical Impact: Future Lung-RADS iterations should consider these findings from real-world practice to improve the system's clinical utility.

Screening for Lung Cancer: CHEST Guideline and Expert Panel Report

BACKGROUND

Low-dose chest CT screening for lung cancer has become a standard of care in the United States, in large part because of the results of the National Lung Screening Trial (NLST). Additional evidence supporting the net benefit of low-dose chest CT screening for lung cancer, and increased experience in minimizing the potential harms, has accumulated since the prior iteration of these guidelines. Here, we update the evidence base for the benefit, harms, and implementation of low-dose chest CT screening. We use the updated evidence base to provide recommendations where the evidence allows, and statements based on experience and expert consensus where it does not.

METHODS

Approved panelists reviewed previously developed key questions using the Population, Intervention, Comparator, Outcome format to address the benefit and harms of low-dose CT screening, and key areas of program implementation. A systematic literature review was conducted using MEDLINE via PubMed, Embase, and the Cochrane Library on a quarterly basis since the time of the previous guideline publication. Reference lists from relevant retrievals were searched, and additional papers were added. Retrieved references were reviewed for relevance by two panel members. The quality of the evidence was assessed for each critical or important outcome of interest using the Grading of Recommendations, Assessment, Development, and Evaluation approach. Meta-analyses were performed when enough evidence was available. Important clinical questions were addressed based on the evidence developed from the systematic literature review. Graded recommendations and ungraded statements were drafted, voted on, and revised until consensus was reached.

RESULTS

The systematic literature review identified 75 additional studies that informed the response to the 12 key questions that were developed. Additional clinical questions were addressed resulting in seven graded recommendations and nine ungraded consensus statements.

CONCLUSIONS

Evidence suggests that low-dose CT screening for lung cancer can result in a favorable balance of benefit and harms. The selection of screen-eligible individuals, the quality of imaging and image interpretation, the management of screen-detected findings, and the effectiveness of smoking cessation interventions can impact this balance.

Lung cancer screening implementation: Complexities and priorities

Lung cancer is the number one cause of cancer death worldwide. The benefits of lung cancer screening to reduce mortality and detect early-stage disease are no longer in any doubt based on the results of two landmark trials using LDCT. Lung cancer screening has been implemented in the US and South Korea and is under consideration by other communities. Successful translation of demonstrated research outcomes into the routine clinical setting requires careful implementation and co-ordinated input from multiple stakeholders. Implementation aspects may be specific to different healthcare settings. Important knowledge gaps remain, which must be addressed in order to optimize screening benefits and minimize screening harms. Lung cancer screening differs from all other cancer screening programmes as lung cancer risk is driven by smoking, a highly stigmatized behaviour. Stigma, along with other factors, can impact smokers' engagement with screening, meaning that smokers are generally 'hard to reach'. This review considers critical points along the patient journey. The first steps include selecting a risk threshold at which to screen, successfully engaging the target population and maximizing screening uptake. We review barriers to smoker engagement in lung and other cancer screening programmes. Recruitment strategies used in trials and real-world (clinical) programmes and associated screening uptake are reviewed. To aid cross-study comparisons, we propose a standardized nomenclature for recording and calculating recruitment outcomes. Once participants have engaged with the screening programme, we discuss programme components that are critical to maximize net benefit. A whole-of-programme approach is required including a standardized and multidisciplinary approach to pulmonary nodule management, incorporating probabilistic nodule risk assessment and longitudinal volumetric analysis, to reduce unnecessary downstream investigations and surgery; the integration of smoking cessation; and identification and intervention for other tobacco related diseases, such as coronary artery calcification and chronic obstructive pulmonary disease. National support, integrated with tobacco control programmes, and with appropriate funding, accreditation, data collection, quality assurance and reporting mechanisms will enhance lung cancer screening programme success and reduce the risks associated with opportunistic, ad hoc screening. Finally, implementation research must play a greater role in informing policy change about targeted LDCT screening programmes.

Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography

Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Our deep learning CVD risk prediction model, trained with 30,286 LDCTs from the National Lung Cancer Screening Trial, achieves an area under the curve (AUC) of 0.871 on a separate test set of 2,085 subjects and identifies patients with high CVD mortality risks (AUC of 0.768). We validate our model against ECG-gated cardiac CT based markers, including coronary artery calcification (CAC) score, CAD-RADS score, and MESA 10-year risk score from an independent dataset of 335 subjects. Our work shows that, in high-risk patients, deep learning can convert LDCT for lung cancer screening into a dual-screening quantitative tool for CVD risk estimation.

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

BACKGROUND

Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be demonstrated in the context of current screening modalities. Here, we present findings on the performance of an AI convolutional neural network (CNN) prototype (AI-RAD Companion, Siemens Healthineers) that automatically detects pulmonary nodules and quantifies coronary artery calcium volume (CACV) on low-dose chest CT (LDCT), and compare results to expert radiologists. We also correlate AI findings with adverse cardiopulmonary outcomes in a retrospective cohort of 117 patients who underwent LDCT.

METHODS

A total of 117 patients were enrolled in this study. Two CNNs were used to identify lung nodules and CACV on LDCT scans. All subjects were used for lung nodule analysis, and 96 subjects met the criteria for coronary artery calcium volume analysis. Interobserver concordance was measured using ICC and Cohen's kappa. Multivariate logistic regression and partial least squares regression were used for outcomes analysis.

RESULTS

Agreement of the AI findings with experts was excellent (CACV ICC = 0.904, lung nodules Cohen's kappa = 0.846) with high sensitivity and specificity (CACV: sensitivity = .929, specificity = .960; lung nodules: sensitivity = 1, specificity = 0.708). The AI findings improved the prediction of major cardiopulmonary outcomes at 1-year follow-up including major adverse cardiac events and lung cancer (AUCMACE = 0.911, AUCLung Cancer = 0.942).

CONCLUSION

We conclude the AI prototype rapidly and accurately identifies significant risk factors for cardiopulmonary disease on standard screening low-dose chest CT. This information can be used to improve diagnostic ability, facilitate intervention, improve morbidity and mortality, and decrease healthcare costs. There is also potential application in countries with limited numbers of cardiothoracic radiologists.

Preoperative coronary artery calcifications in veterans predict higher all-cause mortality in early-stage lung cancer: a cohort study

Background

Lung cancer patients often have comorbidities that may impact survival. This observational cohort study examines whether coronary artery calcifications (CAC) impact all-cause mortality in patients with resected stage I non-small cell lung cancer (NSCLC).

Methods

Veterans with stage I NSCLC who underwent resection at a single institution between 2005 and 2018 were selected from a prospectively collected database. Radiologists blinded to patient outcomes graded CAC severity (mild, moderate, or severe) in preoperative CT scans using a visual estimation scoring system. Inter-rater reliability was calculated using the kappa statistic. All-cause mortality was the primary outcome. Kaplan-Meier survival analysis and Cox proportional hazards regression were used to compare time-to-death by varying CAC.

Results

The Veteran patients (n=195) were predominantly older (median age of 67) male (98%) smokers (96%). The majority (68%) were pathologic stage IA. Overall, 12% of patients had no CAC, 27% mild, 26% moderate, and 36% severe CAC. Median unadjusted survival was 8.8 years for patients with absent or mild CAC versus 6.3 years for moderate and 5.9 years for severe CAC (P=0.01). The adjusted hazard ratio for moderate CAC was 1.44 (95% CI, 0.85–2.46) and for severe CAC was 1.73 (95% CI, 1.03–2.88; P for trend <0.05).

Conclusions

The presence of severe CAC on preoperative imaging significantly impacted the all-cause survival of patients undergoing resection for stage I NSCLC. This impact on mortality should be taken into consideration by multidisciplinary teams when making treatment plans for patients with early-stage disease.

Cardiovascular Risk in the Lung Cancer Screening Population: A Multicenter Study Evaluating the Association Between Coronary Artery Calcification and Preventive Statin Prescription

OBJECTIVE

Coronary artery calcification (CAC) is a marker of atherosclerotic cardiovascular disease (ASCVD), the leading cause of death in individuals receiving lung cancer screening (LCS) with low-dose CT. Our purpose was to determine the proportion of the LCS population eligible for primary ASCVD preventive statin therapy by American College of Cardiology/American Heart Association guidelines, assess statin prescription rates among statin-eligible individuals, and determine associations of CAC on downstream statin prescribing within 90 days of LCS.

METHODS

Individuals receiving LCS between January 1, 2016, and December 31, 2018, across three centers were retrospectively enrolled. Statin eligibility in individuals without pre-existing ASCVD was determined by 2013 American College of Cardiology/American Heart Association guidelines: (1) low-density lipoprotein ≥190 mg/dL, (2) diabetes, or (3) ASCVD risk score ≥7.5%. CAC presence and severity (mild, moderate, heavy) were extracted from LCS reports. Variation in statin prescription rates and associations between CAC and statin prescription were determined using mixed-effects logistic regression.

RESULTS

Of 5,495 individuals receiving LCS, 31.4% (1,724 of 5,495) had pre-existing ASCVD. Of the remaining 3,771 individuals, 73.6% were statin eligible (2,777 of 3,771). However, most lacked statin prescription (60.5%, 1,681 of 2,777). CAC was associated with downstream statin prescribing (adjusted odds ratio = 2.60, 95% confidence interval: 1.12-6.02), with a higher likelihood of statin prescribing with increasing CAC severity (adjusted odds ratio = 2.21, 95% confidence interval: 1.35-3.60).

CONCLUSION

Although most of the LCS population is eligible for guideline-directed statin therapy, statins are underprescribed in this group. Radiologist reporting of CAC at LCS reflects a potential opportunity to raise awareness of ASCVD risk and improve preventive statin prescribing.

Coronary artery calcification in COVID-19 patients: an imaging biomarker for adverse clinical outcomes

BACKGROUND

Recent studies have demonstrated a complex interplay between comorbid cardiovascular disease, COVID-19 pathophysiology, and poor clinical outcomes. Coronary artery calcification (CAC) may therefore aid in risk stratification of COVID-19 patients.

METHODS

Non-contrast chest CT studies on 180 COVID-19 patients ≥ age 21 admitted from March 1, 2020 to April 27, 2020 were retrospectively reviewed by two radiologists to determine CAC scores. Following feature selection, multivariable logistic regression was utilized to evaluate the relationship between CAC scores and patient outcomes.

RESULTS

The presence of any identified CAC was associated with intubation (AOR: 3.6, CI: 1.4-9.6) and mortality (AOR: 3.2, CI: 1.4-7.9). Severe CAC was independently associated with intubation (AOR: 4.0, CI: 1.3-13) and mortality (AOR: 5.1, CI: 1.9-15). A greater CAC score (UOR: 1.2, CI: 1.02-1.3) and number of vessels with calcium (UOR: 1.3, CI: 1.02-1.6) was associated with mortality. Visualized coronary stent or coronary artery bypass graft surgery (CABG) had no statistically significant association with intubation (AOR: 1.9, CI: 0.4-7.7) or death (AOR: 3.4, CI: 1.0-12).

CONCLUSION

COVID-19 patients with any CAC were more likely to require intubation and die than those without CAC. Increasing CAC and number of affected arteries was associated with mortality. Severe CAC was associated with higher intubation risk. Prior CABG or stenting had no association with elevated intubation or death.

Management and Outcomes of Suspected Infectious and Inflammatory Lung Abnormalities Identified on Lung Cancer Screening CT

Background: Incidental findings are frequently encountered during lung cancer screening (LCS). Limited data describe the prevalence of suspected acute infectious and inflammatory lung processes on LCS and how they should be managed. Objective: To determine the prevalence, radiologic reporting and management, and outcome of suspected infectious and inflammatory lung processes identified incidentally during LCS, and to propose a management algorithm. Methods: This retrospective study included 6314 low dose CT (LDCT) examinations performed between June 2014 and April 2019 in 3800 patients as part of an established LCS program. Radiology reports were reviewed, and patients with potentially infectious or inflammatory lung abnormalities were identified and analyzed for descriptors of imaging findings, Lung-RADS designation, recommendations, and clinical outcomes. Based on the descriptors, outcomes and a >2% threshold risk of malignancy, a follow-up algorithm was developed to decrease additional imaging without affecting cancer detection. Results: A total of 331/3800 (8.7%) patients (178 men, 153 women; mean age: 66 ± 7 years) undergoing LCS had lung findings that were attributed to infection or inflammation. These abnormalities were reported as potentially significant findings using the "S" modifier in 149/331 (45.0%) and as the "dominant nodule" determining the Lung-RADS category in 96/331 (29.0%). Abnormalities were multiple or multifocal in 260/331 (78.5%). Common descriptors were ground-glass (155/331; 46.8%), tree-in-bud (56/331; 16.9%), consolidation (41/331; 12.4%), and clustered (67/331; 20.2%) opacities. A follow-up chest CT outside of screening was performed within 12 months or less in 264/331 (79.8%) and within 6 months or less in 286/331 (56.2%). A total of 260/331 (78.5%) opacities resolved on follow-up imaging. Two malignancies (2/331; 0.60%) were associated with these abnormalities, and both had consolidations. Theoretical adoption of a proposed management algorithm for suspected infectious and inflammatory findings reduced unnecessary follow-up imaging by 82.6% without missing a single malignancy. Conclusions: Presumed acute infectious or inflammatory lung abnormalities are frequently encountered in the setting of LCS. These opacities are commonly multifocal and resolve on follow-up. Less than 1% are associated with malignancy. Clinical impact: Adoption of a conservative management algorithm can standardize recommendations and reduce unnecessary imaging without increasing the risk of missing a malignancy.