The Future of Concurrent Automated Coronary Artery Calcium Scoring on Screening Low-Dose Computed Tomography

Waltz, Jeffrey; Kocher, Madison; Kahn, Jacob; Dirr, McKenzie A.; Burt, Jeremy R.

doi:10.7759/cureus.8574

Cited by 12 publications

(9 citation statements)

References 56 publications

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“…33 Based on our results and the growing consensus in the existing literature, CAC scoring on nongated CT is not only valid and reliable, but also can estimate ASCVD risk and subsequent mortality. [34][35][36] Routine chest CTs remain an available resource for providing additional ASCVD risk stratification.…”

Section: Discussionmentioning

confidence: 99%

Reporting Coronary Artery Calcium on Low-Dose Computed Tomography Impacts Statin Management in a Lung Cancer Screening Population

Chin¹

2022

Federal Practitioner

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Background: Cigarette smoking is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). Concomitant use of low-dose computed tomography (LDCT) for coronary artery calcium (CAC) scoring with lung cancer screening (LCS) has been proposed to further determine ASCVD risk and mortality. We aimed to determine the validity of LDCT in identifying CAC and its impact on statin management. Methods: We conducted a retrospective review from November 2020 to May 2021 of Military Health System (MHS) beneficiaries who received LCS with LDCT and were referred for CAC scoring with electrocardiogram-gated CT. Of the 190 participants initially identified, 170 met study eligibility. The Agatston method was used to score CAC on both scan types. Results: Participants had a mean (SD) age of 62.1 (4.6) years and were 70.6% male. CAC was seen more on ECG-gated CT compared with LDCT (88% vs 74%, P < .001). The Spearman correlation and Kendall W coefficient of concordance of CAC scores between the 2 scan types was 0.945 (P < .001) and 0.643, respectively. The κ statistic between CAC scores on the 2 different scans was 0.49 (SEκ = 0.048; 95% CI, -0.726-1.706), and the weighted κ statistic was 0.711. Bland-Altman analysis demonstrated a mean bias of 111.45 Agatston units, with limits of agreement between -268.64 and 491.54, suggesting CAC scores on electrocardiogram-gated CT were on average about 111 units higher than those on LDCT. There was a statistically significant proportion of nonstatin participants who met statin criteria based on additional CAC reporting (P < .001). Conclusions: CAC scores are highly correlated and concordant between LDCT and electrocardiogram-gated CT. Smokers undergoing annual LDCT may benefit from concomitant CAC scoring to help stratify ASCVD risk.

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Section: Discussionmentioning

confidence: 99%

Reporting Coronary Artery Calcium on Low-Dose Computed Tomography Impacts Statin Management in a Lung Cancer Screening Population

Chin¹

2022

Federal Practitioner

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“…Besides early lung cancer detection, there is evidence for the LDCT-based identification of individuals being at increased risk for developing respiratory and cardiovascular diseases 16 17 . Although LDCT uses a non-triggered acquisition protocol, it allows simultaneous, quantitative assessment of coronary calcification (Agatston score 18 ), which has been shown to correlate with the rate of future myocardial infarction, stroke, and death due to cardiovascular disease 19 20 . This has the potential to combine an LCS program with cardiovascular event prevention.…”

Section: Background and Rationalementioning

confidence: 99%

Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography

Vogel‐Claussen

Lasch

Bollmann

et al. 2022

Rofo

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Background Despite the high prevalence and mortality of lung cancer and proven effectiveness of low-dose computed tomography (LDCT) to reduce mortality, Germany still lacks a national screening program. The German Institute for Quality and Efficiency in Health Care (IQWiG) and the Federal Office for Radiation Protection (BfS) both published positive scientific evaluations recommending a quality-controlled national screening program. IQWiG underlined the importance of a clear risk definition, integrated smoking cessation programs, and quality assurance, highlighting the necessity of procedural optimization. Methods and Objectives In the HANSE study, former and current smokers aged 55–79 years are assessed for their lung cancer risk by the NELSON and PLCOM2012 risk scores. 5000 high-risk participants, defined as PLCOM2012 6-year risk ≥ 1.58 % or fulfilling NELSON risk inclusion criteria, will be screened by LDCT at baseline and after 12 months. Lung nodules are analyzed by a modified Lung-RADS 1.1 score of the HANSE study, and values of emphysema and coronary calcium are determined and randomly reported to the participants. 7100 low-risk participants serve as a control. All patients are followed-up for up to 10 years. The sensitivity and specificity of the two risk assessments and LDCT screening, effects of the randomized LDCT reporting, efficiency of lung nodule management, and several other factors are assessed to analyze the success and quality of the holistic screening program. Conclusion The HANSE study is designed as a holistic lung cancer screening study in northern Germany to answer pressing questions for a successful implementation of an effective German lung cancer screening program. Key Points: Citation Format

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“…When used by cardiac imaging experts, this method globally correlates with conventional CAC score groups. The implementation of AI in a LDCT LCS program can potentially provide a reliable and reproducible numerical value to the calcium score, based on whole heart volume scoring of calcium [ 43 ]. This method provides results that closely align with the Agatston scores.…”

Section: Assessment Of Smoking-related Diseases (Comorbidities)mentioning

confidence: 99%

The Potential Role of Artificial Intelligence in Lung Cancer Screening Using Low-Dose Computed Tomography

2022

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Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk smoker populations have shown a reduction in the number of lung cancer deaths in the screening group compared to a control group. Even if various countries are currently considering the implementation of LCS programs, recurring doubts and fears persist about the potentially high false positive rates, cost-effectiveness, and the availability of radiologists for scan interpretation. Artificial intelligence (AI) can potentially increase the efficiency of LCS. The objective of this article is to review the performances of AI algorithms developed for different tasks that make up the interpretation of LCS CT scans, and to estimate how these AI algorithms may be used as a second reader. Despite the reduction in lung cancer mortality due to LCS with LDCT, many smokers die of comorbid smoking-related diseases. The identification of CT features associated with these comorbidities could increase the value of screening with minimal impact on LCS programs. Because these smoking-related conditions are not systematically assessed in current LCS programs, AI can identify individuals with evidence of previously undiagnosed cardiovascular disease, emphysema or osteoporosis and offer an opportunity for treatment and prevention.

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The Future of Concurrent Automated Coronary Artery Calcium Scoring on Screening Low-Dose Computed Tomography

Cited by 12 publications

References 56 publications

Reporting Coronary Artery Calcium on Low-Dose Computed Tomography Impacts Statin Management in a Lung Cancer Screening Population

Reporting Coronary Artery Calcium on Low-Dose Computed Tomography Impacts Statin Management in a Lung Cancer Screening Population

Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography

The Potential Role of Artificial Intelligence in Lung Cancer Screening Using Low-Dose Computed Tomography

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