Prognostic value of heart valve calcifications for cardiovascular events in a lung cancer screening population

To assess the prognostic value of aortic valve and mitral valve/annulus calcifications for cardiovascular events in heavily smoking men without a history of cardiovascular disease. Heavily smoking men without a cardiovascular disease history who underwent non-contrast-enhanced low-radiation-dose chest CT for lung cancer screening were included. Non-imaging predictors (age, smoking status and pack-years) were collected and imaging-predictors (calcium volume of the coronary arteries, aorta, aortic valve and mitral valve/annulus) were obtained. The outcome was the occurrence of cardiovascular events. Multivariable Cox proportional-hazards regression was used to calculate hazard-ratios (HRs) with 95 % confidence interval (CI). Subsequently, concordance-statistics were calculated. In total 3111 individuals were included, of whom 186 (6.0 %) developed a cardiovascular event during a follow-up of 2.9 (Q1-Q3, 2.7-3.3) years. If aortic (n = 657) or mitral (n = 85) annulus/valve calcifications were present, cardiovascular event incidence increased to 9.0 % (n = 59) or 12.9 % (n = 11), respectively. HRs of aortic and mitral valve/annulus calcium volume for cardiovascular events were 1.46 (95 % CI, 1.09-1.84) and 2.74 (95 % CI, 0.92-4.56) per 500 mm(3). The c-statistic of a basic model including age, pack-years, current smoking status, coronary and aorta calcium volume was 0.68 (95 % CI, 0.63-0.72), which did not change after adding heart valve calcium volume. Aortic valve calcifications are predictors of future cardiovascular events. However, there was no added prognostic value beyond age, number of pack-years, current smoking status, coronary and aorta calcium volume for short term cardiovascular events

Prognostic Value of Coronary Computed Tomography Angiography in Patients With Diabetes : A Meta-analysis

OBJECTIVE: The usefulness of coronary computed tomography angiography (CTA) for the evaluation of coronary artery disease (CAD) in patients with diabetes is ambiguous. We therefore performed a meta-analysis of studies reporting event rates and hazard ratios (HR) to determine the prognostic value of CTA in this patient population. RESEARCH DESIGN AND METHODS: We searched PubMed and Embase up to November 2015. Study subjects' characteristics, events (all-cause mortality or cardiac death, nonfatal myocardial infarction, unstable angina pectoris, stroke, revascularization), and events excluding revascularization were collected. We calculated the prevalence of obstructive and nonobstructive CAD on CTA, annualized event rates, and pooled unadjusted and adjusted HR using a generic inverse random model. RESULTS: Eight studies were eligible for inclusion into this meta-analysis, with 6,225 participants (56% male; weighted age, 61 years) with a follow-up period ranging from 20 to 66 months. The prevalence of obstructive CAD, nonobstructive CAD, and no CAD was 38%, 36%, and 25%, respectively. The annualized event rate was 17.1% for obstructive CAD, 4.5% for nonobstructive CAD, and 0.1% for no CAD. Obstructive and nonobstructive CAD were associated with an increased HR of 5.4 and 4.2, respectively. A higher HR for obstructive CAD was observed in studies including revascularization compared with those that did not (7.3 vs. 3.7, P = 0.124). CONCLUSIONS: CTA in patients with diabetes allows for safely ruling out future events, and the detection of CAD could allow for the identification of high-risk patients in whom aggressive risk factor modification, medical surveillance, or elective revascularization could potentially improve survival

Prognostic Value of Coronary Computed Tomography Angiography in Patients With Diabetes : A Meta-analysis

OBJECTIVE: The usefulness of coronary computed tomography angiography (CTA) for the evaluation of coronary artery disease (CAD) in patients with diabetes is ambiguous. We therefore performed a meta-analysis of studies reporting event rates and hazard ratios (HR) to determine the prognostic value of CTA in this patient population. RESEARCH DESIGN AND METHODS: We searched PubMed and Embase up to November 2015. Study subjects' characteristics, events (all-cause mortality or cardiac death, nonfatal myocardial infarction, unstable angina pectoris, stroke, revascularization), and events excluding revascularization were collected. We calculated the prevalence of obstructive and nonobstructive CAD on CTA, annualized event rates, and pooled unadjusted and adjusted HR using a generic inverse random model. RESULTS: Eight studies were eligible for inclusion into this meta-analysis, with 6,225 participants (56% male; weighted age, 61 years) with a follow-up period ranging from 20 to 66 months. The prevalence of obstructive CAD, nonobstructive CAD, and no CAD was 38%, 36%, and 25%, respectively. The annualized event rate was 17.1% for obstructive CAD, 4.5% for nonobstructive CAD, and 0.1% for no CAD. Obstructive and nonobstructive CAD were associated with an increased HR of 5.4 and 4.2, respectively. A higher HR for obstructive CAD was observed in studies including revascularization compared with those that did not (7.3 vs. 3.7, P = 0.124). CONCLUSIONS: CTA in patients with diabetes allows for safely ruling out future events, and the detection of CAD could allow for the identification of high-risk patients in whom aggressive risk factor modification, medical surveillance, or elective revascularization could potentially improve survival

Automated Coronary Artery Calcification Scoring in Non-Gated Chest CT: Agreement and Reliability

Objective: To determine the agreement and reliability of fully automated coronary artery calcium (CAC) scoring in a lung cancer screening population. Materials and Methods: 1793 low-dose chest CT scans were analyzed (non-contrast-enhanced, non-gated). To establish the reference standard for CAC, first automated calcium scoring was performed using a preliminary version of a method employing coronary calcium atlas and machine learning approach. Thereafter, each scan was inspected by one of four trained raters. When needed, the raters corrected initially automaticity-identified results. In addition, an independent observer subsequently inspected manually corrected results and discarded scans with gross segmentation errors. Subsequently, fully automatic coronary calcium scoring was performed. Agatston score, CAC volume and number of calcifications were computed. Agreement was determined by calculating proportion of agreement and examining Bland-Altman plots. Reliability was determined by calculating linearly weighted kappa (k) for Agatston strata and intraclass correlation coefficient (ICC) for continuous values. Results: 44 (2.5%) scans were excluded due to metal artifacts or gross segmentation errors. In the remaining 1749 scans, median Agatston score was 39.6 (P25-P75:0-345.9), median volume score was 60.4 mm(3) (P25-P75:0-361.4) and median number of calcifications was 2 (P25-P75:0-4) for the automated scores. The k demonstrated very good reliability (0.85) for Agatston risk categories between the automated and reference scores. The Bland-Altman plots showed underestimation of calcium score values by automated quantification. Median difference was 2.5 (p25-p75:0.0-53.2) for Agatston score, 7.6 (p25-p75:0.0-94.4) for CAC volume and 1 (p25-p75:0-5) for number of calcifications. The ICC was very good for Agatston score (0.90), very good for calcium volume (0.88) and good for number of calcifications (0.64). Discussion: Fully automated coronary calcium scoring in a lung cancer screening setting is feasible with acceptable reliability and agreement despite an underestimation of the amount of calcium when compared to reference scores

Pulmonary function and CT biomarkers as risk factors for cardiovascular events in male lung cancer screening participants: the NELSON study

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 (FEV1% predicted) and FEV1 divided by forced vital capacity (FVC; FEV1/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 FEV1% predicted, 1.000 (95% CI 0.986-1.015) for FEV1/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(3), 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

Automatic Coronary Artery Calcium Scoring on Radiotherapy Planning CT Scans of Breast Cancer Patients : Reproducibility and Association with Traditional Cardiovascular Risk Factors

OBJECTIVES: Coronary artery calcium (CAC) is a strong and independent predictor of cardiovascular disease (CVD) risk. This study assesses reproducibility of automatic CAC scoring on radiotherapy planning computed tomography (CT) scans of breast cancer patients, and examines its association with traditional cardiovascular risk factors. METHODS: This study included 561 breast cancer patients undergoing radiotherapy between 2013 and 2015. CAC was automatically scored with an algorithm using supervised pattern recognition, expressed as Agatston scores and categorized into five categories (0, 1-10, 11-100, 101-400, >400). Reproducibility between automatic and manual expert scoring was assessed in 79 patients with automatically determined CAC above zero and 84 randomly selected patients without automatically determined CAC. Interscan reproducibility of automatic scoring was assessed in 294 patients having received two scans (82% on the same day). Association between CAC and CVD risk factors was assessed in 36 patients with CAC scores >100, 72 randomly selected patients with scores 1-100, and 72 randomly selected patients without CAC. Reliability was assessed with linearly weighted kappa and agreement with proportional agreement. RESULTS: 134 out of 561 (24%) patients had a CAC score above zero. Reliability of CVD risk categorization between automatic and manual scoring was 0.80 (95% Confidence Interval (CI): 0.74-0.87), and slightly higher for scans with breath-hold. Agreement was 0.79 (95% CI: 0.72-0.85). Interscan reliability was 0.61 (95% CI: 0.50-0.72) with an agreement of 0.84 (95% CI: 0.80-0.89). Ten out of 36 (27.8%) patients with CAC scores above 100 did not have other cardiovascular risk factors. CONCLUSIONS: Automatic CAC scoring on radiotherapy planning CT scans is a reliable method to assess CVD risk based on Agatston scores. One in four breast cancer patients planned for radiotherapy have elevated CAC score. One in three patients with high CAC scores don't have other CVD risk factors and wouldn't have been identified as high risk