Age and sex based reference values for incidental coronary artery and thoracic aorta calcifications on routine clinical chest CT: a powerful tool to appreciate available imaging findings.

OBJECTIVE: To establish age and gender specific reference values for incidental coronary artery and thoracic aorta calcification scores on routine diagnostic CT scans. These reference values can aid in structured reporting and interpretation of readily available imaging data by chest CT readers in routine practice. METHODS: A random sample of 1572 (57% male, median age 61 years) was taken from a study population of 12,063 subjects who underwent diagnostic chest CT for non-cardiovascular indications between January 2002 and December 2005. Coronary artery and thoracic aorta calcifications were graded using a validated ordinal score. The 25th, 50th and 75th percentile cut points were calculated for the coronary artery and thoracic aorta calcification scores within each age/gender stratum. RESULTS: The 75th percentile cut points for coronary artery calcification scores were higher for men than for women across all age groups, with the exception of the lowest age group. The 75th percentile cut points for thoracic aorta calcifications scores were comparable for both genders across all age groups. Based on the obtained age and gender reference values a calculation tool is provided, that allows one to enter an individual's age, gender and calcification scores to obtain the corresponding estimated percentiles. CONCLUSIONS: The calculation tool as provided in this study can be used in daily practice by CT readers to examine whether a subject has high calcifications scores relative to others with the same age and gender.

Incidental imaging findings from routine chest CT used to identify subjects at high risk of future cardiovascular events.

PURPOSE: To investigate the contribution of incidental findings at chest computed tomography (CT) in the detection of subjects at high risk for cardiovascular disease (CVD) by deriving and validating a CT-based prediction rule. MATERIALS AND METHODS: This retrospective study was approved by the ethical review board of the primary participating facility, and informed consent was waived. The derivation cohort comprised 10 410 patients who underwent diagnostic chest CT for noncardiovascular indications. During a mean follow-up of 3.7 years (maximum, 7.0 years), 1148 CVD events (cases) were identified. By using a case-cohort approach, CT scans from the cases and from an approximately 10% random sample of the baseline cohort (n = 1366) were graded visually for several cardiovascular findings. Multivariable Cox proportional hazards analysis with backward elimination technique was used to derive the best-fitting parsimonious prediction model. External validation (discrimination, calibration, and risk stratification) was performed in a separate validation cohort (n = 1653). RESULTS: The final model included patient age and sex, CT indication, left anterior descending coronary artery calcifications, mitral valve calcifications, descending aorta calcifications, and cardiac diameter. The model demonstrated good discriminative value, with a C statistic of 0.71 (95% confidence interval: 0.68, 0.74) and a good overall calibration, as assessed in the validation cohort. This imaging-based model allows accurate stratification of individuals into clinically relevant risk categories. CONCLUSION: Structured reporting of incidental CT findings can mediate accurate stratification of individuals into clinically relevant risk categories and subsequently allow those at higher risk of future CVD events to be distinguished.

Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score.

OBJECTIVES: To enable risk stratification of patients with various types of arterial disease by the development and validation of models for prediction of recurrent vascular event risk based on vascular risk factors, imaging or both. DESIGN: Prospective cohort study. SETTING: University Medical Centre. PATIENTS: 5788 patients referred with various clinical manifestations of arterial disease between January 1996 and February 2010. MAIN OUTCOME MEASURES: 788 recurrent vascular events (ie, myocardial infarction, stroke or vascular death) that were observed during 4.7 (IQR 2.3 to 7.7) years' follow-up. RESULTS: Three Cox proportional hazards models for prediction of 10-year recurrent vascular event risk were developed based on age and sex in addition to clinical parameters (model A), carotid ultrasound findings (model B) or both (model C). Clinical parameters were medical history, current smoking, systolic blood pressure and laboratory biomarkers. In a separate part of the dataset, the concordance statistic of model A was 0.68 (95% CI 0.64 to 0.71), compared to 0.64 (0.61 to 0.68) for model B and 0.68 (0.65 to 0.72) for model C. Goodness-of-fit and calibration of model A were adequate, also in separate subgroups of patients having coronary, cerebrovascular, peripheral artery or aneurysmal disease. Model A predicted < 20% risk in 59% of patients, 20-30% risk in 19% and > 30% risk in 23%. CONCLUSIONS: Patients at high risk for recurrent vascular events can be identified based on readily available clinical characteristics.

A simple adaptation method improved the interpretability of prediction models for composite end points.

OBJECTIVE: The pros and cons of composite end points in prognostic research are discussed, and an adaptation method, designed to accurately adjust absolute risks for a composite end point to risks for the individual component outcomes, is presented. STUDY DESIGN AND SETTING: An example prediction model for recurrent cardiovascular events (composite end point) was used to evaluate the performance regarding the individual component outcomes (cardiovascular death, myocardial infarction, and stroke) before and after the adaptation method. RESULTS: Discrimination for the individual component outcomes (concordance index for myocardial infarction, 0.68; concordance index for stroke, 0.70) was very similar to discrimination for the original composite end point (concordance index, 0.70). For cardiovascular death, it even increased substantially (concordance index, 0.78). After adaptation, calibration plots for the component outcomes also improved, with visible convergence of the predicted risks and the observed incidences. CONCLUSION: In sum, these findings show that the adaptation method is useful when validating or applying a composite end point prediction model to the individual component outcomes. Following from this, recommendations concerning reporting of composite end points in future research are also included. Without the need for extra data, composite end point prediction models can easily be directly expanded to allow for the estimation of risk for each individual component outcome, improving the interpretability for clinicians and patients.

Coronary artery calcium can predict all-cause mortality and cardiovascular events on low-dose CT screening for lung cancer.

OBJECTIVE: Performing coronary artery calcium (CAC) screening as part of low-dose CT lung cancer screening has been proposed as an efficient strategy to detect people with high cardiovascular risk and improve outcomes of primary prevention. This study aims to investigate whether CAC measured on low-dose CT in a population of former and current heavy smokers is an independent predictor of all-cause mortality and cardiac events. SUBJECTS AND METHODS: We used a case-cohort study and included 958 subjects 50 years old or older within the screen group of a randomized controlled lung cancer screening trial. We used Cox proportional-hazard models to compute hazard ratios (HRs) adjusted for traditional cardiovascular risk factors to predict all-cause mortality and cardiovascular events. RESULTS: During a median follow-up of 21.5 months, 56 deaths and 127 cardiovascular events occurred. Compared with a CAC score of 0, multivariate-adjusted HRs for all-cause mortality for CAC scores of 1-100, 101-1000, and more than 1000 were 3.00 (95% CI, 0.61-14.93), 6.13 (95% CI, 1.35-27.77), and 10.93 (95% CI, 2.36-50.60), respectively. Multivariate-adjusted HRs for coronary events were 1.38 (95% CI, 0.39-4.90), 3.04 (95% CI, 0.95-9.73), and 7.77 (95% CI, 2.44-24.75), respectively. CONCLUSION: This study shows that CAC scoring as part of low-dose CT lung cancer screening can be used as an independent predictor of all-cause mortality and cardiovascular events.

The prognostic value of vascular diameter measurements on routine chest computed tomography in patients not referred for cardiovascular indications.

OBJECTIVES: The aim of the study was to investigate whether diameter measurements of the thoracic aorta and the heart can be used as prognostic markers for future cardiovascular disease. METHODS: Following a case-cohort design, a total of 10,410 patients undergoing chest computed tomography were followed up for a mean period of 17 months. The ones with a cardiovascular indication were excluded. Diameter measurements were evaluated with Cox proportional hazard analysis. RESULTS: Five hundred fifteen incident cardiovascular events occurred during follow-up. The heart (hazard ratio [HR], 1.04; 95% confidence interval [CI], 1.03-1.06) and ascending thoracic (HR, 1.002; 95% CI, 1.001-1.004) diameter showed an exponential prognostic effect beyond a threshold diameter of, respectively, 11 and 30 mm; the descending aortic diameter (HR, 1.04; 95% CI, 1.01-1.13) and cardiothoracic ratio (HR, 1.06; 95% CI, 1.04-1.08) showed linear prognostic effects beyond, respectively, 25 and 0.45 mm. CONCLUSION: Intrathoracic diameter measurements can be used as markers to predict cardiovascular events in patients not referred for that disease outcome.

Prediction of cardiovascular events by using non-vascular findings on routine chest CT.

BACKGROUND: Routine computed tomography (CT) examinations contain an abundance of findings unrelated to the diagnostic question. Those with prognostic significance may contribute to early detection and treatment of disease, irrelevant findings can be ignored. We aimed to assess the association between unrequested chest CT findings in lungs, mediastinum and pleura and future cardiovascular events. METHODS: Multi-center case-cohort study in 5 tertiary and 3 secondary care hospitals involving 10410 subjects who underwent routine chest CT for non-cardiovascular reasons. 493 cardiovascular hospitalizations or deaths were recorded during an average follow-up time of 17.8 months. 1191 patients were randomly sampled to serve as a control subcohort. Hazard ratios and annualized event rates were calculated. RESULTS: Abnormalities in the lung (26-44%), pleura (14-15%) and mediastinum (20%) were common. Hazard ratios after adjustment for age and sex were for airway wall thickening 2.26 (1.59-3.22), ground glass opacities 2.50 (1.72-3.62), consolidations 1.97 (1.12-3.47), pleural effusions 2.77 (1.81-4.25) and lymph-nodes 2.04 (1.40-2.96). Corresponding annual event rates were 5.5%, 6.0%, 3.8%, 10.2% and 4.4%. CONCLUSIONS: We have identified several common chest CT findings that are predictive for future risk of cardiovascular events and found that other findings have little utility for this. The added value of the non-vascular predictors to established vascular calcifications on CT remains to be determined.

The association of incidentally detected heart valve calcification with future cardiovascular events.

OBJECTIVES: This study aims to investigate the prognostic value of incidental aortic valve calcification (AVC), mitral valve calcification (MVC) and mitral annular calcification (MAC) for cardiovascular events and non-rheumatic valve disease in particular on routine diagnostic chest CT. METHODS: The study followed a case-cohort design. 10410 patients undergoing chest CT were followed for a median period of 17 months. Patients referred for cardiovascular disease were excluded. A random sample of 1285 subjects and the subjects who experienced an endpoint were graded for valve calcification by three reviewers. Cox-proportional hazard analysis was performed to evaluate the prognostic value. RESULTS: 515 cardiovascular events were ascertained. Compared with patients with no valve calcification, patients with severe AVC, MVC or MAC had respectively 2.03 (1.48-2.78), 2.08 (1.04-4.19) and 1.53 (1.13-2.08) increased risks of experiencing an event during follow-up. For valve endpoints the hazard ratios were respectively 14.57 (5.19-40.53), 8.78 (2.33-33.13) and 2.43 (1.18-4.98). CONCLUSION: Incidental heart valve calcification, detected on routine chest CT is an independent predictor of future cardiovascular events. The study emphasises how incidental imaging findings can contribute to clinical care. It is a step in the process of composing an evidence-based approach in the reporting of incidental subclinical findings.

Cardiovascular disease: prediction with ancillary aortic findings on chest CT scans in routine practice.

PURPOSE: To predict cardiovascular disease (CVD) in a clinical care population by using prevalent subclinical ancillary aortic findings detected on chest computed tomographic (CT) images. MATERIALS AND METHODS: The study was approved by the medical ethics committee of the primary participating facility and the institutional review boards of all other participating centers. From a total of 6975 patients who underwent diagnostic contrast material-enhanced chest CT for noncardiovascular indications, a representative sample population of 817 patients plus 347 patients who experienced a cardiovascular event during a mean follow-up period of 17 months were assigned visual scores for ancillary aortic abnormalities--on a scale of 0-8 for calcifications, a scale of 0-4 for plaques, a scale of 0-4 for irregularities, and a scale of 0-1 for elongation. Four Cox proportional hazard models incorporating different sum scores for the aortic abnormalities plus age, sex, and chest CT indication were compared for discrimination and calibration. The prediction model that performed best was chosen and externally validated. RESULTS: Each aortic abnormality was highly predictive, and all models performed well (c index range, 0.70-0.72; goodness-of-fit P value range, .45-.76). The prediction model incorporating the sum score for aortic calcifications was chosen owing to its good performance (c index, 0.72; goodness-of-fit P = .47) and its applicability to nonenhanced CT scanning. Validation of this model in an external data set also revealed good performance (c index, 0.71; goodness-of-fit P = .25; sensitivity, 46%; specificity, 76%). CONCLUSION: A derived prediction model incorporating ancillary aortic findings detected on routine diagnostic CT images complements established risk scores and may help to identify patients at high risk for CVD. Timely application of preventative measures may ultimately reduce the number or severity of CVD events.

Coronary artery calcification scoring in low-dose ungated CT screening for lung cancer: interscan agreement.

OBJECTIVE: In previous studies detection of coronary artery calcification (CAC) with low-dose ungated MDCT performed for lung cancer screening has been compared with detection with cardiac CT. We evaluated the interscan agreement of CAC scores from two consecutive low-dose ungated MDCT examinations. SUBJECTS AND METHODS: The subjects were 584 participants in the screening segment of a lung cancer screening trial who underwent two low-dose ungated MDCT examinations within 4 months (mean, 3.1 +/- 0.6 months) of a baseline CT examination. Agatston score, volume score, and calcium mass score were measured by two observers. Interscan agreement of stratification of participants into four Agatston score risk categories (0, 1-100, 101-400, > 400) was assessed with kappa values. Interscan variability and 95% repeatability limits were calculated for all three calcium measures and compared by repeated measures analysis of variance. RESULTS: An Agatston score > 0 was detected in 443 baseline CT examinations (75.8%). Interscan agreement of the four risk categories was good (kappa = 0.67). The Agatston scores were in the same risk category in both examinations in 440 cases (75.3%); 578 participants (99.0%) had scores differing a maximum of one category. Furthermore, mean interscan variability ranged from 61% for calcium volume score to 71% for Agatston score (p < 0.01). A limitation of this study was that no comparison of CAC scores between low-dose ungated CT and the reference standard ECG-gated CT was performed. CONCLUSION: Cardiovascular disease risk stratification with low-dose ungated MDCT is feasible and has good interscan agreement of stratification of participants into Agatston score risk categories. High mean interscan variability precludes the use of this technique for monitoring CAC scores for individual patients.