Breast Arterial Calcification: a Novel Cardiovascular Risk Enhancer Among Postmenopausal Women

Does the absence of breast arterial calcification (BAC 0) rule out severe coronary artery disease? A computed tomography angiography study

Background

Cardiovascular risk (CV)-stratification in females is challenging, and current models miss a high proportion at-risk. Breast arterial calcifications (BAC) are independent prognosticators, but their interaction with the coronary artery disease profile by computed tomography (CT) is controverse, and the role of BAC 0 unclear.

Objective

to investigate the interaction of BAC with coronary CT outcomes (CAC score, coronary stenosis severity and high-risk plaque (HRP).

Methods

Consecutive patients referred to mammography (MG) and coronary CTA for clinical indications within 1 year were included. Three different age groups were compared (<55 years;55-65 years;>65 years).

Results

443 patients were included. There were significant age differences for the prevalence of BAC 0 (p<0.001), BAC 0/CAC>300 AU (p=0.0023) and obstructive disease (>50% stenosis)(p=0.0048) but not for high-risk-plaque (HRP)(p=0.4905). High CAC (>300 AU) was present in only 0.82% of females with BAC 0 in less than 55 year, but significantly more often in those above 65 years (p=0.0004;OR=16.58:95% CI: 2.829-361.7) and 55 years with 12.1% and 8.4%. Obstructive coronary disease (>50% stenosis) in BAC 0 was present in 18.2%; with age-dependent differences (10.7% vs 14.7% vs 29.9%) (p=0.0003). The correlation between BAC, CAC and CADRADS was weak (r=0.246 and r=0.243, p<0.001). There was no association of BAC with HRP.

Conclusion

BAC 0 rules out severe CAC >300AU in females <55 years only, but not in those above 55 years- with adherent implications for primary prevention. However, BAC 0 does not to rule out obstructive disease and high-risk plaques in symptomatic patients among all age groups.

Breast calcifications on mammography from systemic amyloidosis: A case report

Calcifications on mammography from systemic disease at times meet diagnostic criteria for histologic sampling to exclude malignancy. We present a case of bilateral groups of new calcifications on mammography that yielded amyloidosis on core biopsy. Awareness of our patient's known diagnosis of systemic light chain amyloidosis (AL) prompted use of Congo red staining to confirm the histologic diagnosis. Knowledge of systemic diseases with possible manifestations on mammography can facilitate cogent and clinically relevant radiology-pathology correlation.

Deep transfer learning for detection of breast arterial calcifications on mammograms: a comparative study

INTRODUCTION

Breast arterial calcifications (BAC) are common incidental findings on routine mammograms, which have been suggested as a sex-specific biomarker of cardiovascular disease (CVD) risk. Previous work showed the efficacy of a pretrained convolutional network (CNN), VCG16, for automatic BAC detection. In this study, we further tested the method by a comparative analysis with other ten CNNs.

MATERIAL AND METHODS

Four-view standard mammography exams from 1,493 women were included in this retrospective study and labeled as BAC or non-BAC by experts. The comparative study was conducted using eleven pretrained convolutional networks (CNNs) with varying depths from five architectures including Xception, VGG, ResNetV2, MobileNet, and DenseNet, fine-tuned for the binary BAC classification task. Performance evaluation involved area under the receiver operating characteristics curve (AUC-ROC) analysis, F1-score (harmonic mean of precision and recall), and generalized gradient-weighted class activation mapping (Grad-CAM++) for visual explanations.

RESULTS

The dataset exhibited a BAC prevalence of 194/1,493 women (13.0%) and 581/5,972 images (9.7%). Among the retrained models, VGG, MobileNet, and DenseNet demonstrated the most promising results, achieving AUC-ROCs > 0.70 in both training and independent testing subsets. In terms of testing F1-score, VGG16 ranked first, higher than MobileNet (0.51) and VGG19 (0.46). Qualitative analysis showed that the Grad-CAM++ heatmaps generated by VGG16 consistently outperformed those produced by others, offering a finer-grained and discriminative localization of calcified regions within images.

CONCLUSION

Deep transfer learning showed promise in automated BAC detection on mammograms, where relatively shallow networks demonstrated superior performances requiring shorter training times and reduced resources.

RELEVANCE STATEMENT

Deep transfer learning is a promising approach to enhance reporting BAC on mammograms and facilitate developing efficient tools for cardiovascular risk stratification in women, leveraging large-scale mammographic screening programs.

KEY POINTS

• We tested different pretrained convolutional networks (CNNs) for BAC detection on mammograms. • VGG and MobileNet demonstrated promising performances, outperforming their deeper, more complex counterparts. • Visual explanations using Grad-CAM++ highlighted VGG16's superior performance in localizing BAC.

Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice: JACC State-of-the-Art Review

Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice and research. The exponential rise in technology powered by AI is defining new frontiers in cardiovascular care, with innovations that span novel diagnostic modalities, new digital native biomarkers of disease, and high-performing tools evaluating care quality and prognosticating clinical outcomes. These digital innovations promise expanded access to cardiovascular screening and monitoring, especially among those without access to high-quality, specialized care historically. Moreover, AI is propelling biological and clinical discoveries that will make future cardiovascular care more personalized, precise, and effective. The review brings together these diverse AI innovations, highlighting developments in multimodal cardiovascular AI across clinical practice and biomedical discovery, and envisioning this new future backed by contemporary science and emerging discoveries. Finally, we define the critical path and the safeguards essential to realizing this AI-enabled future that helps achieve optimal cardiovascular health and outcomes for all.

Polygenic risk and incident coronary heart disease in a large multiethnic cohort

Objective

Many studies support the notion that polygenic risk scores (PRS) improve risk prediction for coronary heart disease (CHD) beyond conventional risk factors. However, PRS are not yet considered risk-enhancing factor in guidelines. Our objective was to determine the predictive performance of a commercially available PRS (CARDIO inCode-Score®) compared with the Pooled Cohorts Equations (PCE) in a contemporary, multi-ethnic cohort.

Methods

Participants (n = 63,070; 67 % female; 18 % non-European) without prior CHD were followed from 2007 through 12/31/2022. The association between the PRS and incident CHD was assessed using Cox regression adjusting for genetic ancestry and risk factors. Event rates were estimated by categories of PCE and by low/intermediate/high genetic risk within PCE categories; risk discrimination and net reclassification improvement (NRI) were also assessed.

Results

There were 3,289 incident CHD events during 14 years of follow-up. Adjusted hazard ratio (aHR) for incident CHD per 1 SD increase in PRS was 1.18 (95 % CI:1.14-1.22), and the aHR for the upper vs lower quintile of the PRS was 1.66 (95 % CI:1.49-1.86). The association was consistent in both sexes, in European participants compared with all minority groups combined and was strongest in the first 5 years of follow-up. The increase in the C-statistic was 0.004 (0.747 vs. 0.751; p < 0.0001); the NRI was 2.4 (0.9-3.8) for the entire cohort and 9.7 (7.5-12.0) for intermediate PCE risk individuals. After incorporating high genetic risk, a further 10 percent of participants at borderline/intermediate PCE risk would be candidates for statin therapy.

Conclusion

Inclusion of polygenic risk improved identification of primary prevention individuals who may benefit from more intensive risk factor modification.

Assessing breast arterial calcification in mammograms and its implications for atherosclerotic cardiovascular disease risk

PURPOSE

Breast arterial calcifications (BAC) are incidentally observed on mammograms, yet their implications remain unclear. We investigated lifestyle, reproductive, and cardiovascular determinants of BAC in women undergoing mammography screening. Further, we investigated the relationship between BAC, coronary arterial calcifications (CAC) and estimated 10-year atherosclerotic cardiovascular (ASCVD) risk.

METHODS

In this cross-sectional study, we obtained reproductive history and CVD risk factors from 215 women aged 18 or older who underwent mammography and cardiac computed tomographic angiography (CCTA) within a 2-year period between 2007 and 2017 at hospital. BAC was categorized as binary (present/absent) and semi-quantitatively (mild, moderate, severe). CAC was determined using the Agatston method and recorded as binary (present/absent). Adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated, accounting for age as a confounding factor. ASCVD risk over a 10-year period was calculated using the Pooled Cohort Risk Equations.

RESULTS

Older age, systolic and diastolic blood pressures, higher parity, and younger age at first birth (≤28 years) were significantly associated with greater odds of BAC. Women with both BAC and CAC had the highest estimated 10-year risk of ASCVD (13.30 %). Those with only BAC (8.80 %), only CAC (5.80 %), and no BAC or CAC (4.40 %) had lower estimated 10-year risks of ASCVD. No association was detected between presence of BAC and CAC.

CONCLUSIONS

These findings support the hypothesis that BAC on a screening mammogram may help to identify women at potentially increased risk of future cardiovascular disease without additional cost and radiation exposure.

Understanding the spectrum of cardiovascular risk in women - A primer for prevention

Cardiovascular disease (CVD) is the leading cause of death in women worldwide and the lifetime risk of CVD in women is similar to men. However, the pathophysiology of CVD varies between women and men necessitating a sex-specific understanding of cardiovascular (CV) risk. A belief that women have a lower CVD risk than men, and an underrepresentation in clinical research for many years has led to a paucity of evidence in the prevention and management of CVD in women. Many recent efforts have tried to bridge the gap. As a result, we now know that traditional risk factors impact CVD risk differently in women when compared with men. There are also numerous sex-specific and pregnancy related risk factors that modify the risk and can predict the future development of CVD in women. This is important as risk calculators, in general, tend to misclassify risk in young women with nontraditional CVD risk factors. To address this, guidelines have introduced the concept of risk enhancers that can suggest a higher risk. The use of coronary artery calcium score can further accurately delineate risk in these women, leading to an appropriate matching of therapy to underlying risk. This review discusses implementation strategies that are essential to mitigate disparities in CVD outcomes and optimizing CVD risk in women.

Mammography-based deep learning model for coronary artery calcification

AIMS

Mammography, commonly used for breast cancer screening in women, can also predict cardiovascular disease. We developed mammography-based deep learning models for predicting coronary artery calcium (CAC) scores, an established predictor of coronary events.

METHODS AND RESULTS

We evaluated a subset of Korean adults who underwent image mammography and CAC computed tomography and randomly selected approximately 80% of the participants as the training dataset, used to develop a convolutional neural network (CNN) to predict detectable CAC. The sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), and overall accuracy of the model's performance were evaluated. The training and validation datasets included 5235 and 1208 women, respectively [mean age, 52.6 (±10.2) years], including non-zero cases (46.8%). The CNN-based deep learning prediction model based on the Resnet18 model showed the best performance. The model was further improved using contrastive learning strategies based on positive and negative samples: sensitivity, 0.764 (95% CI, 0.667-0.830); specificity, 0.652 (95% CI, 0.614-0.710); AUROC, 0.761 (95% CI, 0.742-0.780); and accuracy, 70.8% (95% CI, 68.8-72.4). Moreover, including age and menopausal status in the model further improved its performance (AUROC, 0.776; 95% CI, 0.762-0.790). The Framingham risk score yielded an AUROC of 0.736 (95% CI, 0.712-0.761).

CONCLUSION

Mammography-based deep learning models showed promising results for predicting CAC, performing comparably to conventional risk models. This indicates mammography's potential for dual-risk assessment in breast cancer and cardiovascular disease. Further research is necessary to validate these findings in diverse populations, with a particular focus on representation from national breast screening programmes.

Cardiovascular Imaging in Women

Multimodality cardiovascular imaging is a cornerstone diagnostic tool in the diagnosis, risk stratification, and management of cardiovascular diseases, whether those involving the coronary tree, myocardial, or pericardial diseases in general and particularly in women. This manuscript aims to shed some light and summarize the very features of cardiovascular disease in women, explore their unique characteristics and discuss the role of cardiovascular imaging in ischemic heart disease and cardiomyopathies. The role of four imaging modalities will be discussed including nuclear medicine, echocardiography, noninvasive coronary angiography, and cardiac magnetic resonance.

Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach

OBJECTIVE

Breast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification.

METHODS

In this retrospective study, four readers labelled four-view mammograms as BAC positive (BAC+) or BAC negative (BAC-) at image level. Starting from a pretrained VGG16 model, we trained a convolutional neural network to discriminate BAC+ and BAC- mammograms. Accuracy, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) were used to assess the diagnostic performance. Predictions of calcified areas were generated using the generalized gradient-weighted class activation mapping (Grad-CAM++) method, and their correlation with manual measurement of BAC length in a subset of cases was assessed using Spearman ρ.

RESULTS

A total 1493 women (198 BAC+) with a median age of 59 years (interquartile range 52-68) were included and partitioned in a training set of 410 cases (1640 views, 398 BAC+), validation set of 222 cases (888 views, 89 BAC+), and test set of 229 cases (916 views, 94 BAC+). The accuracy, F1 score, and AUC-ROC were 0.94, 0.86, and 0.98 in the training set; 0.96, 0.74, and 0.96 in the validation set; and 0.97, 0.80, and 0.95 in the test set, respectively. In 112 analyzed views, the Grad-CAM++ predictions displayed a strong correlation with BAC measured length (ρ = 0.88, p < 0.001).

CONCLUSION

Our model showed promising performances in BAC detection and in quantification of BAC burden, showing a strong correlation with manual measurements.

CLINICAL RELEVANCE STATEMENT

Integrating our model to clinical practice could improve BAC reporting without increasing clinical workload, facilitating large-scale studies on the impact of BAC as a biomarker of cardiovascular risk, raising awareness on women's cardiovascular health, and leveraging mammographic screening.

KEY POINTS

• We implemented a deep convolutional neural network (CNN) for BAC detection and quantification. • Our CNN had an area under the receiving operator curve of 0.95 for BAC detection in the test set composed of 916 views, 94 of which were BAC+ . • Furthermore, our CNN showed a strong correlation with manual BAC measurements (ρ = 0.88) in a set of 112 views.

An Opportunity to Seize From Low Hanging Fruits: Capitalising on Incidentally Reported Coronary Artery Calcification

AIM

We investigated the prevalence of incidental coronary artery calcifications (CAC) from non-electrocardiogram (ECG)-gated computed tomography (CT) chest (both contrast and non-contrast) for inpatients. We also assessed for downstream investigation and statin prescription from the inpatient teams. Incidental CAC are frequent findings on non-ECG-gated CT chest. It is associated with adverse prognosis in multiple patient cohorts.

METHOD

All non-ECG-gated CT chest done as inpatients from a single centre referred from 1 January 2022 to 31 December 2022 with reported incidental CAC were reviewed for inclusion. Patients who had a history of known coronary artery disease, history of coronary stent or bypass, and presence of cardiac devices were excluded.

RESULTS

Total of 123 patients were included, making the prevalence 6.2% (123/1,980). The median age is 76 years (interquartile range 69-85) and predominantly male at 54.5%. The majority of CT chest done were contrasted scans (91.1%). Only 26.8% of CAC were reported on severity with visual quantification, with 7.3% each reported for both moderate and severe CAC. Only 2.4% of CAC were reported in the conclusion of the CT report. Most of these patients were asymptomatic (34.1%). A total of 20.3% of patients had further tests done. Inpatient hospital mortality was 8.1%. About 23.6% and 34.1% of patients were on aspirin and statin therapy respectively at baseline. There was only 1 patient (1.2%) who was prescribed with new statin therapy on discharge.

CONCLUSION

Incidental CAC is prevalent in inpatient settings and remains under-recognised by ordering clinicians, with low prescription rate of statin therapy. Practice-changing measures to standardise reporting of incidental CAC is needed to identify patients with subclinical coronary disease and initiate preventive interventions.

Sex, Racial, and Ethnic Disparities in Acute Coronary Syndrome: Novel Risk Factors and Recommendations for Earlier Diagnosis to Improve Outcomes

In this review, sex, racial, and ethnic differences in acute coronary syndromes on a global scale are summarized. The relationship between disparities in presentation and management of acute coronary syndromes and effect on worse clinical outcomes in acute coronary syndromes are discussed. The effect of demographic, geographic, racial, and ethnic factors on acute coronary syndrome care disparities are reviewed. Differences in risk factors including systemic inflammatory disorders and pregnancy-related factors and the pathophysiology underlying them are discussed. Finally, breast arterial calcification and coronary calcium scoring are discussed as methods to detect subclinical atherosclerosis and start early treatment in an attempt to prevent clinical disease.

Correlation Between Breast Arterial Calcifications and Higher Cardiovascular Risk: Awareness and Attitudes Amongst Canadian Radiologists Who Report Mammography

Background: Breast arterial calcification (BAC) on mammography correlates with increased cardiovascular risk. Reporting BAC is not standard practice. Our study evaluates the awareness of Canadian radiologists who report mammography of the clinical significance of BAC and their attitudes towards reporting BAC compared to their European and American counterparts. Methods: Following local institutional ethics approval, a 25 question survey (SurveyMonkey) was disseminated to Canadian radiologists via provincial and national society email lists. Responses were collected over 5 weeks (April-June 2022). Results: One hundred and eighty-six complete responses were collected. Sixty percent (112/186) were aware of the association between BAC and cardiovascular risk and 16% (29/186) document its presence in mammogram reports. Thirty five percent (65/186) occasionally document BAC if severe or in a young patient. Four percent (7/186) had local departmental guidelines on BAC reporting and 82% (153/186) agreed there is a need for national BAC reporting guidelines. Fewer Canadian radiologists were aware of the association between BAC and cardiovascular risk compared to European radiologists (60% vs 81%), report the presence of BAC compared to both European (15% vs 62%) and American (15% vs 35%) radiologists, and inform the patient of the presence of BAC compared to European radiologists (1% vs 46%). Conclusion: Canadian radiologists who report mammography were less aware of the association between BAC and cardiovascular risk than their European and American counterparts and were less likely to document the presence of BAC. Given the correlation of BAC with increased cardiovascular event risk, there is increased need for awareness as well as national BAC reporting guidelines.

Associations of Breast Arterial Calcifications with Cardiovascular Disease

Cardiovascular diseases (CVD), including coronary artery disease (CAD), continue to be the leading cause of global mortality among women. While traditional CVD/CAD prevention tools play a significant role in reducing morbidity and mortality among both men and women, current tools for preventing CVD/CAD rely on traditional risk factor-based algorithms that often underestimate CVD/CAD risk in women compared with men. In recent years, some studies have suggested that breast arterial calcifications (BAC), which are benign calcifications seen in mammograms, may be linked to CVD/CAD. Considering that millions of women older than 40 years undergo annual screening mammography for breast cancer as a regular activity, innovative risk prediction factors for CVD/CAD involving mammographic data could offer a gender-specific and convenient solution. Such factors that may be independent of, or complementary to, current risk models without extra cost or radiation exposure are worthy of detailed investigation. This review aims to discuss relevant studies examining the association between BAC and CVD/CAD and highlights some of the issues related to previous studies' design such as sample size, population types, method of assessing BAC and CVD/CAD, definition of cardiovascular events, and other confounding factors. The work may also offer insights for future CVD risk prediction research directions using routine mammograms and radiomic features other than BAC such as breast density and macrocalcifications.

The association between breast arterial calcification and atherosclerotic cardiovascular disease in an Australian population-based breast cancer case-control study

PURPOSE

Atherosclerotic cardiovascular disease (ASCVD) is a major cause of morbidity and mortality. Breast arterial calcification (BAC) on mammograms is not associated with breast cancer risk. However, there is increasing evidence supporting its association with cardiovascular disease (CVD). This study examines the association between BAC and ASCVD and their risk factors within an Australian population-based breast cancer study.

MATERIALS AND METHODS

Data from the controls who participated in the breast cancer environment and employment study (BCEES) were linked with the Western Australian Department of Health Hospital Morbidity database and Mortality Registry to obtain ASCVD outcomes and related risk factor data. Mammograms from participants with no prior history of ASCVD were assessed for BAC by a radiologist. Cox proportional hazards regression was used to examine the association between BAC and later occurrence of an ASCVD event. Logistic regression was used to investigate the factors associated with BAC.

RESULTS

A total of 1020 women with a mean age of 60 (sd = 7.0 years) were included and BAC found in 184 (18.0%). Eighty (7.8%) of the 1020 participants developed ASCVD, with an average time to event of 6.2 years (sd = 4.6) from baseline. In univariate analysis, participants with BAC were more likely to have an ASCVD event (HR = 1.96 95% CI 1.29-2.99). However, after adjusting for other risk factors, this association attenuated (HR = 1.37 95% CI 0.88-2.14). Increasing age (OR = 1.15, 95% CI 1.12-1.19) and parity (p_LRT < 0.001) were associated with BAC.

CONCLUSION

BAC is associated with increased ASCVD risk, but this is not independent of cardiovascular risk factors.

Mammography biomarkers of cardiovascular and musculoskeletal health: A review

Breast density (BD) and breast arterial calcifications (BAC) can expand the role of mammography. In premenopause, BD is related to body fat composition: breast adipose tissue and total volume are potential indicators of fat storage in visceral depots, associated with higher risk of cardiovascular disease (CVD). Women with fatty breast have an increased likelihood of hypercholesterolemia. Women without cardiometabolic diseases with higher BD have a lower risk of diabetes mellitus, hypertension, chest pain, and peripheral vascular disease, while those with lower BD are at increased risk of cardiometabolic diseases. BAC, the expression of Monckeberg sclerosis, are associated with CVD risk. Their prevalence, 13 % overall, rises after menopause and is reduced in women aged over 65 receiving hormonal replacement therapy. Due to their distinct pathogenesis, BAC are associated with hypertension but not with other cardiovascular risk factors. Women with BAC have an increased risk of acute myocardial infarction, ischemic stroke, and CVD death; furthermore, moderate to severe BAC load is associated with coronary artery disease. The clinical use of BAC assessment is limited by their time-consuming manual/visual quantification, an issue possibly solved by artificial intelligence-based approaches addressing BAC complex topology as well as their large spectrum of extent and x-ray attenuations. A link between BD, BAC, and osteoporosis has been reported, but data are still inconclusive. Systematic, standardised reporting of BD and BAC should be encouraged.

Relationship between Arterial Calcifications on Mammograms and Cardiovascular Events: A Twenty-Three Year Follow-Up Retrospective Cohort Study

PURPOSE

Breast arterial calcifications (BAC) have been associated with cardiovascular diseases. We aimed to examine whether the presence of BAC could predict the development of cardiovascular events in the very long term, as evidence has suggested.

PATIENTS AND METHODS

We conducted a 23-year follow-up retrospective cohort study considering women specifically studied for breast cancer. After reviewing the mammograms of 1759 women, we selected 128 patients with BAC and an equal number of women without BAC.

RESULTS

Women with BAC had higher relative risk (RR) for cardiovascular events, globally 1.66 (95% CI): 1.31-2.10 vs. 0.53 (0.39-0.72), and individually for ischemic heart disease 3.25 (1.53-6.90) vs. 0.85 (0.77-0.94), hypertensive heart disease 2.85 (1.59-5.09) vs. 0.79 (0.69-0.89), valvular heart disease 2.19 (1.28-3.75) vs. 0.83 (0.73-0.94), congestive heart failure 2.06 (1.19-3.56) vs. 0.85 (0.75-0.96), peripheral vascular disease 2.8 (1.42-5.52) vs. 0.85 (0.76-0.94), atrial fibrillation 1.83 (1.09-3.08) vs. 0.86 (0.76-0.98), and lacunar infarction 2.23 (1.21-4.09) vs. 0.86 (0.77-0.96). Cox's multivariate analysis, also considering classical risk factors, indicated that this BAC was significantly and independently associated with survival (both cardiovascular event-free and specific survival; 1.94 (1.38-2.73) and 6.6 (2.4-18.4)).

CONCLUSIONS

Our data confirm the strong association of BAC on mammograms and the development cardiovascular events, but also evidence the association of BAC with cardiovascular event-free and specific survival.

High-sensitivity troponin I is associated with cardiovascular outcomes but not with breast arterial calcification among postmenopausal women

Background

Prior studies support the utility of high sensitivity troponin I (hsTnI) for cardiovascular disease (CVD) risk stratification among asymptomatic populations; however, only two prior studies examined women separately. The association between hsTnI and breast arterial calcification is unknown.

Methods

Cohort study of 2896 women aged 60-79 years recruited after attending mammography screening between 10/2012 and 2/2015. BAC status (presence versus absence) and quantity (calcium mass mg) was determined using digital mammograms. Pre-specified endpoints were incident coronary heart disease (CHD), ischemic stroke, heart failure and its subtypes and all CVD.

Results

After 7.4 (SD = 1.7) years of follow-up, 51 CHD, 30 ischemic stroke and 46 heart failure events were ascertained. At a limit of detection of 1.6 ng/L, 98.3 of the cohort had measurable hsTnI concentration. HsTnI in the 4-10 ng/L range were independently associated of CHD (adjusted hazard ratio[aHR] = 2.78; 95% CI, 1.48-5.22; p = 0.002) and all CVD (aHR = 2.06; 95% CI, 1.37-3.09; p = 0.0005) and hsTnI over 10 ng/L was independently associated with CHD (aHR = 4.75; 95% CI, 1.83-12.3; p = 0.001), ischemic stroke (aHR = 3.81; 95% CI, 1.22-11.9; p = 0.02), heart failure (aHR = 3.29; 95% CI, 1.33-8.13; p = 0.01) and all CVD (aHR = 4.78; 95% CI, 2.66-8.59; p < 0.0001). No significant association was found between hsTnI and BAC. Adding hsTnI to a model containing the Pooled Cohorts Equation resulted in significant and clinical important improved calibration, discrimination (Δ C_index = 6.5; p = 0.02) and reclassification (bias-corrected clinical NRI = 0.18; 95% CI, -0.13-0.49 after adding hsTnI categories).

Conclusions

Our results support the consideration of hsTnI as a risk enhancing factor for CVD in asymptomatic women that could drive preventive or therapeutic decisions.

Extra-coronary Calcification and Cardiovascular Events: What Do We Know and Where Are We Heading?

PURPOSE OF REVIEW

The coronary artery calcium score is a guideline-endorsed aid for further risk stratification in the primary prevention of atherosclerotic cardiovascular disease. The non-contrast scan performed for detection of coronary artery calcium also gives an opportunity to visualize calcifications in the thoracic aorta and in the heart valves, at no additional cost or radiation exposure. The purpose of this review was to discuss the potential clinical value of measuring thoracic aortic calcification, aortic valve calcification, and mitral annulus calcification.

RECENT FINDINGS

After two decades of active research, all three calcifications have been extensively evaluated, across various cohorts. We discuss classic and recent studies, current knowledge gaps, and future directions in this space. The added value of these measurements has traditionally been considered modest at best, and they are not currently discussed in relevant primary prevention guidelines in North America and Europe. However, recent studies evaluating high thoracic calcification thresholds and younger populations have further enriched this space. Specifically, some studies suggest that detection of severe thoracic aortic calcification may be helpful in further risk assessment and that detection of aortic valve calcifications may have important prognostic implications in younger individuals. Although more research is needed, particularly in larger young-to-middle-aged cohorts, future guidelines might consider including these features as risk-enhancing factors.