ArticleScientific reports2020
The correlation of deep learning-based CAD-RADS evaluated by coronary computed tomography angiography with breast arterial calcification on mammography.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 40 citations in OpenAlex.
- Automated assessment of breast arterial calcification: a new frontier in cardiovascular risk prediction.Frontiers in cardiovascular medicine · 2026Review
- Relationship between the prevalence of breast arterial calcifications on mammography and coronary calcifications on Chest CT: A cross-sectional study.Saudi medical journal · 2025Article
- Breast Arterial Calcifications on Mammography: A Review of the Literature.Journal of breast imaging · 2025Review
- The impact of breast cancer radiation therapy exposure on the prevalence of breast arterial calcification.The British journal of radiology · 2024Article
- Computed Tomography Evaluation of Coronary Atherosclerosis: The Road Travelled, and What Lies Ahead.Diagnostics (Basel, Switzerland) · 2024Review
- Does the absence of breast arterial calcification (BAC 0) rule out severe coronary artery disease? A computed tomography angiography study.American journal of preventive cardiology · 2024Article
- Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?Current atherosclerosis reports · 2024Review
- Association between coronary artery disease and clinical outcome in cancer patients: A propensity score matching analysis.Heliyon · 2024Article
- Value of dynamic contrast-enhanced magnetic resonance imaging in combination with mammography for screening early-stage breast cancer.African health sciences · 2023Article
- Comparison of prognostic value between CAD-RADS 1.0 and CAD-RADS 2.0 evaluated by convolutional neural networks based CCTA.Heliyon · 2023Article
- Role and progress of artificial intelligence in radiodiagnosing vascular calcification: a narrative review.Annals of translational medicine · 2023Review
- Article
- Breast arterial calcification rates in a diverse, urban group of screening mammography patients.Annals of epidemiology · 2022Article
- Automated detection of enlarged extraocular muscle in Graves' ophthalmopathy with computed tomography and deep neural network.Scientific reports · 2022Observational
- Tomographic Ultrasound Imaging in the Diagnosis of Breast Tumors under the Guidance of Deep Learning Algorithms.Computational intelligence and neuroscience · 2022Article
- Prognostic value of CAD-RADS classification by coronary CTA in patients with suspected CAD.BMC cardiovascular disorders · 2021Article
- Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.BioMed research international · 2020Review
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study sought to evaluate the association of breast arterial calcification (BAC) on breast screening mammography with the Coronary Artery Disease-Reporting and Data System (CAD-RADS) based on Deep Learning-coronary computed tomography angiography (CCTA). This prospective single institution study included asymptomatic women over 40 who underwent CCTA and breast cancer screening mammography between July 2018 and April 2019. CAD-RADS was scored based on Deep Learning (DL). Mammograms were assessed visually for the presence of BAC. A total of 213 patients were included in the analysis. In comparison to the low CAD-RADS (CAD-RADS < 3) group, the high CAD-RADS (CAD-RADS ≥ 3) group, more often had a history of hypertension (P = 0.036), diabetes (P = 0.017), and chronic kidney disease (P = 0.006). They also had a significantly higher level of LDL-C (P = 0.024), while HDL-C was lower than in the low CAD-RADS group (P = 0.003). BAC was also significantly higher in the high CAD-RADS group (P = 0.002). In multivariate analysis, the presence of BAC [odd ratio (OR) 10.22, 95% CI 2.86-36.49, P < 0.001] maintained a significant associations with CAD-RADS after adjustment by meaningful variable. The same tendency was also found after adjustment by all covariates. There was a significant correlation between the severities of CAD detected by DL based CCTA and BAC in women undergoing breast screening mammography. BAC may be used as an additional diagnostic tool to predict the severity of CAD in this population.
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