International AI-Driven Coronary Plaque Risk Stratification Study Opens — Implications for Australian Cardiology Practice

References

1. 1.Centro Cardiologico Monzino. (2024). Rustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS. ClinicalTrials.gov. NCT06410690. https://clinicaltrials.gov/study/NCT06410690
2. 2.Kolossváry, M., Kellermayer, M., Merkely, B., & Maurovich-Horvat, P. (2019). Cardiac computed tomography radiomics: a comprehensive review on radiomic techniques. Journal of Thoracic Imaging, 34(1), 26-34. https://doi.org/10.1097/RTI.0000000000000394
3. 3.Oikonomou, E. K., Williams, M. C., Kotanidis, C. P., Desai, M. Y., Marwan, M., Antonopoulos, A. S., Thomas, K. E., Thomas, S., Akoumianakis, I., Fan, L. M., Kesavan, S., Herdman, L., Alashi, A., Centeno, E. H., Lyasheva, M., Griffin, B. P., Flamm, S. D., Shirodaria, C., Sabharwal, N., ... Antoniades, C. (2019). A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. European Heart Journal, 40(43), 3529-3543. https://doi.org/10.1093/eurheartj/ehz592
4. 4.Commandeur, F., Goeller, M., Betancur, J., Cadet, S., Doris, M., Chen, X., Berman, D. S., Slomka, P. J., Tamarappoo, B. K., & Dey, D. (2018). Deep learning for quantification of epicardial and thoracic adipose tissue from non-contrast CT. IEEE Transactions on Medical Imaging, 37(8), 1835-1846. https://doi.org/10.1109/TMI.2018.2804799
5. 5.Genders, T. S., Steyerberg, E. W., Alkadhi, H., Leschka, S., Desbiolles, L., Nieman, K., Galema, T. W., Meijboom, W. B., Mollet, N. R., de Feyter, P. J., Cademartiri, F., Maffei, E., Dewey, M., Zimmermann, E., Laule, M., Pugliese, F., Barbagallo, R., Sinitsyn, V., Bogaert, J., ... Hunink, M. M. (2011). A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension. European Heart Journal, 32(11), 1316-1330. https://doi.org/10.1093/eurheartj/ehr014
6. 6.Roth, G. A., Mensah, G. A., Johnson, C. O., Addolorato, G., Ammirati, E., Baddour, L. M., Barengo, N. C., Beaton, A. Z., Benjamin, E. J., Benziger, C. P., Bonny, A., Brauer, M., Brodmann, M., Cahill, T. J., Carapetis, J., Catapano, A. L., Chugh, S. S., Cooper, L. T., Coresh, J., ... GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Writing Group. (2020). Global burden of cardiovascular diseases and risk factors, 1990–2019. Journal of the American College of Cardiology, 76(25), 2982-3021. https://doi.org/10.1016/j.jacc.2020.11.010
7. 7.Libby, P., Pasterkamp, G., Crea, F., & Jang, I. K. (2019). Reassessing the mechanisms of acute coronary syndromes. Circulation Research, 124(1), 150-160. https://doi.org/10.1161/CIRCRESAHA.118.311098
8. 8.Knuuti, J., Wijns, W., Saraste, A., Capodanno, D., Barbato, E., Funck-Brentano, C., Prescott, E., Storey, R. F., Deaton, C., Cuisset, T., Agewall, S., Dickstein, K., Edvardsen, T., Escaned, J., Gersh, B. J., Svitil, P., Gilard, M., Hasdai, D., Hatala, R., ... ESC Scientific Document Group. (2020). 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. European Heart Journal, 41(3), 407-477. https://doi.org/10.1093/eurheartj/ehz425