Deep learning for automatic calcium scoring in population based cardiovascular screening
Authors
Marleen Vonder, Sunyi Zheng, Monique D Dorrius, Carlijn van der Aalst, Harre de Koning, Jaeyoun Yi, Donghoon Yu, Jan-Willen C. Gratama, Dirkjan Kuijpers, Matthijs Oudkerk
The deep learning-based software, AVIEW CAC from CORELINE Soft, demonstrated excellent performance in a population-based screening setting for risk categorization in asymptomatic participants. The study suggested that future deep learning software with the ability to assign uncertain cases for manual human feedback could improve calcium scoring and outperform experienced readers using manual scoring alone. However, the study's limitations include its focus on a cardiac screening setting with a highly standardized protocol, which may limit the generalizability of the results to clinical settings with different populations and scanner settings. In conclusion, the deep learning-based software can accurately categorize risk and initiate preventive treatment in a cardiovascular CT screening setting.