Automated AI-based coronary calcium scoring using retrospective CT data from SCAPIS is accurate and correlates with expert scoring
Question Can AI function as a tool for enhancing the efficiency and accuracy of Coronary Artery Calcium Score (CACS) evaluations in clinical radiology practice? Findings This study confirms the robustness of AI-derived CACS results across extensive datasets, though its generalizability is limited by data acquisition from a single CT system. Clinical relevance This study suggests that AI holds significant promise as a tool for enhancing the efficiency and accuracy of CACS evaluations, with implications for improving patient diagnostics and reducing radiologist workload in clinical practice.
Authors
- Anders Persson (ORCID: https://orcid.org/0000-0002-9446-6981)
- Patrik Nowik (ORCID: https://orcid.org/0000-0001-5575-7797)
- Lilian Henriksson (ORCID: https://orcid.org/0000-0001-5485-6769)
- Mårten Sandstedt (ORCID: https://orcid.org/0000-0002-0973-9499)
Institutions
- Linköping University (SE)
- Karolinska Institutet (SE)
- Siemens (Sweden) (SE)
Publication Details
- Journal
- European Radiology
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1007/s00330-024-11118-3
- Citations
- 4
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Linköpings Universitet