Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography
Minimizing the radiation and contrast medium dose while maintaining CT image quality is highly desirable. High-strength deep learning iterative reconstruction protocol yielded 42% radiation dose reduction compared to conventional protocol. "Double-low" coronary CTA is feasible with high-strength deep learning reconstruction without compromising image quality in non-obese patients.
Authors
- Luca Pugliese (ORCID: https://orcid.org/0000-0001-9061-7247)
- Tiziano Polidori (ORCID: https://orcid.org/0000-0002-4633-6760)
- Andrea Laghi (ORCID: https://orcid.org/0000-0002-3091-7819)
- Giuseppe Tremamunno (ORCID: https://orcid.org/0000-0001-6484-9765)
- Giovanna Grazia Bona
- Domenico De Santis (ORCID: https://orcid.org/0000-0002-1197-456X)
- Antonella Del Gaudio (ORCID: https://orcid.org/0000-0001-6017-8976)
- Damiano Caruso (ORCID: https://orcid.org/0000-0001-9285-4764)
- Marta Zerunian (ORCID: https://orcid.org/0000-0003-4635-7999)
- Curzio Santangeli (ORCID: https://orcid.org/0009-0004-4364-783X)
Institutions
- Sapienza University of Rome (IT)
Publication Details
- Journal
- European Radiology
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1007/s00330-024-11059-x
- Citations
- 19
- Primary Topic
- Radiation Dose and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 7.68