Bolus tracking from pulsed x‐ray projections: A feasibility study using a five‐dimensional cardiac CT contrast dynamics model
In this study, we proposed an innovative real-time way to predict the contrast bolus peak in cardiac CT as well as an innovative approach to train a neural network using virtual but clinically realistic data. Our trained network successfully estimated the shape of the time-intensity curve for the target chambers, which led to accurate bolus peak time estimation. This technique could be used for autonomous diagnostic cardiac CT to trigger a diagnostic scan for optimal contrast enhancement.
Authors
- Ivo G.H. Jansen (ORCID: https://orcid.org/0000-0002-8862-1877)
- Jed D. Pack (ORCID: https://orcid.org/0000-0003-3232-1012)
- Elliot R. McVeigh (ORCID: https://orcid.org/0000-0003-1684-2432)
- Eri Haneda (ORCID: https://orcid.org/0000-0003-2660-9028)
- Pengwei Wu (ORCID: https://orcid.org/0000-0002-2412-3043)
- Albert Hsiao (ORCID: https://orcid.org/0000-0002-9412-1369)
- Bruno De Man (ORCID: https://orcid.org/0000-0001-7250-3406)
Institutions
- University of California San Diego (US)
- GE Global Research (United States) (US)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1002/mp.17464
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute