Artificial Intelligence-Assisted Low-Dose High Atomic Number Contrast Agent for Ultrahigh-Resolution Computed Tomography Angiography
Achieving high resolution while minimizing contrast agent dosage remains a key goal, yet a major challenge in contrast-enhanced computed tomography (CT) imaging. Herein, we propose an artificial intelligence-assisted low-dose high atomic number contrast agent for ultrahigh-resolution CT imaging. As a proof of concept, high-quality PEGylated hafnium oxide nanoparticles (DA-HfO<sub>2</sub> NPs) are synthesized, exhibiting superior X-ray attenuation, high hafnium content (36%), excellent water solubility, appropriate hydrodynamic size (13.5 nm), and prolonged circulation half-life (161.9 min). High-dose DA-HfO<sub>2</sub> NPs enable extended ultrahigh-resolution vascular imaging with a spatial resolution of 0.15 mm and a time window of at least 60 min. More importantly, by integrating artificial intelligence, the low-dose contrast agent (at 25% of the standard dose) achieves imaging quality comparable to that of the high-dose agent in both contrast density and spatial resolution, while simultaneously enhancing biosafety. This strategy enables high-resolution imaging at reduced contrast agent doses and offers a promising approach for sensitive and safe CT angiography.
Authors
- Gang Shu (ORCID: https://orcid.org/0000-0002-3769-0012)
- Houde Wu (ORCID: https://orcid.org/0000-0003-1041-3688)
- Shao‐Kai Sun (ORCID: https://orcid.org/0000-0001-6136-9969)
- Xiaoyi Wang (ORCID: https://orcid.org/0000-0001-5766-0876)
- Xinxing Li (ORCID: https://orcid.org/0000-0002-8329-3587)
- Li Guo (ORCID: https://orcid.org/0000-0001-9377-7107)
- Shujie Li (ORCID: https://orcid.org/0009-0005-8823-9634)
Institutions
- Tianjin Medical University Cancer Institute and Hospital (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- ACS Nano
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1021/acsnano.5c12047
- Citations
- 4
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.70