Synthetic post-contrast imaging through artificial intelligence: Clinical applications of virtual and augmented contrast media Review
| Authors: | Pasquini, L.; Napolitano, A.; Pignatelli, M.; Tagliente, E.; Parrillo, C.; Nasta, F.; Romano, A.; Bozzao, A.; Di Napoli, A. |
| Review Title: | Synthetic post-contrast imaging through artificial intelligence: Clinical applications of virtual and augmented contrast media |
| Abstract: | Contrast media are widely diffused in biomedical imaging, due to their relevance in the diagnosis of numerous disorders. However, the risk of adverse reactions, the concern of potential damage to sensitive organs, and the recently described brain deposition of gadolinium salts, limit the use of contrast media in clinical practice. In recent years, the application of artificial intelligence (AI) techniques to biomedical imaging has led to the development of ‘virtual’ and ‘augmented’ contrasts. The idea behind these applications is to generate synthetic post-contrast images through AI computational modeling starting from the information available on other images acquired during the same scan. In these AI models, non-contrast images (virtual contrast) or low-dose post-contrast images (augmented contrast) are used as input data to generate synthetic post-contrast images, which are often undistinguishable from the native ones. In this review, we discuss the most recent advances of AI applications to biomedical imaging relative to synthetic contrast media. © 2022 by the authors. |
| Keywords: | review; neuroimaging; nuclear magnetic resonance imaging; computer assisted tomography; oncology; abdomen; artificial intelligence; imaging; contrast medium; neck; multiple sclerosis; ct; model; mri; computed tomographic angiography; neurology; artificial neural network; neuroradiology; head; gadolinium chelate; thorax; cardiac imaging; neuro-oncology; human; convolutional neural network; gadolinium-based contrast agents; generative adversarial network; augmented contrast; iodinated contrast agents; synthetic imaging; virtual contrast |
| Journal Title: | Pharmaceutics |
| Volume: | 14 |
| Issue: | 11 |
| ISSN: | 1999-4923 |
| Publisher: | M D P I AG |
| Date Published: | 2022-11-01 |
| Start Page: | 2378 |
| Language: | English |
| DOI: | 10.3390/pharmaceutics14112378 |
| PROVIDER: | scopus |
| PMCID: | PMC9695136 |
| PUBMED: | 36365197 |
| DOI/URL: | |
| Notes: | Review -- Export Date: 1 December 2022 -- Source: Scopus |
