7T-high resolution MRI-derived radiomic analysis for the identification of symptomatic intracranial atherosclerotic plaques
Symptomatic plaques had a distinct signature RFs compared to other plaques within the same subject. A machine learning model built with RFs successfully identified the symptomatic atherosclerotic plaques in most cases. Radiomics is a promising tool for stratification of plaques in patients with ICAD.
Authors
- Sricharan S. Veeturi (ORCID: https://orcid.org/0000-0002-8114-3817)
- Jacob M Miller
- Vincent M. Tutino (ORCID: https://orcid.org/0000-0002-1331-2551)
- Edgar Andres Samaniego (ORCID: https://orcid.org/0000-0003-2764-2268)
- Tatsat R. Patel (ORCID: https://orcid.org/0000-0002-4074-6822)
- Elena Sagues (ORCID: https://orcid.org/0000-0002-8192-1906)
- Sebastian Sanchez (ORCID: https://orcid.org/0009-0000-3696-8361)
- Diego J Ojeda
Institutions
- University of Iowa (US)
- Yale University (US)
- Dent Neurologic Institute (US)
- University at Buffalo, State University of New York (US)
Publication Details
- Journal
- Interventional Neuroradiology
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1177/15910199241275722
- Citations
- 3
- Primary Topic
- Cerebrovascular and Carotid Artery Diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.26
Funders
- Common Fund