Advancing Coronary Risk Assessment Through Combined Radiomic, Mechanical, and Hemodynamic Analysis
Although based on only 39 patients, the results highlight the power of a multi-level integrative approach for coronary plaque assessment. The study revealed that (i) hemodynamics outperformed mechanics and radiomics; (ii) while radiomics maximized sensitivity, mechanics and hemodynamics prioritized specificity, and (iii) integrating at least two variable types added value.
Authors
- Anna Corti (ORCID: https://orcid.org/0000-0001-9603-7825)
- Gabriele Dubini (ORCID: https://orcid.org/0000-0002-0907-2903)
- Vittorio Lissoni
- Alessandro Depaoli (ORCID: https://orcid.org/0000-0003-0672-6278)
- F. Migliavacca
- Marco Stefanati (ORCID: https://orcid.org/0000-0001-7442-0241)
- Matteo Leccardi (ORCID: https://orcid.org/0009-0002-3434-0559)
- Pietro Cerveri (ORCID: https://orcid.org/0000-0003-3995-8673)
- L Mainardi
- José F. Rodriguez Matas
- Valentina D. A. Corino
- Francesco Bruno
Institutions
- University of Pavia (IT)
- Azienda Ospedaliera Citta' della Salute e della Scienza di Torino (IT)
- Centro Cardiologico Monzino (IT)
- University of Turin (IT)
- Politecnico di Milano (IT)
Publication Details
- Journal
- Annals of Biomedical Engineering
- Published
- 2026-02-23
- DOI
- https://doi.org/10.1007/s10439-026-03994-1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- Regione Lombardia
- Fondazione Regionale per la Ricerca Biomedica