Estimation of tumor coverage after RF ablation of hepatocellular carcinoma using single 2D image slices
An AI model that uses 2D images at the center of the tumor and 1 month post-ablation can accurately estimate ablation tumor coverage. In separate validation cohorts, translation could be challenging.
Authors
- Laetitia Saccenti (ORCID: https://orcid.org/0000-0002-9765-0039)
- K. Lee (ORCID: https://orcid.org/0000-0002-8808-9358)
- Bradford J. Wood (ORCID: https://orcid.org/0000-0002-4297-0051)
- Lindsey Hazen (ORCID: https://orcid.org/0000-0003-4013-8226)
- Anna Christou
- Riccardo Lencioni (ORCID: https://orcid.org/0000-0002-8535-6449)
- Antonio Arrichiello (ORCID: https://orcid.org/0000-0002-1250-8675)
- Tabea Borde (ORCID: https://orcid.org/0000-0003-3019-5470)
- Nicole Varble (ORCID: https://orcid.org/0000-0003-2273-7962)
- Ming Li (ORCID: https://orcid.org/0000-0002-1446-4493)
- Sheng Xu (ORCID: https://orcid.org/0000-0002-4462-6297)
Institutions
- University of Pisa (IT)
- National Institutes of Health (US)
- Centre Hospitalier Universitaire Henri-Mondor (FR)
- National Institute of Biomedical Imaging and Bioengineering (US)
- Hôpitaux Universitaires Henri-Mondor (FR)
- Philips (United States) (US)
- Ospedale Maggiore di Lodi (IT)
- National Institutes of Health Clinical Center (US)
- Institut Mondor de Recherche Biomédicale (FR)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2025-06-07
- DOI
- https://doi.org/10.1007/s11548-025-03423-z
- Citations
- 2
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 2.64
Funders
- National Institutes of Health
- NIH Clinical Center