Clinical and radiomics parameter prognostication in metastatic uveal melanoma patients treated with hepatic arterial infusion chemotherapy
We identified independent but synergistic prognostic factors for outcome stratification to guide treatment decisions and optimize patient management. ML-based radiomics features did not significantly enhance prognostic performance.
Authors
- Felix Neumaier (ORCID: https://orcid.org/0000-0002-6376-6391)
- Benedikt M. Schaarschmidt (ORCID: https://orcid.org/0000-0001-6331-7679)
- Jens Theysohn (ORCID: https://orcid.org/0000-0001-5869-7929)
- M. Grubert
- Johannes Haubold (ORCID: https://orcid.org/0000-0003-4843-5911)
- Martin Schüler (ORCID: https://orcid.org/0000-0002-2166-3394)
- Heike Richly
- Jens Thomas Siveke (ORCID: https://orcid.org/0000-0002-8772-4778)
- Halime Kalkavan (ORCID: https://orcid.org/0000-0002-0090-4080)
- Tamara T. Mueller (ORCID: https://orcid.org/0000-0002-1818-1036)
- Nikolaos Emmanouel Bechrakis (ORCID: https://orcid.org/0000-0002-0180-1112)
- Sven T. Liffers
- Juliane Durand
- Tanja Gromke
- Rickmer Braren
Institutions
- German Cancer Research Center (DE)
- University of Cologne (DE)
- Essen University Hospital (DE)
- BG University Hospital Bergmannsheil Bochum (DE)
- University Hospital Cologne (DE)
- West German Heart and Vascular Center Essen (DE)
- Artificial Intelligence in Medicine (Canada) (CA)
- University of Duisburg-Essen (DE)
- Technical University of Munich (DE)
Publication Details
- Journal
- The Oncologist
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1093/oncolo/oyaf385
- Primary Topic
- Ocular Oncology and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00