Radiomic and Clinical–Pathological Factors Predictive of Postoperative Recurrence in Lung Neuroendocrine Tumors: A Pilot Study
This study has shown that radiomics can be a valuable tool in predicting recurrence. Currently, to our knowledge, no other studies on the possible application of radiomics as prognostic factors in patients with lung NET have been published. These encouraging findings warrant further investigations with larger, multicenter cohorts to validate these results and implement them by constructing a predictive model of recurrence.
Authors
- Rossella Mazzilli (ORCID: https://orcid.org/0000-0001-6707-3413)
- Antongiulio Faggiano (ORCID: https://orcid.org/0000-0002-9324-3946)
- Maurizio Martiradonna (ORCID: https://orcid.org/0009-0000-9738-1070)
- Mohsen Ibrahim (ORCID: https://orcid.org/0000-0002-9288-2359)
- Francesco Panzuto (ORCID: https://orcid.org/0000-0003-2789-4289)
- Michela Polici (ORCID: https://orcid.org/0000-0001-7331-6901)
- Matteo Tiracorrendo
- Antonio D’Andrilli
- Alessandra Siciliani (ORCID: https://orcid.org/0000-0002-0376-9697)
- Giulia Arrivi (ORCID: https://orcid.org/0000-0003-0541-415X)
- Virginia Zamponi (ORCID: https://orcid.org/0000-0002-2422-9673)
- Damiano Caruso (ORCID: https://orcid.org/0000-0001-9285-4764)
- Beatrice Trabalza Marinucci (ORCID: https://orcid.org/0000-0002-3786-5716)
- Massimiliano Mancini (ORCID: https://orcid.org/0000-0001-7465-2229)
- Piero Paravani
- Federica Palmeri (ORCID: https://orcid.org/0009-0004-8871-5947)
Institutions
- CTO Andrea Alesini (IT)
- Azienda Ospedaliera Sant'Andrea (IT)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- Cancers
- Published
- 2025-11-28
- DOI
- https://doi.org/10.3390/cancers17233812
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00