Multimodal integration of [18F]PSMA-1007 PET/CT semiquantitative parameters and clinicopathological data for predicting prostate cancer metastasis
The XGBoost-based multimodal model integrating PET/CT semiquantitative parameters with clinicopathological data demonstrated excellent accuracy and interpretability in predicting prostate cancer metastasis. This approach has strong potential for clinical application and may provide a valuable tool for personalized treatment decision-making.
Authors
- Zhiyong Lv
- Jiaying Yang (ORCID: https://orcid.org/0000-0001-9454-2211)
- Qian Zhao (ORCID: https://orcid.org/0000-0001-5257-8283)
- HaiTong Hao (ORCID: https://orcid.org/0009-0003-2010-2864)
- Jian Chen (ORCID: https://orcid.org/0000-0002-2542-9669)
- Yanmei Li (ORCID: https://orcid.org/0009-0001-1232-7954)
- Zhiyong Ma (ORCID: https://orcid.org/0000-0003-1720-9866)
Institutions
- Medical Center Hospital (US)
- Ningxia Medical University (CN)
- Ningxia Medical University General Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-15
- DOI
- https://doi.org/10.3389/fonc.2025.1640159
- Citations
- 1
- Primary Topic
- Prostate Cancer Treatment and Research
- Type
- article
- Field-Weighted Citation Impact
- 1.52