Neural Network-based Automated Classification of 18F-FDG PET/CT Lesions and Prognosis Prediction in Nasopharyngeal Carcinoma Without Distant Metastasis
Preliminary validation of PARS in NPC patients without distant metastasis shows high diagnostic sensitivity and accuracy for lesion identification and classification, and metabolic parameters correlate well with manual. MTV reflects prognosis, and its combination with age enhances prognostic prediction and risk stratification.
Authors
- Xiaoli Lan
- Yuhu Lv (ORCID: https://orcid.org/0000-0002-3269-783X)
- Danzha Zheng
- Zhangyongxue Zhou
- Zairong Gao (ORCID: https://orcid.org/0000-0002-8367-2659)
- Chunxia Qin (ORCID: https://orcid.org/0000-0002-0291-4418)
- Ruiping Wang (ORCID: https://orcid.org/0000-0001-9380-0266)
Institutions
- First Affiliated Hospital Zhejiang University (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Clinical Nuclear Medicine
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1097/rlu.0000000000005942
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36