Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study
BRITISH JOURNAL OF RADIOLOGY, cilt.92, sa.1101, 2019 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 92 Sayı: 1101
- Basım Tarihi: 2019
- Doi Numarası: 10.1259/bjr.20190286
- Dergi Adı: BRITISH JOURNAL OF RADIOLOGY
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Dokuz Eylül Üniversitesi Adresli: Evet
Özet
Objective: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/CT as metastatic and completely responded in patients with known bone metastasis and who were previously treated.