18 F-FDG PET/CT-based deep learning radiomics predicts 5-years disease-free survival after failure to achieve pathologic complete response to neoadjuvant chemotherapy in breast cancer.
Xingxing ZhengYuhong HuangYingyi LinTeng ZhuJiachen ZouShuxia WangKun WangPublished in: EJNMMI research (2023)
The integrated model combining radiomic and depth features extracted from PET/CT images can accurately predict 5-year DFS in non-pCR patients. It can help identify patients with a high risk of recurrence and strengthen adjuvant therapy to improve survival.
Keyphrases
- free survival
- neoadjuvant chemotherapy
- pet ct
- deep learning
- locally advanced
- lymph node
- ejection fraction
- newly diagnosed
- convolutional neural network
- optical coherence tomography
- positron emission tomography
- prognostic factors
- machine learning
- magnetic resonance imaging
- rectal cancer
- computed tomography
- patient reported outcomes
- early stage
- magnetic resonance
- contrast enhanced
- real time pcr