A systematic review on artificial intelligence evaluating PSMA PET scan for intraprostatic cancer.
Jianliang LiuThomas P CundyDixon T S WoonNanadakishor DesaiMarimuthu PalaniswamiNathan L LawrentschukPublished in: BJU international (2024)
Although the current state of AI differentiating high-grade PCa is promising, it remains experimental and not ready for routine clinical application. Benefits of using AI to assess intraprostatic lesions on PSMA PET scans include: local staging, identifying otherwise radiologically occult lesions, standardisation and expedite reporting of PSMA PET scans. Larger, prospective, multicentre studies are needed.
Keyphrases
- pet ct
- artificial intelligence
- computed tomography
- high grade
- machine learning
- pet imaging
- big data
- positron emission tomography
- deep learning
- contrast enhanced
- papillary thyroid
- clinical trial
- low grade
- squamous cell
- magnetic resonance imaging
- adverse drug
- cross sectional
- squamous cell carcinoma
- lymph node metastasis
- case control
- electronic health record