The Evidence for Using Artificial Intelligence to Enhance Prostate Cancer MR Imaging.
Rodrigo CanellasMarc D KohliAntonio C WestphalenPublished in: Current oncology reports (2023)
Artificial intelligence has been applied to prostate cancer MR imaging to improve its diagnostic accuracy and reproducibility of interpretation. Multiple models have been tested for gland segmentation and volume calculation, automated lesion detection, localization, and characterization, as well as prediction of tumor aggressiveness and tumor recurrence. Studies show, for example, that very robust automated gland segmentation and volume calculations can be achieved and that lesions can be detected and accurately characterized. Although results are promising, we should view these with caution. Most studies included a small sample of patients from a single institution and most models did not undergo proper external validation. More research is needed with larger and well-design studies for the development of reliable artificial intelligence tools.
Keyphrases
- artificial intelligence
- deep learning
- prostate cancer
- machine learning
- big data
- convolutional neural network
- end stage renal disease
- radical prostatectomy
- case control
- chronic kidney disease
- newly diagnosed
- ejection fraction
- contrast enhanced
- peritoneal dialysis
- molecular dynamics
- magnetic resonance imaging
- prognostic factors
- computed tomography
- monte carlo
- single cell
- patient reported
- real time pcr
- quantum dots