MRI T2w Radiomics-Based Machine Learning Models in Imaging Simulated Biopsy Add Diagnostic Value to PI-RADS in Predicting Prostate Cancer: A Retrospective Diagnostic Study.
Jia-Cheng LiuXiao-Hao RuanTsun-Tsun ChunChi YaoDa HuangHoi-Lung WongChun-Ting LaiChiu-Fung TsangSze-Ho HoTsui-Lin NgDan-Feng XuRong NaPublished in: Cancers (2024)
The machine learning model based on radiomics analysis of MRI T2w images, along with simulated biopsy, provides additional diagnostic value to the PI-RADS scoring system in predicting PCa.
Keyphrases
- machine learning
- contrast enhanced
- prostate cancer
- magnetic resonance imaging
- deep learning
- artificial intelligence
- lymph node metastasis
- ultrasound guided
- high resolution
- fine needle aspiration
- computed tomography
- diffusion weighted imaging
- magnetic resonance
- big data
- radical prostatectomy
- squamous cell carcinoma
- photodynamic therapy
- fluorescence imaging