LI-RADS v2017 for liver nodules: how we read and report.
Wolfgang SchimaJay HeikenPublished in: Cancer imaging : the official publication of the International Cancer Imaging Society (2018)
The Liver Imaging Reporting and Data System (LI-RADS) standardizes the interpretation and reporting of imaging examinations in patients at risk for hepatocellular carcinoma (HCC). For focal liver observations it assigns categories (LR-1 to 5, LR-M, LR-TIV), which reflect the relative probability of benignity or malignancy of the respective observation. The categories assigned are based on major and ancillary image features, which have been developed by the American College of Radiology (ACR) and validated in many studies. This review summarizes the relevant CT and MRI features and presents an image-guided approach for readers not familiar with LI-RADS on how to use the system. The widespread adoption of LI-RADS for reporting would help reduce inter-reader variability and improve communication among radiologists, hepatologists, hepatic surgeons and oncologists, thus leading to improved patient management.
Keyphrases
- ion batteries
- high resolution
- adverse drug
- end stage renal disease
- artificial intelligence
- electronic health record
- contrast enhanced
- ejection fraction
- newly diagnosed
- magnetic resonance imaging
- solid state
- deep learning
- prognostic factors
- peritoneal dialysis
- machine learning
- magnetic resonance
- fluorescence imaging
- palliative care
- image quality
- photodynamic therapy
- diffusion weighted imaging