User and system pitfalls in liver imaging with LI‐RADS
| Autor: | Mustafa R. Bashir, Victoria Chernyak, Ania Z. Kielar, Elizabeth M. Hecht, Mohab M. Elmohr, Alessandro Furlan, Kathryn J. Fowler, Khaled M. Elsayes, Claude B. Sirlin |
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| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
Carcinoma Hepatocellular Computer science 030218 nuclear medicine & medical imaging Terminology 03 medical and health sciences 0302 clinical medicine medicine Humans Radiology Nuclear Medicine and imaging Medical physics Diagnostic Errors Liver imaging Liver Neoplasms Reproducibility of Results Evidence-based medicine Magnetic Resonance Imaging User Error Clinical Practice Transplantation Organ procurement Radiology Information Systems Liver government.politician government Tomography X-Ray Computed Incorrect Measurement |
| Zdroj: | Journal of Magnetic Resonance Imaging. 50:1673-1686 |
| ISSN: | 1522-2586 1053-1807 |
| Popis: | The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver imaging, created specifically for patients at risk for hepatocellular carcinoma. Over the past years, LI-RADS has been progressively implemented into clinical practice, but pitfalls remain related to user error and inherent limitations of the system. User pitfalls include the inappropriate application of LI-RADS to a low-risk patient population, incorrect measurement techniques, inaccurate assumptions about LI-RADS requirements, and improper usage of LI-RADS terminology and categories. System pitfalls include areas of discordance with the Organ Procurement and Transplantation Network (OPTN) as well as pitfalls related to rare ancillary features. This article reviews common user pitfalls in applying LI-RADS v2018 and how to avoid preventable errors and also highlights deficiencies of the current version of LI-RADS and how it might be improved in the future. Level of Evidence:3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2019;50:1673-1686. |
| Databáze: | OpenAIRE |
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