Title

Role of the radiologist at HCC multidisciplinary conference and use of the LR-TR algorithm for improving workflow

UMMS Affiliation

Department of Radiology

Publication Date

2021-04-27

Document Type

Article

Disciplines

Neoplasms | Oncology | Radiology

Abstract

Multidisciplinary conferences (MDCs) play a major role in management and care of oncology patients. Hepatocellular carcinoma (HCC) is a complex disease benefiting from multidisciplinary discussions to determine optimal patient management. A multitude of liver-directed locoregional therapies have emerged allowing for more options for treatment of HCC. A radiologist dedicated to HCC-MDC is an important member of the team contributing to patient care in multiple ways. The radiologist plays a key role in image interpretation guiding initial therapy discussions as well as interpreting post-treatment imaging following liver-directed therapy. Standardization of image interpretation can lead to more consistent treatment received by the patient as well as accurate assessment of transplant eligibility. The radiologist can facilitate this process using structured reporting that is also supported by stakeholders involved in interdisciplinary management of liver diseases. The Liver Imaging Reporting and Data System (LI-RADS), is a living document which offers a standardized reporting algorithm for consistent communication of radiologic findings for HCC screening and characterization of liver observations in patients at risk for HCC. The LI-RADS post-treatment algorithm (LR-TR algorithm) has been developed to standardize liver observations following liver-directed locoregional therapy. This review article focuses on the role of the radiologist at HCC-MDC and implementation of the LR-TR algorithm for improving workflow.

Keywords

HCC, LI-RADS, LR-TR, Multidisciplinary conference

DOI of Published Version

10.1007/s00261-021-03094-9

Source

Shenoy-Bhangle AS, Tsai LL, Masciocchi M, Arora SS, Kielar AZ. Role of the radiologist at HCC multidisciplinary conference and use of the LR-TR algorithm for improving workflow. Abdom Radiol (NY). 2021 Apr 27. doi: 10.1007/s00261-021-03094-9. Epub ahead of print. PMID: 33904990. Link to article on publisher's site

Journal/Book/Conference Title

Abdominal radiology (New York)

Related Resources

Link to Article in PubMed

PubMed ID

33904990

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