Society of abdominal radiology survey of practice patterns in using LI-RADS treatment response criteria in the evaluation of hepatocellular carcinoma post-locoregional treatment.

HCC Hepatocellular carcinoma LI-RADS treatment response algorithm Locoregional therapy

Journal

Abdominal radiology (New York)
ISSN: 2366-0058
Titre abrégé: Abdom Radiol (NY)
Pays: United States
ID NLM: 101674571

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 11 05 2023
accepted: 05 08 2023
revised: 04 08 2023
pubmed: 4 9 2023
medline: 4 9 2023
entrez: 2 9 2023
Statut: ppublish

Résumé

To examine national trends in the adoption and use of the LI-RADS Treatment Response Algorithm. Members of the Society of Abdominal Radiology (SAR) Disease-Focused Panel (DFP) on LI-RADS Treatment Response (LR-TR) of hepatocellular carcinoma (HCC) developed a 15-question survey which was distributed to radiologists at academic and private practice institutions around the USA and Canada. The survey focused on HCC-related practice patterns as well as the adoption and use of the LR-TR algorithm. Of 122 surveys distributed, a total of 76 radiologists responded (62%). Responders were predominantly from academic centers (85%). Nearly all (96%) participate in multidisciplinary hepatic tumor boards and most (67%) have an active liver transplant program. All responders' institutions perform locoregional therapy for HCC, including radiation-based therapy (TARE and SBRT). There was a preference for use of MRI over CT for follow-up after locoregional therapy. All responders were aware of the LR-TR algorithm and nearly all (92%) used the system in routine practice. Radiologists expressed a need for more visual aids related to the LR-TR system. Multiple respondents requested additional clarity within the LR-TR algorithm regarding the evolution of post-treatment radiation changes over time. Most survey participants use the LR-TR algorithm after locoregional therapy for HCC. Future iterations of the algorithm may benefit from increased clarity regarding response after radiation-based therapies. Educational materials should include more visual aids to improve reader understanding.

Identifiants

DOI: 10.1007/s00261-023-04022-9 PMID: 37658876
pubmed: 37658876
doi: 10.1007/s00261-023-04022-9
pii: 10.1007/s00261-023-04022-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3401-3407

Informations de copyright

© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Références

Kampalath, R., Tran-Harding, K., Do, R. K. G., Mendiratta-Lala, M., & Yaghmai, V. (2021). Evaluation of hepatocellular carcinoma treatment response after Locoregional therapy. Magnetic Resonance Imaging Clinics of North America, 29(3), 389–403. https://doi.org/ https://doi.org/10.1016/j.mric.2021.05.013
doi: 10.1016/j.mric.2021.05.013 pubmed: 34243925
Ganesan, P., & Kulik, L. M. (2023). Hepatocellular carcinoma. Clinics in Liver Disease, 27(1), 85–102. https://doi.org/ https://doi.org/10.1016/j.cld.2022.08.004
doi: 10.1016/j.cld.2022.08.004 pubmed: 36400469
Li-RADS® CT/MRI. American College of Radiology. Retrieved March 13, 2023, from https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS/LI-RADS-CT-MRI-v2018
Shropshire, E. L., Chaudhry, M., Miller, C. M., Allen, B. C., Bozdogan, E., Cardona, D. M., King, L. Y., Janas, G. L., Do, R. K., Kim, C. Y., Ronald, J., & Bashir, M. R. (2019). Li-Rads Treatment Response Algorithm: Performance and diagnostic accuracy. Radiology, 292(1), 226–234. https://doi.org/ https://doi.org/10.1148/radiol.2019182135
doi: 10.1148/radiol.2019182135 pubmed: 31038409
Zhang, Y., Wang, J., Li, H., Zheng, T., Jiang, H., Li, M., & Song, B. (2020). Performance of li-rads version 2018 CT treatment response algorithm in tumor response evaluation and survival prediction of patients with single hepatocellular carcinoma after radiofrequency ablation. Annals of Translational Medicine, 8(6), 388–388. https://doi.org/10.21037/atm.2020.03.120
Cools, K. S., Moon, A. M., Burke, L. M., McGinty, K. A., Strassle, P. D., & Gerber, D. A. (2019). Validation of the liver imaging reporting and Data System Treatment Response Criteria after thermal ablation for hepatocellular carcinoma. Liver Transplantation, 26(2), 203–214. https://doi.org/ https://doi.org/10.1002/lt.25673
doi: 10.1002/lt.25673 pubmed: 31677319 pmcid: 6980979
Chaudhry, M., McGinty, K. A., Mervak, B., Lerebours, R., Li, C., Shropshire, E., Ronald, J., Commander, L., Hertel, J., Luo, S., Bashir, M. R., & Burke, L. M. (2020). The Li-rads version 2018 MRI treatment response algorithm: Evaluation of ablated hepatocellular carcinoma. Radiology, 294(2), 320–326. https://doi.org/ https://doi.org/10.1148/radiol.2019191581
doi: 10.1148/radiol.2019191581 pubmed: 31845843
Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research Electronic Data Capture (redcap)—a metadata-driven methodology and workflow process for providing Translational Research Informatics Support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/ https://doi.org/10.1016/j.jbi.2008.08.010
doi: 10.1016/j.jbi.2008.08.010 pubmed: 18929686
Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O'Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., & Duda, S. N. (2019). The redcap consortium: Building an international community of Software Platform Partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/ https://doi.org/10.1016/j.jbi.2019.103208
doi: 10.1016/j.jbi.2019.103208 pubmed: 31078660 pmcid: 7254481
Alenazi, A. O., Elsayes, K. M., Marks, R. M., Yacoub, J. H., Hecht, E. M., Chernyak, V., Krishna, S., Surabhi, V., Lee, J. T., Ash, R., Cruite, I., & Kielar, A. Z. (2020). Clinicians and surgeon survey regarding current and future versions of CT/MRI Li-rads. Abdominal Radiology, 45(8), 2603–2611. https://doi.org/ https://doi.org/10.1007/s00261-020-02544-0
doi: 10.1007/s00261-020-02544-0 pubmed: 32342150
Mendiratta-Lala, M., Masch, W., Shankar, P. R., Hartman, H. E., Davenport, M. S., Schipper, M. J., Maurino, C., Cuneo, K. C., Lawrence, T. S., & Owen, D. (2019). Magnetic Resonance Imaging Evaluation of hepatocellular carcinoma treated with stereotactic body radiation therapy: Long term imaging follow-up. International Journal of Radiation Oncology*Biology*Physics, 103(1), 169–179. https://doi.org/ https://doi.org/10.1016/j.ijrobp.2018.09.004
doi: 10.1016/j.ijrobp.2018.09.004 pubmed: 30213751
Oldrini, G., Huertas, A., Renard-Oldrini, S., Taste-George, H., Vogin, G., Laurent, V., Salleron, J., & Henrot, P. (2017). Tumor response assessment by MRI following stereotactic body radiation therapy for hepatocellular carcinoma. PLOS ONE, 12(4). https://doi.org/10.1371/journal.pone.0176118

Auteurs

Rony Kampalath (R)

Department of Radiological Sciences, University of California Irvine, 101 The City Drive South, Orange, CA, 92868, USA. rkampala@hs.uci.edu.

Mishal Mendiratta-Lala (M)

Radiology, University of Michigan School of Medicine, 1500 East Medical Center Drive, UH B2A209R, Ann Arbor, MI, 48109-5030, USA.

Sara Lewis (S)

Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1234, New York, NY, 10029-6574, USA.

Thad Benefield (T)

Carolina Mammography Registry, University of North Carolina at Chapel Hill, CB #7510, Bioinformatics Building Room 3125, Chapel Hill, NC, 27599-7515, USA.

Vahid Yaghmai (V)

Department of Radiological Sciences, University of California Irvine, 101 The City Drive South, Orange, CA, 92868, USA.

Lauren Burke (L)

Department of Radiology, University of North Carolina at Chapel Hill School of Medicine, 2000 Old Clinic, CB# 7510, Chapel Hill, NC, 27599, USA.

Classifications MeSH