Literature DB >> 31845843

The LI-RADS Version 2018 MRI Treatment Response Algorithm: Evaluation of Ablated Hepatocellular Carcinoma.

Mohammad Chaudhry1, Katrina A McGinty1, Benjamin Mervak1, Reginald Lerebours1, Cai Li1, Erin Shropshire1, James Ronald1, Leah Commander1, Johann Hertel1, Sheng Luo1, Mustafa R Bashir1, Lauren M B Burke1.   

Abstract

Background The Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is used to assess presumed hepatocellular carcinoma (HCC) after local-regional therapy, but its performance has not been extensively assessed. Purpose To assess the performance of LI-RADS version 2018 TRA in the evaluation of HCC after ablation. Materials and Methods In this retrospective study, patients who underwent ablation therapy for presumed HCC followed by liver transplantation between January 2011 and December 2015 at a single tertiary care center were identified. Lesions were categorized as completely (100%) or incompletely (≤99%) necrotic based on transplant histology. Three radiologists assessed pre- and posttreatment MRI findings using LI-RADS version 2018 and the TRA, respectively. Interreader agreement was assessed by using the Fleiss κ test. Performance characteristics for predicting necrosis category based on LI-RADS treatment response (LR-TR) category (viable or nonviable) were calculated by using generalized mixed-effects models to account for clustering by subject. Results A total of 36 patients (mean age, 58 years ± 5 [standard deviation]; 32 men) with 53 lesions was included. Interreader agreement for pretreatment LI-RADS category was 0.40 (95% confidence interval [CI]: 0.15, 0.67; P < .01) and was lower than the interreader agreement for TRA category (κ = 0.71; 95% CI: 0.59, 0.84; P < .01). After accounting for clustering by subject, sensitivity of tumor necrosis across readers ranged from 40% to 77%, and specificity ranged from 85% to 97% when LR-TR equivocal assessments were treated as nonviable. When LR-TR equivocal assessments were treated as viable, sensitivity of tumor necrosis across readers ranged from 81% to 87%, and specificity ranged from 81% to 85% across readers. Six (11%) of 53 treated lesions were LR-TR equivocal by consensus, with most (five of six) incompletely necrotic at histopathology. Conclusion The Liver Imaging Reporting and Data System treatment response algorithm can be used to predict viable or nonviable hepatocellular carcinoma after ablation. Most ablated lesions rated as treatment response equivocal were incompletely necrotic at histopathology. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Do and Mendiratta-Lala in this issue.

Entities:  

Year:  2019        PMID: 31845843     DOI: 10.1148/radiol.2019191581

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  19 in total

Review 1.  LI-RADS: Future Directions.

Authors:  Victoria Chernyak; Claude B Sirlin
Journal:  Clin Liver Dis (Hoboken)       Date:  2021-04-13

2.  Moving Away from Uncertainty: A Potential Role for Ancillary Features in LI-RADS Treatment Response.

Authors:  Richard K Do; Mishal Mendiratta-Lala
Journal:  Radiology       Date:  2020-07-21       Impact factor: 11.105

3.  LI-RADS Version 2018 Treatment Response Algorithm: The Evidence Is Accumulating.

Authors:  Richard K Do; Mishal Mendiratta-Lala
Journal:  Radiology       Date:  2019-12-17       Impact factor: 11.105

Review 4.  Diagnosis, Staging, and Patient Selection for Locoregional Therapy to Treat Hepatocellular Carcinoma.

Authors:  Zachary T Berman; Isabel Newton
Journal:  Semin Intervent Radiol       Date:  2020-12-11       Impact factor: 1.513

5.  LI-RADS treatment response algorithm after first-line DEB-TACE: reproducibility and prognostic value at initial post-treatment CT/MRI.

Authors:  Ali Pirasteh; E Aleks Sorra; Hector Marquez; Robert C Sibley; Julia R Fielding; Abhinav Vij; Nicole E Rich; Ana Arroyo; Adam C Yopp; Gaurav Khatri; Amit G Singal; Takeshi Yokoo
Journal:  Abdom Radiol (NY)       Date:  2021-03-23

Review 6.  Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma.

Authors:  Guilherme Moura Cunha; Victoria Chernyak; Kathryn J Fowler; Claude B Sirlin
Journal:  J Hepatocell Carcinoma       Date:  2021-05-31

7.  LI-RADS Treatment Response Algorithm: Performance and Diagnostic Accuracy With Radiologic-Pathologic Explant Correlation in Patients With SBRT-Treated Hepatocellular Carcinoma.

Authors:  Mishal Mendiratta-Lala; Anum Aslam; Katherine E Maturen; Maria Westerhoff; Chris Maurino; Neehar D Parikh; Yilun Sun; Christopher J Sonnenday; Erica B Stein; Kimberly L Shampain; Ravi K Kaza; Kyle Cuneo; William Masch; Richard Kinh Gian Do; Theodore S Lawrence; Dawn Owen
Journal:  Int J Radiat Oncol Biol Phys       Date:  2021-10-10       Impact factor: 8.013

Review 8.  LI-RADS treatment response assessment of combination locoregional therapy for HCC.

Authors:  Marielia Gerena; Christopher Molvar; Mark Masciocchi; Sadhna Nandwana; Carl Sabottke; Bradley Spieler; Rishi Sharma; Leo Tsai; Ania Kielar
Journal:  Abdom Radiol (NY)       Date:  2021-06-13

9.  LI-RADS treatment response algorithm for detecting incomplete necrosis in hepatocellular carcinoma after locoregional treatment: a systematic review and meta-analysis using individual patient data.

Authors:  Tae-Hyung Kim; Sungmin Woo; Ijin Joo; Mustafa R Bashir; Mi-Suk Park; Lauren M B Burke; Mishal Mendiratta-Lala; Richard K G Do
Journal:  Abdom Radiol (NY)       Date:  2021-05-23

Review 10.  LI-RADS treatment response lexicon: review, refresh and resolve with emerging data.

Authors:  Roopa Ram; Rony Kampalath; Anuradha S Shenoy-Bhangle; Sandeep Arora; Ania Z Kielar; Mishal Mendiratta-Lala
Journal:  Abdom Radiol (NY)       Date:  2021-06-09
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