Literature DB >> 32692297

Diagnostic Performance of LI-RADS Treatment Response Algorithm for Hepatocellular Carcinoma: Adding Ancillary Features to MRI Compared with Enhancement Patterns at CT and MRI.

Sungeun Park1, Ijin Joo1, Dong Ho Lee1, Jae Seok Bae1, Jeongin Yoo1, Se Woo Kim1, Jeong Min Lee1.   

Abstract

Background The Liver Imaging Reporting and Data System Treatment Response (LR-TR) algorithm is used to assess the response of hepatocellular carcinoma (HCC) to local-regional therapy (LRT) based on enhancement patterns. The potential value of adding MRI ancillary features (AFs) needs to be investigated. Purpose To evaluate the potential application of MRI AFs in category adjustment to detect pathologic tumor viability in comparison with the LR-TR algorithm in CT and gadoxetic acid-enhanced MRI. Materials and Methods This retrospective study included patients with HCCs treated with LRT followed by surgical resection or liver transplantation between January 2014 and December 2017 who underwent both post-LRT CT and gadoxetic acid-enhanced MRI. For each treated observation, treatment response (TR) categories were assigned based on a consensus reading of three radiologists according to the LR-TR algorithm in CT and MRI and according to the MRI-modified TR algorithm in which MRI AFs were allowed for category adjustment. The diagnostic performances of CT LR-TR viable, MRI LR-TR viable, and MRI-modified TR viable categories were compared intraindividually with the McNemar test, with pathologic tumor viability used as a reference standard. Results A total of 138 patients (119 men; mean age, 58 years ± 9 [standard deviation]) with 138 treated observations (108 pathologically viable) were evaluated. The sensitivity and specificity of CT LR-TR viable and MRI LR-TR viable categories for predicting tumor viability were 73% (79 of 108 lesions; 95% confidence interval [CI]: 64%, 81%) versus 76% (82 of 108 lesions; 95% CI: 67%, 84%) and 90% (27 of 30 lesions; 95% CI: 74%, 98%) versus 83% (25 of 30 lesions; 95% CI: 65%, 94%), respectively, without differences between CT and MRI (P = .65 and P = .63, respectively). MRI-modified TR viable category had higher sensitivity (84% [91 of 108 lesions; 95% CI: 76%, 91%]) than CT or MRI LR-TR viable category (P = .002 and P = .01, respectively), without difference in specificity (80% [24 of 30 lesions]; 95% CI: 61%, 92%) (P = .38 and P > .99, respectively). Conclusion The application of MRI ancillary features to the Liver Imaging Reporting and Data System Treatment Response algorithm resulted in higher sensitivity and no change in specificity compared with CT or MRI enhancement patterns alone in the prediction of pathologic tumor viability in patients with hepatocellular carcinoma. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Do and Mendiratta-Lala in this issue.

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Year:  2020        PMID: 32692297     DOI: 10.1148/radiol.2020192797

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


  11 in total

Review 1.  Assessing locoregional treatment response to Hepatocellular Carcinoma: comparison of hepatobiliary contrast agents to extracellular contrast agents.

Authors:  Anum Aslam; Amita Kamath; Bradley Spieler; Mark Maschiocchi; Carl F Sabottke; Victoria Chernyak; Sara C Lewis
Journal:  Abdom Radiol (NY)       Date:  2021-04-15

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 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 4.  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

5.  Application of the CT/MRI LI-RADS Treatment Response Algorithm to Contrast-Enhanced Ultrasound: A Feasibility Study.

Authors:  Si-Min Ruan; Mei-Qing Cheng; Hui Huang; Hang-Tong Hu; Wei Li; Xiao-Yan Xie; Ming-De Lu; Ming Kuang; Man-Xia Lin; Wei Wang
Journal:  J Hepatocell Carcinoma       Date:  2022-05-20

6.  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

7.  Optimized scan delay for late hepatic arterial or pancreatic parenchymal phase in dynamic contrast-enhanced computed tomography with bolus-tracking method.

Authors:  Yoshifumi Noda; Nobuyuki Kawai; Takuma Ishihara; Yoshiki Tsuboi; Tetsuro Kaga; Toshiharu Miyoshi; Fuminori Hyodo; Masayuki Matsuo
Journal:  Br J Radiol       Date:  2021-05-06       Impact factor: 3.629

Review 8.  Interreader Reliability of Liver Imaging Reporting and Data System Treatment Response: A Systematic Review and Meta-Analysis.

Authors:  Dong Wook Kim; Sang Hyun Choi; Ji Sung Lee; So Yeon Kim; So Jung Lee; Jae Ho Byun
Journal:  Diagnostics (Basel)       Date:  2021-02-04

Review 9.  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

10.  Inter-observer agreement using the LI-RADS version 2018 CT treatment response algorithm in patients with hepatocellular carcinoma treated with conventional transarterial chemoembolization.

Authors:  Krzysztof Bartnik; Joanna Podgórska; Grzegorz Rosiak; Krzysztof Korzeniowski; Olgierd Rowiński
Journal:  Abdom Radiol (NY)       Date:  2021-09-28
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