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11.04.2024 | Hepatobiliary

LI-RADS version 2018 treatment response algorithm on extracellular contrast-enhanced MRI in patients treated with transarterial chemoembolization for hepatocellular carcinoma: diagnostic performance and the added value of ancillary features

verfasst von: Di Wang, Yang Zhang, Rong Lyu, Kefeng Jia, Peng-Ju Xu

Erschienen in: Abdominal Radiology | Ausgabe 9/2024

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Abstract

Background

The Liver Imaging Reporting and Data System (LI-RADS) Treatment Response Algorithm (TRA) (LI-RADS TRA) is used for assessing response of HCC to locoregional therapy (LRT), however, the value of ancillary features (AFs) for TACE-treated HCCs has not been extensively investigated on extracellular agent MRI (ECA-MRI).

Purpose

To evaluate the diagnostic performance of LI-RADS v2018 TRA on ECA-MRI for HCC treated with transarterial chemoembolization (TACE) and the value of ancillary features.

Methods

This retrospective study included patients who underwent TACE for HCC and then followed by hepatic surgery between January 2019 and June 2023 with both pre- and post-TACE contrast-enhanced MRI available. Two radiologists independently evaluated the post-treated lesions on MRI using LI-RADS treatment response (TR) (LR-TR) algorithm and modified LR-TR (mLR-TR) algorithm in which ancillary features (restricted diffusion and intermediate T2-weighted hyperintensity) were added, respectively. Lesions were categorized as complete pathologic necrosis (100%, CPN) and non-complete pathologic necrosis (< 100%, non-CPN) on the basis of surgical pathology. The diagnostic performance in predicting viable and non-viable tumors based on LR-TR and mLR-TR algorithms was compared using the McNemar test. Interreader agreement was calculated by using Cohen’s weighted and unweighted κ.

Results

A total of 61 patients [mean age 59 years ± 10 (standard deviation); 47 men] with 79 lesions (57 pathologically viable) were included. For non-CPN prediction, the sensitivity, specificity of LR-TR viable and mLR-TR viable category were 75% (43 of 57), 82% (18 of 22) and 88% (50 of 57), 77% (17 of 22), respectively, the sensitivity of mLR-TR was significantly higher than that of LR-TR (P = 0.016) without difference in specificity (P = 1.000). Interreader agreement for LR-TR and mLR-TR category was moderate (k = 0.50, 95% confidence interval 0.33, 0.67, k = 0.42, 95% confidence interval 0.20, 0.63). The sensitivity of both LR-TR and mLR-TR algorithms in predicting viable tumors between conventional TACE (cTACE) and drug-eluting beads TACE (DEB-TACE) did not have significant difference (cTACE: 76%, 89% vs. DEB-TACE: 73%, 82%).

Conclusions

On ECA-MRI, applying ancillary features to LI-RADS v2018 TRA can improve the sensitivity in predicting pathologic tumor viability in patients treated with TACE for hepatocellular carcinoma with no significant difference in specificity.
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Literatur
1.
Zurück zum Zitat Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209–249. https://doi.org/10.3322/caac.21660 Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209–249. https://​doi.​org/​10.​3322/​caac.​21660
2.
Zurück zum Zitat Kielar, A., Fowler, K. J., Lewis, S., Yaghmai, V., Miller, F. H., Yarmohammadi, H., Kim, C., Chernyak, V., Yokoo, T., Meyer, J., Newton, I., & Do, R. K. (2018). Locoregional therapies for hepatocellular carcinoma and the new LI-RADS treatment response algorithm. Abdominal Radiology (New York), 43(1), 218–230. https://doi.org/https://doi.org/10.1007/s00261-017-1281-6CrossRefPubMed Kielar, A., Fowler, K. J., Lewis, S., Yaghmai, V., Miller, F. H., Yarmohammadi, H., Kim, C., Chernyak, V., Yokoo, T., Meyer, J., Newton, I., & Do, R. K. (2018). Locoregional therapies for hepatocellular carcinoma and the new LI-RADS treatment response algorithm. Abdominal Radiology (New York), 43(1), 218–230. https://​doi.​org/​https://​doi.​org/​10.​1007/​s00261-017-1281-6CrossRefPubMed
3.
Zurück zum Zitat Reig, M., Forner, A., Rimola, J., Ferrer-Fàbrega, J., Burrel, M., Garcia-Criado, Á., Kelley, R. K., Galle, P. R., Mazzaferro, V., Salem, R., Sangro, B., Singal, A. G., Vogel, A., Fuster, J., Ayuso, C., & Bruix, J. (2022). BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. Journal of Hepatology, 76(3), 681–693. https://doi.org/https://doi.org/10.1016/j.jhep.2021.11.018CrossRefPubMed Reig, M., Forner, A., Rimola, J., Ferrer-Fàbrega, J., Burrel, M., Garcia-Criado, Á., Kelley, R. K., Galle, P. R., Mazzaferro, V., Salem, R., Sangro, B., Singal, A. G., Vogel, A., Fuster, J., Ayuso, C., & Bruix, J. (2022). BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. Journal of Hepatology, 76(3), 681–693. https://​doi.​org/​https://​doi.​org/​10.​1016/​j.​jhep.​2021.​11.​018CrossRefPubMed
5.
Zurück zum Zitat 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.2019182135CrossRefPubMed 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.​2019182135CrossRefPubMed
6.
Zurück zum Zitat Mendiratta-Lala, M., Aslam, A., Maturen, K. E., Westerhoff, M., Maurino, C., Parikh, N. D., Sun, Y., Sonnenday, C. J., Stein, E. B., Shampain, K. L., Kaza, R. K., Cuneo, K., Masch, W., Do, R. K. G., Lawrence, T. S., & Owen, D. (2022). LI-RADS Treatment Response Algorithm: Performance and Diagnostic Accuracy with Radiologic–Pathologic Explant Correlation in Patients with SBRT-Treated Hepatocellular Carcinoma. International Journal of Radiation Oncology, Biology, Physics, 112(3), 704–714. https://doi.org/https://doi.org/10.1016/j.ijrobp.2021.10.006CrossRefPubMed Mendiratta-Lala, M., Aslam, A., Maturen, K. E., Westerhoff, M., Maurino, C., Parikh, N. D., Sun, Y., Sonnenday, C. J., Stein, E. B., Shampain, K. L., Kaza, R. K., Cuneo, K., Masch, W., Do, R. K. G., Lawrence, T. S., & Owen, D. (2022). LI-RADS Treatment Response Algorithm: Performance and Diagnostic Accuracy with Radiologic–Pathologic Explant Correlation in Patients with SBRT-Treated Hepatocellular Carcinoma. International Journal of Radiation Oncology, Biology, Physics, 112(3), 704–714. https://​doi.​org/​https://​doi.​org/​10.​1016/​j.​ijrobp.​2021.​10.​006CrossRefPubMed
7.
Zurück zum Zitat 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. B. (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.2019191581CrossRefPubMed 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. B. (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.​2019191581CrossRefPubMed
8.
Zurück zum Zitat Park, S., Joo, I., Lee, D. H., Bae, J. S., Yoo, J., Kim, S. W., & Lee, J. M. (2020). Diagnostic Performance of LI-RADS Treatment Response Algorithm for Hepatocellular Carcinoma: Adding Ancillary Features to MRI Compared with Enhancement Patterns at CT and MRI. Radiology, 296(3), 554–561. https://doi.org/https://doi.org/10.1148/radiol.2020192797CrossRefPubMed Park, S., Joo, I., Lee, D. H., Bae, J. S., Yoo, J., Kim, S. W., & Lee, J. M. (2020). Diagnostic Performance of LI-RADS Treatment Response Algorithm for Hepatocellular Carcinoma: Adding Ancillary Features to MRI Compared with Enhancement Patterns at CT and MRI. Radiology, 296(3), 554–561. https://​doi.​org/​https://​doi.​org/​10.​1148/​radiol.​2020192797CrossRefPubMed
9.
Zurück zum Zitat Kim, S. W., Joo, I., Kim, H. C., Ahn, S. J., Kang, H. J., Jeon, S. K., & Lee, J. M. (2020). LI-RADS treatment response categorization on gadoxetic acid-enhanced MRI: diagnostic performance compared to mRECIST and added value of ancillary features. European Radiology, 30(5), 2861–2870. https://doi.org/https://doi.org/10.1007/s00330-019-06623-9CrossRefPubMed Kim, S. W., Joo, I., Kim, H. C., Ahn, S. J., Kang, H. J., Jeon, S. K., & Lee, J. M. (2020). LI-RADS treatment response categorization on gadoxetic acid-enhanced MRI: diagnostic performance compared to mRECIST and added value of ancillary features. European Radiology, 30(5), 2861–2870. https://​doi.​org/​https://​doi.​org/​10.​1007/​s00330-019-06623-9CrossRefPubMed
10.
Zurück zum Zitat Kim, Y. Y., Kim, M. J., Yoon, J. K., Shin, J., & Roh, Y. H. (2022). Incorporation of Ancillary MRI Features into the LI-RADS Treatment Response Algorithm: Impact on Diagnostic Performance After Locoregional Treatment of Hepatocellular Carcinoma. American Journal of Roentgenology, 218(3), 484–493. https://doi.org/https://doi.org/10.2214/AJR.21.26677CrossRefPubMed Kim, Y. Y., Kim, M. J., Yoon, J. K., Shin, J., & Roh, Y. H. (2022). Incorporation of Ancillary MRI Features into the LI-RADS Treatment Response Algorithm: Impact on Diagnostic Performance After Locoregional Treatment of Hepatocellular Carcinoma. American Journal of Roentgenology, 218(3), 484–493. https://​doi.​org/​https://​doi.​org/​10.​2214/​AJR.​21.​26677CrossRefPubMed
14.
Zurück zum Zitat Bae, J. S., Lee, J. M., Yoon, J. H., Kang, H. J., Jeon, S. K., Joo, I., Lee, K. B., & Kim, H. (2021). Evaluation of LI-RADS Version 2018 Treatment Response Algorithm for Hepatocellular Carcinoma in Liver Transplant Candidates: Intraindividual Comparison between CT and Hepatobiliary Agent-Enhanced MRI. Radiology, 299(2), 336–345. https://doi.org/https://doi.org/10.1148/radiol.2021203537CrossRefPubMed Bae, J. S., Lee, J. M., Yoon, J. H., Kang, H. J., Jeon, S. K., Joo, I., Lee, K. B., & Kim, H. (2021). Evaluation of LI-RADS Version 2018 Treatment Response Algorithm for Hepatocellular Carcinoma in Liver Transplant Candidates: Intraindividual Comparison between CT and Hepatobiliary Agent-Enhanced MRI. Radiology, 299(2), 336–345. https://​doi.​org/​https://​doi.​org/​10.​1148/​radiol.​2021203537CrossRefPubMed
15.
Zurück zum Zitat Polikoff, A., Wessner, C. E., Balasubramanya, R., Dulka, S., Liu, J. B., Machado, P., Savsani, E., Lyshchik, A., Shaw, C. M., & Eisenbrey, J. R. (2022). Imaging appearance of residual HCC following incomplete trans-arterial chemoembolization on contrast-enhanced imaging. Abdominal Radiology (New York), 47(1), 152–160. https://doi.org/https://doi.org/10.1007/s00261-021-03298-zCrossRefPubMed Polikoff, A., Wessner, C. E., Balasubramanya, R., Dulka, S., Liu, J. B., Machado, P., Savsani, E., Lyshchik, A., Shaw, C. M., & Eisenbrey, J. R. (2022). Imaging appearance of residual HCC following incomplete trans-arterial chemoembolization on contrast-enhanced imaging. Abdominal Radiology (New York), 47(1), 152–160. https://​doi.​org/​https://​doi.​org/​10.​1007/​s00261-021-03298-zCrossRefPubMed
16.
Zurück zum Zitat Seo, N., Kim, M. S., Park, M. S., Choi, J. Y., Do, R. K. G., Han, K., & Kim, M. J. (2020). Evaluation of treatment response in hepatocellular carcinoma in the explanted liver with Liver Imaging Reporting and Data System version 2017. European Radiology, 30(1), 261–271. https://doi.org/https://doi.org/10.1007/s00330-019-06376-5CrossRefPubMed Seo, N., Kim, M. S., Park, M. S., Choi, J. Y., Do, R. K. G., Han, K., & Kim, M. J. (2020). Evaluation of treatment response in hepatocellular carcinoma in the explanted liver with Liver Imaging Reporting and Data System version 2017. European Radiology, 30(1), 261–271. https://​doi.​org/​https://​doi.​org/​10.​1007/​s00330-019-06376-5CrossRefPubMed
17.
Zurück zum Zitat Kim TH, Woo S, Joo I, Bashir MR, Park MS, Burke LMB, Mendiratta-Lala M, Do RKG. 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. Abdom Radiol (NY). 2021 Aug;46(8):3717–3728. doi: https://doi.org/10.1007/s00261-021-03122-8 Kim TH, Woo S, Joo I, Bashir MR, Park MS, Burke LMB, Mendiratta-Lala M, Do RKG. 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. Abdom Radiol (NY). 2021 Aug;46(8):3717–3728. doi: https://​doi.​org/​10.​1007/​s00261-021-03122-8
19.
Zurück zum Zitat Golfieri, R., Giampalma, E., Renzulli, M., Cioni, R., Bargellini, I., Bartolozzi, C., Breatta, A. D., Gandini, G., Nani, R., Gasparini, D., Cucchetti, A., Bolondi, L., Trevisani, F., & Precision Italia Study Group (2014). Randomised controlled trial of doxorubicin-eluting beads vs conventional chemoembolisation for hepatocellular carcinoma. British Journal of Cancer, 111(2), 255–264. https://doi.org/10.1038/bjc.2014.199 Golfieri, R., Giampalma, E., Renzulli, M., Cioni, R., Bargellini, I., Bartolozzi, C., Breatta, A. D., Gandini, G., Nani, R., Gasparini, D., Cucchetti, A., Bolondi, L., Trevisani, F., & Precision Italia Study Group (2014). Randomised controlled trial of doxorubicin-eluting beads vs conventional chemoembolisation for hepatocellular carcinoma. British Journal of Cancer, 111(2), 255–264. https://​doi.​org/​10.​1038/​bjc.​2014.​199
20.
Zurück zum Zitat Kwan, S. W., Fidelman, N., Ma, E., Kerlan, R. K., Jr, & Yao, F. Y. (2012). Imaging predictors of the response to transarterial chemoembolization in patients with hepatocellular carcinoma: a radiological–pathological correlation. Liver Transplantation: Official Publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society, 18(6), 727–736. https://doi.org/https://doi.org/10.1002/lt.23413CrossRefPubMed Kwan, S. W., Fidelman, N., Ma, E., Kerlan, R. K., Jr, & Yao, F. Y. (2012). Imaging predictors of the response to transarterial chemoembolization in patients with hepatocellular carcinoma: a radiological–pathological correlation. Liver Transplantation: Official Publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society, 18(6), 727–736. https://​doi.​org/​https://​doi.​org/​10.​1002/​lt.​23413CrossRefPubMed
Metadaten
Titel
LI-RADS version 2018 treatment response algorithm on extracellular contrast-enhanced MRI in patients treated with transarterial chemoembolization for hepatocellular carcinoma: diagnostic performance and the added value of ancillary features
verfasst von
Di Wang
Yang Zhang
Rong Lyu
Kefeng Jia
Peng-Ju Xu
Publikationsdatum
11.04.2024
Verlag
Springer US
Erschienen in
Abdominal Radiology / Ausgabe 9/2024
Print ISSN: 2366-004X
Elektronische ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-024-04275-y

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