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DOI: 10.1055/s-0043-1768059
Response Assessment of Treated Hepatocellular Carcinoma

Abstract
Hepatocellular carcinoma (HCC) is a leading cause of morbidity and mortality worldwide, including in India. The incidence of HCC has been rising due to lifestyle diseases such as obesity, diabetes, non-alcoholic fatty liver disease (NAFLD), and alcoholic liver disease (ALD), as well as viral hepatitis infections. Various locoregional therapies (LRTs) are used to treat HCC, including thermal ablation, transarterial therapies, stereotactic body radiotherapy (SBRT), and transarterial radioembolization (TARE). Traditional response evaluation criteria like WHO and RECIST, which rely on size-based measurements, may not accurately assess treatment response to LRTs. To address this limitation, modified response evaluation criteria for solid tumors (mRECIST) and the LI-RADS treatment response algorithm (LR-TRA) have been developed. mRECIST assesses patient-level response, while LR-TRA provides lesion-level response assessment specifically for HCC treated with LRTs. This article discusses the imaging protocols for diagnosing HCC and the imaging appearances of treated lesions after different LRTs. It explains the criteria for categorizing treatment response, such as LR-TR viable, LR-TR non-viable, and LR-TR equivocal. It also highlights the challenges and future directions in response assessment, including the incorporation of ancillary findings, the assessment of patients receiving a combination of locoregional and systemic therapies, and the potential use of biomarkers like serum AFP, AFP-L3, and PIVKA-II. In conclusion, locoregional therapies have expanded the treatment options for HCC, and accurate response assessment is crucial for optimizing patient management. mRECIST and LR-TRA provide valuable tools for evaluating treatment response, and future updates are expected to address specific challenges and incorporate newer approaches like iRECIST and quantitative imaging assessment. Additionally, the use of biomarkers may complement imaging-based response assessment in the future.
Publication History
Article published online:
26 July 2023
© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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