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Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making.

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Title: Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making.
Authors: Sobirey, Rabea1,2 (AUTHOR), Matuschewski, Nickolai1,2 (AUTHOR), Gross, Moritz1,2 (AUTHOR), Lin, MingDe1,3 (AUTHOR), Kao, Tabea1,2 (AUTHOR), Kasolowsky, Victor1,2 (AUTHOR), Strazzabosco, Mario4 (AUTHOR), Stein, Stacey5 (AUTHOR), Savic, Lynn Jeanette2 (AUTHOR), Gebauer, Bernhard2 (AUTHOR), Jaffe, Ariel4 (AUTHOR), Duncan, James1 (AUTHOR), Madoff, David C.1,5,6 (AUTHOR), Chapiro, Julius1,4 (AUTHOR) julius.chapiro@yale.edu
Source: European Radiology. Jan2025, Vol. 35 Issue 1, p73-83. 11p.
Subjects: Immune checkpoint inhibitors, Magnetic resonance imaging, Overall survival, Regression analysis, Hepatocellular carcinoma
Abstract: Objective: To compare the performance of 1D and 3D tumor response assessment for predicting median overall survival (mOS) in patients who underwent immunotherapy for hepatocellular carcinoma (HCC). Methods: Patients with HCC who underwent immunotherapy between 2017 and 2023 and received multi-phasic contrast-enhanced MRIs pre- and post-treatment were included in this retrospective study. Tumor response was measured using 1D, RECIST 1.1, and mRECIST, and 3D, volumetric, and percentage quantitative EASL (vqEASL and %qEASL). Patients were grouped into disease control vs progression and responders vs non-responders. Kaplan–Meier curves analyzed with log-rank tests assessed the predictive value for mOS. Cox regression modeling evaluated the association of clinical baseline parameters with mOS. Results: This study included 37 patients (mean age, 69.1 years [SD, 8.0]; 33 men). The mOS was 16.9 months. 3D vqEASL and %qEASL successfully stratified patients into disease control and progression (vqEASL: HR 0.21, CI: 0.55–0.08, p < 0.001; %qEASL: HR 0.18, CI: 0.83–0.04, p = 0.013), as well as responder and nonresponder (vqEASL: HR 0.25, CI: 0.08–0.74, p = 0.007; %qEASL: HR 0.17, CI: 0.04–0.72, p = 0.007) for predicting mOS. The 1D criteria, mRECIST stratified into disease control and progression only (HR 0.24, CI: 0.65–0.09, p = 0.002), and RECIST 1.1 showed no predictive value in either stratification. Multivariate Cox regression identified alpha-fetoprotein > 500 ng/mL as a predictor for poor mOS (p = 0.04). Conclusion: The 3D quantitative enhancement-based response assessment tool qEASL can predict overall survival in patients undergoing immunotherapy for HCC and could identify non-responders. Clinical relevance statement: Using 3D quantitative enhancement-based tumor response criteria (qEASL), radiologists' predictions of tumor response in patients undergoing immunotherapy for HCC can be further improved. Key Points: MRI-based tumor response criteria predict immunotherapy survival benefits in HCC patients. 3D tumor response assessment methods surpass current evaluation criteria in predicting overall survival during HCC immunotherapy. Enhancement-based 3D tumor response criteria are robust prognosticators of survival for HCC patients on immunotherapy. [ABSTRACT FROM AUTHOR]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making.
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  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Sobirey%2C+Rabea%22&quot;&gt;Sobirey, Rabea&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Matuschewski%2C+Nickolai%22&quot;&gt;Matuschewski, Nickolai&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Gross%2C+Moritz%22&quot;&gt;Gross, Moritz&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Lin%2C+MingDe%22&quot;&gt;Lin, MingDe&lt;/searchLink&gt;&lt;relatesTo&gt;1,3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Kao%2C+Tabea%22&quot;&gt;Kao, Tabea&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Kasolowsky%2C+Victor%22&quot;&gt;Kasolowsky, Victor&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Strazzabosco%2C+Mario%22&quot;&gt;Strazzabosco, Mario&lt;/searchLink&gt;&lt;relatesTo&gt;4&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Stein%2C+Stacey%22&quot;&gt;Stein, Stacey&lt;/searchLink&gt;&lt;relatesTo&gt;5&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Savic%2C+Lynn+Jeanette%22&quot;&gt;Savic, Lynn Jeanette&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Gebauer%2C+Bernhard%22&quot;&gt;Gebauer, Bernhard&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Jaffe%2C+Ariel%22&quot;&gt;Jaffe, Ariel&lt;/searchLink&gt;&lt;relatesTo&gt;4&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Duncan%2C+James%22&quot;&gt;Duncan, James&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Madoff%2C+David+C%2E%22&quot;&gt;Madoff, David C.&lt;/searchLink&gt;&lt;relatesTo&gt;1,5,6&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Chapiro%2C+Julius%22&quot;&gt;Chapiro, Julius&lt;/searchLink&gt;&lt;relatesTo&gt;1,4&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; julius.chapiro@yale.edu&lt;/i&gt;
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22European+Radiology%22&quot;&gt;European Radiology&lt;/searchLink&gt;. Jan2025, Vol. 35 Issue 1, p73-83. 11p.
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  Label: Abstract
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  Data: Objective: To compare the performance of 1D and 3D tumor response assessment for predicting median overall survival (mOS) in patients who underwent immunotherapy for hepatocellular carcinoma (HCC). Methods: Patients with HCC who underwent immunotherapy between 2017 and 2023 and received multi-phasic contrast-enhanced MRIs pre- and post-treatment were included in this retrospective study. Tumor response was measured using 1D, RECIST 1.1, and mRECIST, and 3D, volumetric, and percentage quantitative EASL (vqEASL and %qEASL). Patients were grouped into disease control vs progression and responders vs non-responders. Kaplan–Meier curves analyzed with log-rank tests assessed the predictive value for mOS. Cox regression modeling evaluated the association of clinical baseline parameters with mOS. Results: This study included 37 patients (mean age, 69.1 years [SD, 8.0]; 33 men). The mOS was 16.9 months. 3D vqEASL and %qEASL successfully stratified patients into disease control and progression (vqEASL: HR 0.21, CI: 0.55–0.08, p &lt; 0.001; %qEASL: HR 0.18, CI: 0.83–0.04, p = 0.013), as well as responder and nonresponder (vqEASL: HR 0.25, CI: 0.08–0.74, p = 0.007; %qEASL: HR 0.17, CI: 0.04–0.72, p = 0.007) for predicting mOS. The 1D criteria, mRECIST stratified into disease control and progression only (HR 0.24, CI: 0.65–0.09, p = 0.002), and RECIST 1.1 showed no predictive value in either stratification. Multivariate Cox regression identified alpha-fetoprotein &gt; 500 ng/mL as a predictor for poor mOS (p = 0.04). Conclusion: The 3D quantitative enhancement-based response assessment tool qEASL can predict overall survival in patients undergoing immunotherapy for HCC and could identify non-responders. Clinical relevance statement: Using 3D quantitative enhancement-based tumor response criteria (qEASL), radiologists&#39; predictions of tumor response in patients undergoing immunotherapy for HCC can be further improved. Key Points: MRI-based tumor response criteria predict immunotherapy survival benefits in HCC patients. 3D tumor response assessment methods surpass current evaluation criteria in predicting overall survival during HCC immunotherapy. Enhancement-based 3D tumor response criteria are robust prognosticators of survival for HCC patients on immunotherapy. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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