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Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection

OBJECTIVES: This study aims to better characterize potential responders of Y-90-radioembolization at baseline through analysis of clinical variables and contrast enhanced (CE) MRI tumor volumetry in order to adjust therapeutic regimens early on and to improve treatment outcomes. METHODS: Fifty-eight...

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Autores principales: Lüdemann, Willie, Kahn, Johannes, Pustelnik, Daniel, Hardt, Juliane, Böning, Georg, Jonczyk, Martin, Amthauer, Holger, Gebauer, Bernhard, Hamm, Bernd, Wieners, Gero
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213379/
https://www.ncbi.nlm.nih.gov/pubmed/35230518
http://dx.doi.org/10.1007/s00330-022-08585-x
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author Lüdemann, Willie
Kahn, Johannes
Pustelnik, Daniel
Hardt, Juliane
Böning, Georg
Jonczyk, Martin
Amthauer, Holger
Gebauer, Bernhard
Hamm, Bernd
Wieners, Gero
author_facet Lüdemann, Willie
Kahn, Johannes
Pustelnik, Daniel
Hardt, Juliane
Böning, Georg
Jonczyk, Martin
Amthauer, Holger
Gebauer, Bernhard
Hamm, Bernd
Wieners, Gero
author_sort Lüdemann, Willie
collection PubMed
description OBJECTIVES: This study aims to better characterize potential responders of Y-90-radioembolization at baseline through analysis of clinical variables and contrast enhanced (CE) MRI tumor volumetry in order to adjust therapeutic regimens early on and to improve treatment outcomes. METHODS: Fifty-eight HCC patients who underwent Y-90-radioembolization at our center between 10/2008 and 02/2017 were retrospectively included. Pre- and post-treatment target lesion volumes were measured as total tumor volume (TTV) and enhancing tumor volume (ETV). Survival analysis was performed with Cox regression models to evaluate 65% ETV reduction as surrogate endpoint for treatment efficacy. Univariable and multivariable logistic regression analyses were used to evaluate the combination of baseline clinical variables and tumor volumetry as predictors of ≥ 65% ETV reduction. RESULTS: Mean patients’ age was 66 (SD 8.7) years, and 12 were female (21%). Sixty-seven percent of patients suffered from liver cirrhosis. Median survival was 11 months. A threshold of ≥ 65% in ETV reduction allowed for a significant (p = 0.04) separation of the survival curves with a median survival of 11 months in non-responders and 17 months in responders. Administered activity per tumor volume did predict neither survival nor ETV reduction. A baseline ETV/TTV ratio greater than 50% was the most important predictor of arterial devascularization (odds ratio 6.3) in a statistically significant (p = 0.001) multivariable logistic regression model. The effect size was strong with a Cohen’s f of 0.89. CONCLUSION: We present a novel approach to identify promising candidates for Y-90 radioembolization at pre-treatment baseline MRI using tumor volumetry and clinical baseline variables. KEY POINTS: • A decrease of 65% enhancing tumor volume (ETV) on follow-up imaging 2–3 months after Y-90 radioembolization of HCC enables the early prediction of significantly improved median overall survival (11 months vs. 17 months, p = 0.04). • Said decrease in vascularization is predictable at baseline: an ETV greater than 50% is the most important variable in a multivariable logistic regression model that predicts responders at a high level of significance (p = 0.001) with an area under the curve of 87%. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-08585-x.
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spelling pubmed-92133792022-06-23 Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection Lüdemann, Willie Kahn, Johannes Pustelnik, Daniel Hardt, Juliane Böning, Georg Jonczyk, Martin Amthauer, Holger Gebauer, Bernhard Hamm, Bernd Wieners, Gero Eur Radiol Interventional OBJECTIVES: This study aims to better characterize potential responders of Y-90-radioembolization at baseline through analysis of clinical variables and contrast enhanced (CE) MRI tumor volumetry in order to adjust therapeutic regimens early on and to improve treatment outcomes. METHODS: Fifty-eight HCC patients who underwent Y-90-radioembolization at our center between 10/2008 and 02/2017 were retrospectively included. Pre- and post-treatment target lesion volumes were measured as total tumor volume (TTV) and enhancing tumor volume (ETV). Survival analysis was performed with Cox regression models to evaluate 65% ETV reduction as surrogate endpoint for treatment efficacy. Univariable and multivariable logistic regression analyses were used to evaluate the combination of baseline clinical variables and tumor volumetry as predictors of ≥ 65% ETV reduction. RESULTS: Mean patients’ age was 66 (SD 8.7) years, and 12 were female (21%). Sixty-seven percent of patients suffered from liver cirrhosis. Median survival was 11 months. A threshold of ≥ 65% in ETV reduction allowed for a significant (p = 0.04) separation of the survival curves with a median survival of 11 months in non-responders and 17 months in responders. Administered activity per tumor volume did predict neither survival nor ETV reduction. A baseline ETV/TTV ratio greater than 50% was the most important predictor of arterial devascularization (odds ratio 6.3) in a statistically significant (p = 0.001) multivariable logistic regression model. The effect size was strong with a Cohen’s f of 0.89. CONCLUSION: We present a novel approach to identify promising candidates for Y-90 radioembolization at pre-treatment baseline MRI using tumor volumetry and clinical baseline variables. KEY POINTS: • A decrease of 65% enhancing tumor volume (ETV) on follow-up imaging 2–3 months after Y-90 radioembolization of HCC enables the early prediction of significantly improved median overall survival (11 months vs. 17 months, p = 0.04). • Said decrease in vascularization is predictable at baseline: an ETV greater than 50% is the most important variable in a multivariable logistic regression model that predicts responders at a high level of significance (p = 0.001) with an area under the curve of 87%. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-08585-x. Springer Berlin Heidelberg 2022-03-01 2022 /pmc/articles/PMC9213379/ /pubmed/35230518 http://dx.doi.org/10.1007/s00330-022-08585-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Interventional
Lüdemann, Willie
Kahn, Johannes
Pustelnik, Daniel
Hardt, Juliane
Böning, Georg
Jonczyk, Martin
Amthauer, Holger
Gebauer, Bernhard
Hamm, Bernd
Wieners, Gero
Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
title Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
title_full Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
title_fullStr Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
title_full_unstemmed Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
title_short Yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
title_sort yttrium-90 radioembolization for unresectable hepatocellular carcinoma: predictive modeling strategies to anticipate tumor response and improve patient selection
topic Interventional
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213379/
https://www.ncbi.nlm.nih.gov/pubmed/35230518
http://dx.doi.org/10.1007/s00330-022-08585-x
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