AI-derived body composition parameters as prognostic factors in patients with HCC undergoing TACE in a multicenter study

Background & Aims - Body composition assessment (BCA) parameters have recently been identified as relevant prognostic factors for patients with hepatocellular carcinoma (HCC). Herein, we aimed to investigate the role of BCA parameters for prognosis prediction in patients with HCC undergoing tran...

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Hauptverfasser: Müller, Lukas (VerfasserIn) , Mähringer-Kunz, Aline (VerfasserIn) , Auer, Timo Alexander (VerfasserIn) , Fehrenbach, Uli (VerfasserIn) , Gebauer, Bernhard (VerfasserIn) , Haubold, Johannes (VerfasserIn) , Schaarschmidt, Benedikt Michael (VerfasserIn) , Kim, Moon-Sung (VerfasserIn) , Hosch, René (VerfasserIn) , Nensa, Felix (VerfasserIn) , Kleesiek, Jens (VerfasserIn) , Diallo, Thierno D. (VerfasserIn) , Eisenblätter, Michel (VerfasserIn) , Kuzior, Hanna (VerfasserIn) , Roehlen, Natascha (VerfasserIn) , Bettinger, Dominik (VerfasserIn) , Wagner, Verena (VerfasserIn) , Mayer, Philipp (VerfasserIn) , Zopfs, David (VerfasserIn) , Pinto Dos Santos, Daniel (VerfasserIn) , Kloeckner, Roman (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: August 2024
In: JHEP reports
Year: 2024, Jahrgang: 6, Heft: 8, Pages: 1-11
ISSN:2589-5559
DOI:10.1016/j.jhepr.2024.101125
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.jhepr.2024.101125
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2589555924001290
Volltext
Verfasserangaben:Lukas Müller, Aline Mähringer-Kunz, Timo Alexander Auer, Uli Fehrenbach, Bernhard Gebauer, Johannes Haubold, Benedikt Michael Schaarschmidt, Moon-Sung Kim, René Hosch, Felix Nensa, Jens Kleesiek, Thierno D. Diallo, Michel Eisenblätter, Hanna Kuzior, Natascha Roehlen, Dominik Bettinger, Verena Steinle, Philipp Mayer, David Zopfs, Daniel Pinto Dos Santos, Roman Kloeckner

MARC

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520 |a Background & Aims - Body composition assessment (BCA) parameters have recently been identified as relevant prognostic factors for patients with hepatocellular carcinoma (HCC). Herein, we aimed to investigate the role of BCA parameters for prognosis prediction in patients with HCC undergoing transarterial chemoembolization (TACE). - Methods - This retrospective multicenter study included a total of 754 treatment-naïve patients with HCC who underwent TACE at six tertiary care centers between 2010-2020. Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition was performed to assess skeletal muscle volume (SM), total adipose tissue (TAT), intra- and intermuscular adipose tissue, visceral adipose tissue, and subcutaneous adipose tissue (SAT) on pre-intervention computed tomography scans. BCA parameters were normalized to the slice number of the abdominal cavity. We assessed the influence of BCA parameters on median overall survival and performed multivariate analysis including established estimates of survival. - Results - Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (p <0.001), high TAT volume (p = 0.013), and high SAT volume (p = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (p = 0.039), while TAT and SAT volumes no longer showed predictive ability. This predictive role of SM was confirmed in a subgroup analysis of patients with BCLC stage B. - Conclusions - SM is an independent prognostic factor for survival prediction. Thus, the integration of SM into novel scoring systems could potentially improve survival prediction and clinical decision-making. Fully automated approaches are needed to foster the implementation of this imaging biomarker into daily routine. - Impact and implications: - Body composition assessment parameters, especially skeletal muscle volume, have been identified as relevant prognostic factors for many diseases and treatments. In this study, skeletal muscle volume has been identified as an independent prognostic factor for patients with hepatocellular carcinoma undergoing transarterial chemoembolization. Therefore, skeletal muscle volume as a metaparameter could play a role as an opportunistic biomarker in holistic patient assessment and be integrated into decision support systems. Workflow integration with artificial intelligence is essential for automated, quantitative body composition assessment, enabling broad availability in multidisciplinary case discussions. 
650 4 |a Artificial Intelligence 
650 4 |a Body Composition 
650 4 |a Hepatocellular Carcinoma 
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