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<p>There is a need for robust evaluations of noninvasive biomarkers for metabolic dysfunction-associated steatotic liver disease. This prospective multicenter study assessed the diagnostic accuracy of imaging (including liver stiffness measurement (LSM) using magnetic resonance elastography (MRE) and FibroScan (vibration-controlled transient elastography (VCTE)), serum biomarkers (including NIS2+) and composite scores (including Agile 3+ and Agile 4) for centrally read steatohepatitis and fibrosis. For cirrhosis, several biomarkers exceeded the minimum acceptable performance criterion (MAC), including MRE (area under the receiver operating curve (AUC) 0.91; <i>P</i> &lt; 0.01), VCTE-LSM (AUC 0.87; <i>P</i> &lt; 0.01), Agile 3+ (AUC 0.89; <i>P</i> &lt; 0.01) and Agile 4 (AUC 0.88; <i>P</i> &lt; 0.01). Among 357 participants, fibrosis stages F0–F4 were present in 12%, 16%, 25%, 32% and 15%, respectively. NIS2+ had the highest diagnostic accuracy among serum biomarkers for metabolic dysfunction-associated steatohepatitis (MASH; AUC 0.83) and at-risk MASH (MASH with at least stage 2 fibrosis; AUC 0.82), although neither significantly exceeded the MAC (<i>P</i> = 0.15 and <i>P</i> = 0.19). Among imaging biomarkers, MRE showed the highest performance for MASH (AUC 0.71) and at-risk MASH (AUC 0.75), but these remained below the MAC. For fibrosis staging, performance was stronger: MRE met the MAC for advanced fibrosis (AUC 0.91; <i>P</i> &lt; 0.01), as did Agile 3+ (AUC 0.84; <i>P</i> = 0.03). For cirrhosis, several biomarkers exceeded the MAC, including MRE (AUC 0.91; <i>P</i> &lt; 0.01), VCTE-LSM (AUC 0.87; <i>P</i> &lt; 0.01), Agile 3+ (AUC 0.89; <i>P</i> &lt; 0.01) and Agile 4 (AUC 0.88; <i>P</i> &lt; 0.01). Serum biomarkers tended to outperform imaging for identifying at-risk MASH, whereas elastography and composite scores showed excellent accuracy for staging advanced fibrosis and cirrhosis.</p>

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Prospective validation of imaging and serum diagnostic biomarkers of steatohepatitis and fibrosis in MASLD: the LITMUS Imaging Study

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  • 发表日期：

    2026年7月24日

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  • Michael Pavlides,
  • Yasaman Vali,
  • Ferenc E. Mózes,
  • Kristy Wonders,
  • Salma Akhtar,
  • Paul D. Hockings,
  • Elizabeth Shumbayawonda,
  • Kay Pepin,
  • Isabel Fernandez-Lizaranzu,
  • Diana Julie Leeming,
  • Jeremy F. Cobbold,
  • Michael E. D. Allison,
  • Guruprasad P. Aithal,
  • Manuel Romero-Gomez,
  • Rocio Aller,
  • Juan M. Pericàs,
  • Jérôme Boursier,
  • Salvatore Petta,
  • Jörn M. Schattenberg,
  • Mattias Ekstedt,
  • Annalisa Berzigotti,
  • Hannele Yki-Järvinen,
  • Miljen Martic,
  • Theresa Tuthill,
  • Clifford A. Brass,
  • Michael Kalutkiewicz,
  • Rajarshi Banerjee,
  • Richard L. Ehman,
  • Moritz J. Schneider,
  • Dina Tiniakos,
  • Morten Karsdal,
  • Jeremy Magnanensi,
  • Céline Fournier-Poizat,
  • Vlad Ratziu,
  • Carla Yunis,
  • Elisabetta Bugianesi,
  • Stephen A. Harrison,
  • Quentin M. Anstee,
  • Ann Daly,
  • Fiona Oakley,
  • Simon J. Cockell,
  • Dina Tiniakos,
  • Pierre Bedossa,
  • Heather J. Cordell,
  • Christopher P. Day,
  • Kristy Wonders,
  • Olivier Govaere,
  • Paolo Missier,
  • Matthew McTeer,
  • Luke Vale,
  • Yemi Oliboyede,
  • Matt Breckons,
  • Patrick M. Bossuyt,
  • Yasaman Vali,
  • Jenny Lee,
  • Max Nieuwdorp,
  • Yair Acherman,
  • Arnold van de Laar,
  • Athanasios Angelakis,
  • Adriaan G. Holleboom,
  • Vlad Ratziu,
  • Karine Clément,
  • Rafael Patino-Navarrete,
  • Raluca Pais,
  • Valerie Paradis,
  • Mathilde Wagner,
  • Jörn M. Schattenberg,
  • Maurice Michel,
  • Detlef Schuppan,
  • Sudha Myneni,
  • Rambabu Surabattula,
  • Beate K. Straub,
  • Emrich Tilman,
  • Toni Vidal-Puig,
  • Sergio Rodrigues-Cuenca,
  • Ioannis Kamzolas,
  • Evangelia Petsalaki,
  • Mark Campbell,
  • Chris J. Lelliott,
  • Michael E. D. Allison,
  • Susan Davies,
  • Edmund Godfrey,
  • Michele Vacca,
  • Matej Orešič,
  • Aidan McGlinchey,
  • Tuulia Hyötyläinen,
  • Jose M. Mato,
  • Óscar Millet,
  • Annalisa Berzigotti,
  • Jean-François Dufour,
  • Naomi F. Lange,
  • Adrian T. Huber,
  • Michael Pavlides,
  • Jeremy F. Cobbold,
  • Stefan Neubauer,
  • Ferenc E. Mozes,
  • Salma Akhtar,
  • Stephen A. Harrison,
  • Seliat Olodo-Atitebi,
  • Rajarshi Banerjee,
  • Elizabeth Shumbayawonda,
  • Andrea Dennis,
  • Anneli Andersson,
  • Manuel Romero-Gómez,
  • Rocío Gallego-Durán,
  • Rocío Montero-Vallejo,
  • Isabel Fernandez-Lizarazu,
  • Sheila Gato,
  • Javier Castell,
  • Morten Karsdal,
  • Diana Julie Leeming,
  • Kishwar Musa,
  • Maria Manuela Tonini,
  • Elisabetta Bugianesi,
  • Chiara Rosso,
  • Angelo Armandi,
  • Ricardo Faletti,
  • Fabio Marra,
  • Amalia Gastaldelli,
  • Fabrizia Carli,
  • Gianluca Svegliati-Baroni,
  • Jérôme Boursier,
  • Marc de Saint Loup,
  • Pierre Celea,
  • Christophe Aube,
  • Sven M. A. Francque,
  • Wilhelmus J. Kwanten,
  • Luisa Vonghia,
  • An Verrijken,
  • Eveline Dirinck,
  • Ann Driessen,
  • Mattias Ekstedt,
  • Stergios Kechagias,
  • Peter Lundberg,
  • Hannele Yki-Järvinen,
  • Kimmo Porthan,
  • Johanna Arola,
  • Saskia van Mil,
  • George Papatheodoridis,
  • Helena Cortez-Pinto,
  • Mariana Verdelho Machado,
  • Sofia Carvalhana,
  • Cecilia M. P. Rodrigues,
  • Luca V. C. Valenti,
  • Serena Pelusi,
  • Salvatore Petta,
  • Grazia Penisi,
  • Rosaria Maria Pipitone,
  • Adele Tulone,
  • Stefania Grimaudo,
  • Michela Antonucci,
  • Luca Miele,
  • Antonio Liguori,
  • Francesca D’Ambrosio,
  • Andreas Geier,
  • P. D. Monika Rau,
  • Hans Benno Leicht,
  • Florian Reiter,
  • Guruprasad P. Aithal,
  • Susan Francis,
  • Naaventhan Palaniyappan,
  • Christopher Bradley,
  • Paul D. Hockings,
  • Moritz J. Schneider,
  • Philip N. Newsome,
  • David Wenn,
  • Jeremy Magnanensi,
  • Aldo Trylesinski,
  • Rebeca Mayo,
  • Cristina Alonso,
  • Kevin L. Duffin,
  • James W. Perfield,
  • Mark L. Hartman,
  • Yu Chen,
  • Carla Yunis,
  • Theresa Tuthill,
  • Trenton Ross,
  • Barbara Bernardo,
  • Magdalena Alicja Harrington,
  • Euan McLeod,
  • Judith Ertle,
  • Ramy Younes,
  • Harvey Coxson,
  • Joseph Gogain,
  • Hannah R. Biegel,
  • Leigh Alexander,
  • Rachel Ostroff,
  • Mette Skalshøi Kjær,
  • Lea Mørch Harder,
  • Sanne S. Veidal,
  • Naba Al-Sari,
  • Daniel Guldager Kring Rasmussen,
  • Maria-Magdalena Balp,
  • Clifford A. Brass,
  • Lori Jennings,
  • Miljen Martic,
  • Jurgen Loffler,
  • Douglas Applegate,
  • Richard Torstenson,
  • Daniel Lindén,
  • Céline Fournier-Poizat,
  • Anne Llorca,
  • Michael Kalutkiewicz,
  • Richard L. Ehman,
  • Kay Pepin,
  • Gerald Horan,
  • Gideon Ho,
  • Dean Tai,
  • Elaine Chng,
  • Yayun Ren,
  • Scott D. Patterson,
  • Andrew N. Billin,
  • Lynda C. Doward,
  • James Twiss,
  • Paresh Thakker,
  • Zoltan Derdak,
  • Henrik Landgren,
  • Carolin Lackner,
  • Annette S. H. Gouw,
  • Prodromos Hytiroglou,
  • Rocio Aller,
  • Rebeca Sigüenza González,
  • Juan M. Pericàs,
  • Salvador Agustin,
  • Jesús M. Rivera-Esteban,
  • Sergio Muñoz-Martínez,
  • Alba M. Jiménez-Masip,
  • Laura Pagès,
  • Diego Rojo,
  • Patrick M. Bossuyt,
  • Quentin M. Anstee

摘要

There is a need for robust evaluations of noninvasive biomarkers for metabolic dysfunction-associated steatotic liver disease. This prospective multicenter study assessed the diagnostic accuracy of imaging (including liver stiffness measurement (LSM) using magnetic resonance elastography (MRE) and FibroScan (vibration-controlled transient elastography (VCTE)), serum biomarkers (including NIS2+) and composite scores (including Agile 3+ and Agile 4) for centrally read steatohepatitis and fibrosis. For cirrhosis, several biomarkers exceeded the minimum acceptable performance criterion (MAC), including MRE (area under the receiver operating curve (AUC) 0.91; P < 0.01), VCTE-LSM (AUC 0.87; P < 0.01), Agile 3+ (AUC 0.89; P < 0.01) and Agile 4 (AUC 0.88; P < 0.01). Among 357 participants, fibrosis stages F0–F4 were present in 12%, 16%, 25%, 32% and 15%, respectively. NIS2+ had the highest diagnostic accuracy among serum biomarkers for metabolic dysfunction-associated steatohepatitis (MASH; AUC 0.83) and at-risk MASH (MASH with at least stage 2 fibrosis; AUC 0.82), although neither significantly exceeded the MAC (P = 0.15 and P = 0.19). Among imaging biomarkers, MRE showed the highest performance for MASH (AUC 0.71) and at-risk MASH (AUC 0.75), but these remained below the MAC. For fibrosis staging, performance was stronger: MRE met the MAC for advanced fibrosis (AUC 0.91; P < 0.01), as did Agile 3+ (AUC 0.84; P = 0.03). For cirrhosis, several biomarkers exceeded the MAC, including MRE (AUC 0.91; P < 0.01), VCTE-LSM (AUC 0.87; P < 0.01), Agile 3+ (AUC 0.89; P < 0.01) and Agile 4 (AUC 0.88; P < 0.01). Serum biomarkers tended to outperform imaging for identifying at-risk MASH, whereas elastography and composite scores showed excellent accuracy for staging advanced fibrosis and cirrhosis.