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<p>The clinical course of Mantle Cell Lymphoma (MCL) varies between individual patients. Early detection of risk is crucial to assign MCL patients to novel treatment strategies. Most of the established biomarkers of outcome require specifically trained pathologists or molecular analysis. Here we introduce MAIPI (MCL Artificial Intelligence Prognostic Index), a deep learning algorithm trained only on Hematoxylin and Eosin (H&amp;E) images of diagnostic biopsies of <i>n</i> = 428 MCL patients from clinical trials to assess prognosis. The capability of MAIPI to predict disease outcome was validated in an independent cohort of <i>n</i> = 140 patients treated with immunochemotherapy with and without ibrutinib. MAIPI selects areas of interest by itself and provides prognostic information independent of the MCL International Prognostic Index (MIPI) and Ki67 and without the need of molecular testing or expert pathologists evaluation.</p>

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Mantle cell lymphoma artificial intelligence prognostic index using hematoxylin and eosin histology

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月7日

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  • Jonas Lippl,
  • Sarah Reinke,
  • Karoline Koch,
  • Ilske Oschlies,
  • Stefan Schrod,
  • Lukas Wolfseher,
  • Paul Hüttl,
  • Michael Huttner,
  • Silvia Beà,
  • Elias Campo,
  • Marco Ladetto,
  • Sergio Cogliatti,
  • Mats Ehinger,
  • Grzegorz Rymkiewicz,
  • Valentina Tabanelli,
  • Hilka Rauert-Wunderlich,
  • Andreas Rosenwald,
  • Rainer Spang,
  • Eva Hoster,
  • Martin Dreyling,
  • Michael Altenbuchinger,
  • Wolfram Klapper,
  • Martin Dreyling,
  • Sílvia Beà,
  • Marco Ladetto,
  • Elias Campo,
  • Francesca Cordero,
  • Sara Ek,
  • Simone Ferrero,
  • Eva Ginè,
  • Georg Hess,
  • Eva Hoster,
  • Mats Jerkeman,
  • Wolfram Klapper,
  • Pavel Klener,
  • Christiane Pott,
  • Hilka Rauert-Wunderlich,
  • Andreas Rosenwald

摘要

The clinical course of Mantle Cell Lymphoma (MCL) varies between individual patients. Early detection of risk is crucial to assign MCL patients to novel treatment strategies. Most of the established biomarkers of outcome require specifically trained pathologists or molecular analysis. Here we introduce MAIPI (MCL Artificial Intelligence Prognostic Index), a deep learning algorithm trained only on Hematoxylin and Eosin (H&E) images of diagnostic biopsies of n = 428 MCL patients from clinical trials to assess prognosis. The capability of MAIPI to predict disease outcome was validated in an independent cohort of n = 140 patients treated with immunochemotherapy with and without ibrutinib. MAIPI selects areas of interest by itself and provides prognostic information independent of the MCL International Prognostic Index (MIPI) and Ki67 and without the need of molecular testing or expert pathologists evaluation.