Медицинская библиотека · Nature cancer · 2026

Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes.

Jin Darui, Shmatko Artem, Patel Areeba, Rutz Samuel, Friedrich Lukas, Banan Rouzbeh, Rahmanzade Ramin, Sievers Philipp, Hamelmann Stefan, Schrimpf Daniel, Göbel Kirsten, Bogumil Henri, Maas Sybren L N, Sill Martin, Hinz Felix E, Suwala Abigail K, Keller Felix, Habel Antje, Rukhovich Gleb, Zettl Ferdinand, Alhalabi Obada T, Ille Sebastian, Sehring Jannik, Amsel Daniel, Wiestler Benedikt, Piovesan Lago Pedro, Suchorska Bogdana, Ahmad Olfat, Sturm Dominik, Reuss David, Wesseling Pieter, Wöhrer Adelheid, Heppner Frank L, Blümcke Ingmar, Delbridge Claire, Jakobs Martin, Herold-Mende Christel, Krieg Sandro M, Wick Wolfgang, Jones David T W, Pfister Stefan M, Al-Hussaini Maysa, Hou Yanghao, D'Almeida Costa Felipe, Schweizer Leonille, Bertero Luca, Acker Till, Tauziede-Espariat Arnault, Varlet Pascale, Merkler Doron, Egervari Kristof, Dohmen Hildegard, Zoroquiain Pablo, Gejman Roger, Brandner Sebastian, Bai Xiangzhi, von Deimling Andreas, Sahm Felix, Gerstung Moritz

СтатьяВалидационное исследованиеПеревод в очереди

Аннотация

Molecular testing is essential for classifying central nervous system (CNS) tumors, with methylation profiling providing the highest diagnostic granularity. However, this requires more resources and time than conventional hematoxylin and eosin (H&E) histopathology, which is widely available globally. Here we propose Hetairos, an artificial intelligence algorithm that predicts 102 methylation-based CNS tumor subtypes from digital H&E slides. Built and validated on 9,606 patients and over 11,000 slides from 11 centers across four continents, Hetairos identified 50-70% of cases with high confidence, achieving an accuracy of 0.87 for its highest-rated predictions. Hetairos outperformed five board-certified neuropathologists in a direct histology-only comparison (0.68 versus 0.30). Prospective evaluation in routine diagnostics confirmed its performance, reducing turnaround time from 12 days (molecular testing) to 12 min. Hetairos supports diagnostic decision-making across the full spectrum of pediatric and adult CNS tumors by narrowing differential diagnoses and guiding efficient testing.

Для цитирования: Jin Darui, Shmatko Artem, Patel Areeba, Rutz Samuel, Friedrich Lukas, Banan Rouzbeh, Rahmanzade Ramin, Sievers Philipp, Hamelmann Stefan, Schrimpf Daniel, Göbel Kirsten, Bogumil Henri, Maas Sybren L N, Sill Martin, Hinz Felix E, Suwala Abigail K, Keller Felix, Habel Antje, Rukhovich Gleb, Zettl Ferdinand, Alhalabi Obada T, Ille Sebastian, Sehring Jannik, Amsel Daniel, Wiestler Benedikt, Piovesan Lago Pedro, Suchorska Bogdana, Ahmad Olfat, Sturm Dominik, Reuss David, Wesseling Pieter, Wöhrer Adelheid, Heppner Frank L, Blümcke Ingmar, Delbridge Claire, Jakobs Martin, Herold-Mende Christel, Krieg Sandro M, Wick Wolfgang, Jones David T W, Pfister Stefan M, Al-Hussaini Maysa, Hou Yanghao, D'Almeida Costa Felipe, Schweizer Leonille, Bertero Luca, Acker Till, Tauziede-Espariat Arnault, Varlet Pascale, Merkler Doron, Egervari Kristof, Dohmen Hildegard, Zoroquiain Pablo, Gejman Roger, Brandner Sebastian, Bai Xiangzhi, von Deimling Andreas, Sahm Felix, Gerstung Moritz. Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes.. Nature cancer. 2026. DOI: 10.1038/s43018-026-01186-3.

Предметные рубрики MeSH

Central Nervous System Neoplasms DNA Methylation Prediction Algorithms Risk Assessment Hematoxylin Coloring Agents Staining and Labeling Eosine Yellowish-(YS)Fluorescent Dyes Molecular Diagnostic Techniques Time Factors Image Processing, Computer-Assisted Predictive Learning Models Intelligent Systems Humans Survival Rate

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