Fast intraoperative detection of primary CNS lymphoma and differentiation from common CNS tumors using stimulated Raman histology and deep learning.

Autor:	Reinecke D; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA.; Department of General Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Maarouf N; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA., Smith A; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA., Alber D; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA., Markert J; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA.; Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, USA., Goff NK; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA.; Department of Neurosurgery, University of Texas at Austin Dell Medical School, Austin, USA., Hollon TC; Machine Learning in Neurosurgery Laboratory, Department of Neurosurgery, University of Michigan, Ann Arbor, USA., Chowdury A; Machine Learning in Neurosurgery Laboratory, Department of Neurosurgery, University of Michigan, Ann Arbor, USA., Jiang C; Machine Learning in Neurosurgery Laboratory, Department of Neurosurgery, University of Michigan, Ann Arbor, USA., Hou X; Machine Learning in Neurosurgery Laboratory, Department of Neurosurgery, University of Michigan, Ann Arbor, USA., Meissner AK; Department of General Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Fürtjes G; Department of General Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Ruge MI; Department of Stereotactic and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.; Center for Integrated Oncology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Ruess D; Department of Stereotactic and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.; Center for Integrated Oncology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Stehle T; Institute for Neuropathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Al-Shughri A; Institute for Neuropathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Körner LI; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria., Widhalm G; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria., Roetzer-Pejrimovsky T; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.; Comprehensive Center for Clinical Neurosciences & Mental Health, Medical University of Vienna, Vienna, Austria., Golfinos JG; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA., Snuderl M; Department of Pathology, New York Grossman School of Medicine, New York, USA., Neuschmelting V; Department of General Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.; Center for Integrated Oncology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany., Orringer DA; Department of Neurosurgery, New York University Grossman School of Medicine, New York, USA.; Department of Pathology, New York Grossman School of Medicine, New York, USA.
Jazyk:	angličtina
Zdroj:	Neuro-oncology [Neuro Oncol] 2024 Dec 14. Date of Electronic Publication: 2024 Dec 14.
DOI:	10.1093/neuonc/noae270
Abstrakt:	Background: Accurate intraoperative diagnosis is crucial for differentiating between primary CNS lymphoma (PCNSL) and other CNS entities, guiding surgical decision-making, but represents significant challenges due to overlapping histomorphological features, time constraints, and differing treatment strategies. We combined stimulated Raman histology (SRH) with deep learning to address this challenge. Methods: We imaged unprocessed, label-free tissue samples intraoperatively using a portable Raman scattering microscope, generating virtual H&E-like images within less than three minutes. We developed a deep learning pipeline called RapidLymphoma based on a self-supervised learning strategy to (1) detect PCNSL, (2) differentiate from other CNS entities, and (3) test the diagnostic performance in a prospective international multicenter cohort and two additional independent test cohorts. We trained on 54,000 SRH patch images sourced from surgical resections and stereotactic-guided biopsies, including various CNS neoplastic/non-neoplastic lesions. Training and test data were collected from four tertiary international medical centers. The final histopathological diagnosis served as ground-truth. Results: In the prospective test cohort of PCNSL and non-PCNSL entities (n=160), RapidLymphoma achieved an overall balanced accuracy of 97.81% ±0.91, non-inferior to frozen section analysis in detecting PCNSL (100% vs. 77.77%). The additional test cohorts (n=420, n=59) reached balanced accuracy rates of 95.44% ±0.74 and 95.57% ±2.47 in differentiating IDH-wildtype diffuse gliomas and various brain metastasis from PCNSL. Visual heatmaps revealed RapidLymphoma's capabilities to detect class-specific histomorphological key features. Conclusions: RapidLymphoma proves reliable and valid for intraoperative PCNSL detection and differentiation from other CNS entities. It provides visual feedback within three minutes, enabling fast clinical decision-making and subsequent treatment strategy planning. (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
Databáze:	MEDLINE
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