Intelligent Histology for Tumor Neurosurgery

• URL: http://arxiv.org/abs/2507.03037v1
• Date: Thu, 03 Jul 2025 03:45:09 GMT
• Title: Intelligent Histology for Tumor Neurosurgery
• Authors: Xinhai Hou, Akhil Kondepudi, Cheng Jiang, Yiwei Lyu, Samir Harake, Asadur Chowdury, Anna-Katharina Meißner, Volker Neuschmelting, David Reinecke, Gina Furtjes, Georg Widhalm, Lisa Irina Koerner, Jakob Straehle, Nicolas Neidert, Pierre Scheffler, Juergen Beck, Michael Ivan, Ashish Shah, Aditya Pandey, Sandra Camelo-Piragua, Dieter Henrik Heiland, Oliver Schnell, Chris Freudiger, Jacob Young, Melike Pekmezci, Katie Scotford, Shawn Hervey-Jumper, Daniel Orringer, Mitchel Berger, Todd Hollon,
• Abstract summary: Intelligent histology integrates artificial intelligence (AI) with stimulated Raman histology (SRH)<n>SRH generates high-resolution digital images of surgical specimens within seconds, enabling AI-driven tumor histologic analysis, molecular classification, and tumor infiltration detection.<n>Future directions include the development of AI foundation models through multi-institutional datasets, incorporating clinical and radiologic data for multimodal learning, and predicting patient outcomes.
• Score: 12.480562493406904
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standard-of-care intraoperative pathology workflow is based on light microscopy and H\&E histology, which is slow, resource-intensive, and lacks real-time digital imaging capabilities. Here, we present an emerging and innovative method for intraoperative histologic analysis, called Intelligent Histology, that integrates artificial intelligence (AI) with stimulated Raman histology (SRH). SRH is a rapid, label-free, digital imaging method for real-time microscopic tumor tissue analysis. SRH generates high-resolution digital images of surgical specimens within seconds, enabling AI-driven tumor histologic analysis, molecular classification, and tumor infiltration detection. We review the scientific background, clinical translation, and future applications of intelligent histology in tumor neurosurgery. We focus on the major scientific and clinical studies that have demonstrated the transformative potential of intelligent histology across multiple neurosurgical specialties, including neurosurgical oncology, skull base, spine oncology, pediatric tumors, and periperal nerve tumors. Future directions include the development of AI foundation models through multi-institutional datasets, incorporating clinical and radiologic data for multimodal learning, and predicting patient outcomes. Intelligent histology represents a transformative intraoperative workflow that can reinvent real-time tumor analysis for 21st century neurosurgery.

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