Intelligent Histology for Tumor Neurosurgery
Xinhai Hou, Akhil Kondepudi, Cheng Jiang, Yiwei Lyu, Samir Harake, Asadur Chowdury, Anna-Katharina Mei{\ss}ner, Volker Neuschmelting, David Reinecke, Gina Furtjes, Georg Widhalm, Lisa Irina Koerner, Jakob Straehle, Nicolas Neidert, Pierre Scheffler, Juergen Beck, Michael Ivan

TL;DR
Intelligent Histology combines AI with stimulated Raman histology to enable rapid, real-time, digital tumor tissue analysis during neurosurgery, potentially transforming intraoperative decision-making.
Contribution
The paper introduces a novel intraoperative histologic method integrating AI with stimulated Raman histology for real-time tumor analysis.
Findings
SRH provides high-resolution digital images within seconds.
AI enables tumor classification and infiltration detection.
Potential to improve surgical outcomes through rapid analysis.
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…
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