Evidence map›Paper›PMID 41938755›Full record

ReviewNeuro-oncology advances

Intelligent histology for tumor neurosurgery.

Xinhai Hou, Akhil V Kondepudi, Cheng Jiang, Yiwei Lyu, Edward Samir Harake, Asadur Chowdury, Anna-Katharina Meißner, Volker Neuschmelting, David Reinecke, Gina Fürtjes and 20 more

Abstract readReview
In one paragraph

Review in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Contemporary surgical strategies for resection of intracranial gliomas.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors.

Xinhai HouDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Akhil V KondepudiDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Cheng JiangDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Yiwei LyuDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Edward Samir HarakeDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Asadur ChowduryDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Anna-Katharina MeißnerDepartment of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Volker NeuschmeltingDepartment of Neurosurgery, University Hospital Cologne, Cologne, Germany.
David ReineckeDepartment of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Gina FürtjesDepartment of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Georg WidhalmDepartment of Neurosurgery, Medical University of Vienna, Vienna, Austria.
Lisa Irinia KörnerDepartment of Neurosurgery, Medical University of Vienna, Vienna, Austria.
Jakob StraehleDepartment of Neurosurgery, University Medical Center Freiburg, Freiburg, Germany.
Nicolas NeidertDepartment of Neurosurgery, University Medical Center Freiburg, Freiburg, Germany.
Pierre SchefflerDepartment of Neurosurgery, University Medical Center Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0002-6596-456X
Jüergen BeckDepartment of Neurosurgery, University Medical Center Freiburg, Freiburg, Germany.
Michael E IvanDepartment of Neurosurgery, University of Miami, Miami, Florida.
Ashish H ShahDepartment of Neurosurgery, University of Miami, Miami, Florida.
Aditya S PandeyDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.
Sandra Camelo-PiraguaDepartment of Pathology, University of Michigan, Ann Arbor, Michigan.
Dieter Henrik HeilandDepartment of Neurosurgery, University Hospital Erlangen, Erlangen, Germany.
Oliver SchnellDepartment of Neurosurgery, University Hospital Erlangen, Erlangen, Germany.
Chris FreudigerInvenio Imaging Inc., Santa Clara, California.
Jacob YoungDepartment of Neurosurgery, University of California, San Francisco, California.
Melike PekmezciDepartment of Neurosurgery, University of California, San Francisco, California.
Katie ScotfordDepartment of Neurosurgery, University of California, San Francisco, California.
Shawn Hervey-JumperDepartment of Neurosurgery, University of California, San Francisco, California.ORCID https://orcid.org/0000-0003-4699-260X
Daniel OrringerDepartment of Neurosurgery, NYU Langone Health, New York, New York.ORCID https://orcid.org/0000-0001-6427-8376
Mitchel BergerDepartment of Neurosurgery, University of California, San Francisco, California.ORCID https://orcid.org/0000-0003-1983-4892
Todd HollonDepartment of Neurosurgery, University of Michigan, Ann Arbor, Michigan.ORCID https://orcid.org/0000-0001-5987-6531

Funding

MICHIGAN MEDICAL SCIENTIST TRAINING PROGRAMT32GM007863 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COLLINS, KATHLEEN L. · 1985 to 2024
$38.3M
Transitioning Early Career Neurosurgeons to Scientific IndependenceK12NS080223 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI ESKANDAR, EMAD N · 2012 to 2022
$9.2M
Clinical Translation of Stimulated Raman HistologyR01CA226527 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ORRINGER, DANIEL · 2018 to 2025
$4.4M
UCSF Paul Calabresi K12 Career Development Program in Clinical OncologyK12CA260225 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BERGSLAND, EMILY K, BIVONA, TREVER G · 2021 to 2025
$2.6M
DeepSRH: Transforming Molecular Cancer Screening with Stimulated Raman Histology and Deep Neural NetworksR01CA292529 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HOLLON, TODD CHARLES, LEE, HONGLAK · 2025 to 2025
$2.3M
Single-cell optical phenotyping for diffuse gliomas using artificial intelligence and label-free microscopyF31NS135973 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Cheng Jiang · 2024 to 2026
$128k
NCI NIH HHS K12 CA260225NCI NIH HHS R01 CA226527NCI NIH HHS R01 CA292529NIGMS NIH HHS T32 GM007863NINDS NIH HHS F31 NS135973NINDS NIH HHS K12 NS080223
6 · The paper itself

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 describe 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 peripheral 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.

Identifiers

PMID41938755
PMCPMC13047285

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.