Evidence map›Paper›PMID 41322957›Full record

ArticleEuropean urology open science2025

Validation of Artificial Intelligence-enhanced Stimulated Raman Histopathology for Intraoperative Margin Assessment During Robot-assisted Radical Prostatectomy: Preliminary Results from the ROBOSPEC Study.

Arif Özkan, Karl-Moritz Schröder, Peter Bronsert, Julia Franz, Maximilian Glienke, August Sigle, Jürgen Beck, Martin Werner, Christian Gratzke, Jakob Straehle and 3 more

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Article in European urology open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Review
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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

13 authors.

Arif ÖzkanDepartment of Urology, University of Freiburg Medical Center, Freiburg, Germany.
Karl-Moritz SchröderFaculty of Medicine, University of Freiburg, Freiburg, Germany.
Peter BronsertFaculty of Medicine, University of Freiburg, Freiburg, Germany.
Julia FranzDepartment of Urology, University of Freiburg Medical Center, Freiburg, Germany.
Maximilian GlienkeDepartment of Urology, University of Freiburg Medical Center, Freiburg, Germany.
August SigleDepartment of Urology, University of Freiburg Medical Center, Freiburg, Germany.
Jürgen BeckFaculty of Medicine, University of Freiburg, Freiburg, Germany.
Martin WernerFaculty of Medicine, University of Freiburg, Freiburg, Germany.
Christian GratzkeDepartment of Urology, University of Freiburg Medical Center, Freiburg, Germany.
Jakob StraehleFaculty of Medicine, University of Freiburg, Freiburg, Germany.
Samir S TanejaDepartment of Urology, NYU Langone Health, New York, NY, USA.
Miles P MannasDepartment of Urologic Sciences, University of British Columbia, Vancouver, Canada.
Nikolaos LiakosDepartment of Urology, University of Freiburg Medical Center, Freiburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective: Stimulated Raman histology (SRH) offers promising near-real-time tissue visualization for intraoperative pathology assessment. We present preliminary results from the ROBOSPEC study, with a focus on the accuracy of results obtained via an integrated artificial intelligence (AI) tool. Methods: ROBOSPEC is a prospective, single-arm pilot study involving patients with prostate cancer undergoing robot-assisted radical prostatectomy (RARP). Probes from the RP specimens from the first 18 patients with intermediate-risk or high-risk prostate cancer were collected bilaterally from the dorsolateral sides of the prostate and examined with frozen section with hematoxylin and eosin staining (cryo-HE), SRH imaging (NIO laser imaging system, Invenio Imaging, Santa Clara, CA, USA). A previously published New York University AI algorithm (NYU-AI) that is based on the Inception-ResNet-v2 CNN architecture was used to generate three-color overlays to assist in interpretation. SRH images were reviewed by blinded urologists using this AI-enhanced output. Key findings and limitations: NYU-AI identified positive surgical margins in 22% of patients, with no statistically significant difference in comparison to cryo-HE ( Conclusions and clinical implications: Our preliminary findings support the potential of SRH with NYU-AI for intraoperative detection of positive surgical margins during RARP. Implementation of this technique should be further discussed after more studies have been conducted. Patient summary: We looked at an artificial intelligence program using a method called stimulated Raman histology to assess the cancer status of the cutting margin during robot-assisted surgery to remove the prostate. Our preliminary results show that this method could be an alternative to the current standard as it provides accurate and faster results.

Indexed as

Artificial intelligenceIntraoperative frozen sectionsRobot-assisted prostatectomyStimulated Raman spectroscopy

Identifiers

PMID41322957
PMCPMC12663661

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