Evidence map›Paper›PMID 42234114›Full record

ArticleVirchows Archiv : an international journal of pathology2026

An artificial intelligence solution for evaluation of prostate needle core biopsy specimens: impact in a non-specialist setting.

Gerald Niedobitek, Gernot Schmitz, Manuel Fella, André Oliveira, John Theunissen, Manuela Vecsler, Jens Köllermann

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Article in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Gerald NiedobitekInstitute for Pathology, Sana Klinikum Lichtenberg, Berlin, Germany. niedobitekg@gmail.com.ORCID http://orcid.org/0000-0003-4474-1882
Gernot SchmitzInstitute for Pathology, Sana Klinikum Lichtenberg, Berlin, Germany.
Manuel FellaInstitute for Pathology, Sana Klinikum Lichtenberg, Berlin, Germany.
André OliveiraInstitute for Pathology, Sana Klinikum Lichtenberg, Berlin, Germany.
John TheunissenIbex Medical Analytics, Tel Aviv, Israel.
Manuela VecslerIbex Medical Analytics, Tel Aviv, Israel.
Jens KöllermannDr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt/M, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diagnosis of prostate cancer rests on the histopathological evaluation of prostate needle core biopsy specimens (NCBS) supplemented by immunohistochemistry as required. Because of the well-known interobserver variability in diagnosis and grading of prostate cancer, we have studied the capability of a commercially available artificial intelligence (AI) solution to aid in the diagnosis of PCa in a non-expert setting. For this, 2828 H&E stained NCBS slides from 249 cases were digitised to produce whole slide images (WSI) and subjected to second-read analysis using the Ibex prostate AI solution. Ground truth was established by a combination of primary pathologists' diagnoses supplemented by immunohistochemistry and external expert revision. For cancer detection, the AI solution achieved a false negative rate of 0.2%, significantly lower than that of the reporting pathologists (1.5%). False positive rates were similar for reporting pathologists (2.3%) and prostate AI solution (3.1%). A Gleason pattern 4 alert was raised by the AI solution in 2 of 29 cases (7%) of cases originally diagnosed as Gleason score 3 + 3, both of which were upheld after expert review. Because of the therapeutic consequences, the triggering of a "higher than 3 + 3 Gleason score" alert represents a useful safety feature. In conclusion, our findings support the growing evidence that by enhancing diagnostic accuracy AI-based diagnostic solutions can play a pivotal role in alleviating the increasing workload faced by pathologists due to the rising global incidence of prostate cancer.

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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.