Evidence map›Paper›PMID 42129021›Full record

ArticleInsights into imaging2026

Imaging-based clinical decision tree enables risk stratification of extraprostatic extension before radical prostatectomy in prostate cancer patients.

Charlie A Hamm, Tim Rüterhenke, Georg L Baumgärtner, Catherina Mayerosch, Simon Schallenberg, Maximilian Lindholz, Nick L Beetz, Patrick Asbach, Tobias Penzkofer

Abstract read
In one paragraph

Article in Insights into imaging, 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

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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

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

9 authors.

Charlie A HammDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany. charlie.hamm@charite.de.ORCID http://orcid.org/0000-0003-4104-4758
Tim RüterhenkeDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Georg L BaumgärtnerDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Catherina MayeroschDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Simon SchallenbergDepartment of Pathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Maximilian LindholzDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Nick L BeetzDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Patrick AsbachDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Tobias PenzkoferDepartment of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesExtraprostatic extension (EPE) significantly impacts surgical planning for prostate cancer (PCa) patients, influencing nerve-sparing surgery and neoadjuvant therapy decisions. However, Likert-scale-based radiological (r)EPE assessment lacks sufficient diagnostic accuracy for reliable clinical decision-making. Therefore, the aim was to evaluate rEPE scoring alongside clinical parameters to develop a clinically feasible decision tree for preoperative risk stratification.

methodsThis retrospective single-center study included 429 consecutive PCa patients undergoing radical prostatectomy between January 2012 and October 2018. All patients underwent multiparametric MRI with PI-RADS scoring and rEPE grading (grades 0-3). Clinical parameters included PSA density (PSAD) and ISUP grade group (GG) at biopsy. Univariate and multivariate logistic regression identified predictors of EPE. A clinical decision tree was developed using binary classification to stratify patients into risk groups.

resultsEPE was confirmed in 145 patients (33.8%). Multivariate analysis identified rEPE grade (OR 2.64, p < 0.001) and GG at biopsy (OR 1.41, p < 0.001) as independent predictors. The decision tree assigned 48% of patients to the high-risk (rEPE grade 3: 89% EPE risk) and low-risk group (rEPE < 3 + PSAD < 0.2 ng/mL² + GG < 4: 13% EPE risk), while 52% showed intermediate risk (28-45% EPE risk).

conclusionsThe developed decision tree combining MRI-derived rEPE grading, PSAD, and biopsy GG enables reliable identification of patients at high and low risk for EPE. This tool supports informed decision-making regarding nerve-sparing surgery and neoadjuvant therapy, potentially contributing to personalized treatment planning. CRITICAL RELEVANCE STATEMENT: Decision tree combining routine MRI-based and clinical markers reliably stratifies prostate cancer patients into high-risk and low-risk groups for EPE, supporting personalized surgical planning. KEY POINTS: EPE affects surgical planning decisions in prostate cancer patients. Combining EPE grade at MRI, PSAD, and biopsy grade improves risk stratification. The developed decision tree reliably stratified every second patient into distinct EPE-risk groups, potentially improving personalized surgical planning.

Indexed as

Clinical decision-makingMagnetic resonance imagingProstate-specific antigenProstatic neoplasmsSurgery

Identifiers

PMID42129021
PMCPMC13172209

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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.