Evidence map›Paper›PMID 40397135›Full record

ArticleNeuroradiology2025

PET/MR for predicting extranodal extension of head and neck cancer.

Vanessa Sanchez, Daniele A Pizzuto, Alexander Maurer, Urs J Muehlematter, Bert-Ram Sah, Lars Husmann, Stephan Skawran, Caecilia E Mader, Gregoire B Morand, Simon A Mueller and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuroradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

16 authors.

Vanessa SanchezDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Daniele A PizzutoDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Alexander MaurerDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Urs J MuehlematterDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Bert-Ram SahDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Lars HusmannDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Stephan SkawranDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Caecilia E MaderDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Gregoire B MorandDepartment of Otorhinolaryngology, Head and Neck Surgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Simon A MuellerDepartment of Otorhinolaryngology, Head and Neck Surgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Christian MeerweinDepartment of Otorhinolaryngology, Head and Neck Surgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Niels J RuppDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Sandra FreibergerDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Martin LanzerDepartment of Cranio-Maxillo-Facial and Oral Surgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Michael MesserliDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Martin W HuellnerDepartment of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland. martin.huellner@usz.ch.ORCID http://orcid.org/0000-0002-4849-3292

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo analyze the diagnostic accuracy of multiparametric FDG-PET/MR in identifying pathologic extranodal extension (pENE) of lymph node metastases (LNM) in head and neck squamous cell carcinoma (HNSCC) patients. METHODS AND MATERIALS: Retrospective analysis of 57 HNSCC patients who underwent preoperative FDG-PET/MR imaging. PET parameters of LNM SUVmax and MTV, lymph node size as well as MR parameters flare sign, shaggy margin sign and vanishing border sign were analyzed. Histopathological assessment of neck dissection specimens served as standard of reference.

resultsA logistic regression model consisting of lymph node size (p = 0.029), shaggy margin sign (p = 0.031) and MTV (p = 0.035) proved that all three parameters significantly contributed to the prediction of pENE (χ²(3) = 54.23, p < 0.001). A second model without the reader-dependent parameter shaggy margin sign yielded similar results (χ²(2) = 45.36, p < 0.001), with every increase in lymph node size (p = 0.006) by 1 mm increasing the likelihood of pENE by a factor of 1.41 (95%-CI[1.11, 1.81]), and every increase in MTV (p = 0.023) by 1 cm3 increasing the likelihood of pENE by a factor of 1.64 (95%-CI[1.07, 2.50]). This model yielded an accuracy of 94.7% (95%-CI [85.4, 98.9]) for predicting pENE, with a specificity of 97.3% (95%-CI [85.8, 99.9]) and a sensitivity of 90.0% (95%-CI [68.3, 98.8]). Internal validation using a test dataset confirmed high accuracy of this model.

conclusionPET/MR-based multivariate binomial logistic regression models consisting of MTV, lymph node size and/or shaggy lymph node margins predict pENE with high accuracy.

Indexed as

Carcinoma, Squamous CellHead and Neck NeoplasmsMagnetic Resonance ImagingMultimodal ImagingPositron-Emission TomographyAdultAgedExtranodal ExtensionFemaleFluorodeoxyglucose F18HumansLymphatic MetastasisMaleMiddle AgedRadiopharmaceuticalsRetrospective StudiesFluorodeoxyglucose F18Radiopharmaceuticals2- [18F]-fluorodeoxy-D-glucoseExtranodal extensionHead and neck cancerHybrid imagingPET/MR

Identifiers

PMID40397135
PMCPMC12391167

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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.