Evidence map›Paper›PMID 39824854›Full record

ArticleScientific reports2025

Comparison of 1D and 3D volume measurement techniques in NF2-associated vestibular schwannoma monitoring.

Isabel Gugel, Nuran Aboutaha, Bianca Pfluegler, Ulrike Ernemann, Martin Ulrich Schuhmann, Marcos Tatagiba, Florian Grimm

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

7 authors.

Isabel GugelDepartment of Neurosurgery, Centre of Neurofibromatosis and Schwannomatosis, Centre for Rare Diseases, University Hospital Tübingen, Tübingen, Germany. isabel.gugel@med.uni-tuebingen.de.
Nuran AboutahaDepartment of Neurosurgery, University Hospital Tübingen, Tübingen, Germany.
Bianca PflueglerDepartment of Neurosurgery, University Hospital Tübingen, Tübingen, Germany.
Ulrike ErnemannDepartment of Neuroradiology, University Hospital Tübingen, Tübingen, Germany.
Martin Ulrich SchuhmannDepartment of Neurosurgery, Centre of Neurofibromatosis and Schwannomatosis, Centre for Rare Diseases, Division of Pediatric Neurosurgery, University Hospital Tübingen, Tübingen, Germany.
Marcos TatagibaDepartment of Neurosurgery, Centre of Neurofibromatosis and Schwannomatosis, Centre for Rare Diseases, University Hospital Tübingen, Tübingen, Germany.
Florian GrimmDepartment of Neurosurgery, University Hospital Tübingen, Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To compare 1D (linear) tumor volume calculations and classification systems with 3D-segmented volumetric analysis (SVA), focusing specifically on their effectiveness in the evaluation and management of NF2-associated vestibular schwannomas (VS). VS were clinically followed every 6 months with cranial, thin-sliced (< 3 mm) MRI. We retrospectively reviewed and used T1-weighted post-contrast enhanced (gadolinium) images for both SVA and linear measurements. 3D-SVA was performed manually or combined with semiautomated segmentation by using axial planes. The maximum linear dimensions (MLD) were determined in three dimensions (anteroposterior, transverse, and craniocaudal planes) using axial and coronal planes. The MLD was cubed (MLD

Indexed as

Imaging, Three-DimensionalNeurofibromatosis 2Neuroma, AcousticAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesTumor BurdenYoung AdultLinear measurementsNeurofibromatosis type 2 associated SchwannomatosisSegmented volumetric analysisTumor GrowthVestibular Schwannoma

Identifiers

PMID39824854
PMCPMC11742393

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Registered trials

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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.