Evidence map›Paper›PMID 35207499›Full record

ArticleLife (Basel, Switzerland)2022

Whole Body MRI in the Detection of Lymph Node Metastases in Patients with Testicular Germ Cell Cancer.

Vassiliki Pasoglou, Sandy Van Nieuwenhove, Julien Van Damme, Nicolas Michoux, Aline Van Maanen, Laurence Annet, Jean-Pascal Machiels, Bertrand Tombal, Frederic E Lecouvet

Open access · goldAbstract read
In one paragraph

Article in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 21% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Guideline
  2. Review
  3. Review
  4. 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

9 authors at 1 institution in 1 country.

Vassiliki PasoglouDepartment of Radiology, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc & Institut de Recherche Expérimentale et Clinique (IREC), Pôle IMAG, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.
Sandy Van NieuwenhoveDepartment of Radiology, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc & Institut de Recherche Expérimentale et Clinique (IREC), Pôle IMAG, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.
Julien Van DammeDivision of Urology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.
Nicolas MichouxDepartment of Radiology, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc & Institut de Recherche Expérimentale et Clinique (IREC), Pôle IMAG, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.
Aline Van MaanenStatistical Support Unit, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium.
Laurence AnnetDepartment of Radiology, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc & Institut de Recherche Expérimentale et Clinique (IREC), Pôle IMAG, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.
Jean-Pascal MachielsDepartment of Medical Oncology, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc & Institut de Recherche Expérimentale et Clinique (IREC), Pôle MIRO, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.ORCID 0000-0001-6369-9742
Bertrand TombalDivision of Urology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.
Frederic E LecouvetDepartment of Radiology, Institut Roi Albert II Cancer Center, Cliniques Universitaires Saint-Luc & Institut de Recherche Expérimentale et Clinique (IREC), Pôle IMAG, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium.ORCID 0000-0003-3568-3254
Cliniques Universitaires Saint-Luc · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-Body Magnetic Resonance Imaging (WB-MRI) is increasingly used for metastatic screening in oncology. This prospective single center study assesses the diagnostic value of WB-MRI including diffusion weighted imaging (DWI) and identifies the sufficient protocol for metastatic lymph node detection in patients with testicular germ cell cancer (TGCC). Forty-three patients underwent contrast enhanced thoraco-abdominopelvic CT (TAP-CT) and WB-MRI with DWI for metastatic lymph node screening. Two independent readers reviewed CTs and WB-MRIs. The diagnostic performance of different imaging protocols (CT, complete WB-MRI, T1W + DWI, T2W + DWI), the agreement between these protocols and the reference standard, the reproducibility of findings and the image quality (Signal and contrast to Noise Ratios, Likert scale) were studied. Reproducibility was very good regardless of both lesion locations (retroperitoneal vs distant lymph nodes, other lesions) and the reader. Diagnostic accuracy of MRI was ≥95% (regardless of the locations and imaging protocol); accuracy of CT was ≥93%. There was a strict overlap of 95% CIs associated with this accuracy between complete WB-MRI, T1W + DWI and T2W + DWI, regardless of the reader. Higher Likert score and SNR were observed for DWI, followed by T2W and T1W sequences. In conclusion, a fast WB-MRI protocol including T2W and DWI is a sufficient, accurate, non-irradiating alternative to TAP-CT for metastatic lymph node screening in TGCC.

Indexed as

computed tomographylymph node metastasisMRIstagingtesticular germ cell cancer (TGCC)whole body MRI

Identifiers

PMID35207499
PMCPMC8875751
OpenAlexW4214517431

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.