Evidence map›Paper›PMID 35389110›Full record

ArticleJournal of cancer research and clinical oncology2023

Can whole-body MRI replace CT in management of metastatic testicular cancer? A prospective, non-inferiority study.

Solveig Kärk Abildtrup Larsen, Vibeke Løgager, Catharina Bylov, Hanne Nellemann, Mads Agerbæk, Anne Birgitte Als, Erik Morre Pedersen

Registry-linked trialOpen access · greenAbstract readEquivalence Trial
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03436901 (Whole Body MRI With DWI for Monitoring Patients Treated for Testicular Cancer Stage II-III), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 16% 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.

NCT03436901 nacompletednot on this map

Whole Body MRI With DWI for Monitoring Patients Treated for Testicular Cancer Stage II-III

TypeinterventionalSponsorAarhus University HospitalRan2018 to 2021Enrolled90ConditionsTesticular NeoplasmArmsMRI with DWI vs CT
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Nuclear medicine imaging in non-seminomatous germ cell tumors: lessons learned from the past failures.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
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 at 2 institutions in 1 country.

Solveig Kärk Abildtrup LarsenDepartment of Radiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark. solveig.larsen@auh.rm.dk.ORCID http://orcid.org/0000-0001-5482-7650
Vibeke LøgagerDepartment of Radiology, Herlev Hospital, Borgmester Ib Juuls Vej 1, 2730, Herlev, Denmark.
Catharina BylovDepartment of Radiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
Hanne NellemannDepartment of Radiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
Mads AgerbækDepartment of Oncology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
Anne Birgitte AlsDepartment of Oncology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
Erik Morre PedersenDepartment of Radiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark.
Aarhus University Hospital · DKHerlev Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeConcerns of imaging-related radiation exposure in young patients with high survival rates have increased the use of magnetic resonance imaging (MRI) in testicular cancer (TC) stage I. However, computed tomography (CT) is still preferred for metastatic TC. The purpose of this study was to compare whole-body MRI incl. diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) with contrast-enhanced, thoracoabdominal CT in metastatic TC.

methodsA prospective, non-inferiority study of 84 consecutive patients (median age 33 years) with newly diagnosed metastatic TC (February 2018-January 2021). Patients had both MRI and CT before and after treatment. Anonymised images were reviewed by experienced radiologists. Lesion malignancy was evaluated on a Likert scale (1 benign-4 malignant). Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were calculated on patient and lesion level. The primary outcome was demonstrating non-inferiority regarding sensitivity of MRI compared to CT. The non-inferiority margin was set at 5%. ROC curves and interobserver agreement were calculated.

resultsOn patient level, MRI had 98% sensitivity and 75% specificity compared to CT. On lesion level within each modality, MRI had 99% sensitivity and 78% specificity, whereas CT had 98% sensitivity and 88% specificity. MRI sensitivity was non-inferior to CT (difference 0.57% (95% CI - 1.4-2.5%)). The interobserver agreement was substantial between CT and MRI.

conclusionMRI with DWIBS was non-inferior to contrast-enhanced CT in detecting metastatic TC disease.

trial registrationwww. CLINICALTRIALS: gov NCT03436901, finished July 1st 2021.

Indexed as

Neoplasms, Second PrimaryTesticular NeoplasmsAdultDiffusion Magnetic Resonance ImagingHumansMagnetic Resonance ImagingMaleProspective StudiesRadiopharmaceuticalsSensitivity and SpecificityTomography, X-Ray ComputedWhole Body ImagingRadiopharmaceuticalsCT (computed tomography)DWIBS (diffusion-weighted whole-body imaging with background body signal suppression)DWI (diffusion-weighted imaging)MRI (magnetic resonance imaging)Non-inferiority studyTesticular cancer

Identifiers

PMID35389110
PMCPMC11797432
OpenAlexW4225765390

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.