Evidence map›Paper›PMID 33768288›Full record

ArticleEuropean radiology2021

Improved detection of in-transit metastases of malignant melanoma with BSREM reconstruction in digital [

Virginia Liberini, Michael Messerli, Lars Husmann, Ken Kudura, Hannes Grünig, Alexander Maurer, Stephan Skawran, Erika Orita, Daniele A Pizzuto, Désirée Deandreis and 5 more

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 22 citations in OpenAlex.

  1. Reduced count pediatric whole-bodyPediatric radiology · 2024
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. PET/CT variants and pitfalls in malignant melanoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022
    Review
  7. Article
  8. 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

15 authors at 2 institutions in 3 countries.

Virginia LiberiniDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland. virginia.liberini@unito.it.ORCID http://orcid.org/0000-0001-9416-6965
Michael MesserliDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Lars HusmannDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Ken KuduraDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Hannes GrünigDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Alexander MaurerDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Stephan SkawranDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Erika OritaDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Daniele A PizzutoDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
Désirée DeandreisDepartment of Nuclear Medicine, Città della Salute e della Scienza di Torino, University of Turin, Turin, Italy.
Reinhard DummerDepartment of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Joanna ManganaDepartment of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Daniela Mihic-ProbstDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Niels RuppDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Martin W HuellnerDepartment of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, CH-8091, Zürich, Switzerland.
University of Zurich · CHUniversity of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare block sequential regularized expectation maximization (BSREM) and ordered subset expectation maximization (OSEM) for the detection of in-transit metastasis (ITM) of malignant melanoma in digital [

methodsWe retrospectively analyzed a cohort of 100 [

resultsBSREM reconstruction led to the detection of 287 ITM (39% more than OSEM). PET parameters of ITM were significantly different between BSREM and OSEM reconstructions (p < 0.001). SUVmax and TBR were higher (76.5% and 77.7%, respectively) and MTV lower (49.5%) on BSREM. ITM missed with OSEM had significantly lower SUVmax (mean 2.03 vs. 3.84) and TBR (mean 1.18 vs. 2.22) and higher MTV (mean 2.92 vs. 1.01) on OSEM compared to BSREM (all p < 0.001).

conclusionsBSREM detects significantly more ITM than OSEM, owing to higher SUVmax, higher TBR, and less blurring. BSREM is particularly helpful in small and less avid lesions, which are more often missed with OSEM. KEY POINTS: • In melanoma patients, [

Indexed as

MelanomaPositron Emission Tomography Computed TomographyAlgorithmsFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedRadiopharmaceuticalsRetrospective StudiesFluorodeoxyglucose F18RadiopharmaceuticalsAlgorithmsFluorodeoxyglucose F18MelanomaPositron Emission Tomography / Computed TomographySkin neoplasms

Identifiers

PMID33768288
PMCPMC8452544
OpenAlexW3136055434

What OpenQuestion holds

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LicenceCC BY
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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.