Evidence map›Paper›PMID 28317128›Full record

ArticleMedical physics2017

Comparison of DCE-MRI kinetic parameters and FMISO-PET uptake parameters in head and neck cancer patients.

Urban Simoncic, Sara Leibfarth, Stefan Welz, Nina Schwenzer, Holger Schmidt, Gerald Reischl, Christina Pfannenberg, Christian la Fougère, Konstantin Nikolaou, Daniel Zips and 1 more

Abstract read
In one paragraph

Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Is there a role for [Clinical and translational imaging · 2024
    Article
  3. The optimalEuropean journal of nuclear medicine and molecular imaging · 2022
    Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Improving Tumor Hypoxia Location inRadiology. Imaging cancer · 2021
    Article
  10. EJNMMI research · 2020
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. [EJNMMI research · 2017
    Article
  17. Molecular mechanisms of hypoxia in cancer.Clinical and translational imaging · 2017
    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

11 authors.

Urban SimoncicSection for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
Sara LeibfarthSection for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
Stefan WelzDepartment of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
Nina SchwenzerDiagnostic and Interventional Radiology, Department of Radiology, University Hospital Tübingen, Tübingen, Germany.
Holger SchmidtDiagnostic and Interventional Radiology, Department of Radiology, University Hospital Tübingen, Tübingen, Germany.
Gerald ReischlPreclinical Imaging and Radiopharmacy, Department of Radiology, University Hospital Tübingen, Tübingen, Germany.
Christina PfannenbergDiagnostic and Interventional Radiology, Department of Radiology, University Hospital Tübingen, Tübingen, Germany.
Christian la FougèreNuclear Medicine, Department of Radiology, University Hospital Tübingen, Tübingen, Germany.
Konstantin NikolaouDiagnostic and Interventional Radiology, Department of Radiology, University Hospital Tübingen, Tübingen, Germany.
Daniel ZipsDepartment of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
Daniela ThorwarthSection for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTumor hypoxia is a major cause of radiation resistance, often present in various solid tumors. Dynamic [

methodsThis study was done on head and neck cancer patients (N = 6), who were imaged dynamically with FMISO-PET and DCE-MRI on the same day. Images were registered and analyzed for kinetics on a voxel basis. FMISO-PET images were analyzed with the two-tissue compartment three rate-constant model. Additionally, tumor-to-muscle ratio (TMR) maps were evaluated. DCE-MRI was analyzed with the extended Tofts model. Voxel-wise Pearson's coefficients were calculated for each patient to assess pairwise parameter correlations.

resultsMedian correlations between FMISO uptake parameters and DCE-MRI kinetic parameters varied across the parameter pairs in the range from -0.05 to 0.71. The highest median correlation of r = 0.71 was observed for the pair V

conclusionsBased on this clinical evidence, we can conclude that the vascular fraction parameters obtained through DCE-MRI kinetic analysis or FMISO kinetic analysis measure the same biological property, while other kinetic parameters are unrelated. These results might be useful in the design of future clinical trials involving FMISO-PET/DCE-MR multimodality imaging for the assessment of tumor microenvironment.

Indexed as

Magnetic Resonance ImagingPositron-Emission TomographyContrast MediaHead and Neck NeoplasmsHumansKineticsMisonidazoleContrast MediafluoromisonidazoleMisonidazoleDCE-MRIFMISOhypoxiaimage quantificationkinetic analysisPETvascular kinetic parameters

Identifiers

PMID28317128
PMCPMC5485084

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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.