Evidence map›Paper›PMID 26767969›Full record

ArticleBMC medical imaging2016

An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited.

Frank G Zöllner, Markus Daab, Steven P Sourbron, Lothar R Schad, Stefan O Schoenberg, Gerald Weisser

Abstract read
In one paragraph

Article in BMC medical imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  4. Hyperpolarized [1-Experimental physiology · 2021
    Article
  5. Article
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  7. Article
  8. Article
  9. Variability and Reproducibility of 3Scientific reports · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Automating Perforator Flap MRA and CTA Reporting.Journal of digital imaging · 2017
    Article
  14. 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

6 authors.

Frank G ZöllnerComputer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany. frank.zoellner@medma.uni-heidelberg.de.
Markus DaabComputer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany. markus.daab@medma.uni-heidelberg.de.
Steven P SourbronDivision of Biomedical Imaging, University of Leeds, Leeds, UK. S.Sourbron@leeds.ac.uk.
Lothar R SchadComputer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany. lothar.schad@medma.uni-heidelberg.de.
Stefan O SchoenbergDepartment of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany. Stefan.schoenberg@umm.de.
Gerald WeisserDepartment of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany. gerald.weisser@umm.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPerfusion imaging has become an important image based tool to derive the physiological information in various applications, like tumor diagnostics and therapy, stroke, (cardio-) vascular diseases, or functional assessment of organs. However, even after 20 years of intense research in this field, perfusion imaging still remains a research tool without a broad clinical usage. One problem is the lack of standardization in technical aspects which have to be considered for successful quantitative evaluation; the second problem is a lack of tools that allow a direct integration into the diagnostic workflow in radiology.

resultsFive compartment models, namely, a one compartment model (1CP), a two compartment exchange (2CXM), a two compartment uptake model (2CUM), a two compartment filtration model (2FM) and eventually the extended Toft's model (ETM) were implemented as plugin for the DICOM workstation OsiriX. Moreover, the plugin has a clean graphical user interface and provides means for quality management during the perfusion data analysis. Based on reference test data, the implementation was validated against a reference implementation. No differences were found in the calculated parameters.

conclusionWe developed open source software to analyse DCE-MRI perfusion data. The software is designed as plugin for the DICOM Workstation OsiriX. It features a clean GUI and provides a simple workflow for data analysis while it could also be seen as a toolbox providing an implementation of several recent compartment models to be applied in research tasks. Integration into the infrastructure of a radiology department is given via OsiriX. Results can be saved automatically and reports generated automatically during data analysis ensure certain quality control.

Indexed as

HumansMagnetic Resonance ImagingPerfusion ImagingSoftwareUser-Computer Interface

Identifiers

PMID26767969
PMCPMC4712457

What OpenQuestion holds

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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.