Evidence map›Paper›PMID 22832894›Full record

ArticleJournal of digital imaging2013

UMMPerfusion: an open source software tool towards quantitative MRI perfusion analysis in clinical routine.

Frank G Zöllner, Gerald Weisser, Marcel Reich, Sven Kaiser, Stefan O Schoenberg, Steven P Sourbron, Lothar R Schad

Abstract read
In one paragraph

Article in Journal of digital imaging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. AI-enhanced simultaneous multiparametricEuropean journal of nuclear medicine and molecular imaging · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Impact of the Number of Iterations in Compressed Sensing Reconstruction on Ultrafast Dynamic Contrast-enhanced Breast MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2019
    Article
  12. Article
  13. Observational
  14. Article
  15. Hyperpolarized [1-Scientific reports · 2017
    Article
  16. Article
  17. Can HyperpolarizedTomography (Ann Arbor, Mich.) · 2017
    Article
  18. Article
  19. Article
  20. 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.

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
Gerald Weisser
Marcel Reich
Sven Kaiser
Stefan O Schoenberg
Steven P Sourbron
Lothar R Schad

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To develop a generic Open Source MRI perfusion analysis tool for quantitative parameter mapping to be used in a clinical workflow and methods for quality management of perfusion data. We implemented a classic, pixel-by-pixel deconvolution approach to quantify T1-weighted contrast-enhanced dynamic MR imaging (DCE-MRI) perfusion data as an OsiriX plug-in. It features parallel computing capabilities and an automated reporting scheme for quality management. Furthermore, by our implementation design, it could be easily extendable to other perfusion algorithms. Obtained results are saved as DICOM objects and directly added to the patient study. The plug-in was evaluated on ten MR perfusion data sets of the prostate and a calibration data set by comparing obtained parametric maps (plasma flow, volume of distribution, and mean transit time) to a widely used reference implementation in IDL. For all data, parametric maps could be calculated and the plug-in worked correctly and stable. On average, a deviation of 0.032 ± 0.02 ml/100 ml/min for the plasma flow, 0.004 ± 0.0007 ml/100 ml for the volume of distribution, and 0.037 ± 0.03 s for the mean transit time between our implementation and a reference implementation was observed. By using computer hardware with eight CPU cores, calculation time could be reduced by a factor of 2.5. We developed successfully an Open Source OsiriX plug-in for T1-DCE-MRI perfusion analysis in a routine quality managed clinical environment. Using model-free deconvolution, it allows for perfusion analysis in various clinical applications. By our plug-in, information about measured physiological processes can be obtained and transferred into clinical practice.

Indexed as

Image Interpretation, Computer-AssistedSoftwareDiffusion Magnetic Resonance ImagingHumansMalePerfusion Imaging

Identifiers

PMID22832894
PMCPMC3597952

What OpenQuestion holds

Textmetadata
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.