UMMPerfusion: an Open Source Software Tool Towards Quantitative MRI Perfusion Analysis in Clinical Routine.
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...
| Publicado en: | Journal of Digital Imaging Vol. 26; no. 2; pp. 344 - 353 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104249480&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104249480 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2013 vid: 26 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104249480 86060012 10.1007/s10278-012-9510-6 NLM22832894 PMC3597952 104249480 ppf: 344 ppct: 9 formats: fmt: @attributes: type: P tig: atl: UMMPerfusion: an Open Source Software Tool Towards Quantitative MRI Perfusion Analysis in Clinical Routine. aug: au: Zöllner, Frank Weisser, Gerald Reich, Marcel Kaiser, Sven Schoenberg, Stefan Sourbron, Steven Schad, Lothar affil: Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3 68167 Mannheim Germany sug: subj: Perfusion Imaging Software Magnetic Resonance Imaging Image Processing, Computer Assisted Software Design Algorithms Calibration Contrast Media DICOM Quality Assurance Retrospective Design Evaluation Research T-Tests P-Value Human ab: 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. pubtype: Academic Journal doctype: diagnostic images pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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