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Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI
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SYSNO ASEP 0466902 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI Author(s) Kratochvíla, Jiří (UPT-D) RID, ORCID, SAI
Jiřík, Radovan (UPT-D) RID, ORCID, SAI
Bartoš, M. (CZ)
Standara, M. (CZ)
Starčuk jr., Zenon (UPT-D) RID, ORCID, SAI
Taxt, T. (NO)Number of authors 6 Source Title Magnetic Resonance in Medicine. - : Wiley - ISSN 0740-3194
Roč. 75, č. 3 (2016), s. 1355-1365Number of pages 11 s. Publication form Print - P Language eng - English Country US - United States Keywords dynamic contrast-enhanced magnetic resonance imaging ; multi-channel blind deconvolution ; arterial input function ; impulse residue function ; renal cell carcinoma Subject RIV BM - Solid Matter Physics ; Magnetism R&D Projects GAP102/12/2380 GA ČR - Czech Science Foundation (CSF) LO1212 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) ED0017/01/01 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Institutional support UPT-D - RVO:68081731 UT WOS 000370593700042 EID SCOPUS 84927591890 DOI 10.1002/mrm.25619 Annotation PurposeOne of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used.
MethodsMulti-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested.
ResultsThe proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates.
ConclusionBlind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup.Workplace Institute of Scientific Instruments Contact Martina Šillerová, sillerova@ISIBrno.Cz, Tel.: 541 514 178 Year of Publishing 2017
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