Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F16%3A00466902" target="_blank" >RIV/68081731:_____/16:00466902 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26220/15:PU115072 RIV/00209805:_____/16:N0000005
Result on the web
<a href="http://dx.doi.org/10.1002/mrm.25619" target="_blank" >http://dx.doi.org/10.1002/mrm.25619</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/mrm.25619" target="_blank" >10.1002/mrm.25619</a>
Alternative languages
Result language
angličtina
Original language name
Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI
Original language description
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.nMethodsMulti-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. nResultsThe 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.nConclusionBlind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BM - Solid-state physics and magnetism
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Magnetic Resonance in Medicine
ISSN
0740-3194
e-ISSN
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Volume of the periodical
75
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
1355-1365
UT code for WoS article
000370593700042
EID of the result in the Scopus database
2-s2.0-84927591890