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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

  • Czech description

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

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

  • 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