Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI
Identifikátory výsledku
Kód výsledku v 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>
Nalezeny alternativní kódy
RIV/00216305:26220/15:PU115072 RIV/00209805:_____/16:N0000005
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
BM - Fyzika pevných látek a magnetismus
OECD FORD obor
—
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Magnetic Resonance in Medicine
ISSN
0740-3194
e-ISSN
—
Svazek periodika
75
Číslo periodika v rámci svazku
3
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
11
Strana od-do
1355-1365
Kód UT WoS článku
000370593700042
EID výsledku v databázi Scopus
2-s2.0-84927591890