Single voxel vascular transport functions of arteries, capillaries and veins, and the associated arterial input function in dynamic susceptibility contrast magnetic resonance brain perfusion imaging

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F21%3A00546148" target="_blank" >RIV/68081731:_____/21:00546148 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0730725X21001387?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0730725X21001387?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.mri.2021.08.008" target="_blank" >10.1016/j.mri.2021.08.008</a>

Result language

angličtina

Original language name

Single voxel vascular transport functions of arteries, capillaries and veins, and the associated arterial input function in dynamic susceptibility contrast magnetic resonance brain perfusion imaging

Original language description

Purpose: The composite vascular transport function of a brain voxel consists of one convolutional component for the arteries, one for the capillaries and one for the veins in the voxel of interest. Here, the goal is to find each of these three convolutional components and the associated arterial input function. Pharmacokinetic modelling: The single voxel vascular transport functions for arteries, capillaries and veins were all modelled as causal exponential functions. Each observed multipass tissue contrast function was as a first approximation modelled as the resulting parametric composite vascular transport function convolved with a nonparametric and voxel specific multipass arterial input function. Subsequently, the residue function was used in the true perfusion equation to optimize the three parameters of the exponential functions. Deconvolution methods: For each voxel, the parameters of the three exponential functions were estimated by successive iterative blind deconvolutions using versions of the Lucy-Richardson algorithm. The final multipass arterial input function was then computed by nonblind deconvolution using the Lucy-Richardson algorithm and the estimated composite vascular transport function. Results: Simulations showed that the algorithm worked. The estimated mean transit time of arteries, capillaries and veins of the simulated data agreed with the known input values. For real data, the estimated capillary mean transit times agreed with known values for this parameter. The nonparametric multipass arterial input functions were used to derive the associated map of the arrival time. The arrival time map of a healthy volunteer agreed with known arterial anatomy and physiology. Conclusion: Clinically important new voxelwise hemodynamic information for arteries, capillaries and veins separately can be estimated using multipass tissue contrast functions and the iterative blind Lucy-Richardson deconvolution algorithm.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20601 - Medical engineering

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

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Magnetic Resonance Imaging

ISSN

0730-725X

e-ISSN

1873-5894

Volume of the periodical

84

Issue of the periodical within the volume

December

Country of publishing house

US - UNITED STATES

Number of pages

14

Pages from-to

101-114

UT code for WoS article

000708295300008

EID of the result in the Scopus database

2-s2.0-85115888868