Spatially regularized estimation of the tissue homogeneity model parameters in DCE‐MRI using proximal minimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F19%3A00507670" target="_blank" >RIV/68081731:_____/19:00507670 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/19:00507670 RIV/00216305:26220/19:PU130915

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/10.1002/mrm.27874" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/mrm.27874</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/mrm.27874" target="_blank" >10.1002/mrm.27874</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Spatially regularized estimation of the tissue homogeneity model parameters in DCE‐MRI using proximal minimization

Popis výsledku v původním jazyce

The Tofts and the extended Tofts models are the pharmacokinetic models commonly used in dynamic contrast‐enhanced MRI (DCE‐MRI) perfusion analysis, although they do not provide two important biological markers, namely, the plasmaflow and the permeability‐surface area product. Estimates of such markers are possible using advanced pharmacokinetic models describing the vascular distribution phase, such as the tissue homogeneity model. However, the disadvantage of theadvanced models lies in biased and uncertain estimates, especially when the estimates are computed voxelwise. The goal of this work is to improve the reliability of the estimates by including information from neighboring voxels. Information from the neighboring voxels is incorporated in the estimation process through spatial regularization in the form of total variation. The spatial regularization is applied on five maps of perfusion parameters estimated using the tissue homogeneity model. Since the total variation is not differentiable, two proximal techniques of convex optimization are used to solve the problem numerically. The proposed algorithm helps to reduce noise in the estimated perfusionparameter maps together with improving accuracy of the estimates. These conclusions are proved using a numerical phantom. In addition, experiments on real datanshow improved spatial consistency and readability of perfusion maps without considerable lowering of the quality of fit. The reliability of the DCE‐MRI perfusion analysis using the tissue homogeneity model can be improved by employing spatial regularization. The proposed utilization of modern optimization techniques implies only slightly higher computational costs compared to the standard approach without spatial regularization.

Název v anglickém jazyce

Spatially regularized estimation of the tissue homogeneity model parameters in DCE‐MRI using proximal minimization

Popis výsledku anglicky

The Tofts and the extended Tofts models are the pharmacokinetic models commonly used in dynamic contrast‐enhanced MRI (DCE‐MRI) perfusion analysis, although they do not provide two important biological markers, namely, the plasmaflow and the permeability‐surface area product. Estimates of such markers are possible using advanced pharmacokinetic models describing the vascular distribution phase, such as the tissue homogeneity model. However, the disadvantage of theadvanced models lies in biased and uncertain estimates, especially when the estimates are computed voxelwise. The goal of this work is to improve the reliability of the estimates by including information from neighboring voxels. Information from the neighboring voxels is incorporated in the estimation process through spatial regularization in the form of total variation. The spatial regularization is applied on five maps of perfusion parameters estimated using the tissue homogeneity model. Since the total variation is not differentiable, two proximal techniques of convex optimization are used to solve the problem numerically. The proposed algorithm helps to reduce noise in the estimated perfusionparameter maps together with improving accuracy of the estimates. These conclusions are proved using a numerical phantom. In addition, experiments on real datanshow improved spatial consistency and readability of perfusion maps without considerable lowering of the quality of fit. The reliability of the DCE‐MRI perfusion analysis using the tissue homogeneity model can be improved by employing spatial regularization. The proposed utilization of modern optimization techniques implies only slightly higher computational costs compared to the standard approach without spatial regularization.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20601 - Medical engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Magnetic Resonance in Medicine

ISSN

0740-3194

e-ISSN

1522-2594

Svazek periodika

82

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

2257-2272

Kód UT WoS článku

000483797700024

EID výsledku v databázi Scopus

2-s2.0-85071714198