Literature DB >> 21452717

Is Weisskoff model valid for the correction of contrast agent extravasation with combined T1 and T2* effects in dynamic susceptibility contrast MRI?

Ho-Ling Liu1, Yi-Ying Wu, Wei-Shan Yang, Chih-Feng Chen, Kun-Eng Lim, Yuan-Yu Hsu.   

Abstract

PURPOSE: The Weisskoff model has been widely applied for correcting the T1 effect of the contrast agent leakage in the measured dynamic susceptibility contrast (DSC)-MRI signals. This study aimed to modify the Weisskoff model for the inclusion of both T1 and T2 effects of the contrast agent extravasation.
METHODS: A two-compartment model was proposed and implemented into the original Weisskoff model to describe the combined T1 and T2 effects from the contrast agent leakage in the measured DSC-MRI signals. A computer simulation was performed to evaluate the dependence of T, versus T2 dominance on imaging parameter, field strength, baseline T1, and severity of the leakage. The modified Weisskoff model was employed to correct the relative cerebral blood volume (rCBV) maps in three patients with brain tumors to demonstrate its use.
RESULTS: The resultant equation had the same mathematical form as the original model, but with a different expression for the fitting constant K2. This new parameter can be of either a positive or a negative value. Results of the computer simulation showed more probable T2 dominance with longer TE, higher field strength, shorter baseline T1, and greater extraction of the contrast agent. Clinical data were well fitted by the model, with a positive K2 indicating T1 dominance and underestimated rCBV and a negative K2 indicating T2 dominance and overestimated rCBV. The K2 values of normal-appearing brain tissues were distributed in a much smaller range than the K2 values of enhancing tumors. The ratios of corrected over uncorrected normalized CBV (nCBV) for gray matter (GM) were in the range between 1.04 and 1.05, meaning that the nCBV remained rather stable before and after correction. The ratios for the tumors were 0.65, 0.42, and 2.81, either much smaller or greater than the ratios for GM.
CONCLUSIONS: This study proposed a modified Weisskoff model that was able to explain both T1 and T2 dominant effects of the contrast agent extravasation in DSC-MRI. Further development is needed to make the K2 parameter a quantitative indicator of the vessel permeability.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21452717     DOI: 10.1118/1.3534197

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  17 in total

1.  Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project.

Authors:  K M Schmainda; M A Prah; S D Rand; Y Liu; B Logan; M Muzi; S D Rane; X Da; Y-F Yen; J Kalpathy-Cramer; T L Chenevert; B Hoff; B Ross; Y Cao; M P Aryal; B Erickson; P Korfiatis; T Dondlinger; L Bell; L Hu; P E Kinahan; C C Quarles
Journal:  AJNR Am J Neuroradiol       Date:  2018-05-24       Impact factor: 3.825

2.  Permeability measurement using dynamic susceptibility contrast magnetic resonance imaging enhances differential diagnosis of primary central nervous system lymphoma from glioblastoma.

Authors:  Ji Ye Lee; Atle Bjørnerud; Ji Eun Park; Bo Eun Lee; Joo Hyun Kim; Ho Sung Kim
Journal:  Eur Radiol       Date:  2019-03-15       Impact factor: 5.315

3.  Simultaneous perfusion and permeability measurements using combined spin- and gradient-echo MRI.

Authors:  Heiko Schmiedeskamp; Jalal B Andre; Matus Straka; Thomas Christen; Seema Nagpal; Lawrence Recht; Reena P Thomas; Greg Zaharchuk; Roland Bammer
Journal:  J Cereb Blood Flow Metab       Date:  2013-03-06       Impact factor: 6.200

4.  Systematic assessment of multi-echo dynamic susceptibility contrast MRI using a digital reference object.

Authors:  Ashley M Stokes; Natenael B Semmineh; Ashley Nespodzany; Laura C Bell; C Chad Quarles
Journal:  Magn Reson Med       Date:  2019-08-09       Impact factor: 4.668

5.  On the Use of DSC-MRI for Measuring Vascular Permeability.

Authors:  J T Skinner; P L Moots; G D Ayers; C C Quarles
Journal:  AJNR Am J Neuroradiol       Date:  2015-10-01       Impact factor: 3.825

6.  Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma.

Authors:  L S Hu; Z Kelm; P Korfiatis; A C Dueck; C Elrod; B M Ellingson; T J Kaufmann; J M Eschbacher; J P Karis; K Smith; P Nakaji; D Brinkman; D Pafundi; L C Baxter; B J Erickson
Journal:  AJNR Am J Neuroradiol       Date:  2015-09-10       Impact factor: 3.825

7.  Effects of MRI Protocol Parameters, Preload Injection Dose, Fractionation Strategies, and Leakage Correction Algorithms on the Fidelity of Dynamic-Susceptibility Contrast MRI Estimates of Relative Cerebral Blood Volume in Gliomas.

Authors:  K Leu; J L Boxerman; B M Ellingson
Journal:  AJNR Am J Neuroradiol       Date:  2016-12-29       Impact factor: 3.825

8.  Validation of a T1 and T2* leakage correction method based on multiecho dynamic susceptibility contrast MRI using MION as a reference standard.

Authors:  Ashley M Stokes; Natenael Semmineh; C Chad Quarles
Journal:  Magn Reson Med       Date:  2015-09-12       Impact factor: 4.668

9.  Pseudo-extravasation rate constant of dynamic susceptibility contrast-MRI determined from pharmacokinetic first principles.

Authors:  Xin Li; Csanad G Varallyay; Seymur Gahramanov; Rongwei Fu; William D Rooney; Edward A Neuwelt
Journal:  NMR Biomed       Date:  2017-09-08       Impact factor: 4.044

10.  The basics of diffusion and perfusion imaging in brain tumors.

Authors:  Panagiotis Korfiatis; Bradley Erickson
Journal:  Appl Radiol       Date:  2014-07-04
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.