Literature DB >> 15503330

Comparative study of methods for determining vascular permeability and blood volume in human gliomas.

Judith U Harrer1, Geoff J M Parker, Hamied A Haroon, David L Buckley, Karl Embelton, Caleb Roberts, Danielle Balériaux, Alan Jackson.   

Abstract

PURPOSE: To characterize human gliomas using T1-weighted dynamic contrast-enhanced MRI (DCE-MRI), and directly compare three pharmacokinetic analysis techniques: a conventional established technique and two novel techniques that aim to reduce erroneous overestimation of the volume transfer constant between plasma and the extravascular extracellular space (EES) (Ktrans) in areas of high blood volume.
MATERIALS AND METHODS: Eighteen patients with high-grade gliomas underwent DCE-MRI. Three kinetic models were applied to estimate Ktrans and fractional blood plasma volume (vp). We applied the Tofts and Kermode (TK) model without arterial input function (AIF) estimation, the TK model modified to include vp and AIF estimation (mTK), and a "first pass" variant of the TK model (FP).
RESULTS: KTK values were considerably higher than KmTK and KFP values (P <0.001). KmTK and KFP were more comparable and closely correlated (rho=0.744), with KmTK generally higher than KFP (P <0.001). Estimates of vp(mTK) and vp(FP) also showed a significant difference (P <0.001); however, these values were very closely correlated (rho=0.901). KTK parameter maps showed "pseudopermeability" effects displaying numerous vessels. These were not visualized on KmTK and KFP maps but appeared on the corresponding vp maps, indicating a failure of the TK model in commonly occurring vascular regions.
CONCLUSION: Both of the methods that incorporate a measured AIF and an estimate of vp provide similar pathophysiological information and avoid erroneous overestimation of Ktrans in areas of significant vessel density, and thus allow a more accurate estimation of endothelial permeability.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15503330     DOI: 10.1002/jmri.20182

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  35 in total

1.  Automatic determination of arterial input function for dynamic contrast enhanced MRI in tumor assessment.

Authors:  Jeremy Chen; Jianhua Yao; David Thomasson
Journal:  Med Image Comput Comput Assist Interv       Date:  2008

2.  Prognosis prediction of non-enhancing T2 high signal intensity lesions in glioblastoma patients after standard treatment: application of dynamic contrast-enhanced MR imaging.

Authors:  Rihyeon Kim; Seung Hong Choi; Tae Jin Yun; Soon-Tae Lee; Chul-Kee Park; Tae Min Kim; Ji-Hoon Kim; Sun-Won Park; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim
Journal:  Eur Radiol       Date:  2016-06-29       Impact factor: 5.315

3.  Incorporating a vascular term into a reference region model for the analysis of DCE-MRI data: a simulation study.

Authors:  A Z Faranesh; T E Yankeelov
Journal:  Phys Med Biol       Date:  2008-04-25       Impact factor: 3.609

4.  Quantitative dynamic contrast-enhanced MR imaging shows widespread blood-brain barrier disruption in mild traumatic brain injury patients with post-concussion syndrome.

Authors:  Roh-Eul Yoo; Seung Hong Choi; Byung-Mo Oh; Sang Do Shin; Eun Jung Lee; Dong Jae Shin; Sang Won Jo; Koung Mi Kang; Tae Jin Yun; Ji-Hoon Kim; Chul-Ho Sohn
Journal:  Eur Radiol       Date:  2018-07-31       Impact factor: 5.315

5.  A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: I. Simulations.

Authors:  Matthias C Schabel; Jacob U Fluckiger; Edward V R DiBella
Journal:  Phys Med Biol       Date:  2010-08-03       Impact factor: 3.609

6.  Dynamic contrast-enhanced MR imaging in predicting progression of enhancing lesions persisting after standard treatment in glioblastoma patients: a prospective study.

Authors:  Roh-Eul Yoo; Seung Hong Choi; Tae Min Kim; Chul-Kee Park; Sung-Hye Park; Jae-Kyung Won; Il Han Kim; Soon Tae Lee; Hye Jeong Choi; Sung-Hye You; Koung Mi Kang; Tae Jin Yun; Ji-Hoon Kim; Chul-Ho Sohn
Journal:  Eur Radiol       Date:  2016-12-14       Impact factor: 5.315

Review 7.  Advanced magnetic resonance imaging of the physical processes in human glioblastoma.

Authors:  Jayashree Kalpathy-Cramer; Elizabeth R Gerstner; Kyrre E Emblem; Ovidiu Andronesi; Bruce Rosen
Journal:  Cancer Res       Date:  2014-09-01       Impact factor: 12.701

8.  High-resolution longitudinal assessment of flow and permeability in mouse glioma vasculature: Sequential small molecule and SPIO dynamic contrast agent MRI.

Authors:  M M Pike; C N Stoops; C P Langford; N S Akella; L B Nabors; G Y Gillespie
Journal:  Magn Reson Med       Date:  2009-03       Impact factor: 4.668

9.  Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response.

Authors:  R Venkatasubramanian; R B Arenas; M A Henson; N S Forbes
Journal:  Br J Cancer       Date:  2010-07-13       Impact factor: 7.640

10.  Comparison of microvascular permeability measurements, K(trans), determined with conventional steady-state T1-weighted and first-pass T2*-weighted MR imaging methods in gliomas and meningiomas.

Authors:  S Cha; L Yang; G Johnson; A Lai; M-H Chen; T Tihan; M Wendland; W P Dillon
Journal:  AJNR Am J Neuroradiol       Date:  2006-02       Impact factor: 3.825

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.