Literature DB >> 11599071

Method for quantitative mapping of dynamic MRI contrast agent uptake in human tumors.

M Rijpkema1, J H Kaanders, F B Joosten, A J van der Kogel, A Heerschap.   

Abstract

A method is presented for the acquisition and analysis of dynamic contrast-enhanced (DCE) MRI data, focused on the characterization of tumors in humans. Gadolinium (Gd) contrast was administered by bolus injection, and its effect was monitored in time by fast T1-weighted MRI. A simple algorithm was developed for automatic extraction of the arterial input function (AIF) from the DCE-MRI data. This AIF was used in the pixelwise pharmacokinetic determination of physiological vascular parameters in normal and tumor tissue. Maps were reconstructed to show the spatial distribution of parameter values. To test the reproducibility of the method 11 patients with different types of tumors were measured twice, and the rate of contrast agent uptake in the tumor was calculated. The results show that normalizing the DCE-MRI data using individual coregistered AIFs, instead of one common AIF for all patients, substantially reduces the variation between successive measurements. It is concluded that the proposed method enables the reproducible assessment of contrast agent uptake rates. Copyright 2001 Wiley-Liss, Inc.

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Year:  2001        PMID: 11599071     DOI: 10.1002/jmri.1207

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


  40 in total

1.  An expectation-maximisation approach for simultaneous pixel classification and tracer kinetic modelling in dynamic contrast enhanced-magnetic resonance imaging.

Authors:  Mario Sansone; Roberta Fusco; Antonella Petrillo; Mario Petrillo; Marcello Bracale
Journal:  Med Biol Eng Comput       Date:  2010-11-03       Impact factor: 2.602

Review 2.  Dynamic contrast-enhanced magnetic resonance imaging and pharmacokinetic models in prostate cancer.

Authors:  Tobias Franiel; Bernd Hamm; Hedvig Hricak
Journal:  Eur Radiol       Date:  2010-12-24       Impact factor: 5.315

3.  Head and neck cancer: how imaging predicts treatment outcome.

Authors:  Robert Hermans
Journal:  Cancer Imaging       Date:  2006-10-31       Impact factor: 3.909

4.  Perfusion CT for head and neck tumors: pilot study.

Authors:  Zoran Rumboldt; Riyadh Al-Okaili; John P Deveikis
Journal:  AJNR Am J Neuroradiol       Date:  2005-05       Impact factor: 3.825

5.  Correlation of volume transfer coefficient Ktrans with histopathologic grades of gliomas.

Authors:  Na Zhang; Lijuan Zhang; Bensheng Qiu; Li Meng; Xiaoyi Wang; Bob L Hou
Journal:  J Magn Reson Imaging       Date:  2012-05-11       Impact factor: 4.813

6.  Comparison between population average and experimentally measured arterial input function in predicting biopsy results in prostate cancer.

Authors:  Ran Meng; Silvia D Chang; Edward C Jones; S Larry Goldenberg; Piotr Kozlowski
Journal:  Acad Radiol       Date:  2010-01-13       Impact factor: 3.173

7.  Uncertainty and bias in contrast concentration measurements using spoiled gradient echo pulse sequences.

Authors:  Matthias C Schabel; Dennis L Parker
Journal:  Phys Med Biol       Date:  2008-04-17       Impact factor: 3.609

8.  Effect of breathing a hyperoxic hypercapnic gas mixture on the oxygenation of meningiomas; preliminary results.

Authors:  Janneke Schuuring; Mark Rijpkema; Hans Bernsen; Pieter Bernsen; Richard van der Maazen; Johannes Kaanders; Albert van der Kogel; Arend Heerschap
Journal:  J Neurooncol       Date:  2002-04       Impact factor: 4.130

9.  Respiratory motion-compensated radial dynamic contrast-enhanced (DCE)-MRI of chest and abdominal lesions.

Authors:  Wei Lin; Junyu Guo; Mark A Rosen; Hee Kwon Song
Journal:  Magn Reson Med       Date:  2008-11       Impact factor: 4.668

10.  Magnetic resonance imaging defines cervicovaginal anatomy, cancer, and VEGF trap antiangiogenic efficacy in estrogen-treated K14-HPV16 transgenic mice.

Authors:  Joel R Garbow; Andrea C Santeford; Jeff R Anderson; John A Engelbach; Jeffrey M Arbeit
Journal:  Cancer Res       Date:  2009-09-29       Impact factor: 12.701

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