Literature DB >> 10581502

MR imaging of tumor microcirculation: promise for the new millennium.

J S Taylor1, P S Tofts, R Port, J L Evelhoch, M Knopp, W E Reddick, V M Runge, N Mayr.   

Abstract

Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is a method of imaging the physiology of the microcirculation. A series of recent clinical studies have shown that DCE MRI can measure and predict tumor response to therapy. Recent advances in MR technology provide the enhanced spatial and temporal resolution that allow the application of this methodology in the management of cancer patients. The September issue of this journal provided a microcirculation section to update readers on this exciting and challenging topic. Evidence is mounting that DCE MRI-based measures correlate well with tumor angiogenesis. DCE MRI has already been shown in several types of tumors to correlate well with traditional outcome measures, such as histopathologic studies, and with survival. These new measures are sensitive to tumor physiology and to the pharmacokinetics of the contrast agent in individual tumors. Moreover, they can present anatomical images of tumor microcirculation at excellent spatial resolution. Several issues have emerged from recent international workshops that must be addressed to move this methodology into routine clinical practice. First, is complex modeling of DCE MRI really necessary to answer clinical questions reliably? Clinical research has shown that, for tumors such as bone sarcomas, reliable outcome measures of tumor response to chemotherapy can be extracted from DCE MRI by methods ranging from simple measures of enhancement to pharmacokinetic models. However, the use of similar methods to answer a different question-the differentiation of malignant from benign breast tumors-has yielded contradictory results. Thus, no simple, one-size-fits-all-tumors solution has yet been identified. Second, what is the most rational and reliable data collection procedure for the DCE MRI evaluation? Several groups have addressed population variations in some key variables, such as tumor T(1)0 (T(1) prior to contrast administration) and the arterial input function C(a)(t) for contrast agent, and how they influence the precision and accuracy of DCE MRI outcomes. However, despite these potential complications, clinical studies in this section show that some tumor types can be assessed by relatively simple dynamic measures and analyses. The clinical scenario and tumor type may well determine the required complexity of the DCE MRI exam procedure and its analysis. Finally, we suggest that a consensus on naming conventions (nomenclature) is needed to facilitate comparison and analysis of the results of studies conducted at different centers. J. Magn. Reson. Imaging 10:903-907, 1999. Copyright 1999 Wiley-Liss, Inc.

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Year:  1999        PMID: 10581502     DOI: 10.1002/(sici)1522-2586(199912)10:6<903::aid-jmri1>3.0.co;2-a

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


  47 in total

1.  Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors.

Authors:  Wei Yang; Jin Wei Qiang; Hai Ping Tian; Bing Chen; Ai Jun Wang; Jian Guo Zhao
Journal:  Eur Radiol       Date:  2017-08-04       Impact factor: 5.315

2.  [Dynamic magnetic resonance tomography (dMRT). It's value in advanced head-neck tumors treated with radiochemotherapy].

Authors:  M Helbig; H-P Schlemmer; M Lumer; M V Knopp; A Dietz
Journal:  HNO       Date:  2003-04-09       Impact factor: 1.284

Review 3.  Perfusion-weighted magnetic resonance imaging of the brain: techniques and application in children.

Authors:  Thierry A G M Huisman; A Gregory Sorensen
Journal:  Eur Radiol       Date:  2003-06-25       Impact factor: 5.315

4.  An in vivo correlate of exercise-induced neurogenesis in the adult dentate gyrus.

Authors:  Ana C Pereira; Dan E Huddleston; Adam M Brickman; Alexander A Sosunov; Rene Hen; Guy M McKhann; Richard Sloan; Fred H Gage; Truman R Brown; Scott A Small
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-20       Impact factor: 11.205

Review 5.  Update on brain tumor imaging: from anatomy to physiology.

Authors:  S Cha
Journal:  AJNR Am J Neuroradiol       Date:  2006-03       Impact factor: 3.825

Review 6.  Musculoskeletal tumors: how to use anatomic, functional, and metabolic MR techniques.

Authors:  Laura M Fayad; Michael A Jacobs; Xin Wang; John A Carrino; David A Bluemke
Journal:  Radiology       Date:  2012-11       Impact factor: 11.105

7.  A reference agent model for DCE MRI can be used to quantify the relative vascular permeability of two MRI contrast agents.

Authors:  Julio Cárdenas-Rodríguez; Christine M Howison; Terry O Matsunaga; Mark D Pagel
Journal:  Magn Reson Imaging       Date:  2013-04-11       Impact factor: 2.546

8.  High-resolution magnetic resonance angiography in the mouse using a nanoparticle blood-pool contrast agent.

Authors:  Gabriel P Howles; Ketan B Ghaghada; Yi Qi; Srinivasan Mukundan; G Allan Johnson
Journal:  Magn Reson Med       Date:  2009-12       Impact factor: 4.668

9.  Effects of tyrosine kinase inhibitors and CXCR4 antagonist on tumor growth and angiogenesis in rat glioma model: MRI and protein analysis study.

Authors:  Meser M Ali; Sanath Kumar; Adarsh Shankar; Nadimpalli R S Varma; A S M Iskander; Branislava Janic; Wilson B Chwang; Rajan Jain; Abbas Babajeni-Feremi; Thaiz F Borin; Hassan Bagher-Ebadian; Stephen L Brown; James R Ewing; Ali S Arbab
Journal:  Transl Oncol       Date:  2013-12-01       Impact factor: 4.243

10.  Ultra-early predictive assay for treatment failure using functional magnetic resonance imaging and clinical prognostic parameters in cervical cancer.

Authors:  Nina A Mayr; William T C Yuh; David Jajoura; Jian Z Wang; Simon S Lo; Joseph F Montebello; Kyle Porter; Dongqing Zhang; D Scott McMeekin; John M Buatti
Journal:  Cancer       Date:  2010-02-15       Impact factor: 6.860

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