Literature DB >> 15723402

Shutter-speed analysis of contrast reagent bolus-tracking data: Preliminary observations in benign and malignant breast disease.

Xin Li1, Wei Huang, Thomas E Yankeelov, Alina Tudorica, William D Rooney, Charles S Springer.   

Abstract

The standard pharmacokinetic model applied to contrast reagent (CR) bolus-tracking (B-T) MRI (dynamic-contrast-enhanced) data makes the intrinsic assumption that equilibrium transcytolemmal water molecule exchange is effectively infinitely fast. Theory and simulation have suggested that this assumption can lead to significant errors. Recent analyses of animal model experimental data have confirmed two predicted signature inadequacies: a specific temporal mismatch with the B-T time-course and a CR dose-dependent underestimation of model parameters. The most parsimonious adjustment to account for this aspect leads to the "shutter-speed" pharmacokinetic model. Application of the latter to the animal model data mostly eliminates the two signature inadequacies. Here, the standard and shutter-speed models are applied to B-T data obtained from routine human breast examinations. The signature standard model temporal mismatch is found for each of the three invasive ductal carcinoma (IDC) cases and for each of the three fibroadenoma (FA) cases studied. It is effectively eliminated by use of the shutter-speed model. The size of the mismatch is considerably greater for the IDC lesions than for the FA lesions, causing the shutter-speed model to exhibit improved discrimination of malignant IDC tumors from the benign FA lesions compared with the standard model. Furthermore, the shutter-speed model clearly reveals focal "hot spots" of elevated CR perfusion/permeation present in only the malignant tumors. (c) 2005 Wiley-Liss, Inc.

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Year:  2005        PMID: 15723402     DOI: 10.1002/mrm.20405

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  35 in total

1.  Integration of quantitative DCE-MRI and ADC mapping to monitor treatment response in human breast cancer: initial results.

Authors:  Thomas E Yankeelov; Martin Lepage; Anuradha Chakravarthy; Elizabeth E Broome; Kenneth J Niermann; Mark C Kelley; Ingrid Meszoely; Ingrid A Mayer; Cheryl R Herman; Kevin McManus; Ronald R Price; John C Gore
Journal:  Magn Reson Imaging       Date:  2006-11-21       Impact factor: 2.546

2.  Diagnosis of suspicious breast lesions using an empirical mathematical model for dynamic contrast-enhanced MRI.

Authors:  Xiaobing Fan; Milica Medved; Gregory S Karczmar; Cheng Yang; Sean Foxley; Sanaz Arkani; Wendy Recant; Marta A Zamora; Hiroyuki Abe; Gillian M Newstead
Journal:  Magn Reson Imaging       Date:  2006-11-30       Impact factor: 2.546

3.  Incorporating the effects of transcytolemmal water exchange in a reference region model for DCE-MRI analysis: theory, simulations, and experimental results.

Authors:  Thomas E Yankeelov; Jeffrey J Luci; Laura M DeBusk; P Charles Lin; John C Gore
Journal:  Magn Reson Med       Date:  2008-02       Impact factor: 4.668

4.  Dynamic-contrast-enhanced-MRI with extravasating contrast reagent: rat cerebral glioma blood volume determination.

Authors:  Xin Li; William D Rooney; Csanád G Várallyay; Seymur Gahramanov; Leslie L Muldoon; James A Goodman; Ian J Tagge; Audrey H Selzer; Martin M Pike; Edward A Neuwelt; Charles S Springer
Journal:  J Magn Reson       Date:  2010-07-31       Impact factor: 2.229

5.  Active trans-plasma membrane water cycling in yeast is revealed by NMR.

Authors:  Yajie Zhang; Marie Poirier-Quinot; Charles S Springer; James A Balschi
Journal:  Biophys J       Date:  2011-12-07       Impact factor: 4.033

6.  The evaluation of esophageal adenocarcinoma using dynamic contrast-enhanced magnetic resonance imaging.

Authors:  Eugene Y Chang; Xin Li; Michael Jerosch-Herold; Ryan A Priest; C Kristian Enestvedt; Jingang Xu; Charles S Springer; Blair A Jobe
Journal:  J Gastrointest Surg       Date:  2007-09-01       Impact factor: 3.452

7.  Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast-enhanced MRI.

Authors:  Samantha L Heller; Linda Moy; Sherlin Lavianlivi; Melanie Moccaldi; Sungheon Kim
Journal:  J Magn Reson Imaging       Date:  2012-10-23       Impact factor: 4.813

8.  Current and future trends in magnetic resonance imaging assessments of the response of breast tumors to neoadjuvant chemotherapy.

Authors:  Lori R Arlinghaus; Xia Li; Mia Levy; David Smith; E Brian Welch; John C Gore; Thomas E Yankeelov
Journal:  J Oncol       Date:  2010-09-29       Impact factor: 4.375

9.  Feasibility of using limited-population-based average R10 for pharmacokinetic modeling of osteosarcoma dynamic contrast-enhanced magnetic resonance imaging data.

Authors:  Wei Huang; Ya Wang; David M Panicek; Lawrence H Schwartz; Jason A Koutcher
Journal:  Magn Reson Imaging       Date:  2009-03-17       Impact factor: 2.546

10.  Gaussian mixture model-based classification of dynamic contrast enhanced MRI data for identifying diverse tumor microenvironments: preliminary results.

Authors:  S H Han; E Ackerstaff; R Stoyanova; S Carlin; W Huang; J A Koutcher; J K Kim; G Cho; G Jang; H Cho
Journal:  NMR Biomed       Date:  2013-02-25       Impact factor: 4.044

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