Literature DB >> 22442041

Predicting breakdown of the blood-brain barrier in multiple sclerosis without contrast agents.

R T Shinohara1, J Goldsmith, F J Mateen, C Crainiceanu, D S Reich.   

Abstract

BACKGROUND AND
PURPOSE: Disruption of the BBB in MS is associated with the development of new lesions and clinical relapses and signifies the presence of active inflammation. It is most commonly detected as enhancement on MR imaging performed with contrast agents that are costly and occasionally toxic. We investigated whether the BBB status in white matter lesions may be indirectly ascertained via examination of features on T1- and T2-weighted images obtained before the injection of a contrast agent.
MATERIALS AND METHODS: We considered 93 brain MR imaging studies on 16 patients that included T1-, T2-, and T2-weighted FLAIR images and predicted voxel wise enhancement after intravenous injection of a gadolinium chelate. We then used these voxel-level predictions to determine the presence or absence of abnormal enhancement anywhere in the brain.
RESULTS: On a voxel-by-voxel basis, enhancement can be predicted by using contrast-free measures with an AUC of 0.83 (95% CI, 0.80-0.87). At the whole-brain level, enhancement can be predicted with an AUC of 0.72 (95% CI, 0.62-0.82).
CONCLUSIONS: In many cases, breakdown of the BBB in acute MS lesions may be inferred without the need to inject an MR imaging contrast agent. The inference relies on intrinsic properties of tissue damage in acute lesions. Although contrast studies are more accurate, they may sometimes be unnecessary.

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Year:  2012        PMID: 22442041      PMCID: PMC3555688          DOI: 10.3174/ajnr.A2997

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  12 in total

1.  Relapsing and remitting multiple sclerosis: pathology of the newly forming lesion.

Authors:  Michael H Barnett; John W Prineas
Journal:  Ann Neurol       Date:  2004-04       Impact factor: 10.422

2.  Uncovering and characterizing multiple sclerosis lesions: the aid of fluid-attenuated inversion recovery images in the presence of gadolinium contrast agent.

Authors:  Francesca Bagnato
Journal:  J Neuroimaging       Date:  2009-01-29       Impact factor: 2.486

3.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

Authors:  J G Sled; A P Zijdenbos; A C Evans
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4.  Frequency and severity of adverse effects of iodinated and gadolinium contrast materials: retrospective review of 456,930 doses.

Authors:  Christopher H Hunt; Robert P Hartman; Gina K Hesley
Journal:  AJR Am J Roentgenol       Date:  2009-10       Impact factor: 3.959

5.  Frequency and severity of acute allergic-like reactions to gadolinium-containing i.v. contrast media in children and adults.

Authors:  Jonathan R Dillman; James H Ellis; Richard H Cohan; Peter J Strouse; Sophia C Jan
Journal:  AJR Am J Roentgenol       Date:  2007-12       Impact factor: 3.959

Review 6.  Current status of gadolinium toxicity in patients with kidney disease.

Authors:  Mark A Perazella
Journal:  Clin J Am Soc Nephrol       Date:  2009-02       Impact factor: 8.237

7.  Nephrogenic systemic fibrosis: a case series suggesting gadolinium as a possible aetiological factor.

Authors:  J A Moreno-Romero; S Segura; J M Mascaró; S E Cowper; M Julià; E Poch; A Botey; C Herrero
Journal:  Br J Dermatol       Date:  2007-07-11       Impact factor: 9.302

Review 8.  Nephrogenic systemic fibrosis: a gadolinium-associated fibrosing disorder in patients with renal dysfunction.

Authors:  J Kay
Journal:  Ann Rheum Dis       Date:  2008-12       Impact factor: 19.103

9.  Early contrast-enhanced magnetic resonance imaging with fluid-attenuated inversion recovery in multiple sclerosis.

Authors:  Hiroshi Kataoka; Toshiaki Taoka; Satoshi Ueno
Journal:  J Neuroimaging       Date:  2008-10-22       Impact factor: 2.486

10.  Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria.

Authors:  Chris H Polman; Stephen C Reingold; Brenda Banwell; Michel Clanet; Jeffrey A Cohen; Massimo Filippi; Kazuo Fujihara; Eva Havrdova; Michael Hutchinson; Ludwig Kappos; Fred D Lublin; Xavier Montalban; Paul O'Connor; Magnhild Sandberg-Wollheim; Alan J Thompson; Emmanuelle Waubant; Brian Weinshenker; Jerry S Wolinsky
Journal:  Ann Neurol       Date:  2011-02       Impact factor: 10.422

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  14 in total

1.  Quantitative MRI for Analysis of Active Multiple Sclerosis Lesions without Gadolinium-Based Contrast Agent.

Authors:  I Blystad; I Håkansson; A Tisell; J Ernerudh; Ö Smedby; P Lundberg; E-M Larsson
Journal:  AJNR Am J Neuroradiol       Date:  2015-10-15       Impact factor: 3.825

2.  Scan-stratified case-control sampling for modeling blood-brain barrier integrity in multiple sclerosis.

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Journal:  Stat Med       Date:  2015-05-04       Impact factor: 2.373

Review 3.  Neuroinflammatory imaging biomarkers: relevance to multiple sclerosis and its therapy.

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Journal:  Neurotherapeutics       Date:  2013-01       Impact factor: 7.620

4.  A Spatio-Temporal Model for Longitudinal Image-on-Image Regression.

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5.  Deep Learning for Predicting Enhancing Lesions in Multiple Sclerosis from Noncontrast MRI.

Authors:  Ponnada A Narayana; Ivan Coronado; Sheeba J Sujit; Jerry S Wolinsky; Fred D Lublin; Refaat E Gabr
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Review 6.  Clinical quantitative susceptibility mapping (QSM): Biometal imaging and its emerging roles in patient care.

Authors:  Yi Wang; Pascal Spincemaille; Zhe Liu; Alexey Dimov; Kofi Deh; Jianqi Li; Yan Zhang; Yihao Yao; Kelly M Gillen; Alan H Wilman; Ajay Gupta; Apostolos John Tsiouris; Ilhami Kovanlikaya; Gloria Chia-Yi Chiang; Jonathan W Weinsaft; Lawrence Tanenbaum; Weiwei Chen; Wenzhen Zhu; Shixin Chang; Min Lou; Brian H Kopell; Michael G Kaplitt; David Devos; Toshinori Hirai; Xuemei Huang; Yukunori Korogi; Alexander Shtilbans; Geon-Ho Jahng; Daniel Pelletier; Susan A Gauthier; David Pitt; Ashley I Bush; Gary M Brittenham; Martin R Prince
Journal:  J Magn Reson Imaging       Date:  2017-03-10       Impact factor: 4.813

7.  Magnetic Susceptibility from Quantitative Susceptibility Mapping Can Differentiate New Enhancing from Nonenhancing Multiple Sclerosis Lesions without Gadolinium Injection.

Authors:  Y Zhang; S A Gauthier; A Gupta; L Tu; J Comunale; G C-Y Chiang; W Chen; C A Salustri; W Zhu; Y Wang
Journal:  AJNR Am J Neuroradiol       Date:  2016-06-30       Impact factor: 3.825

8.  Quantitative Susceptibility Mapping and R2* Measured Changes during White Matter Lesion Development in Multiple Sclerosis: Myelin Breakdown, Myelin Debris Degradation and Removal, and Iron Accumulation.

Authors:  Y Zhang; S A Gauthier; A Gupta; W Chen; J Comunale; G C-Y Chiang; D Zhou; G Askin; W Zhu; D Pitt; Y Wang
Journal:  AJNR Am J Neuroradiol       Date:  2016-06-02       Impact factor: 3.825

9.  OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.

Authors:  Elizabeth M Sweeney; Russell T Shinohara; Navid Shiee; Farrah J Mateen; Avni A Chudgar; Jennifer L Cuzzocreo; Peter A Calabresi; Dzung L Pham; Daniel S Reich; Ciprian M Crainiceanu
Journal:  Neuroimage Clin       Date:  2013-03-15       Impact factor: 4.881

10.  Biomarkers in Multiple Sclerosis: An Up-to-Date Overview.

Authors:  Serafeim Katsavos; Maria Anagnostouli
Journal:  Mult Scler Int       Date:  2013-01-22
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