Effects of Gadolinium Contrast Agent Administration on Automatic Brain Tissue Classification of Patients with Multiple Sclerosis

References

1. 1.↵
   1. Barkhof F

   . The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 2002;15:239–45

   CrossRefPubMedWeb of Science
2. 2.↵
   1. Chard D,
   2. Miller D

   . Is multiple sclerosis a generalized disease of the central nervous system? An MRI perspective. Curr Opin Neurol 2009;22:214–18

   CrossRefPubMedWeb of Science
3. 3.↵
   1. Minneboo A,
   2. Uitdehaag BM,
   3. Jongen P,
   4. et al

   . Association between MRI parameters and the MS severity scale: a 12 year follow-up study. Mult Scler 2009;15:632–37

   Abstract/FREE Full Text
4. 4.↵
   1. Zivadinov R,
   2. Cox JL

   . Neuroimaging in multiple sclerosis. Int Rev Neurobiol 2007;79:449–74

   CrossRefPubMedWeb of Science
5. 5.↵
   1. Filippi M,
   2. Tortorella C,
   3. Bozzali M

   . Normal-appearing white matter changes in multiple sclerosis: the contribution of magnetic resonance techniques. Mult Scler 1999;5:273–82

   Abstract/FREE Full Text
6. 6.↵
   1. Miller DH,
   2. Barkhof F,
   3. Frank JA,
   4. et al

   . Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain 2002;125:1676–95

   Abstract/FREE Full Text
7. 7.↵
   1. Mortazavi D,
   2. Kouzani AZ,
   3. Soltanian-Zadeh H

   . Segmentation of multiple sclerosis lesions in MR images: a review. Neuroradiology 2012;54:299–320

   CrossRefPubMed
8. 8.↵
   1. Grassiot B,
   2. Desgranges B,
   3. Eustache F,
   4. et al

   . Quantification and clinical relevance of brain atrophy in multiple sclerosis: a review. J Neurol 2009;256:1397–412

   CrossRefPubMedWeb of Science
9. 9.↵
   1. Chard DT,
   2. Griffin CM,
   3. Parker GJ,
   4. et al

   . Brain atrophy in clinically early relapsing-remitting multiple sclerosis. Brain 2002;125:327–37

   Abstract/FREE Full Text
10. 10.↵
    1. Andersen AH,
    2. Zhang Z,
    3. Avison MJ,
    4. et al

    . Automated segmentation of multispectral brain MR images. J Neurosci Methods 2002;122:13–23

    CrossRefPubMed
11. 11.↵
    1. Alfano B,
    2. Brunetti A,
    3. Covelli EM,
    4. et al

    . Unsupervised, automated segmentation of the normal brain using a multispectral relaxometric magnetic resonance approach. Magn Reson Med 1997;37:84–93

    CrossRefPubMedWeb of Science
12. 12.↵
    1. Ishii K,
    2. Soma T,
    3. Kono AK,
    4. et al

    . Automatic volumetric measurement of segmented brain structures on magnetic resonance imaging. Radiat Med 2006;24:422–30

    CrossRefPubMed
13. 13.↵
    1. Ashburner J,
    2. Friston KJ

    . Unified segmentation. Neuroimage 2005;26:839–51

    CrossRefPubMedWeb of Science
14. 14.↵
    1. Fischl B

    . FreeSurfer. Neuroimage 2012;62:774–81

    CrossRefPubMedWeb of Science
15. 15.↵
    1. Hasan KM,
    2. Walimuni IS,
    3. Abid H,
    4. et al

    . Human brain atlas-based multimodal MRI analysis of volumetry, diffusimetry, relaxometry and lesion distribution in multiple sclerosis patients and healthy adult controls: implications for understanding the pathogenesis of multiple sclerosis and consolidation of quantitative MRI results in MS. J Neurol Sci 2012;313:99–109

    CrossRefPubMed
16. 16.↵
    1. West J,
    2. Warntjes JB,
    3. Lundberg P

    . Novel whole brain segmentation and volume estimation using quantitative MRI. Eur Radiol 2012;22:998–1007

    CrossRefPubMed
17. 17.↵
    1. Anbeek P,
    2. Vincken KL,
    3. van Bochove GS,
    4. et al

    . Probabilistic segmentation of brain tissue in MR imaging. Neuroimage 2005;27:795–804

    CrossRefPubMedWeb of Science
18. 18.↵
    1. Shattuck DW,
    2. Sandor-Leahy SR,
    3. Schaper KA,
    4. et al

    . Magnetic resonance image tissue classification using a partial volume model. Neuroimage 2001;13:856–76

    PubMedWeb of Science
19. 19.↵
    1. Kovacevic N,
    2. Lobaugh NJ,
    3. Bronskill MJ,
    4. et al

    . A robust method for extraction and automatic segmentation of brain images. Neuroimage 2002;17:1087–100

    CrossRefPubMedWeb of Science
20. 20.↵
    1. Jovicich J,
    2. Czanner S,
    3. Han X,
    4. et al

    . MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths. Neuroimage 2009;46:177–92

    CrossRefPubMedWeb of Science
21. 21.↵
    1. MacKay A,
    2. Laule C,
    3. Vavasour I.,
    4. et al

    . Insights into brain microstructure from the T2 distribution. Magn Reson Imaging 2006;24:515–25

    CrossRefPubMedWeb of Science
22. 22.↵
    1. Larsson HB,
    2. Frederiksen J,
    3. Petersen,
    4. et al

    . Assessment of demyelineation, edema and gliosis by in-vivo determination of T1 and T2 in the brain of patients with acute attack of multiple sclerosis. J Magn Reson Med 1989;11:337–38

    CrossRef
23. 23.↵
    1. Pengas G,
    2. Pereira JMS,
    3. Williams GB,
    4. et al

    . Comparative reliability of total intracranial volume estimation methods and the influence of atrophy in a longitudinal semantic dementia cohort. J Neuroimaging 2009;19:37–46

    CrossRefPubMedWeb of Science
24. 24.↵
    1. Ambarki K,
    2. Lindqvist T,
    3. Wåhlin A,
    4. et al

    . Evaluation of automatic measurement of the intracranial volume based on quantitative MR imaging. AJNR Am J Neuroradiol 2012;33:1951–56

    Abstract/FREE Full Text
25. 25.↵
    1. Vågberg M,
    2. Lindqvist T,
    3. Ambarki K,
    4. et al

    . Automated determination of brain parenchymal fraction in multiple sclerosis. AJNR Am J Neuroradiol 2013;34:498–504

    Abstract/FREE Full Text
26. 26.↵
    1. Warntjes JB,
    2. Dahlqvist Leinhard O,
    3. West J,
    4. et al

    . Optimization for clinical usage of rapid magnetic resonance quantification on the brain. Magn Reson Med 2008;60:320–29

    CrossRefPubMed
27. 27.↵
    1. Tofts P

    . Quantitative MRI of the Brain. Chichester, UK: Wiley; 2003
28. 28.↵
    1. Poser CM,
    2. Paty DW,
    3. Scheinberg L,
    4. et al

    . New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13:227–31

    CrossRefPubMedWeb of Science
29. 29.↵
    1. McDonald WI,
    2. Compston A,
    3. Edan G,
    4. et al

    . Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the Diagnosis of Multiple Sclerosis. Ann Neurol 2001;50:121–27

    CrossRefPubMedWeb of Science
30. 30.↵
    1. Kurtzke JF

    . Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983;33:1444–52

    CrossRefPubMed
31. 31.↵
    1. Whitwell JL,
    2. Crum WR,
    3. Watt HC,
    4. et al

    . Normalization of cerebral volumes by use of intracranial volume: implications for longitudinal quantitative MR imaging. AJNR Am J Neuroradiol 2001;22:1483–89

    Abstract/FREE Full Text
32. 32.↵
    1. Rudick RA,
    2. Fisher E,
    3. Lee JC,
    4. et al

    . Use of brain parenchymal fraction to measure whole brain atrophy in relapsing-remitting MS: Multiple Sclerosis Collaborative Group. Neurology 1999;53:1698–704

    CrossRef
33. 33.↵
    1. DeCarli C,
    2. Massaro J,
    3. Harvey D,
    4. et al

    . Measures of brain morphology and infarction in the Framingham Heart Study: establishing what is normal. Neurobiol Aging 2005;26:491–510

    CrossRefPubMedWeb of Science
34. 34.↵
    1. Battaglini M,
    2. Jenkinson M,
    3. De Stefano N

    . Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp 2012;33:2062–71

    CrossRefPubMedWeb of Science