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  • Print publication year: 2011
  • Online publication date: December 2011

16 - The use of MRI in multiple sclerosis clinical trials

from Section II - Clinical trial methodology


The Food and Drug Administration (FDA) has offered guidance on using health related quality of life (HRQoL) measures to support labeling claims, and the definition of HRQoL has become more systematized. HRQoL measures look at patients' reports of their perceived health in either very general or very particular terms. Utility assessment is an increasingly active area of research in multiple sclerosis (MS). HRQoL data are used for three general purposes: to classify or group patients by levels of disease severity, predict the health of subjects at a future point in time, and as outcome variables. MS-specific HRQoL measures have been included as endpoints in many clinical studies, including some randomized controlled clinical trials. Selection of the most appropriate disease-specific measures by investigators should be based on available validity and reliability data for those measures and the specific questions that the researcher hopes to answer.


1. Polman CH, Reingold SC, Barkhof F, et al. Ethics of placebo-controlled clinical trials in multiple sclerosis: a reassessment. Neurology 2008; 70(13, 2):1134–40.
2. Sormani MP, Rovaris M, Bagnato F, et al. Sample size estimations for MRI-monitored trials of MS comparing new vs standard treatments. Neurology 2001; 57(10):1883–5.
3. Paty DW, McFarland H. Magnetic resonance techniques to monitor the long term evolution of multiple sclerosis pathology and to monitor definitive clinical trials. J Neurol, Neurosurg Psychiatry 1998; 64(Suppl 1):S47–51.
4. Martinelli Boneschi F, Rovaris M, Comi G, et al. The use of magnetic resonance imaging in multiple sclerosis: lessons learned from clinical trials. Mult Scler 2004; 10(4):341–7.
5. Prentice RL. Surrogate endpoints in clinical trials: definition and operational criteria. Stat Med 1989; 8(4):431–40.
6. Stone LA, Frank JA, Albert PS, et al. Characterization of MRI response to treatment with interferon beta-1b: contrast-enhancing MRI lesion frequency as a primary outcome measure. Neurology 1997; 49(3):862–9.
7. Smith ME, Stone LA, Albert PS, et al. Clinical worsening in multiple sclerosis is associated with increased frequency and area of gadopentetate dimeglumine-enhancing magnetic resonance imaging lesions. Ann Neurol 1993; 33(5):480–9.
8. Filippi M, Rovaris M, Capra R, et al. A multi-centre longitudinal study comparing the sensitivity of monthly MRI after standard and triple dose gadolinium-DTPA for monitoring disease activity in multiple sclerosis. Implications for phase II clinical trials. Brain 1998; 121 (Pt 10):2011–20.
9. Silver NC, Good CD, Sormani MP, et al. A modified protocol to improve the detection of enhancing brain and spinal cord lesions in multiple sclerosis. J Neurol 2001; 248(3):215–24.
10. Molyneux PD, Filippi M, Barkhof F, et al. Correlations between monthly enhanced MRI lesion rate and changes in T2 lesion volume in multiple sclerosis. Ann Neurol 1998; 43(3):332–9.
11. Stone LA, Albert PS, Smith ME, et al. Changes in the amount of diseased white matter over time in patients with relapsing-remitting multiple sclerosis. Neurology 1995; 45(10):1808–14.
12. Simon JH, Miller DE. Measures of gadolinium enhancement, T1 black holes and T2-hyperintense lesions on magnetic resonance imaging. In Cohen JA, Rudick RA, eds. London, UK: Informa Healthcare, 2007;113,114–142.
13. Li DK, Paty DW. Magnetic resonance imaging results of the PRISMS trial: a randomized, double-blind, placebo-controlled study of interferon-beta1a in relapsing–remitting multiple sclerosis. Prevention of relapses and disability by interferon-beta1a subcutaneously in multiple Sclerosis. Ann Neurol 1999; 46(2):197–206.
14. Moraal B, Van Den Elskamp IJ, Knol DL, et al. Long-interval T2-weighted subtraction magnetic resonance imaging: a powerful new outcome measure in multiple sclerosis trials. Ann Neurol 2010; 67(5):667–75.
15. Sormani MP, Bonzano L, Roccatagliata L, et al. Magnetic resonance imaging as a potential surrogate for relapses in multiple sclerosis: a meta-analytic approach. Ann Neurol 2009; 65(3):268–75.
16. Sormani MP, Rovaris M, Comi G, et al. A reassessment of the plateauing relationship between T2 lesion load and disability in MS. Neurology 2009; 73(19):1538–42.
17. Rudick RA, Lee JC, Simon J, et al. Significance of T2 lesions in multiple sclerosis: A 13-year longitudinal study. Ann Neurol 2006; 60(2):236–42.
18. Bakshi R, Ariyaratana S, Benedict RH, et al. Fluid-attenuated inversion recovery magnetic resonance imaging detects cortical and juxtacortical multiple sclerosis lesions. Arch Neurol 2001 May; 58(5):742–8.
19. Filippi M, Rocca MA, Gasperini C, et al. Interscanner variation in brain MR lesion load measurements in multiple sclerosis using conventional spin-echo, rapid relaxation-enhanced, and fast-FLAIR sequences. Am J Neuroradiol 1999; 20(1):133–7.
20. Sanfilipo MP, Benedict RH, Sharma J, et al. The relationship between whole brain volume and disability in multiple sclerosis: a comparison of normalized gray vs. white matter with misclassification correction. Neuroimage 2005; 26(4):1068–77.
21. van Walderveen MA, Kamphorst W, Scheltens P, et al. Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis. Neurology 1998; 50(5):1282–8.
22. Rudick RA, Fisher E, Lee JC, et al. Use of the brain parenchymal fraction to measure whole brain atrophy in relapsing-remitting MS. Multiple Sclerosis Collaborative Research Group. Neurology 1999; 53(8):1698–704.
23. Paolillo A, Pozzilli C, Gasperini C, et al. Brain atrophy in relapsing-remitting multiple sclerosis: relationship with ‘black holes’, disease duration and clinical disability. J Neurol Sci 2000; 174(2):85–91.
24. Simon JH, Lull J, Jacobs LD, et al. A longitudinal study of T1 hypointense lesions in relapsing MS: MSCRG trial of interferon beta-1a. Multiple Sclerosis Collaborative Research Group. Neurology 2000; 55(2):185–92.
25. Filippi M, Rovaris M, Rocca MA, et al. Glatiramer acetate reduces the proportion of new MS lesions evolving into “black holes”. Neurology 2001; 57(4):731–3.
26. Barkhof F, Hulst HE, Drulovic J, et al. Ibudilast in relapsing-remitting multiple sclerosis: a neuroprotectant? Neurology 2010; 74(13):1033–40.
27. Kappos L, Moeri D, Radue EW, et al. Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Gadolinium MRI Meta-analysis Group. Lancet 1999; 353(9157):964–9.
28. Sormani MP, Bruzzi P, Comi G, et al. MRI metrics as surrogate markers for clinical relapse rate in relapsing-remitting MS patients. Neurology 2002; 58(3):417–21.
29. Paolillo A, Coles AJ, Molyneux PD, et al. Quantitative MRI in patients with secondary progressive MS treated with monoclonal antibody Campath 1H. Neurology 1999; 53(4):751–7.
30. Rice GP, Filippi M, Comi G. Cladribine and progressive MS: clinical and MRI outcomes of a multicenter controlled trial. Cladribine MRI Study Group. Neurology 2000; 54(5):1145–55.
31. Miller DH, Barkhof F, Frank JA, et al. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain 2002; 125(8):1676–95.
32. Bermel RA, Bakshi R. The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol 2006; 5(2):158–70.
33. Paolillo A, Piattella MC, Pantano P, et al. The relationship between inflammation and atrophy in clinically isolated syndromes suggestive of multiple sclerosis: a monthly MRI study after triple-dose gadolinium-DTPA. J Neurol 2004; 251(4):432–9.
34. Brex PA, Jenkins R, Fox NC, et al. Detection of ventricular enlargement in patients at the earliest clinical stage of MS. Neurology 2000; 54(8):1689–91.
35. Fisher E, Rudick RA, Cutter G, et al. Relationship between brain atrophy and disability: an 8-year follow-up study of multiple sclerosis patients. Mult Scler 2000; 6(6):373–7.
36. Pelletier D, Garrison K, Henry R. Measurement of whole-brain atrophy in multiple sclerosis. [Review] [53 refs]. J Neuroimaging 2004; 14(3 Suppl):11S–9S.
37. Simon JH. Linear and regional measures of brain atrophy in multiple sclerosis. In Zivadinov R, Bakshi R, eds. Hauppauge: Nova Science; 2004:15–27.
38. Bermel RA, Sharma J, Tjoa CW, et al. A semiautomated measure of whole-brain atrophy in multiple sclerosis. J Neurol Sci 2003; 208(1–2):57–65.
39. Smith SM, Zhang Y, Jenkinson M, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 2002; 17(1):479–89.
40. Ge Y, Grossman RI, Udupa JK, et al. Brain atrophy in relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis: longitudinal quantitative analysis. Radiology 2000; 214(3):665–70.
41. Smith SM, De Stefano N, Jenkinson M, et al. Normalized accurate measurement of longitudinal brain change. J Comput Assist Tomogr 2001; 25(3):466–75.
42. Fox NC, Jenkins R, Leary SM, et al. Progressive cerebral atrophy in MS: a serial study using registered, volumetric MRI. Neurology 2000; 54(4):807–12.
43. Kappos L, Radue EW, O’Connor P, et al. A placebo-controlled trial of oral fingolimod in relapsing multiple sclerosis. N Engl J Med 2010; 362(5):387–401.
44. Anderson VM, Bartlett JW, Fox NC, et al. Detecting treatment effects on brain atrophy in relapsing remitting multiple sclerosis: sample size estimates. J Neurol 2007; 254(11):1588–94.
45. Filippi M, Rovaris M, Inglese M, et al. Interferon beta-1a for brain tissue loss in patients at presentation with syndromes suggestive of multiple sclerosis: a randomised, double-blind, placebo-controlled trial. Lancet 2004; 364(9444):1489–96.
46. Jones CK, Riddehough A, Li DKB, et al. MRI cerebral atrophy in relapsing-remitting MS: results from the PRISMS trial [abstract]. Neurology 2001; 56 (Suppl 3):A379.
47. Zivadinov R, Grop A, Sharma J, et al. Reproducibility and accuracy of quantitative magnetic resonance imaging techniques of whole-brain atrophy measurement in multiple sclerosis. J Neuroimaging 2005; 15(1):27–36.
48. Fox RJ, Fisher E, Tkach J, et al. Brain atrophy and magnetization transfer ratio following methylprednisolone in multiple sclerosis: short-term changes and long-term implications. Mult Scler 2005; 11(2):140–5.
49. Kapoor R, Furby J, Hayton T, et al. Lamotrigine for neuroprotection in secondary progressive multiple sclerosis: a randomised, double-blind, placebo-controlled, parallel-group trial. Lancet Neurol 2010; 9(7):681–8.
50. van Waesberghe JH, Kamphorst W, De Groot CJ, et al. Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol 1999; 46(5):747–54.
51. Phillips MD, Grossman RI, Miki Y, et al. Comparison of T2 lesion volume and magnetization transfer ratio histogram analysis and of atrophy and measures of lesion burden in patients with multiple sclerosis. Am J Neuroradiol 1998; 19(6):1055–60.
52. Cercignani M, Iannucci G, Rocca MA, et al. Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI. Neurology 2000; 54(5):1139–44.
53. Filippi M, Iannucci G, Tortorella C, et al. Comparison of MS clinical phenotypes using conventional and magnetization transfer MRI. Neurology 1999; 52(3):588–94.
54. Kalkers NF, Hintzen RQ, van Waesberghe JH, et al. Magnetization transfer histogram parameters reflect all dimensions of MS pathology, including atrophy. J Neurol Sci 2001; 184(2):155–62.
55. Inglese M, van Waesberghe JH, Rovaris M, et al. The effect of interferon beta-1b on quantities derived from MT MRI in secondary progressive MS. Neurology 2003; 60(5):853–60.
56. Chen JT, Schneider C, Nakamura K, et al. Validation of MRI-based measurements of subpial cortical demyelination in an MS brain. Mult Scler 2010; 16(S10):S107.
57. van Waesberghe JH, van Walderveen MA, Castelijns JA, et al. Patterns of lesion development in multiple sclerosis: longitudinal observations with T1-weighted spin-echo and magnetization transfer MR. AJNR Am J Neuroradiol 1998; 19(4):675–83.
58. Richert ND, Ostuni JL, Bash CN, et al. Interferon beta-1b and intravenous methylprednisolone promote lesion recovery in multiple sclerosis. Mult Scler 2001; 7(1):49–58.
59. Kita M, Goodkin DE, Bacchetti P, et al. Magnetization transfer ratio in new MS lesions before and during therapy with IFNbeta-1a. Neurology 2000; 54(9):1741–5.
60. Horsfield MA, Barker GJ, Barkhof F, et al. Guidelines for using quantitative magnetization transfer magnetic resonance imaging for monitoring treatment of multiple sclerosis. J Magn Reson Imaging 2003; 17(4):389–97.
61. Fox RJ, Sakaie K, Lee JC, et al. A validation study of multi-centre diffusion tensor imaging. Mult Scler 2007; 13(S7):S76.
62. Rocca MA, Cercignani M, Iannucci G, et al. Weekly diffusion-weighted imaging of normal-appearing white matter in MS. Neurology 2000; 55(6):882–4.
63. Werring DJ, Brassat D, Droogan AG, et al. The pathogenesis of lesions and normal-appearing white matter changes in multiple sclerosis: a serial diffusion MRI study. Brain 2000; 123: 1667–76.
64. Fox RJ. Picturing multiple sclerosis: conventional and diffusion tensor imaging. Semin Neurol 2008; 28(4):453–66.
65. Harrison DM, Caffo BS, Shiee N, et al. Longitudinal changes in diffusion tensor–based quantitative MRI in multiple sclerosis. Neurology 2011; 76(2):179–86.
66. Bjartmar C, Battistuta J, Terada N, et al. N-acetylaspartate is an axon-specific marker of mature white matter in vivo: a biochemical and immunohistochemical study on the rat optic nerve. Ann Neurol 2002; 51(1):51–8.
67. Matthews PM, Pioro E, Narayanan S, et al. Assessment of lesion pathology in multiple sclerosis using quantitative MRI morphometry and magnetic resonance spectroscopy. Brain 1996; 119 (3):715–22.
68. Fu L, Matthews PM, De Stefano N, et al. Imaging axonal damage of normal-appearing white matter in multiple sclerosis. Brain 1998; 121 (1):103–13.
69. Sarchielli P, Presciutti O, Tarducci R, et al. 1H-MRS in patients with multiple sclerosis undergoing treatment with interferon beta-1a: results of a preliminary study. J Neurol Neurosurg Psychiatry 1998; 64(2):204–12.
70. Parry A, Corkill R, Blamire AM, et al. Beta-Interferon treatment does not always slow the progression of axonal injury in multiple sclerosis. J Neurol 2003; 250(2):171–8.
71. Khan O, Shen Y, Caon C, et al. Axonal metabolic recovery and potential neuroprotective effect of glatiramer acetate in relapsing-remitting multiple sclerosis. Mult Scler 2005; 11(6):646–51.
72. Inglese M, Ge Y, Filippi M, et al. Indirect evidence for early widespread gray matter involvement in relapsing-remitting multiple sclerosis. Neuroimage 2004; 21(4):1825–9.
73. Rovaris M, Gambini A, Gallo A, et al. Axonal injury in early multiple sclerosis is irreversible and independent of the short-term disease evolution. Neurology 2005; 65(10):1626–30.
74. De Stefano N, Filippi M, Miller D, et al. Guidelines for using proton MR spectroscopy in multicenter clinical MS studies. Neurology 2007; 69(20):1942–52.
75. Sailer M, Fischl B, Salat D, et al. Focal thinning of the cerebral cortex in multiple sclerosis. Brain 2003; 126(8):1734–44.
76. Fisher E, Lee JC, Nakamura K, et al. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol 2008; 64(3):255–65.
77. Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain 2004; 127(5):1101–7.
78. Chen JT, Collins DL, Atkins HL, et al. Brain atrophy after immunoablation and stem cell transplantation in multiple sclerosis. Neurology 2006; 66(12):1935–7.
79. Benedict RH, Ramasamy D, Munschauer F, et al. Memory impairment in multiple sclerosis: correlation with deep grey matter and mesial temporal atrophy. J Neurol Neurosurg Psychiatry 2009; 80(2):201–6.
80. Sanfilipo MP, Benedict RH, Weinstock-Guttman B, et al. Gray and white matter brain atrophy and neuropsychological impairment in multiple sclerosis. Neurology 2006; 66(5):685–92.
81. Stevenson VL, Leary SM, Losseff NA, et al. Spinal cord atrophy and disability in MS: a longitudinal study. Neurology 1998; 51(1):234–8.
82. Horsfield MA, Sala S, Neema M, et al. Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: application in multiple sclerosis. Neuroimage 2010; 50(2):446–55.
83. Filippi M, Rocca MA, Colombo B, et al. Functional magnetic resonance imaging correlates of fatigue in multiple sclerosis. Neuroimage 2002; 15(3):559–67.
84. Polman CH, Reingold SC, Banwell B, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald Criteria. Ann Neurol 2011; 69(2):292–302.
85. Martinez-Yelamos S, Martinez-Yelamos A, Martin Ozaeta G, et al. Regression to the mean in multiple sclerosis. Mult Scler 2006; 12(6):826–9.
86. Panitch HS, Hirsch RL, Schindler J, et al. Treatment of multiple sclerosis with gamma interferon: exacerbations associated with activation of the immune system. Neurology 1987; 37(7):1097–102.
87. TNF neutralization in MS: results of a randomized, placebo-controlled multicenter study. The Lenercept Multiple Sclerosis Study Group and The University of British Columbia MS/MRI Analysis Group. Neurology 1999; 53(3):457–65.
88. Bielekova B, Goodwin B, Richert N, et al. Encephalitogenic potential of the myelin basic protein peptide (amino acids 83–99) in multiple sclerosis: results of a phase II clinical trial with an altered peptide ligand. Nat Med 2000; 6(10):1167–75.
89. Ransohoff RM. Natalizumab and PML. Nat Neurosci 2005; 8(10):1275.
90. Illes J, Kirschen MP, Edwards E, et al. Practical approaches to incidental findings in brain imaging research. Neurology 2008; 70(5):384–90.
91. Morris Z, Whiteley WN, Longstreth WT, et al. Incidental findings on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ; 339.
92. Kappos L, Antel J, Comi G, et al. Oral fingolimod (FTY720) for relapsing multiple sclerosis. N Engl J Med 2006; 355(11):1124–40.
93. Hauser SL, Waubant E, Arnold DL, et al. B-cell depletion with rituximab in relapsing-remitting multiple sclerosis. N Engl J Med 2008; 358(7):676–88.
94. O’Connor P, Miller D, Riester K, et al. Relapse rates and enhancing lesions in a phase II trial of natalizumab in multiple sclerosis. Mult Scler 2005; 11(5):568–72.
95. Polman CH, O’Connor PW, Havrdova E, et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N Engl J Med 2006; 354(9):899–910.
96. Rudick RA, Stuart WH, Calabresi PA, et al. Natalizumab plus interferon beta-1a for relapsing multiple sclerosis. N Engl J Med 2006; 354(9):911–23.
97. Healy BC, Ikle D, Macklin EA, et al. Optimal design and analysis of phase I/II clinical trials in multiple sclerosis with gadolinium-enhanced lesions as the endpoint. Mult Scler 2010; 16(7):840–7.
98. Sormani MP, Miller DH, Comi G, et al. Clinical trials of multiple sclerosis monitored with enhanced MRI: new sample size calculations based on large data sets. J Neurol Neurosurg Psychiatry 2001; 70(4):494–9.
99. Filippi M, Yousry T, Campi A, et al. Comparison of triple dose versus standard dose gadolinium-DTPA for detection of MRI enhancing lesions in patients with MS. Neurology 1996; 46(2):379–84.
100. Gasperini C, Pozzilli C, Bastianello S, et al. The influence of clinical relapses and steroid therapy on the development of Gd-enhancing lesions: a longitudinal MRI study in relapsing-remitting multiple sclerosis patients. Acta Neurol Scand 1997; 95(4):201–7.
101. Goodin DS. Magnetic resonance imaging as a surrogate outcome measure of disability in multiple sclerosis: have we been overly harsh in our assessment? Ann Neurol 2006; 59(4):597–605.
102. Cohen JA, Barkhof F, Comi G, et al. Oral fingolimod or intramuscular interferon for relapsing multiple sclerosis. N Engl J Med 2010; 362(5):402–15.
103. Molyneux PD, Miller DH, Filippi M, et al. The use of magnetic resonance imaging in multiple sclerosis treatment trials: power calculations for annual lesion load measurement. J Neurol 2000; 247(1):34–40.
104. Matts JP, Lachin JM. Properties of permuted-block randomization in clinical trials. Control Clin Trials 1988; 9(4):327–44.
105. Begg CB, Iglewicz B. A treatment allocation procedure for sequential clinical trials. Biometrics 1980; 36(1):81–90.
106. Cohen JA, Imrey PB, Calabresi PA, et al. Results of the Avonex Combination Trial (ACT) in relapsing–remitting MS. Neurology 2009; 72(6):535–41.
107. Comi G, Cohen JA, Arnold DL, et al. Phase III dose-comparison study of glatiramer acetate for multiple sclerosis. Ann Neurol 2011; 69(1):75–82.
108. Morgan CJ, Aban IB, Katholi CR, et al. Modeling lesion counts in multiple sclerosis when patients have been selected for baseline activity. Mult Scler 2010; 16(8):926–34.
109. Van Den Elskamp I, Knol D, Uitdehaag B, et al. The distribution of new enhancing lesion counts in multiple sclerosis: further explorations. Mult Scler 2009; 15(1):42–9.
110. Aban IB, Cutter GR, Mavinga N. Inferences and power analysis concerning two negative binomial distributions with an application to MRI lesion counts data. Comput Stat Data Anal 2009; 53(3):820–33.
111. Radue EW, Stuart WH, Calabresi PA, et al. Natalizumab plus interferon beta-1a reduces lesion formation in relapsing multiple sclerosis. J Neurol Sci 2010; 292(1–2):28–35.
112. Koch GG, Tangen CM, Jung JW, et al. Issues for covariance analysis of dichotomous and ordered categorical data from randomized clinical trials and non-parametric strategies for addressing them. Stat Med 1998; 17(15–16):1863–92.
113. Li DK, Held U, Petkau J, et al. MRI T2 lesion burden in multiple sclerosis: a plateauing relationship with clinical disability. Neurology 2006; 66(9):1384–9.
114. Lange KL, Little RJA, Taylor JMG. Robust Statistical Modeling Using the Distribution. J Am Stat Assoc 1989; 84(408):pp. 881–96.
115. Lin TI, Lee JC. A robust approach to linear mixed models applied to multiple sclerosis data. Stat Med 2006; 25(8):1397–412.
116. Gill PS. A robust mixed linear model analysis for longitudinal data. Stat Med 2000; 19(7):975–87.
117. D’yachkova Y, Petkau J, White R. Longitudinal analyses for magnetic resonance imaging outcomes in multiple sclerosis clinical trials. J Biopharm Stat 1997; 7(4):501–31.
118. Altman RM, Petkau AJ. Application of hidden Markov models to multiple sclerosis lesion count data. Stat Med 2005; 24(15):2335–44.
119. Chataway J, Nicholas R, Todd S, et al. A novel adaptive design strategy increases the efficiency of clinical trials in secondary progressive multiple sclerosis. Mult Scler 2011; 17(1):81–8.
120. Friede T, Schmidli H. Blinded sample size reestimation with negative binomial counts in superiority and non-inferiority trials. Methods Inf Med 2010; 49(6):618–24.
121. Gasperini C, Rovaris M, Sormani MP, et al. Intra-observer, inter-observer and inter-scanner variations in brain MRI volume measurements in multiple sclerosis. Mult Scler 2001; 7(1):27–31.
122. Han X, Jovicich J, Salat D, et al. Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. Neuroimage 2006; 32(1):180–94.
123. Molyneux PD, Wang L, Lai M, et al. Quantitative techniques for lesion load measurement in multiple sclerosis: an assessment of the global threshold technique after non uniformity and histogram matching corrections. Eur J Neurol 1998; 5(1):55–60.
124. Raff U, Rojas GM, Hutchinson M, et al. Quantitation of T2 lesion load in patients with multiple sclerosis: a novel semiautomated segmentation technique. Acad Radiol 2000; 7(4):237–47.
125. Alfano B, Brunetti A, Larobina M, et al. Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis. J Magn Reson Imaging 2000; 12(6):799–807.
126. Anbeek P, Vincken KL, van Osch MJ, et al. Automatic segmentation of different-sized white matter lesions by voxel probability estimation. Med Image Anal 2004; 8(3):205–15.
127. Wu Y, Warfield SK, Tan IL, et al. Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI. Neuroimage 2006; 32(3):1205–15.
128. Achiron A, Gicquel S, Miron S, et al. Brain MRI lesion load quantification in multiple sclerosis: a comparison between automated multispectral and semi-automated thresholding computer-assisted techniques. Magn Reson Imaging 2002; 20(10):713–20.
129. Nakamura K, Fisher E. Segmentation of brain magnetic resonance images for measurement of gray matter atrophy in multiple sclerosis patients. Neuroimage 2009; 44(3):769–76.