Mapping the Progressive Treatment-Related Reduction of Active MRI Lesions in Multiple Sclerosis

Antonio Giorgio, Marco Battaglini, Giordano Gentile, Maria Laura Stromillo, Claudio Gasperini, Andrea Visconti, Andrea Paolillo, Nicola De Stefano, Antonio Giorgio, Marco Battaglini, Giordano Gentile, Maria Laura Stromillo, Claudio Gasperini, Andrea Visconti, Andrea Paolillo, Nicola De Stefano

Abstract

Objective: To assess treatment-related spatio-temporal dynamics of active MRI lesions in relapsing-remitting multiple sclerosis (RRMS) patients. Methods: We performed a post-hoc analysis of MRI data acquired at weeks 4, 8, 12, and 16, in RRMS patients from the multicenter randomized IMPROVE study, which compares patients treated with 44 mcg subcutaneous interferon β-1a three times weekly (n = 120) versus placebo (n = 60). We created lesion probability maps (LPMs) of the cumulative combined unique active (CUA) lesions in each patient group at each time point. Group differences were tested in terms of lesion spatial distribution and frequency of occurrence. Results: Spatial distribution of CUA lesions throughout the study was less widespread in the treated than placebo group, with a 50% lower lesion accrual (24 vs. 48 cm3/month). Similar results were obtained with the WM tract analysis, with a reduction ranging from -47 to -66% in the treated group (p < 0.001). On voxel-wise analysis, CUA lesion frequency was lower in the treated group than the placebo group at week 4 (p = 0.07, corrected), becoming particularly pronounced (p ≤ 0.03, corrected) from week 8 onwards in large clusters of WM tracts, with peaks along fronto-parietal parts of the corticospinal tract, thalamic radiation, and superior longitudinal fascicle. Conclusion: LPM showed, in the short term, a treatment-related reduction of MRI lesion activity in RRMS patients in specific, clinically relevant brain locations. Such a quantitative approach might be a promising additional endpoint in future MS studies alongside the number and volume of WM lesions. Clinical Trial Registration: ClinicalTrials.gov identifier NCT00441103.

Keywords: MRI; brain; lesion probability map; multiple sclerosis; white matter.

Copyright © 2020 Giorgio, Battaglini, Gentile, Stromillo, Gasperini, Visconti, Paolillo and De Stefano.

Figures

Figure 1
Figure 1
Registration workflow for the creation of the study template in standard space (A), registration onto the template of T1-weighted images, (B) and combined unique active (CUA) lesion masks (C) of all study patients. See text for details.
Figure 2
Figure 2
Illustrative slices of lesion probability map (LPM) of the spatial distribution of active MRI lesions, expressed as combined unique active (CUA) lesions, in the placebo and interferon (IFN) β-1a groups at weeks 4, 8, 12, and 16. Red-to-yellow represents the frequency of CUA lesion occurrence (range: 0.1–10%). The background image is the study template in standard space (MNI 2 mm3). An animated version of this figure regarding data visualization of the entire brains of each group at each time point is available as Supplementary Material.
Figure 3
Figure 3
Lesion probability map (LPM) of the spatial distribution of active MRI lesions, expressed as combined unique active (CUA) lesions, mapped on some representative white matter (WM) tracts (in white: corticospinal tract [CST], superior longitudinal fascicle [SLF], cingulum [Cg]). Red-to-yellow represents the frequency of CUA lesion occurrence (range: 0.1–10%). The background image is the study template in standard space (MNI 2 mm3).
Figure 4
Figure 4
Clusters of active MRI lesions, expressed as combined unique active (CUA) lesions, showing lower frequency in the interferon (IFN) β-1a than placebo group at weeks 4, 8, 12, and 16. Red-to-yellow represents the significance level (p-value, range: 0.07–0.001, corrected for multiple comparisons across space). Crosshair points at local maxima, representing the highest reduction in CUA lesion frequency (see Table 2). Background image is the study template in standard space (MNI 2 mm3). The most informative slices are shown.
Figure 5
Figure 5
Clusters of on-study active MRI lesions, expressed as combined unique active (CUA) lesions averaged across all follow-up time points (week 4, 8, 12, and 16), showing lower frequency in the interferon (IFN) β-1a than placebo group. Red-to-yellow color represents the significance level (p-value, range: 0.05–0.0002, corrected for multiple comparisons across space). The background image is the study template in standard space (MNI 2 mm3). The most informative slices are shown.

References

    1. Narayanan S, Fu L, Pioro E, De Stefano N, Collins DL, Francis GS, et al. Imaging of axonal damage in multiple sclerosis: spatial distribution of magnetic resonance imaging lesions. Ann Neurol. (1997) 41:385–91. 10.1002/ana.410410314
    1. DeCarli C, Fletcher E, Ramey V, Harvey D, Jagust WJ. Anatomical mapping of white matter hyperintensities (WMH): exploring the relationships between periventricular WMH, deep WMH, and total WMH burden. Stroke. (2005) 36:50–5. 10.1161/01.STR.0000150668.58689.f2
    1. Enzinger C, Smith S, Fazekas F, Drevin G, Ropele S, Nichols T, et al. . Lesion probability maps of white matter hyperintensities in elderly individuals: results of the Austrian stroke prevention study. J Neurol. (2006) 253:1064–70. 10.1007/s00415-006-0164-5
    1. Di Perri C, Battaglini M, Stromillo ML, Bartolozzi ML, Guidi L, Federico A, et al. . Voxel-based assessment of differences in damage and distribution of white matter lesions between patients with primary progressive and relapsing-remitting multiple sclerosis. Arch Neurol. (2008) 65:236–43. 10.1001/archneurol.2007.51
    1. Bodini B, Battaglini M, De Stefano N, Khaleeli Z, Barkhof F, Chard D, et al. . T2 lesion location really matters: a 10 year follow-up study in primary progressive multiple sclerosis. J Neurol Neurosurg Psychiatry. (2011) 82:72–7. 10.1136/jnnp.2009.201574
    1. Calabrese M, Battaglini M, Giorgio A, Atzori M, Bernardi V, Mattisi I, et al. . Imaging distribution and frequency of cortical lesions in patients with multiple sclerosis. Neurology. (2010) 75:1234–40. 10.1212/WNL.0b013e3181f5d4da
    1. De Stefano N, Stromillo ML, Rossi F, Battaglini M, Giorgio A, Portaccio E, et al. . Improving the characterization of radiologically isolated syndrome suggestive of multiple sclerosis. PLoS ONE. (2011) 6:e19452. 10.1371/journal.pone.0019452
    1. Rossi F, Giorgio A, Battaglini M, Stromillo ML, Portaccio E, Goretti B, et al. . Relevance of brain lesion location to cognition in relapsing multiple sclerosis. PLoS ONE. (2012) 7:e44826. 10.1371/journal.pone.0044826
    1. Giorgio A, Battaglini M, Rocca MA, De Leucio A, Absinta M, van Schijndel R, et al. . Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis. Neurology. (2013) 80:234–41. 10.1212/WNL.0b013e31827debeb
    1. Matthews L, Marasco R, Jenkinson M, Kuker W, Luppe S, Leite MI, et al. . Distinction of seropositive NMO spectrum disorder and MS brain lesion distribution. Neurology. (2013) 80:1330–7. 10.1212/WNL.0b013e3182887957
    1. Giorgio A, Di Donato I, De Leucio A, Zhang J, Salvadori E, Poggesi A, et al. . Relevance of brain lesion location for cognition in vascular mild cognitive impairment. Neuroimage Clin. (2019) 22:101789. 10.1016/j.nicl.2019.101789
    1. Lapucci C, Saitta L, Bommarito G, Sormani MP, Pardini M, Bonzano L, et al. . How much do periventricular lesions assist in distinguishing migraine with aura from CIS? Neurology. (2019) 92:1739–44. 10.1212/WNL.0000000000007266
    1. Zhang J, Giorgio A, Vinciguerra C, Stromillo ML, Battaglini M, Mortilla M, et al. . Gray matter atrophy cannot be fully explained by white matter damage in patients with MS. Mult Scler. (2020) 24:1352458519900972. 10.1177/1352458519900972
    1. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, et al. . Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. (2001) 50:121–7. 10.1002/ana.1032
    1. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. (1983) 33:1444–52. 10.1212/WNL.33.11.1444
    1. De Stefano N, Curtin F, Stubinski B, Blevins G, Drulovic J, Issard D, et al. . Rapid benefits of a new formulation of subcutaneous interferon beta-1a in relapsing-remitting multiple sclerosis. Mult Scler. (2010) 16:888–92. 10.1177/1352458510362442
    1. De Stefano N, Sormani MP, Stubinski B, Blevins G, Drulovic JS, Issard D, et al. . Efficacy and safety of subcutaneous interferon beta-1a in relapsing-remitting multiple sclerosis: further outcomes from the IMPROVE study. J Neurol Sci. (2012) 312:97–101. 10.1016/j.jns.2011.08.013
    1. 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) 46:197–206. 10.1002/1531-8249(199908)46:2<197::AID-ANA9>;2-P
    1. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, et al. . Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. (2004) 23:208–19. 10.1016/j.neuroimage.2004.07.051
    1. Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM. Fsl. Neuroimage. (2012) 62:782–90. 10.1016/j.neuroimage.2011.09.015
    1. Battaglini M, Jenkinson M, De Stefano N. Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp. (2011) 33:2062–71. 10.1002/hbm.21344
    1. Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Med Image Anal. (2001) 5:143–56. 10.1016/S1361-8415(01)00036-6
    1. Andersson JLR, Jenkinson M, Smith S. Non-Linear Registration, aka Spatial Normalisation. FMRIB Technical Report TR07JA2 (2007). p. 1–21. Available online at: (accessed January 22, 2014).
    1. Giorgio A, Palace J, Johansen-Berg H, Smith SM, Ropele S, Fuchs S, et al. . Relationships of brain white matter microstructure with clinical and MR measures in relapsing-remitting multiple sclerosis. J Magn Reson Imaging. (2010) 31:309–16. 10.1002/jmri.22062
    1. Giorgio A, Stromillo ML, De Leucio A, Rossi F, Brandes I, Hakiki B, et al. . Appraisal of brain connectivity in radiologically isolated syndrome by modeling imaging measures. J Neurosci. (2015) 35:550–8. 10.1523/JNEUROSCI.2557-14.2015
    1. Giorgio A, Zhang J, Stromillo ML, Rossi F, Battaglini M, Nichelli L, et al. Pronounced structural and functional damage in early adult pediatric-onset multiple sclerosis with no or minimal clinical disability. Front Neurol. (2017) 8:608 10.3389/fneur.2017.00608

Source: PubMed

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