Use of Magnetic Resonance Imaging In Multiple Sclerosis Trials Richard A. Rudick, M.D. Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic March 7, 2009
Conflict of Interest Statement Cleveland Clinic has accepted research funding from NIH (NINDS, NCRR), NMSS, Biogen Idec, and Nancy Davis Center Without Walls for my research I have accepted honoraria or consulting fees (< $10,000 per annum) from Biogen Idec, Millenium, Genzyme, Teva, and Novartis
Grant Support For Work Presented Today NIH PO1 NS38667 Project 3 and MRI/Pathology Core Pathogenesis of Multiple Sclerosis (Brain atrophy in multiple sclerosis) NIH RO1 NS38667; NMSS RG 3099 MSCRG Trial of IM IFN -1a for RR-MS NMSS RG 3099 Brain atrophy in CIS NMSS PP0540 MS image analysis methodology Biogen Idec (BGEN 801) F/U of IFN -1a study Nancy Davis Center Without Walls Clinical trial methodology
Outline of Talk MRI / Clinical Correlations Relapses / Disability Use of MRI in MS Trials Hot topics MRI Defined Rx Response Gray Matter Pathology
Multiple Sclerosis: Clinical Course SUBCLINICAL Preclinical Relapsing-RemittingSecondary Progressive Time Disability MS Relapses Progressive Disability (5-25 years)
MRI in Multiple Sclerosis Useful in diagnosis, management Used to test new treatments Provides insight into pathogenesis
Evolution of MS MRI lesions GAD T2 lesion Black Hole Richert N. unpublished (1998)
MRI in MS
FLAIR/T2: all “lesions” (edema, inflammation, demyelination, gliosis, axonal loss) Gad-enhancing: breakdown of blood-brain barrier, active inflammation T1 hypointense: axonal loss, severe tissue destruction MTR hypointense:demyelination, axonal loss
Low Correlation Between MRI Lesions and Relapses (SLC data) MRI lesions did not predict relapses in a multivariate model (n = 306); Held et al, Neurology 2005 : The project to validate MRI lesions as a relapse surrogate was stopped since the pre-requisite of correlation between MRI lesions and relapses was not met (n = 208); Petkau et al, Mult Scler 2008 : Retrospectice analysis of 31 placebo arms of RCT: no correlation between Gad lesions and relapses (n = 409) Daumer et al, Neurology 2009
Most lesions are clinically silent Kinetics (particularly as relates to disability) Low Correlation Between MRI Lesions and Relapses
Most lesions are clinically silent Kinetics (particularly as relates to disability) Low Correlation Between MRI Lesions and Relapses
Disease Activity Over 6.5 Years
If 90% Of New Lesions Are Subclinical, The Correlation Between New Lesions And Relapses Would Be 0.34
23 RCTs with MRI and relapse data Does the treatment effect on MRI lesions correlate with the treatment effect on relapses? A weighted linear regression was run Annals of Neurology, 2009, in press
log(REL effect) = log (MRI effect)
Validation with separate studies
In groups, the effect of a treatment on new lesions explains > 80% of the variance of the relapse treatment effect
Most lesions are clinically silent Kinetics (particularly as relates to disability) Low Correlation Between MRI Lesions and Relapses
SUBCLINICAL Preclinical Relapsing-RemittingSecondary Progressive Time Disability Variable (5-25 years) MRI Disability Or Atrophy Does MRI Predict Future Clinical Status?
Do MRI Lesions Predict Future Status?
Baseline T2 Lesion Load Predicts Disability at 5 Years Filippi et al. Neurology 1994; 44: % EDSS > 3.0
Brex et al. NEJM 2002:346; : EDSS < 3 EDSS > 3 SPMS Years from presentation T2 Lesion Volume BL 5 years 10 years 14 years T2 Lesion Growth In 5 Years Predicts Disability at 14 Years
Chard et al. JNNP 2003; 74: T2 Lesion Growth In 5 Years Predicts Brain Atrophy at 14 Years
Rudick et al. Ann. Neurol.2006;60: No correlation between T2 LL and future EDSS T2 Lesions In RRMS Predict Atrophy and Clinical Disability after 13 Years RRMS from Phase III trial (IFNB-1a)
BPF BPF = z = BPF = z = BPF = z = Healthy Controls (n=16) Mean +/- 2 SD Placebo Patients (n=72) Mean +/-SEM p < Baseline Year 1 Year 2 p = Brain Atrophy in the IM IFNβ-1a Clinical Trial (RRMS) Rudick, et al. Neurology 1999; 53:
% > EDSS 6.0 At F/U Brain Atrophy During The Trial Correlates With Disability At 8 Year F/U Fisher, et al. Neurology 2002 Quartiles of BPF During 2 Year Clinical Trial
MRI Predicts EDSS > 6 SmallMedium Large Estimated Effect Size
MRI / Clinical Correlations (in RRMS) Lesions correlate with relapses in early MS Effect of intervention on lesions correlates strongly with relapse effect Lesions correlate with future disability and brain atrophy Brain atrophy during RR-MS correlates with future neurological disability
Natural History Of Multiple Sclerosis “BenignMS” Never Progresses Progressive Disability Threshold Amount Of CNS Injury “Typical MS” SP-MS Years After Onset “Severe MS” SP-MS After 5 Years Years After MS Onset
Outline of Talk UseMRI / Clinical Correlations Relapses / Disability MRI in MS Trials Hot topics MRI Defined Rx Response Gray Matter Pathology
MRI Parameters in MS Trials Gadolinium lesions are the primary outcome measure used to screen treatments Secondary outcome measures for registration trials Gad lesions / T2 lesions T1 holes / brain atrophy
Disease Modifying Drugs: Clinical and MRI Outcomes IM IFNb-1aSC IFNb-1a (44-µg) IFNb-1b (8-MIU) Glatiramer Acetate Relapse rate % reduction 32 p= p< p= p=0.007 Disability progression % reduction 37 p= p< p=NS 12 p=NS Number of Gd+ lesions % reduction 52 p= * p<0.001 NR 29* p= N/E T2 lesion number % reduction 33 p= p< p= * p<0.003 * = at 9 months
Disease Modifying Drugs: Clinical and MRI Outcomes IM IFNb-1aSC IFNb-1a (44-µg) IFNb-1b (8-MIU) Glatiramer Acetate Relapse rate % reduction 32 p= p< p= p=0.007 Disability progression % reduction 37 p= p< p=NS 12 p=NS Number of Gd+ lesions % reduction 52 p= * p<0.001 NR 29* p= N/E T2 lesion number % reduction 33 p= p< p= * p<0.003 * = at 9 months
Brain Atrophy in MS Trials Measured in nearly all trials (usually brain volume normalized to brain size) Issues Slow rate of atrophy, short trial durations Kinetic issues - fluid shifts and time course of neurodegeneration Multiple studies show reduced atrophy with anti-inflammatory therapies in RRMS No study has shown an atrophy effect in SPMS or PPMS
MRI Parameters in MS Trials Newer measures Diffusion Tensor Imaging Magnetic Resonance Spectroscopy Magnetization Transfer Imaging T1, T2 Relaxation Times Functional MRI NYRFPT
Outline of Talk Use of MRI in MS Trials MRI / Clinical Correlations Relapses / Disability Hot Topics MRI Defined Rx Response GM Pathology
Original Avonex Study The 2-year cohort 167 patients Classification of responders Relapses in 2yr – cutoff 2 or more Gd+ lesions (yr 1 + yr2) – cutoff 2 or more New T2 at yr 2 (versus baseline)- cutoff 3 or more Outcome: EDSS, MSFC, BPF
EDSS Change In Responder Groups Based on T2 Lesions P=0.05 P=0.48 n=62 n=20 n=46 n=39 Rudick et al, Annals of Neurology 2004
P<0.01p=0.45 n=47 n=18 n=36 n=33 Rudick et al, Annals of Neurology 2004
Do Lesions During Initial 2 Years Predict Outcome (EDSS 6) At 15 Years?
n=30n=36 p = 0.03
n=30n=36 p = 0.59
n=32n=35 p = 0.04
n=32n=35 p = 1.0
AuthorResponder ClassificationResults Rudick Number of N/E T2 lesions at 2 yrs in PLC-controlled trial of IM IFNβ- 1a; Gad lesions at Yr 1 and pts studied for 2 years. > 3 new lesions predicted worse disease progression over 2 years; f/u at 15 years confirmed findings Pozzilli Gad lesions or new T2 lesions 1 year after beginning IFNβ 101 of 242 pts had MRI activity as defined. Higher likelihood of relapses in the 4-year observation (OR 3.6) Tomassini Gad lesions 1 year after beginning IFNβ; NAb while on IFN 68 patients followed for 6 years. Gad lesions predicted relapse or disability (OR 7.9); NAb associated with poor outcome (OR 7.3) Rio N/E T2 lesions or Gad lesions 1 year after starting IFNβ 152 pts studied for 2 years. >2 active lesions at 1 year was the primary factor predicting sustained EDSS progression (OR 8.3) Durelli Gad or T2 lesions 6 months after starging IFNβ; and IFNβ NAb during study 147 pts studied for 2 years. MRI lesions and/or NAb predicted relapse or sustained EDSS increase in the next 18 months KinkelGad or new T2 lesions 6 months after starting IFNβ in CIS 383 pts with CIS studied up to 2 years. Active MRI lesions predicted CDMS in IFNβ-1a but not placebo patients
Longitudinal studies consistently indicate that MRI activity while using IFNβ indicates patients with a relatively poor response to therapy and poor prognosis
Outline of Talk Use of MRI in MS Trials MRI / Clinical Correlations Relapses / Disability Hot Topics MRI Defined Rx Response GM Pathology
SPMS Cortical Pathology in MS Post-Mortem Studies > 90% of MS patients have cortical lesions (Lumsden 1970) Percentage of demyelinated area significantly higher in cortex than WM % vs. 6.5% (Bo, et al. 2003) Most cortical lesions are not detectable on conventional MRI (Geurts, et al. 2005) Kutzelnigg et al Brain 2005 Focal demyelinated WM plaque Cortical demyelination
Gray Matter Atrophy Segmentation of gray matter based on intensity and anatomic probability Gray matter fraction: GMF = GM volume / brain volume Provides estimate of overall amount of GM tissue damage Final GM AnatomicalGMT2w Nakamura and Fisher. NeuroImage 2009
Gray Matter Atrophy in Multiple Sclerosis: NIH Longitudinal Study 87 subjects followed over 4 years 17 controls 7 CIS 37 RRMS 26 SPMS Measured EDSS, MSFC, change in fractional brain volumes, lesion volumes, MTR Fisher, et al. Ann Neurol 2008
Atrophy Rates Relative to Healthy Controls Fisher, et al. Ann Neurol 2008
Gray Matter Atrophy Correlates with MS Disability Progression 87 subjects followed over 6.5 years 17 healthy controls 7 CIS 36 RRMS 27 SPMS Measured EDSS, MSFC, changes in fractional brain volumes Categorized patients as “progressed” or “stable” based on MSFC change over 6.5 years Rudick, et al. (JNNP 2009)
Rudick, et al. (JNNP 2008) Gray Matter Atrophy Correlates with MS Disability Progression
Gray Matter Pathology in MS Gray matter pathology increasingly dominates the pathology Gray matter atrophy correlates with disability progression Is MS a gray matter disease?
Outline of Talk MRI / Clinical Correlations Relapses / Disability Use of MRI in MS Trials Hot topics MRI Defined Rx Response Gray Matter Pathology
Future MRI Directions More specific MRI measures of MS pathology Imaging markers for GM pathology Use of MRI in neuroprotection trials Use of MRI to monitor / manage Rx
Collaborators
Biomedical Engineering: Elizabeth Fisher, Ph.D. Raghavan Gopalakrishnan, M.S. Patricia Jagodnik, B.S. Kunio Nakamura, B.S. Smitha Thomas, M.D. Bhaskar Thoomukuntla, M.S. Neurosciences: Angela Chang, M.D. Richard Ransohoff, M.D. Susan Staugaitis, M.D., Ph.D. Bruce Trapp, Ph.D. Radiology: John Cowan, R.T. Mark Lowe, Ph.D. Mike Phillips, M.D. Derek Tew, R.T. Mellen Center: Jeff Cohen, M.D. Bob Fox, M.D. Claire Hara-Cleaver, RN, NNP Dee Ivancic Lael Stone, M.D. Biostatistics: Jar-Chi Lee, M.S. Acknowledgements
Thank You For Your Attention