MRI Workshop Dr. Ben Turner held an MRI workshop in November 2018. He discussed the principles of magnetic resonance imaging, different MRI techniques like T2 imaging and flair images, and how MRI is beneficial but also has drawbacks for monitoring multiple sclerosis. MRI is most useful for research, diagnosis, therapeutic innovation for drug trials, and monitoring therapies. New diagnostic criteria for multiple sclerosis were also presented, focusing on dissemination of lesions in space and time with no better explanation. Factors like lesion number and location provide prognostic information about progression.

1. MRI WorkshopMRI Workshop
Dr Ben Turner, MBBS MD FRCPDr Ben Turner, MBBS MD FRCP
Consultant Neurologist and Honorary Senior LecturerConsultant Neurologist and Honorary Senior Lecturer
55thth
November 2018November 2018

2. MRI Workshop
MRI stands for:
a)Mind Radar Interrogator
b)Molecular Resonance Impact
c)Mama-Mia Repeat Imagine
d)Magnetic Research Impression

3. Magnetic Resonance Principles
• What are you measuring

4. Magnetic Resonance Principles

5. Magnetic Resonance Principles

6. Conventional MRI
Non-conventional
•Magnetic Transfer Imaging
•Spectroscopy
•Microglial activity
•Functional MRI

7. T2 imaging – axial / transverse plane

8. T2 imaging
Saggital plane

9. Flair images – axial / transverse plane

10. T1 lesions with gadolinium enhancement

11. T1 ‘BLACKHOLES’ HYPOINTENSE LESIONS

12. Magnetic resonance scanning in MS
Benefits
• Demonstrates 5-20 times more disease activity than clinically apparent - greater
sensitivity, shorter studies, fewer patients
• Relatively objective measurement
• Easily blinded assessment
Drawbacks
• ‘Clinico-MRI’ paradox in MS
• shortcomings of clinical and radiological measures, r = 0.4 between MRI and EDSS
• IFN trials 80 % reduction in MRI activity and 30% in clinical relapse activity (poor
surrogate marker)
• ‘conventional’ MRI , T2 lesions, poor sensitivity – ‘tip of the iceberg’

13. MRI in MS
• MRI’s Greatest Contribution to MS
a)Research
b)Diagnosis
c)Therapeutic innovation – phase II studies
d)Monitoring of therapies

14. New Diagnostic Criteria for
Multiple Sclerosis

15. Multiple sclerosis definition
Pathological Definition: Inflammatory disease of the CNS
characterised by demyelination and variable degrees of
axonal loss and gliosis.
Clinical Definition: Objective CNS dysfunction, i.e.
involvement of two or more white matter structures
(space) separated by time, with no other aetiology.

16. The evolving clinical definition of MS
1. Schumacker, et al. Problems of Experimental Trials of Therapy in
Multiple Sclerosis: Report by the Panel on the Evaluation of Experimental
Trials of Therapy in Multiple Sclerosis. Ann N Y Acad Sci 1965;122:552-
68.
2. Poser, et al. New diagnostic criteria for multiple sclerosis: guidelines for
research protocols. Ann Neurol 1983;13(3):227-31.
3. McDonald, et al. Recommended diagnostic criteria for multiple sclerosis:
guidelines from the International Panel on the diagnosis of multiple
sclerosis. Ann Neurol 2001;50(1):121-7.
4. Polman CH, et al. Diagnostic criteria for multiple sclerosis: 2005
revisions to the "McDonald Criteria". Ann Neurol 2005;58(6):840-6.

17. ““To be suggestive of MSTo be suggestive of MS
lesions have to be disseminated inlesions have to be disseminated in
space and time.space and time.
And there must be no betterAnd there must be no better
explanationexplanation.”.”
Ian McDonaldIan McDonald
1933 – 20061933 – 2006
McDonaldMcDonald criteriacriteria

20. Clinically Isolated Syndrome
Definition - a first neurological event suggestive of Multiple Sclerosis
lasting for at least 24 hours and with symptoms and signs indicating
a single or multiple lesions.
e.g. – optic neuritis, spinal cord syndrome, brainstem lesion – INO
Sensory Symptoms – 34 %
Weakness 22 %
Ataxia 11 %
Visual symptoms 13 %
Diplopia 8 %
Bladder symptoms 1 %

21. New Diagnostic Criteria for
Multiple Sclerosis

22. New Diagnostic Criteria for
Multiple Sclerosis

25. Swanton JK, et al. JNNP 2006Swanton JK, et al. JNNP 2006
Lesions in different locationsLesions in different locations

26. Swanton JK, et al. JNNP 2006Swanton JK, et al. JNNP 2006
Lesions developing over timeLesions developing over time
≥≥30 days30 days

27. Periventricular, white matter lesions

29. Age
Comorbidity
Migraine
HT
Cholesterol
Diabetes

30. RR 20 year old male, left then right leg paraesthesia and
weakness
progressing to left upper limb and torso involvement,
commenced Oct 2014

32. JS – 28 year old female -February 2014 – paraesthesia of upper limbs and thorax,
resolved after 4 weeks,stable since, ANA +ve and lupus anticoagulant, Raynaud’s phenomenon

33. 13 Feb 2014 03 June 2014

34. Whiting, et al. BMJ 2006;332(7546):875-84.
““Many evaluations of the accuracy of magnetic resonance
imaging for the early detection of multiple sclerosis have
produced inflated estimates of test performance owing to
methodological weaknesses. Use of magnetic resonance
imaging to confirm multiple sclerosis on the basis of a single
attack of neurological dysfunction may lead to over-diagnosis
and over- treatment.”

35. 03 March 2014 31 March 2014 03 June 2014
Infratentorial Lesions

36. 31 March 2014 Gadolinium enhancement of symptomatic lesion

38. Spinal Lesions

41. cord lesion

42. 30 year old female, presented 2009 with paraesthesia hands
and lower limbs, intermittent symptoms since, had 2 children
since, no physical signs……

46. days
Progression to McDMS over 2
years
*MS by McDonald criteria
McDonaldMS
85%
69%
51%
28%

47. ClinicallyDefiniteMS Placebo
(n=176)
Betaferon
(n=292)
45%
28%
Progression to CDMS over 2
years
Primary endpoint -time to CDMS (Poser)
p=0.000075

48. The Evolution of MS
Clinical
Threshold
MRI ActivityMRI Activity
Number of LesionsNumber of Lesions
Total lesion loadTotal lesion load
CIS RRMS SPMSPre-clinical
McDonald
MS
Poser
CDMS
First clinical
event

49. Prognostic Significance of MRI in CIS:
Rate of Conversion to CDMS
Number of lesions
at baseline
The data presented for years 5, 10, and 14 were obtained from different publications based on the same longitudinal
study.
Morrissey et al. Brain. 1993;116:135; O’Riordan et al. Brain. 1998;121:495; Brex et al. N Engl J Med. 2002;346:158.
0
20
40
60
80
100
5 10 14
Years
Patientsconverting
toCDMS(%)
0 lesions
1-3 lesions
4-10 lesions
>10 lesions

50. 0
20
40
60
10 14
Years
Patientsconvertingto
EDSS≥5.5(%)
0 Lesions
1-3 Lesions
4-10 Lesions
>10 Lesions
Prognostic significance of MRI: rate of progression
to EDSS ≥5.5
the number of lesions at presentation associated with risk
of progression to EDSS ≥5.5*
* Data at 14 years represents progression to EDSS ≥6.0.
The data presented for years 10 and 14 were obtained from different publications based on the same longitudinal
study.
O’Riordan et al. Brain. 1998;121:495; Brex et al. N Engl J Med. 2002;346:158.
Number of lesions
at baseline

51. 27 21 18 15 30
26
26
28
25
33
20
17
14
13
11
0
20
40
60
T2LV
0 5 10 14 20
year
CIS RRMS
SPMS
Bars show IQR; Numbers of patients shown
Fig1: Median T2 lesion volume (T2LV) (cm3
) over time
for patient groups
20-year follow-up
Results: Serial median T2 LL (cm3)
European Charcot Foundation Satellite Symposium, ECTRIMS, Prague 11/10/2007Fisniku LK et al. Unpublished
Estimated rate of lesion growth in SPMS
2.89 cm3
/year
Estimated rate of lesion growth in RRMS
0.80 cm3
/year (p<0.001)

52. Baseline brain and spinal MRI predictors
of SPMS 15 years after CIS
Odds ratio 95% CI p
Baseline GdE lesions
1
2+
Baseline spinal cord lesions
1.33
3.16
4.71
0.35, 5.07
1.08, 9.23
1.72, 12.92
0.68
0.04
<0.01
Estimated risk of SPMS at 15 years
No gad lesions and no spinal cord lesions = 5.3%
Two gad lesions and at least one spinal cord lesion = 45.5%
Brownlee et al. ECTRIMS 2017

53. 53
Defining the clinical
course of multiple
sclerosis
The 2013 revisions
Lublin at al
Advisory Committee
on Clinical
Trials of MS.

54. Verifying MRI detected pathology:Verifying MRI detected pathology:
Co-registration IICo-registration II
Schmierer-lab, Blizard InstituteSchmierer-lab, Blizard Institute

55. 9
*
*
*
**
*
*
*
**
b
*
?
* 10mm
Schmierer-lab, Blizard InstituteSchmierer-lab, Blizard Institute

56. Marburg O. Jahrbücher für Psychiatrie und Neurologie 27, 1906.Marburg O. Jahrbücher für Psychiatrie und Neurologie 27, 1906.
““In terms of location lesions seem distributed atIn terms of location lesions seem distributed at
random. In the spinal cord there is perhaps a slightrandom. In the spinal cord there is perhaps a slight
preference for the white mater… Distribution ofpreference for the white mater… Distribution of
lesions in the cerebrum is non-systematic…lesions in the cerebrum is non-systematic… In theIn the
cortex lesions preferentially affect inner, rather thancortex lesions preferentially affect inner, rather than
superficial layers.”superficial layers.”
““In terms of location lesions seem distributed atIn terms of location lesions seem distributed at
random. In the spinal cord there is perhaps a slightrandom. In the spinal cord there is perhaps a slight
preference for the white mater… Distribution ofpreference for the white mater… Distribution of
lesions in the cerebrum is non-systematic…lesions in the cerebrum is non-systematic… In theIn the
cortex lesions preferentially affect inner, rather thancortex lesions preferentially affect inner, rather than
superficial layers.”superficial layers.”

58. Sethi, et al.Sethi, et al.
JNNP 2012JNNP 2012
DIRDIR FLAIRFLAIR PSIRPSIR
PSIR= Phase sensitive reconstructed IR (range of TPSIR= Phase sensitive reconstructed IR (range of T11w factor -1 to 1 instead of 0 to 1 in Tw factor -1 to 1 instead of 0 to 1 in T11SE)SE)

59. Cortical grey matter pathologyCortical grey matter pathology
• DemyelinationDemyelination
• RemyelinationRemyelination
• BBB disruptionBBB disruption
• (Meningeal) inflammation / macrophages(Meningeal) inflammation / macrophages
• Neuronal lossNeuronal loss
• GliosisGliosis
• AtrophyAtrophy
• Iron depositsIron deposits
• ……

60. Causes of MRI ‘white matter’ lesionsCauses of MRI ‘white matter’ lesions
Multiple sclerosisMultiple sclerosis
Ageing (30% of subjects aged > 50 years)Ageing (30% of subjects aged > 50 years)
Cerebro-vascular diseaseCerebro-vascular disease
LeucodystrophiesLeucodystrophies HTLV-1 a/myelopathyHTLV-1 a/myelopathy
NeurosarcoidosisNeurosarcoidosis HydrocephalusHydrocephalus
Neuromyelitis opticaNeuromyelitis optica IrradiationIrradiation
Acute disseminated encephalomyelitisAcute disseminated encephalomyelitis LymphomaLymphoma
Systemic lupus erythematosusSystemic lupus erythematosus ToxinsToxins
Behcet’s diseaseBehcet’s disease PhenylketonuriaPhenylketonuria
PMLPML HIVHIV
Decompression sicknessDecompression sickness SSPESSPE
CADASILCADASIL
CNS vasculitisCNS vasculitis and more…and more…

61. MS under the microscopeMS under the microscope
The veins in MS LesionsThe veins in MS Lesions
Schmierer, et al. Ann Neurol 2004Schmierer, et al. Ann Neurol 2004
The blood inThe blood in

62. TT22** FLAIRFLAIR
FLAIRFLAIR**
Sati, et al. Radiology 2012Sati, et al. Radiology 2012

63. TheThe
“vein in lesion”“vein in lesion”
o n= 25 pwRMS, 10 pwSVDn= 25 pwRMS, 10 pwSVD
o MRI @ 3T:MRI @ 3T:
o 3D FLAIR (post Gd injection),3D FLAIR (post Gd injection),
3D T3D T22 and Tand T22**
Tom CampionTom CampionMarc MiquelMarc Miquel
Campion, et al.Campion, et al. under revisionunder revision

64. Mistry et al. JAMA Neurol. 2013;70:623-8.Mistry et al. JAMA Neurol. 2013;70:623-8.

65. • 338 lesions (13.5 ± 7)338 lesions (13.5 ± 7)
• Proportion of CVSProportion of CVS++
lesions: 88%lesions: 88%
• All patients met MSAll patients met MS
criterion (≥45% CVScriterion (≥45% CVS++
))
• 3/25 fulfilled McDonald3/25 fulfilled McDonald
criteriacriteria using a singleusing a single
MRI head scan.MRI head scan.
Results – FLAIR* in MS & SVDResults – FLAIR* in MS & SVD
Campion, et al.Campion, et al. under revisionunder revision

66. Schmierer, etSchmierer, et
al. Brain 2010al. Brain 2010
N= 28 lesionsN= 28 lesions
N= 10N= 10 type 1type 1
N= 16N= 16 type 3type 3
N= 2N= 2 type 4type 4
Type I & III cortical grey matter lesionsType I & III cortical grey matter lesions

68. AverageAverage 0.5-1% loss of volume0.5-1% loss of volume
tissue in one year using SIENAtissue in one year using SIENA
Brain atrophy in MSBrain atrophy in MS
• Global measure of neurodegenerationGlobal measure of neurodegeneration
• Predicts future disability in RRMS (8 yrs)Predicts future disability in RRMS (8 yrs)
Fisher, et al Neurology 2002Fisher, et al Neurology 2002
Filippi et al Lancet 2004; Miller et al Neurology 2007, Kappos et alFilippi et al Lancet 2004; Miller et al Neurology 2007, Kappos et al
NEJM 2010; Barkhof et al Neurology 2010; Comi et al NEJM 2012NEJM 2010; Barkhof et al Neurology 2010; Comi et al NEJM 2012

69. Brain atrophy: across all stagesBrain atrophy: across all stages
n= 963 pwMSn= 963 pwMS
De Stefano, et al. Neurology 2010De Stefano, et al. Neurology 2010

70. Assumptions & hypothesisAssumptions & hypothesis
1.1. Spinal cord atrophy predicts disabilitySpinal cord atrophy predicts disability
2.2. Disability is due to axonal lossDisability is due to axonal loss
3.3. Hence, axonal loss must be the keyHence, axonal loss must be the key
substrate of spinal cord atrophy!substrate of spinal cord atrophy!

71. Revisiting spinal cord axonal lossRevisiting spinal cord axonal loss
D CarassitiD Carassiti
F ScaravilliF Scaravilli
N PetrovaN Petrova
Petrova, et al.Petrova, et al. under revisionunder revision

72. Spinal cordsSpinal cords n=13 pwMS and n=5 HCn=13 pwMS and n=5 HC
Age (years)Age (years) MS: 65 ± 11 HC: 82 ± 7MS: 65 ± 11 HC: 82 ± 7
MS durationMS duration 29 ± 11 years29 ± 11 years
-Sequential sections of tissue blocks obtained at everySequential sections of tissue blocks obtained at every
available nerve root levelavailable nerve root level
-Immuno-stained for myelin basic protein andImmuno-stained for myelin basic protein and
phosphorylated neurofilaments.phosphorylated neurofilaments.
Material & methodsMaterial & methods
Petrova, et al.Petrova, et al. under revisionunder revision

73. ResultsResults
- 20%- 20%
Petrova, et al.Petrova, et al. under revisionunder revision

74. JNNP 2014JNNP 2014
Ann Neurol 2014;76:568-80Ann Neurol 2014;76:568-80
n= 113 pwMSn= 113 pwMS
n= 20 HCn= 20 HC
3T MRI (PSIR) @ level C2/33T MRI (PSIR) @ level C2/3

75. • n= 182 cases, 7562 lesionsn= 182 cases, 7562 lesions
• Mean disease duration= 29 yearsMean disease duration= 29 years
• 57% of lesions mixed in/active (chronic active)57% of lesions mixed in/active (chronic active)
• Shorter time to EDSS 6 correlates with:Shorter time to EDSS 6 correlates with:
– higher lesion loadhigher lesion load
– higher proportion of chronic active lesionshigher proportion of chronic active lesions
• PP and SP show comparable lesion activityPP and SP show comparable lesion activity
• n= 182 cases, 7562 lesionsn= 182 cases, 7562 lesions
• Mean disease duration= 29 yearsMean disease duration= 29 years
• 57% of lesions mixed in/active (chronic active)57% of lesions mixed in/active (chronic active)
• Shorter time to EDSS 6 correlates with:Shorter time to EDSS 6 correlates with:
– higher lesion loadhigher lesion load
– higher proportion of chronic active lesionshigher proportion of chronic active lesions
• PP and SP show comparable lesion activityPP and SP show comparable lesion activity

76. MyelinMyelin AxonsAxons
Above lesionAbove lesion
Below lesionBelow lesion
LesionLesion
Petrova, et al. Brain Pathol 2018;28:334-48.Petrova, et al. Brain Pathol 2018;28:334-48.
Demyelination has significant effect on axonal lossDemyelination has significant effect on axonal loss

77. Petrova, et al. Brain Pathol 2018;28:334-48.Petrova, et al. Brain Pathol 2018;28:334-48.
Demyelination has significant effect on axonal lossDemyelination has significant effect on axonal loss

78. Axonal lossAxonal loss
- 60%- 60%
Petrova, et al. Brain Pathol 2018;28:334-48.Petrova, et al. Brain Pathol 2018;28:334-48.
Only predictor of axonal loss:Only predictor of axonal loss:
DDisease Durationisease Duration

79. -- 39%39%
MSMS No MSNo MS
Carassiti D et al. Neuropathol Appl Nerobiol 2017; doi: 10.1111/nan.12405.doi: 10.1111/nan.12405.

80. Grey matter volume loss and disabilityGrey matter volume loss and disability
Fisniku, et al. Ann Neurol 2008Fisniku, et al. Ann Neurol 2008
n= 73 patients with initial diagnosis CIS, followed up for 20 yearsn= 73 patients with initial diagnosis CIS, followed up for 20 years

81. MRI in monitoring

82. Rio et al ECTRIMS 2015
Quixotic guidelines
209 patients

83. 84
Pooled analysis of those with ≥1 gadolinium-enhancing lesion
Accuracy improves significantly when looking for gadolinium-enhancing lesions rather than new T2
lesions; when compared with image analysis software, concordance correlation was high (0.8–0.96)
for gadolinium-enhancing lesions, intermediate (0.6– 0.8) for new T2 lesions, and very poor (0.0–
0.14) for enlarging lesions.
Pooled analysis of those with ≥1 new T2 lesion at 1 year

84. 85
13,500

85. Principles and Challenges of NEDA
86
In other fields, also known as ‘treat to target’ (TTT)
TTT is proactive, has a clear endpoint (the “target”), and can
be operationalized as a specific treatment algorithm,
simplifying the multitude of complex medication sequences.
Long established in diabetes – HbA1C, hyperlipidaemia,
hypertension
RA – similar issues to MS, less well defined targets – patient
symptoms (subjectivity)
Pt perception of benefit and risk of escalation of therapies
T2 lesions are an objective measure of disease activity
Solomon, D. H., A. Bitton, J. N. Katz, H. Radner, E. M. Brown and L. Fraenkel (2014). "Review:
treat to target in rheumatoid arthritis: fact, fiction, or hypothesis?" Arthritis Rheumatol 66(4):
775-782.

86. NEDANEDA
Is it time to target no evident disease activity (NEDA) in
multiple sclerosis?
Giovannoni G, Turner B, Gnanapavan S, Offiah C, Schmierer K, Marta M.
Mult Scler Relat Disord. 2015 Jul;4(4):329-33. doi:
10.1016/j.msard.2015.04.006. Epub 2015 May 8. Review.
1.Relapses
2.Disability progrression
3.MRI lesional activity
• Gd enhancing lesions
• T2 lesions

87. DB - ? escalation
• FS – 2000 right sided paraesthesia
• Diagnosed 2002
• 2002 May commenced Copaxone, did not tolerate
• 2004 – October Avonex (eventually)
• 2005 – relapse, switched to Rebif, ab neg, 1-2
relapses per year
• Rebif IFN 2010
• 2013 June - fingolimod

91. Choose therapy
A B C
Define the individual’s MS
Treatment failure?
• Patient’s preferences?
• Your choice?
Individual measures:
•Evidence of disease activity?
•Tolerability/safety?
•Adherence?
•Drug or inhibitory markers,
e.g. NABs?
Monitoring
Personalisation:
•MS prognosis based on clinical
and MRI indices
•Lifestyle and goals
•Shared goals for therapy
Rebaseline
Rebaselining:
•IFNβ, natalizumab, fingolimod,
teriflunomide, Dimethyl-Fumarate= 3-
6 months
•Glatiramer acetate= 9 months
•Induction= (6 and) 24 months
Choose a therapeutic strategy
Maintenance-escalation Immunosuppression…reconstitution
Choose therapy
X Z
Rebaseline
Monitoring
Initiate, switch or escalate Rx Complete course / Re-treat
Breakthrough disease
NoYes Yes
• Two licensed ‘reconstitution’
therapies at present
IFNβ = interferon-beta; NABs = neutralizing antibodies; Rx = treatment
Giovannoni G, et al. Mult Scler Relat Disord 2015;4:329-33.Giovannoni G, et al. Mult Scler Relat Disord 2015;4:329-33.
Y
Consider changing RxConsider changing Rx
BARTS-MS T2T-NEDA ALGORITHM
T2T = treating-to-target; NEDA = no evident disease activity

92. Relapses
Unreported relapses
Clinical disease progression
Subclinical relapses: focal MRI activity
Focal gray and white matter lesions
not detected by MRI
Brain atrophy
Spinal fluid neurofilament levels
MS Iceberg
Clinical activity
Focal MRI activity
Hidden focal and diffuse MRI activity
Microscopic or biochemical pathology
Biomarkers
NEDA
END-ORGANDAMAGE