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https://doi.org/10.1177/13524585221118677
https://doi.org/10.1177/13524585221118677
MULTIPLE
SCLEROSIS MSJ
JOURNAL
journals.sagepub.com/home/msj 1
Multiple Sclerosis Journal
1 –9
DOI: 10.1177/
13524585221118677
© The Author(s), 2022.
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permissions
Introduction
The need for accurate, early diagnosis and considera-
tion of early treatment of multiple sclerosis (MS)
introduces challenges for clinicians.1 The 2017 modi-
fied McDonald diagnostic criteria2 necessitate typical
clinical symptoms and the presence of white matter
lesions (WMLs) on magnetic resonance imaging
(MRI). These criteria shorten time to diagnosis3 and
improve the sensitivity of diagnosing MS.4 Yet misdi-
agnosis is still common,5,6 especially when the MRI
criteria are incorrectly applied outside of a typical
clinical presentation or when there is incorrect inter-
pretation of MRI findings. It has been suggested that
recent changes to the MRI criteria decreased the diag-
nostic specificity,7–9 as WMLs can be present in other
conditions such as migraine,10 neuromyelitis optica
spectrum disorder (NMOSD)11 and central nervous
system vasculitis.12
There is growing acceptance of the role of the central
vein sign (CVS) in diagnosing MS13 leading to
increased use of phase-sensitive imaging at the time
of first clinical presentation.14,15
Some chronic MS lesions have persistent active
demyelination, the products of which are engulfed
Paramagnetic rims are a promising diagnostic
imaging biomarker in multiple sclerosis
Isobel Meaton*, Amjad Altokhis*, Christopher Martin Allen,
Margareta A Clarke , Tim Sinnecker, Dominik Meier, Christian Enzinger,
Massimiliano Calabrese, Nicola De Stefano , Alain Pitiot , Antonio Giorgio,
Menno M Schoonheim, Friedemann Paul, Mikolaj A Pawlak , Reinhold Schmidt,
Cristina Granziera , Ludwig Kappos , Xavier Montalban, Àlex Rovira , Jens Wuerfel*
and Nikos Evangelou*; on behalf of the MAGNIMS study group
Abstract
Background: White matter lesions (WMLs) on brain magnetic resonance imaging (MRI) in multiple
sclerosis (MS) may contribute to misdiagnosis. In chronic active lesions, peripheral iron-laden macro-
phages appear as paramagnetic rim lesions (PRLs).
Objective: To evaluate the sensitivity and specificity of PRLs in differentiating MS from mimics using
clinical 3T MRI scanners.
Method: This retrospective international study reviewed MRI scans of patients with MS (n = 254), MS
mimics (n = 91) and older healthy controls (n = 217). WMLs, detected using fluid-attenuated inversion
recovery MRI, were analysed with phase-sensitive imaging. Sensitivity and specificity were assessed for
PRLs.
Results: At least one PRL was found in 22.9% of MS and 26.1% of clinically isolated syndrome (CIS)
patients. Only one PRL was found elsewhere. The identification of ⩾1 PRL was the optimal cut-off and
had high specificity (99.7%, confidence interval (CI) = 98.20%–99.99%) when distinguishing MS and
CIS from mimics and healthy controls, but lower sensitivity (24.0%, CI = 18.9%–36.6%). All patients
with a PRL showing a central vein sign (CVS) in the same lesion (n = 54) had MS or CIS, giving a speci-
ficity of 100% (CI = 98.8%–100.0%) but equally low sensitivity (21.3%, CI = 16.4%–26.81%)
Conclusion: PRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnos-
tic biomarker, especially when used in conjunction with the CVS.
Keywords: Multiple sclerosis, MRI, CIS, biomarkers
Date received: 11 January 2022; revised: 3 July 2022; accepted: 12 July 2022
Correspondence to:
N Evangelou
Mental Health and Clinical
Neurosciences Academic
Unit, School of Medicine,
University of Nottingham,
Queen’s Medical Centre,
Nottingham NG7 2UH, UK.
nikos.evangelou@
nottingham.ac.uk
Isobel Meaton
Amjad Altokhis
Christopher Martin Allen
Nikos Evangelou
Mental Health and Clinical
Neurosciences Academic
Unit, School of Medicine,
University of Nottingham,
Nottingham, UK
Margareta A Clarke
Institute of Imaging Science,
Vanderbilt University
Medical Center, Vanderbilt
University, Nashville, TN,
USA
Tim Sinnecker
Dominik Meier
Medical Image Analysis
Center AG and Department
of Biomedical Engineering,
University Basel, Basel,
Switzerland
Christian Enzinger
Department of Neurology,
Medical University of Graz,
Graz, Austria
Massimiliano Calabrese
Neurology Unit, Department
of Neuroscience,
Biomedicine and Movement
Sciences, University of
Verona, Verona, Italy
Nicola De Stefano
Antonio Giorgio
Department of Medicine,
Surgery and Neuroscience,
University of Siena, Siena,
Italy
Alain Pitiot
Laboratory of Image and
Data Analysis, Ilixa Ltd,
London, UK
Menno M Schoonheim
Department of Anatomy and
Neurosciences, Amsterdam
Neuroscience, Amsterdam
UMC, Vrije Universiteit
1118677MSJ0010.1177/13524585221118677Multiple Sclerosis JournalI Meaton, A Altokhis
research-article20222022
Original Research Paper
Multiple Sclerosis Journal 00(0)
2 journals.sagepub.com/home/msj
within activated microglia/macrophages on the
periphery of the lesion. One such product is ferrous
iron released into the extracellular space during the
destruction of oligodendrocytes.16,17 This can be
detected in vivo with phase-sensitive imaging where
it presents as a paramagnetic rim (PR).16,17
Paramagnetic rim lesions (PRLs) appear as a hypoin-
tense, ring-like structures that surround WML on
phase-sensitive MRI sequences. PRLs may increase
in size whereas non-PRLs decrease in size or remain
unchanged.18,19
This imaging marker has been studied in detail using
7 Tesla (T) MRI.19–22 Importantly, 3T MRI studies
have also detected PRLs in MS23–25 and corroborated
the possible diagnostic and prognostic value.26,27
However, there are reservations on the clinical utility
as PRLs are only seen in a minority of WMLs.13,28
This retrospective international, multicentre study
within the Magnetic Resonance Imaging in MS
(MAGNIMS) Study Group aimed to test the potential
for PRLs in clinical practice. MRIs for patients with
MS and MS mimics (including cerebral small vessel
disease, migraine and NMOSD) were compared. This
dataset was originally collected by Sinnecker et al.14
to evaluate the value of CVS in MS.
Methods
Participants
The study included 562 participants scanned at 7 MS
centres across Europe between 2010 and 2016. The
participants were enrolled in ongoing observational
studies or included in neuroimaging research data-
bases, all of which were approved by the institutional
review board at each centre. All patients provided
written informed consent prior to MRI. The inclusion
criteria, diagnostic criteria and patient demographics
have been reported previously.16 All patients with
NMOSD had antibodies against aquaporin 4.14
Susceptibility-weighted imaging (SWI) and three-
dimensional (3D) fluid-attenuated inversion recovery
(FLAIR) scans acquired at 3T of sufficient quality
were analysed. Scan acquisition details for each cen-
tre can be found in the supplementary materials of
Sinneker et al.16
Image post-processing
FLAIR images from each participant were co-regis-
tered to the SWI using the ITK registration library
(Insight Software Consortium), which was imple-
mented in 3D Slicer, version 4.6.2 (Slicer Community).
Insufficient co-registration resulted in exclusion from
analysis. The registered images were then sectioned
into eight equal-sized 3D blocks to ensure blinding of
assessors to the patients’ diagnosis.14
Image analysis
All image analysis was performed by two trained
investigators (A.A. and I.M.) using 3D Slicer (version
4.11.2). Each 3D block was reviewed by A.A. or I.M.
and results were collated after all image analysis was
performed to avoid lesion classification in one part of
a brain influencing assessment of other regions of the
same brain. The supratentorial regions of the FLAIR
MRI scans were analysed for WMLs with a long
axis ⩾ 3 mm. Lesions were classified based on their
location as cortical/juxtacortical (in direct contact
with the cerebral cortex), periventricular (in direct
contact with the lateral/third ventricles), deep WML
(not in direct contact with the cortex or ventricles) or
in direct contact with deep grey matter structures.29
The SWI scans were then analysed for the presence of
PRLs. A PRL was defined as a hypointense, ring-like
structure on phase-sensitive imaging. The rim had to
correspond to the WML edge on the FLAIR scan, encir-
cle it fully or partially and must be visible on at least two
consecutive image slices (Figure 1). As part of this
study, CVS was also analysed using the North American
Imaging in MS Cooperative (NAIMS) criteria.30
Quality assessment
Each block was assessed for artefacts and co-registra-
tion quality of FLAIR and SWI before the detection
of WMLs. A total of 18 out of 5196 blocks failed this
quality test and were excluded from the analysis.
Once image analysis was completed, the blocks were
de-anonymised and matched to patient data.
Statistical analysis
The statistical analysis was performed using IBM
SPSS statistics, version 20 (IBM). Sensitivity and
specificity were calculated for having at least one
PRL per complete scan and presented with 95% con-
fidence intervals (CIs). A secondary analysis was per-
formed, only considering lesions that demonstrated
both the PRL and CVS; this was also presented as
sensitivity and specificity with 95% CI. Then, a
sequential analysis was performed that first checks
for the PRL and then, if no PRL is detected, checks for
CVS across the entire scan. A chi-square test was per-
formed to investigate the location of PRL and WMLs
(deep white matter vs all other locations).
Amsterdam, Amsterdam, the
Netherlands
Friedemann Paul
Neurocure Clinical
Research Center, Charité-
Universitätsmedizin Berlin,
Corporate Member of
Freie Universität Berlin,
Humboldt-Universität zu
Berlin and Berlin Institute of
Health, Berlin, Germany
Mikolaj A Pawlak
Department of Neurology
and Cerebrovascular
Disorders, Poznan University
of Medical Sciences, Poznan,
Poland
Reinhold Schmidt
Department of Neurology,
Medical University of Graz,
Graz, Austria
Cristina Granziera
Ludwig Kappos
Research Center for
Clinical Neuroimmunology
and Neuroscience Basel
(RC2NB), Departments
of Head, Spine and
Neuromedicine, Clinical
Research and Biomedical
Engineering, University
Hospital, University of Basel,
Basel, Switzerland
Xavier Montalban
Centre d’Esclerosi Multiple
de Catalunya (Cemcat),
Department of Neurology/
Neuroimmunology, Hospital
Universitari Vall d’Hebron,
Universitat Autonoma de
Barcelona, Barcelona, Spain
Àlex Rovira
Section of Neuroradiology,
Department of Radiology,
Hospital Universitari Vall
d’Hebron, Universitat
Autònoma de Barcelona,
Barcelona, Spain
Jens Wuerfel
Medical Image Analysis
Center AG and Department
of Biomedical Engineering,
University Basel, Basel,
Switzerland/Neurocure
Clinical Research Center,
Charité-Universitätsmedizin
Berlin, Corporate Member
of Freie Universität Berlin,
Humboldt-Universität zu
Berlin and Berlin Institute of
Health, Berlin, Germany
*These authors contributed
equally to this manuscript.
I Meaton, A Altokhis et al.
journals.sagepub.com/home/msj 3
The logistic regression was used to produce receiver-
operating characteristic (ROC) curves. In the logistic
model, diagnosis (MS vs MS-mimics) was set as a
dependent variable and PRL (or CVS) as an inde-
pendent variable. The ROC curve is a plot of sensitiv-
ity against 1 − specificity. The sensitivity and
specificity values were obtained by varying the cut-
off to dichotomise PRL (or CVS) (S1).
Interrater reliability
Interrater and intra-rater reliability for lesion identifica-
tion and PRL detection was assessed in a randomly
selected enriched data set of 100 blocks (53 with a PRL
and 47 without) containing MS and non-MS lesions.
Reliability was calculated using Cohen’s Kappa.
Results
Cohort description
The demographics of the 562 participants (182 males
and 380 females) are shown in Table 1.
Lesion count and distribution
A total of 6017 WMLs were analysed, with 3987 in
MS or clinically isolated syndrome (CIS) patients. The
Figure 1. Consecutive slices of a paramagnetic rim lesion (with a central vein) detected using the fluid-attenuated inversion
recovery (a.i. and b.i.) and phase-sensitive imaging (a.ii. and b.ii.), at 3T. As per the study protocol, the lesions demonstrate a
hypointense, ring-like structure corresponding to the lesion edge which is present on at least two consecutive slices.
Multiple Sclerosis Journal 00(0)
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Table 1. Overview of participants and analysed lesions.
MS CIS Cluster
headache
Migraine SLE NMOSD Diabetes
mellitus
Ageing healthy
controls
Total
Number of patients (female) 166 (110) 88 (59) 3 (1) 21 (18) 19 (16) 30 (26) 18 (10) 217 (140) 562 (380)
Mean age [SD] 37.3 [7.4] 32.6 [7.7] 49.3 [12.6] 40.8 [8.7] 32.5 [9.5] 46.5 [11.8] 68.3 [14.0] 64.1 [18.1] 48.4 [17.8]
Symptom duration, mean (range) 6.5 (0–30.5) 0.3 (0–2.5) – – – 2.9 (0–9.6) – – –
White matter lesions analysed
No. of patients with ⩾1 WML, (%) 164 (98.8) 84 (95.4) 2 (66.7) 21 (100.0) 15 (78.9) 18 (60.0) 18 (100) 163 (75.1) 485 (86.3)
No. of lesions 3065 922 19 266 77 171 355 1142 6017
Median no. per patient (range) 17 (0–61) 7 (0–54) 9.5 (4–15) 10 (1–38) 4 (0–12) 1 (0–38) 17.5 (1–66) 3 (0–30) 7 (0–66)
Paramagnetic rim lesions
No. of patients with ⩾1 PRL, (%) 38 (22.9) 23 (26.1) 0 0 0 0 1 (5.6) 0 62 (11.3)
No. of lesions (%) 72 (2.3) 57 (6.2) 0 0 0 0 1 (0.3) 0 130 (2.2)
Median no. per patient (range) 0 (0–6) 0 (0–8) 0 0 0 0 0 (0–1) 0 0 (0–8)
MS: multiple sclerosis; CIS: clinically isolated syndrome; NMOSD: neuromyelitis optica disorder; SD: standard deviation; SLE: systematic lupus erythematosus; WML: white matter lesion; PRL:
paramagnetic rim lesions.
I Meaton, A Altokhis et al.
journals.sagepub.com/home/msj 5
mean and interquartile ranges of WMLs per patient
found in each condition are represented in Figure 2.
Across the analysis, inter-rater reliability for lesion
and PRL detection between investigators showed a
substantial agreement with a Cohen’s Kappa value of
0.640 and 0.696, respectively. Furthermore, intra-rater
reliability had a Cohen’s Kappa value of 0.827.
Paramagnetic rim lesions
PRLs were detected in 130 lesions across 62 patients.
Within the MS cohort, 38 patients (22.9% (CI = 16.7%–
30.0%)) had at least one PRL. In the CIS cohort, the
proportion of individuals with at least one PRL was
26.1% (CI = 17.3%–36.6%), or 23 patients. Half of
PRL positive scans had a single PRL (Figure 3). A
single PRL was found in the scan of a diabetic patient,
and this was the only PRL detected outside of the MS/
CIS cohorts. Although the combined sensitivity of
PRL for MS/CIS was 24.0% (CI = 18.9%–29.8%),
PRLs had a very high specificity of 99.7%
(CI = 98.2%–99.99%) and a PPV (positive predictive
value) of 98.39.
All patients with a PRL showing a CVS in the same
lesion (n = 54) had MS or CIS, giving a specificity of
100% (CI = 98.8%–100.0%) and a PPV of 100. The
sensitivity of PRL with a CVS for MS was 20.5%
(CI = 12.9%–25.4%) and 22.7% (CI = 14.5%–32.3%)
in the CIS patients. In all MS/CIS patients displaying
a PRL, 88.5% had a lesion displaying both PRL and
CVS. The single PRL detected in the patient with dia-
betes did not display the CVS.
The identification of ⩾ 1 PRL (optimal cut-off) was
associated with high specificity of 99.7%, but low
sensitivity of 24.0%, and overall accuracy: area under
the curve (AUC) = 0.71, 95% CI = 0.64–0.78. CVS
detection alone (optimal cut-off of ⩾ 4 CVS) had
specificity of 88.3%, sensitivity of 56.7% and accu-
racy: AUC = 0.82, 95% CI = 0.79–0.86.
The combination of the two biomarkers (fulfilment of
either ⩾ 1 PRL or ⩾ 4 CVS) further improved the
specificity (90.6%), and a relative increase in the sen-
sitivity (57.9%). The overall accuracy: AUC = 0.83
(95% CI = 0.79–0.87).
We also performed sequential analysis of the two signs:
identification of any PRLs first, and if no PRL was
identified followed by assessment of the presence of
⩾4 CVS. The sensitivity of this two-stage analysis was
79.55% (CI = 74.6–83.9) and 70.9% (CI = 64.8–76.4).
Figure 2. A box and whisker plot showing the mean and interquartile ranges of the number of white matter lesions per
patient in each condition analysed.
NMOSD: neuromyelitis optica spectrum disorder; Control: healthy control; CIS: clinically isolated syndrome; MS: multiple sclerosis.
Multiple Sclerosis Journal 00(0)
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Across the cohort, 73.1% of WMLs were found in
the deep white matter, 19.4% in the periventricular
region, 7.2% were juxtacortical and only 0.3% adja-
cent to deep grey matter structures. In the MS and
CIS cohorts, 70.1% and 66.5% of WMLs were
located in the deep white matter, respectively. Yet in
the MS cohort, 84.2% of PRLs were identified in
the deep white matter. The chi-square test investi-
gating the location of the PRLs and WMLs found
PRLs to be more common in the deep white matter
(p = 0.003).
Discussion
The PRLs detected in phase-sensitive imaging have
potential to aid MS diagnosis. In this article, we
expand beyond our original MAGNIMS study of the
CVS14 to evaluate PRLs using clinically determined
3T MRI protocols. We found the presence of any PRL
highly specific for MS/CIS. Furthermore, the combi-
nation of PRL with CVS was found only in patients
with MS or CIS and not in any other diseases studied
with WMLs. Maggi et al.26 also reported in their large
study low sensitivity and high specificity of PRL in
MS. Our study, conducted in different centres, sup-
ports their findings. It further adds value as
we examined a higher number of patients with MS
mimics and ageing controls with brain scans showing
WMLs, which more commonly cause diagnostic dif-
ficulties for MS clinicians.
In addition to the analysis of the value of PRL and
CVS, we performed a sequential analysis (first look-
ing for the presence of PRL, and in the absence of any
PRL assessing for ⩾ 4 CVS). Although this did not
lead to improvement of sensitivity and specificity of
the diagnosis of MS, it may prove popular with MS
clinicians as it is time efficient while reviewing MRI
scans with WMLs. This sequential analysis of course
needs to be tested in a prospective study.
In both Sinnecker et al.14 and this analysis, we have
recognised that the special distribution of the MS
lesions and lesion characteristics may inadvertently
un-blind the observer to the diagnosis and influence
subsequent lesion characterisation on the same scan.
For that reason, we have tried to improve the blinding
by parcellating the brain into eight blocks and ran-
domising the order of blocks analysis. In this way, we
are certain that the investigators assessed individual
lesions without influence of other brain/lesion
characteristics.
Figure 3. The number of paramagnetic rim lesions per patient for each cohort with ⩾1 paramagnetic rim lesion.
CIS: clinically isolated syndrome; MS: multiple sclerosis.
I Meaton, A Altokhis et al.
journals.sagepub.com/home/msj 7
Although CVS is sensitive to MS, it was found to be
less specific than PRL. Both of these imaging bio-
markers are acquired on the same MRI sequence
and may reduce the need for oligoclonal band test-
ing which many patients find unpleasant. Our study
strengthens the evidence for the role of phase-sensi-
tive imaging in the diagnostic pathway of MS.
Our study is pragmatic, with clinical scans acquired
by many centres, resulting in variability of scan qual-
ity, sequences and operators. The results are therefore
representative of the performance of this radiological
biomarker in clinical practice. The patient-level prev-
alence of PRLs is within the range previously
described by K.C. Ng Kee Kwong et al.31 In this
cross-sectional study, we did not aim to report on the
natural history of PRLs but found that the percentage
of lesions with an iron rim was higher in CIS com-
pared to MS. This corroborates previous longitudinal
studies which have suggested that PRLs may eventu-
ally dissipate as neuroinflammation is replaced by
neurodegenerative pathology.19,32
While in our study we examined the role of PRLs in
the diagnosis of MS, the debate continues whether
most smouldering lesions produce a visible PR.
Expanding lesion volume is important since it may be
predictive of long-term clinical disability.18 Our results
suggest that one PRL is enough to help the diagnosis
of MS, but counting the number of PRL might be
important as a prognostic factor for long-term disabil-
ity. Studies suggest that some PRLs shrink after
7 years, at which point the iron rim has faded along
with the diffuse hyperintensity outside the rim.13,30 It
would be useful to examine the effect of disease-mod-
ifying treatments on PRLs. Unfortunately, data about
the multiple disease-modifying treatments used in our
cohort is unavailable. Furthermore, the scans available
were not taken at the time of diagnosis of MS, thus we
have been unable to determine at what point in the dis-
ease progression PRLs may be most prevalent.
As this cohort was previously reported, the limita-
tions are similar.14 This study relied on the investiga-
tors’ clinical diagnosis and we did not independently
assess the accuracy of the MS diagnosis or MS by
subtype. Some publications suggest that relapsing-
remitting and secondary progressive MS have a dif-
fering prevalence of PRLs.33,34 The parcellated nature
of the blocks, although essential for blinding, may
also have resulted in lesions not being counted if they
were dissected by the border of the blocks. This may
account for why not all the MS patients had lesions
found on their scans, although we also excluded
lesions smaller than 3 mm in their longest axis. The
parcellation method used to truly blind the investiga-
tors might have resulted in the moderate reproducibil-
ity we report. We suspect that in clinical practice,
clinicians will be influenced also by other MRI diag-
nostic features of the WM lesions. Using automated
techniques may prove to be beneficial in improving
the accuracy of PRL detection by eliminating human
errors. Once again only prospective studies can assess
the true diagnostic value of a test.
Conclusion
Paramagnetic rims are a potential imaging biomarker,
with high diagnostic specificity for MS. They have a
clinical role to play in decreasing the diagnostic
uncertainty in MS. In this large study, a quarter of
MS/CIS patients had at least one PRL. Furthermore,
3T phase-sensitive MRI is widely available and has
already been proven to reliably identify the CVS. The
combination of these radiological markers detected
with the same MRI sequence shows great promise
and requires further prospective evaluation, perhaps
with added improvements to sequence optimisation.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of inter-
est with respect to the research, authorship and/or
publication of this article.
Funding
The author(s) received no financial support for the
research, authorship and/or publication of this
article.
ORCID iDs
Margareta A Clarke https://orcid.org/0000-0001-
5531-796X
Nicola De Stefano https://orcid.org/0000-0003-
4930-7639
Alain Pitiot https://orcid.org/0000-0003-0146-
8572
Mikolaj A Pawlak https://orcid.org/0000-0002-
8607-0194
Cristina Granziera https://orcid.org/0000-0002-
4917-8761
Ludwig Kappos https://orcid.org/0000-0003-
4175-5509
Àlex Rovira https://orcid.org/0000-0002-2132-
6750
Supplemental Material
Supplemental material for this article is available
online.
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8 journals.sagepub.com/home/msj
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