MRI Features Associated with Rapid Disease Activity in Clinically Isolated Syndrome Patients at High Risk for Multiple Sclerosis

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MRI Features Associated with Rapid Disease Activity in Clinically Isolated Syndrome Patients at High Risk for Multiple Sclerosis Amy De Lury , Joseph Bisulca , Patricia K Coyle , Robert Peyster , Lev Bangiyev , Tim Q. Duong PII: DOI: Reference:

S2211-0348(20)30061-4 https://doi.org/10.1016/j.msard.2020.101985 MSARD 101985

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Multiple Sclerosis and Related Disorders

Received date: Revised date: Accepted date:

31 August 2019 31 January 2020 3 February 2020

Please cite this article as: Amy De Lury , Joseph Bisulca , Patricia K Coyle , Robert Peyster , Lev Bangiyev , Tim Q. Duong , MRI Features Associated with Rapid Disease Activity in Clinically Isolated Syndrome Patients at High Risk for Multiple Sclerosis, Multiple Sclerosis and Related Disorders (2020), doi: https://doi.org/10.1016/j.msard.2020.101985

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Highlights: Lesion location (spinal cord and infratentorial), older age, and non-treatment are predictive of rapid disability T2 lesion volume and number are also predictive of rapid disability White matter atrophy is not associated with rapid disability progression Atrophy, T1 hypointensity, and T1 contrast-enhanced lesions need further study

_____________________________________________________________________________________________ Abbreviations CDMS=Clinically Definite Multiple Sclerosis, CHI3L1=Chitinase-3-Like Protein 1, CIS=Clinically Isolated Syndrome, CNS=Central Nervous System, CSF=Cerebrospinal Fluid, DIS=Dissemination in Space, DIT=Dissemination in Time, DTI=Diffusion Tensor Imaging, IgG=Immunoglobulin G, MS=Multiple Sclerosis, PPMS=Primary Progressive Multiple Sclerosis, RIS=Radiologically Isolated Syndrome, RRMS=RelapsingRemitting Multiple Sclerosis, SC=Spinal Cord, SPMS=Secondary Progressive Multiple Sclerosis

MRI Features Associated with Rapid Disease Activity in Clinically Isolated Syndrome Patients at High Risk for Multiple Sclerosis Amy De Lury*, Joseph Bisulca*, Patricia K Coyle, Robert Peyster, Lev Bangiyev, Tim Q. Duong Departments of Radiology and Neurology, Stony Brook Medicine, Stony Brook, New York 11794, USA *ADL and JB contributed equally Corresponding author: Tim Q Duong, PhD Department of Radiology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794 631 444 8033 [email protected]

Key words: white matter disease, neurodegenerative disease, clinically isolated syndrome, magnetic resonance imaging, expanded disability status scale

ABSTRACT Clinically isolated syndrome (CIS) is a central nervous system inflammatory and demyelinating event that lasts at least 24 hours and can represent the first episode of relapsing-remitting multiple sclerosis. MRI is an important imaging tool in the diagnosis and longitudinal monitoring of CIS progression. Accurate differential diagnosis of high-risk versus low-risk CIS is important because high-risk CIS patients could be treated early. Although a few studies have previously characterized CIS and explored possible imaging predictors of CIS conversion to MS, it remains unclear which amongst the commonly measured MRI features, if any, are good predictors of rapid disease progression in CIS patients. The goal of this review paper is to identify MRI features in high-risk CIS patients that are associated with rapid disease activity within 5 years as measured by clinical disability.

1. Introduction Clinically isolated syndrome (CIS) refers to the first episode of neurologic symptoms that lasts at least 24 hours and is caused by inflammation or demyelination of the central nervous system. It can

represent the first episode of relapsing-remitting multiple sclerosis (MS) [1]. CIS is about three times more common in women than in men [2]. Seventy percent of patients diagnosed with CIS are 20-40 years old, but CIS can develop at younger or older ages [2]. Many individuals who experience CIS turn out to have MS. According to the 2017 revised McDonald diagnostic criteria for MS, the diagnosis of MS can be made when CIS is accompanied by MRI findings consistent with dissemination in time and space. The new criteria also allow for the presence of oligoclonal bands in a person's cerebrospinal fluid (CSF) to help make the diagnosis. However, not all individuals who experience CIS have MS. When CIS is accompanied by MRI brain lesions that are similar to those seen in MS, the individual has a 60% to 80% chance of a second neurologic event and diagnosis of MS within several years. When CIS is not accompanied by MRI-detected brain lesions, the individual has about a 20% chance of developing MS over the same period of time [2]. Thus, MRI has the potential to inform likelihood of CIS progression to MS. Accurate differential diagnosis of high-risk versus low-risk CIS is important because people with a high risk of developing MS are encouraged to begin treatment with a disease-modifying therapy (DMT), which is aimed to delay or prevent a second neurologic episode. In addition, early treatment may minimize future disability caused by further inflammation and damage to nerve cells, which are sometimes silent (occurring without any noticeable symptoms). Although a few studies have previously characterized CIS [3, 4], it remains unclear which amongst the commonly measured MRI features, if any, are good predictors of rapid disease progression in CIS patients. MRI plays an important role in the diagnosis of CIS and MS. Typical MRI protocols used in the diagnosis of CIS and MS are summarized in Table 1. From these images, many features can be abstracted: the number of lesions, volume and location of lesions, lesion characteristics, whether lesions are contrast-enhanced (indicative of active lesions with permeable blood-brain barrier), and fractional anisotropy (FA) measures for the brain and spinal cord. Along with MRI, CSF analysis could be performed to further determine if there are immune abnormalities within the CNS. The 2017 revised McDonald criteria allow for MS to be diagnosed by two pathways: MRI lesion dissemination in time and space; or the presence of CSF-specific oligoclonal bands with lesion dissemination in space [1]. This may allow a typical CIS patient to be diagnosed with MS, as opposed to requiring a second clinical attack; however, other conditions must be ruled out. The most common measure of clinical worsening in CIS and MS individuals is the

Expanded Disability Status Scale (EDSS) [5]. A recent review article by Odenthal and Coulthard [6] investigated the relationship between CIS and disability in the form of EDSS and cognitive impairment, but did not use a consistent measure of disability. Furthermore, it lacked a specificity for high-risk CIS, and it did not address gray matter atrophy and its potential role in EDSS-related disability. The goal of our review paper is to identify MRI features in high-risk CIS patients that are associated with rapid disease activity within 5 years as measured by EDSS. High-risk CIS is defined as having two or more lesions on a T2-weighted MRI apart from the symptomatic lesion [2]. Identifying imaging features associated with high likelihood of rapid disability progression could lead to further development or optimization of imaging biomarkers, help physicians monitor specific features more diligently, and treat high-risk patients more aggressively with a DMT.

Table 1. MRI protocol for monitoring MS and CIS patients [7-9] ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– I. Brain MRI protocol includes: a. Proton density or T2-weighted sequence b. T2-weighted fluid attenuated inversion recovery (FLAIR) sequence c. Pre- and post-contrast T1-weighted spin echo sequence d. Sometimes: double-inversion recovery to enhance lesion conspicuity i. First inversion pulse suppresses cerebrospinal fluid (CSF) signal ii. Second inversion pulse suppresses white-matter signal e. Research setting: diffusion-weighted MRI and diffusion-tensor imaging (DTI) i. Detects microstructural and white-matter changes II. Spinal cord MRI a. Challenging compared to brain MRI due to small structure, location, and length of the spinal cord, which could limit lesion detection b. Protocol typically includes: i. Proton density ii. Short T1 inversion recovery (STIR) iii. Multi-echo recombined gradient echo (MERGE) iv. Post-contrast T1-weighted spin echo –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––

2. Methods This literature review was conducted by searching PubMed with the following title and abstract keywords: clinically isolated syndrome, CIS, clinically isolated syndrome high-risk, multiple sclerosis, MS, prediction, disability, and EDSS. We concluded our literature search on December 23, 2019, and even though there was no filter for publication date, all of the articles

were published after 1980. We included only original articles and excluded case series or individual case studies. High-risk CIS was determined as having 2 or more asymptomatic lesions apart from the symptomatic lesion [2]. In order to determine if the CIS subjects in a study were high-risk, we examined the study‟s methods for the selection of patients with asymptomatic lesions and we investigated how many patients had more than 1 lesion, which implies asymptomatic lesions. If we restricted our review to studies with only high-risk subjects, there would only be five studies that specifically reported on disability in CIS [10-14]. Therefore, in order to qualify for inclusion, a study needed a simple majority of CIS patients to be high-risk. We examined the CIS literature (see Figure 1 for inclusion/exclusion) and sorted out all of the predictive and non-predictive factors for worsening disability (see Table 2). We defined significant disability as an EDSS score of 3.0 (moderate disability in one functional system, or mild disability in three or four functional systems, though fully ambulatory) or greater, with rapid disability defined as this development occurring within 5 years. While there are limitations, we focused on EDSS scores as it is the most commonly used scale of clinical worsening and disability in MS [5]. We categorized predictors as factors deemed significant in predicting rapid or worsening disability in high-risk CIS patients, whereas non-predictors show limited to no association with rapid disability. During our review, we examined the statistical analyses within each paper, sample size, methods, the authors‟ opinions, and other evidence-based commentary that contributed to the strengths of predictors and non-predictors of rapid disease activity. Many factors were presented as predictors for disability in some studies, but also as non-predictors in others. Therefore, we assessed the arguments and quality of evidence between all of the articles to determine its value in predicting disability, as well as the follow-up times to see if a characteristic was more relevant for long-term disability. However, if we could not reach a definitive conclusion, we categorized that particular factor as controversial, warranting future research. We included 30 articles, which consisted of a cumulative 8189 patients. The table reporting predictive and non-predictive factors (Table 3) indicates the sample size of CIS patients within studies reporting a particular factor as predictive or non-predictive. The number of studies for each factor is also noted. The categories noted in Table 3 are broad groupings of specific factors, thus each are further elaborated. This review summarizes our perspectives and interpretation of the predictors, current controversial factors, and non-predictors of rapid or worsening disability.

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Fig. 1. The PRISMA flow diagram used to sort through the articles.

Table 2: Summary of CIS study and patient information. Note that the tabulated factors are either categorized, by article, as positively predictive (“Predictive Factor” column) or non-predictive (“Non-predictive Factor” column). FollowMean Mean % Conversion to Up Time (Median) High-Risk Control/Fe (Median) Disability (EDSS: Range in Time to CIS (%) male Follow-Up 3 or more) Years EDSS in Years (IQR) 3.0

Journal and Impact Factor

Number of CIS/Female

Arrabimide, et al.; 2018

Multiple Sclerosis Journal, 5.649

207/131F

65.20%

None

6.30%

2.98

—

Beck, et al.; 2004

JAMA Neurology, 12.321

131/83F

73.23%

None

35%

—

Bommarito, et al.; 2017

Multiple Sclerosis Journal, 5.649

27/17F

70.37%

24/11F

—

1 year follow-up

Author; Year

Brex, et al.; 2002

New England Journal of Medicine, 70.670

Multiple Sclerosis Brownlee, et al.; 2017 Journal, 5.649

Brownlee, et al.; 2019

Brownlee, et al.; 2019b

71/49F

131/83F

63.00%

100%

None

None

33.80%

16.00%

14.10

5.00

Predictive Factor

Nonpredictive Factor

DMTs

Comments

2.00

Spinal Cord Lesions (independent)

—

43.50%

—

10-12

—

Non Optic-Neuritis

Number of T2 Baseline Lesions

More than half

—

—

—

Corticospinal tract volume

MD; FA; Corpus Callosal volume

37.04%

—

—

—

—

More T2 lesions; Larger T2 Lesion Volumes; Non-Optic Neuritis

—

—

Proposed other factors for disability; axonal loss in lesions, abnormalities in the normalappearing tissues, diffuse atrophy, and spinal cord disease.

—

Higher number of Asymptomatic Spinal Cord Lesions (independent); Spinal Cord Atrophy (Upper Cervical Cord Area) (independent); Greater baseline T2 Lesion volume (independent)

T2 Lesion Load; Brain Atrophy; Age; Sex;

—

Location of Brain and Spinal Cord Lesions was not considered

Did not say how many patients had EDSS of 3.0 or 22.916666 higher; all SPMS 67 patients had EDSS higher than 3.0; used 2010 McDonald criteria

Journal of Neurology, Neuropsychiatry, and Psychiatry, 8.272

96/71F

81.25%

34/23F

13.54166667

15-year follow-up

—

—

Brain total sodium concentration (in those who converted to MS: within cortical gray matter and T1 hypointensities)

Brain, 11.814

164/109F

76%

None

—

15-year follow-up

—

—

Contrast-Enhanced Lesions (Baseline); Spinal Cord Lesions

Supratentorial Lesions; Infratentorial 0.2073170 Used 2010 Lesions; Brain 732 McDonald criteria Volume; Spinal Cord Volume

Age; Sex; Brain Volume;

Brain, 11.814

813/593F

56.21%

559/300F

16.00%

5.4 (4.6)

—

—

CSF CHI3L1 (independent);

IgG Oligoclonal bands; Barkhof Criteria

33.33%

CHI3L1 also led to MS conversion and rapid disability as well as long-term, but the rapid disability part disappeared with early treatment

Crnosija, et al.; 2019

European Journal of Neurology, 4.387

94/67F

89.36%

None

—

2.9

1.4-4.1

—

Evoked Potential > 13; Number of T2 Lesions (Baseline)

Age; Sex

—

Effect of DMTs was considered negligible

Dekker, et al.; 2018

Multiple Sclerosis Journal, 5.649

178/119F

100.00%

None

39.30%

(6.00)

(5.0010.44)

—

—

Spinal Cord Lesions

—

— 20 year follow-up; unmodified with DMTs

Canto, et al.; 2015

Fisniku, et al.; 2008

Brain, 11.814

107/71F

79.44%

None

44%

20.20

18.0027.70

—

T2 Lesion Volume; Growing T2 Lesion Volume

—

0.00%

Fisniku, et al.; 2008b

Annals of Neurology, 9.496

73/49F

64.00%

5

30%

20.00

—

—

Gray Matter Fraction; T2 Lesion Load

White Matter Fraction

—

—

0.4858841 01

Observed disability worsening; used 2005 McDonald criteria

Gasperi, et al.; 2019

JAMA Neurology, 12.321

673/459F

67.31%

None

—

4-year follow-up

—

IgM and IgA synthesis;

—

Intrathecal IgG syntehesis

—

66.66%

The percentage under conversion to disability is disability worsening; pediatric population

Iaffaldano, et al.; 2017

Annals of Neurology, 9.496

770/544F

88.30%

None

24.30%

(5.40)

(1.9010.80)

—

Multifocal; Spinal cord or optic neuritis involvement; lack of DMTs

Jakimovski, et al.; 2019

Multiple Sclerosis Journal, 5.649

20/17F

60%

52/38F

—

5-year follow-up

—

—

Serum Neurofilament Light Chain Levels;

—

0.6

Predicted disability in 5 years; used 2010 McDonald criteria

Jokubaitis, et al.; 2015

Annals of Clinical and Translational Neurology, 4.656

1989/1418F

96.10%

None

—

(3.00)

0.75-9.9

(1.50)

Lack of DMT; Older Age; Pyramidal Dysfunction

9 or more T2 Lesions (dependent and weak);

67.30%

Because DMTs are given early with a high lesion load, DMTs skew

Kappos, et al.; 2009

the results; baseline edss shown Lancet Neurology, 28.755

468/331F

100.00%

None

9.00%

5 year follow-up

—

5 year followup

—

Interferon-Beta 1b

76.50%

Clinical trial involving early and delayed treatment

None

—

—

5-10 years followup

—

Shorter Telomere Length

—

—

Accounted for DMTs; used 2001 McDonald criteria

Krysko, et al.; 2019

Annals of Neurology, 9.496

80

Majority of CIS fulfill Revised McDonald Criteria for MS

Loizou, et al.; 2015

Journal of Neuroradiology, 2.467

38/21F

100.00%

20/12F

60.53%

5.00

(0.501.00)

—

Sum Average; Inverse Difference Moment; Coarseness; Increased Heterogeneity

New Lesions (weak); Increase in Disease Volume (weak)

0.00%

—

Minneboo, et al.; 2004

JAMA Neurology, 12.321

42/25F

81.00%

None

33.33%

(8.70)

(7.9-9.3)

—

Infratentorial Lesions (2 or more)

Contrast-Enhanced Lesions; T1 Hypointense Lesions (Black Holes)

0.00%

—

Morrissey, et al.; 1993

Brain, 11.814

89/53F

64.00%

None

20.22%

5 year follow-up

—

—

Number of T2 Baseline Lesions (>4); New T2 lesions

—

0.00%

—

—

0.00%

No spinal cord MRI done; used 0.5 T MRI

Brain, 11.814

81/53F

67.00%

None

35%

9.70

10.00

—

Number of T2 Baseline Lesions (>10); New T2 lesions over 5 years and 5-10 years

Perez-Miralles, et al.; 2013

Multiple Sclerosis Journal, 5.649

117/79F

77.80%

None

—

4.42

—

—

Decreased % of Brain Volume Change; Global and grey matter atrophy (rapid disability); short-term global brain volume loss

White Matter Atrophy

40.20%

2005 McDonald Criteria

Roosendaal, et al.; 2011

Multiple Sclerosis Journal, 5.649

95/61F

100.00%

None

—

—

—

—

Grey Matter T1 and T2 volume (independent);

White Matter T1 and T2 Volume; T1 and T2 Lesion Volume

29.50%

—

—

2-year follow-up

0%

FA Reductions in cerebellum and cerebral peduncles were associated with disability in RRMS; used 2005 McDonald criteria

O'Riordan, et al.; 1998

Frontiers in Schneider, et al.; 2019 Neurology, 2.635

51/32F

100%

49/32F

—

—

—

FA; mean diffusivity

Spinal cord, infratentorial, and contrast-enhanced lesions within 3 months of optic neuritis; new T2 lesions after 3 months

T2 Lesion Load

—

Contrast-enhanced lesions and new T2 lesions not considered significant for disability in CDMS converters; DMTs accounted for in final model

Swanton, et al.; 2009

Neurology, 8.689

100/67F

100.00%

None

16%

(6.00)

(5.1-7.2)

Tintore, et al.; 2006

Neurology, 8.689

175/120F

69.71%

None

7% (5 years); 40% (8 years)

(7.00)

(6.177.75)

8.00

10 or more T2 lesions; Barkhof Criteria; Presence of new lesions after 1 year and 5 years

DMTs (DMTs reduced relapses but not necessarily disability)

29% (5 years)

DMTs may have skewed the results

Tintore, et al.; 2010

Neurology, 8.689

246/167F

61.38%

None

19%

(7.70)

(6.309.50)

—

Infratentorial Lesions (stressed Brainstem Lesions); Spinal Cord Lesions

Cerebellar Lesions;

25.60%

DMTs may have skewed the results

Sex

38.23%

Used 2005 McDonald criteria; percentage of disability based on who got MRI (n=951)

MRI Activity; T2 Hyperintense Lesion Load

Only short-term therapy given

Found T1Weighted images to be better

Tintore, et al.; 2015

Brain, 11.814

1015/686F

70.54%

None

12.41%

6.75

—

—

30 years or over (low-risk); Non Optic-Neuritis Presentation (marginal); Oligoclonal Bands (mediumrisk and independent); 10 or more lesions (high-risk); no DMT prior to second attack; spinal cord lesions

Walderveen, et al.; 1995

Neurology, 8.689

48/36F

Majority

None

—

(2.00)

(0.833.5)

—

T1 Hypointense Lesions (Black Holes)

3. Results and Discussion Table 3 shows the number of studies, and their respective number of subjects, reporting particular factors as predictive and/or non-predictive for rapid disease activity and worsening disability. The major factors are categorized as lesion location, lesion characteristics, CNS volume loss, non-MRI characteristics, and blood biomarkers.

Table 3. Cumulative number of studies, and their respective number of subjects, reporting particular factors as positively predictive and/or non-predictive for rapid disease activity, defined as the development of an EDSS score of 3.0 or greater within 5 years, and worsening disability. The percentages reported in parenthesis represent the percentage of subjects within predictive (or non -predictive) studies for a specific factor out of the cumulative number of patients between both predictive and non-predictive studies for that same factor. Predictive Non-Predictive Factor # of studies # of subjects # of studies # of subjects 1699 Spinal Cord (T2) Lesions 5 1 178 (9.5%) (90.5%) Lesion Location Infratentorial Lesions 3 388 (48.6%) 2 410 (51.4%) Baseline 1634 2399 7 5 T2 Lesions (40.5%) (62.6%) Lesions New Lesions 4 445 (95.7%) 1 20 (4.3%) Lesion T2 Lesion Volume 3 309 (76.5%) 1 95 (23.5%) Characteristics Contrast-Enhancement 2 264 (86.3%) 1 42 (13.7%) T1 Hypointensity 2 144 (77.4%) 1 42 (22.6%) Gray Matter 3 285 – – White Matter 1 27 (5.5%) 4 312 (92.0%) CNS Volume Loss Spinal Cord 1 117 – – Brain 1 117 (34.0%) 2 227 (66.0%) DiffusionFA and Diffusivity – – 2 93 Tensor MRI Sex – – 2 1146 1989 Older Age at CIS Onset 1 2 227 (10.2%) (89.8%) Non-MRI 1217 Characteristics Optic Neuritis 3 1 770 (38.8%) (61.2%) 3774 Lack of DMT Use 3 2 643 (14.6%) (85.4%) 1015 Oligoclonal Bands 1 1 813 (44.5%) (55.5%) CHI3L1 1 813 – – Blood biomarkers Neurofilament Light 1 20 – – Chains Other Biomarkers 3 849 (55.8%) 1 673 (44.2%)

3.1. Lesion Location Lesion location is an important predictive factor in a total of 7 studies and 2511 patients (Note that the number of studies adds up to 7 because we avoided double-counting, where some articles discussed both spinal cord (T2) lesions and infratentorial lesions. The same comment applies to the number of patients). They consist of spinal cord lesions and infratentorial lesions. Five papers (n=1699) found spinal cord lesions to be predictive for disability [14-18]. One reported that asymptomatic spinal cord lesions do not predict the time to disability [10]. Arrambide et al. found that spinal cord lesions were an independent risk factor for short-term disability within a mean follow-up time of 2.98 years [15]. Likewise, Brownlee et al. found them as independent factors, specifically for rapid disability over 5 years [16]. Swanton et al. reported spinal cord lesions to predict disability within 6 years [14]. Tintore et al. in 2010 and 2015 did not find spinal cord lesions to predict disability for a specific period of time, but found them to be generally predictive independent of other factors [17, 18]. Infratentorial lesions were found to be predictive for disability in 3 studies (n=388) [14, 17, 19]. Tintore et al. found brainstem lesions rather than cerebellar lesions in the infratentorial area were more responsible for long-term disability [17]. Minneboo et al. found infratentorial lesions to be responsible for long-term disability [19]. Swanton found infratentorial lesions to predict disability within 6 years [14]. All of these studies had relatively long follow-up times ranging from a median of 6 years to 8.70 years. However, one study (n=164) did not find infratentorial lesions to be predictive [20]. Similarly, a recent review by Odenthal and Coulthard [6] found infratentorial lesions as a predictor of rapid disability; however, it did not look at the role of macroscopic spinal cord lesions with disability. On the other hand, our paper found that more studies support using spinal cord lesions as a prognostic for disability based on EDSS, thus suggesting the importance of spinal cord imagining in CIS. In summary, lesion location appears to be a strong predictor for both short-term and long-term disability.

3.2. Lesion Characteristics Lesion characteristics have a total of 13 studies (n=2244) that support using them for disability prediction, while 7 studies (n=2536) do not. They consist of T2 lesion volume, T1 hypointensities, contrast-enhanced lesions, and T2 lesions (baseline and new). T2 lesion volume was found to be predictive in 3 studies (n=309) [16, 21, 22]. Brex et al. found that EDSS score after 14 years had a moderate correlation to lesion volume at 5 years, the increase in lesion volume within the first 5 years. Brownlee et al. found patients with disability at 5 years had larger T2 lesion volumes at baseline. Fisniku et al. found T2 lesion volume correlated with disability after 20 years. Roosendaal et al. found that T2 lesion volume was a poorer predictor of disability compared to gray matter atrophy [13], although this was a crosssectional study and no follow-up time was provided. Therefore, T2 lesion volume may be a predictor for long-term disability. Results for T1 hypointense „black holes‟ and contrast-enhanced lesions are mixed. There is no conclusive evidence supporting their use as a disability prognostic. Walderveen et al. (n=48) claimed T1 hypointensities were predictive for disability, even arguing that they are better at predicting disability than the hyperintense T2 lesion load [23]. Likewise, Brownlee et al. (n=96) found that the sodium content of T1 hypointensities correlated to EDSS scores for the MS group [24]. In contrast, Minneboo et al. (n=42) did not find “prognostic value” in T1 hypointensities [19]. The difference may be accounted for in follow-time, with Mineboo et al. having a longer median follow-up time (8.7 years) than Walderveen et al. (24 months) and a shorter follow-up time than Brownlee et al. (15 years). Similarly, Swanton et al. claimed T1 gadolinium-enhanced lesions within 3 months of optic neuritis onset were important for disability prognosis but excluded CDMS patients [14]. Brownlee et al. also argued that baseline gadolinium-enhancing lesions held a consistent association with EDSS [20]. On the other hand, Mineboo et al. found that T1 gadoliniumenhanced lesions had no predictive value [19]. All of the studies had relatively small sample sizes, so their conclusions on T1 hypointensities and contrast-enhanced lesions are not robust. Baseline T2 lesions were found as disability predictors in 7 studies (n=1634) [18, 22, 2529]. In Crnošija et al. 2019, the total number of T2 lesions predicted sustained accumulation of disability along with evoked potential scores above 13 [25]. More baseline T2 lesions resulted in a higher proportion of patients with significant disability in 20 years [22]. In O‟Riordan et al., 10 or more baseline T2 lesions corresponded with significant disability after 10 years [28]. Four or more baseline T2 lesions were related to disability after 5 years according to Morrissey et al., while Tintore et al. in 2006 found the number of baseline lesions corresponded to worsening

disability in the same timeframe [27, 29]. In 2015, Tintore et al. found that 10 or more baseline T2 lesions were a high-risk prognostic factor for disability [18]. Despite these findings, five studies (n=2399) found that baseline T2 lesions did not predict or weakly predicted disability [14, 16, 23, 30, 31]. Swanton et al. did not find baseline T2 lesion load to be significant in the univariate analysis of predictors [14]. In a 2017 study focusing on spinal cord lesions, including brain T2 lesion load and brain atrophy only modestly increased the predictive power (from R2=0.53 to R2=0.64) of a model between disability and upper cervical cord area and the number of spinal cord lesions [16]. However, this sample size is skewed by a large study of 1989 patients [31], which reported that T2 lesions were a weak predictor of disability accumulation. Walderveen et al. found the correlation between T2 lesion load and disability to be weak (Spearman Rank Correlation Coefficient=0.19). A 2004 longitudinal study found the degree of disability to be unrelated to the number of baseline lesions (p=0.14) [30]. A very large study (n=1989) found that the number of baseline T2 lesions to be non-predictive when evaluating the adjusted hazard ratio (p > 0.578) [31]. All these studies with a single exception [30] had relatively short follow-up times of 6 years or less. As a result, baseline T2 lesions appear to be more predictive for long-term disability but not for rapid disability. New T2 lesions after follow-up were found to predict disability in 4 studies [14, 27-29]. New T2 lesions within 10 years (especially if they occurred within the first 5 years) significantly correlated to a worsening EDSS score at 10 years [28]. Swanton et al. found new T2 lesions within 3 months predicted disability after 6 years, but they were not significant in determining worsening disability in CDMS patients [14]. New T2 lesions after 5 years correlated to EDSS [27, 29]. In Tintore et al. 2006, new T2 lesions after one year also correlated to EDSS after 5 years [29]. In summary, T2 lesion volume and the number of T2 lesions appear to predict long-term disability. In contrast, T1 hypointense and contrast-enhanced lesions are disputed risk factors for disability. As a whole, lesion characteristics warrant further study. 3.3. CNS Volume and Diffusion-Tensor MRI Volume and diffusion-tensor MRI are other disputed prognostic factors for disability. This category consists of 1) gray matter volume, 2) white matter volume, 3) total brain volume, 4) spinal cord area and microstructural damage. Gray Matter Atrophy: Gray matter atrophy was found to be predictive in 3 studies involving 285 patients [13, 26, 32]. In Fisniku et al., gray matter atrophy based on gray matter fraction was more predictive of disability within 20 years than white matter atrophy [26].

According to another study, gray matter atrophy was especially correlated with disability accrual as early as a year into CIS (Spearman‟s rank coefficient = -0.48), and gray matter fractions were associated with EDSS score at follow-up [32]. In a 2011 study, gray matter volumes were significantly lower in RRMS patients than CIS patients and explained physical and cognitive impairment better than white matter [13]. White Matter Volume: White matter volume loss was found to be non-predictive in 4 studies and 312 patients [13, 22, 32, 33]. In a 2017 study, corticospinal tract volumes were significantly associated with EDSS within a year, but corpus callosum volumes were not [33]. A larger study with a similar mean follow-up time of 4.42 years found that white matter fractions for CIS and MS were unchanged [32]. Fisniku et al. found that white matter volumes were not significantly different between RRMS patients and CIS patients after 20 years [26]. A 2011 study found normalized white matter volumes to have a p-value greater than 0.1 in the multiple ordinal regression model [13]. Likewise, another 2017 study found that the corpus callosal area was relevant in predicting CDMS from CIS but not relevant as a disability prognostic within 5 years; however, Odenthal et al. did not differentiate between high and low-risk CIS patients [34]. Total Brain Volume: Studies, with similar follow-up times, on total brain volume are mixed on its impact as a disability predictor [16, 20, 32]. Perez-Miralles et al. found that global atrophy was related to EDSS changes especially within the first few years [32]. A 2017 study found that brain atrophy only modestly increased the predictive power of spinal cord lesion and spinal cord atrophy model for disability [16]. Brownlee et al. found that brain volume was inconsistent in predicting EDSS compared to contrast-enhanced lesions and spinal cord lesions [20]. Ghione et al. found that all brain volume measurements correlated with EDSS for CIS and MS, but Ghione et al. did not differentiate between high and low-risk CIS patients [35]. Spinal Cord Area Loss and Diffusion-Tensor MRI: One paper reported on spinal cord area loss and found that the changes in upper cervical cord cross-sectional area (C2/C3 disc) along with macroscopic spinal cord lesions were independently associated with EDSS [16]. A 2017 paper with a 1-year follow-up time did not find fractional anisotropy or mean diffusivity by diffusion-tensor MRI of the corticospinal tract or the corpus callosum as a marker of disability [33]. Fractional anisotropy provides sensitive microstructure information about white-matter integrity. Another paper failed to find a correlation between EDSS and diffusion measures like fractional anisotropy and mean diffusivity for CIS [36]. With recently advanced diffusion-tensor MRI methods, it may be possible to detect subtle and early white-mater changes that could be informative of CIS progression. Although diffusion-tensor MRI has been

increasingly utilized in other neurological disorders, it is rarely used in MS or CIS in clinical settings to date. Further studies are needed. In summary, CNS tissue loss (atrophy) and DTI need more studies to confirm its relevance as a disability predictor. Gray matter atrophy appears to predict rapid and long-term disability, whereas white matter atrophy does not appear to predict disability, but more studies are needed for both. 3.4. Clinical and Demographic Features Clinical and demographic features, or non-MRI characteristics in Table 3, consist of lack of DMT use, non-optic neuritis, sex, and older age. Three papers with 3774 patients found that a lack of DMT use led to worsening disability [18, 31, 37]. Iaffaldano et al. found a protective effect for DMTs in relation to disability [37]. Tintore et al. in 2015 found that DMT administration before the second attack reduced the risk of disability accumulation [18]. The third study found that patients exposed to DMTs for 80% of their follow-up time reduced the risk of disability by 57% for 3-month confirmed and 12-month confirmed disability worsening [31]. In this study, first-line drug effectiveness with interferon beta-1a (intramuscular and subcutaneous), interferon beta-1b, and glatiramer acetate reduced the rate of 3-month and 12month disability worsening events [31]. Although two studies and 643 patients found DMT administration did not matter for disability [11, 29], the clinical trial [11, 29] was much larger than the 2006 study [11, 29], which skews the n-value. The clinical trial also tested only one DMT, interferon beta-1b. Both the non-predictive studies also had similar follow-up times from 5 to 7 years. In contrast, all of the papers finding that DMT reduced or delayed disability worsening were large studies, with the smallest having 770 patients, and they had varying follow-up times from 3 years to a median follow-up time of 6.75 years. Three studies and 1217 patients found that CIS not presenting as optic neuritis showed higher risk of disability [18, 21, 30]. A 2004 study by the Optic Neuritis Study Group found CDMS patients presenting with an initial episode of optic neuritis were associated with a lower risk for disability, with at least ten years of a relatively benign disease course [30]. In an earlier study with a 14-year follow-up time, the largest subgroup had optic neuritis, which was suggested to have a more benign prognosis than other initial symptom presentations [21]. In a 2015 study with a shorter mean follow-up time of 6.75 years, optic neuritis patients had a lower risk of conversion to MS and a lower risk of disability, but the lower risk of disability was marginal [18]. Only one study associated optic neuritis with a higher incidence of EDSS

worsening events, but this study was in the pediatric population [37]. It is unclear why the presence of optic neuritis is related to a lower-risk for worsening disability. There are 4 papers with similar follow-up times that found sex to be non-predictive for disability [16, 18, 24, 25]. Two large studies with varying follow-up times found older age as a risk factor for disability [18, 31]. In a 2015 study, each older decade (30-39 years old vs. 40-49 years old) at onset reduced the risk of converting to MS but increased the risk of disability and had low impact [18]. Similar to the 2015 study, a 2019 study found older age at CIS onset to predict 3-month and 12-month disability worsening events [31]. Only one smaller study found age to have a negligible effect on the correlations for disability [16]. In summary, lack of DMT use and older age appear to be predictive of disability, while sex was not. Optic neuritis may have a protective effect regarding long-term disability, but more studies are needed. 3.5. Non-Imaging Biomarkers There are 6 studies and 2697 patients that support predictive value for biomarkers, and 2 studies and 1486 patients claiming that certain biomarkers are not predictive for disability. Biomarkers consist of oligoclonal bands, chitinase-3-like protein 1 (CHI3L1), neurofilament light protein, and miscellaneous biomarkers. One study (n=1015) found IgG oligoclonal bands predicted disability [18] while another study (n=813) did not [38]. In the predictive study, oligoclonal bands were found to be mediumrisk predictors for disability within a mean follow-up time of 6.75 years [18]. In the nonpredictive study oligoclonal bands were found as inferior predictors compared to CSF CHI3L1, with a median follow-up time of 4.6 years and mean follow-up time of 5.4 years. CHI3L1 was found to be a predictor of disability in one large study [38]. Its importance was related to both rapidity and degree of long-term disability, but early treatment reduced the biomarker‟s predictive effect on rapid disability. Neurofilament Light Protein: Neurofilament light protein was found to be predictive in one study (n=20) [39]. In the predictive paper, serum neurofilament light chain proteins predicted EDSS scores in 5 years [39]. Similarly, CSF neurofilament light protein levels correlated with EDSS score in CIS patients, but CIS patients were not differentiated between high and low-risk [40]. In another paper, CSF neurofilament light protein significantly correlated with EDSS after a mean follow-up time of a year initially; when adjusted for age, the significant correlation disappeared, but this paper also failed to distinguish between high and low-risk CIS patients [41].

Three studies found other biomarkers to be predictive for disability [20, 42, 43]. One found that higher cortical gray matter sodium levels associated with disability using the emerging imaging technique of sodium MRI [24]. Gasperi et al. associated intrathecal IgG synthesis with EDSS worsening in 4 years [42]. A separate study found a 0.2 decrease in leukocyte telomere length to increase EDSS by 0.34 [43]. Two other studies found different biomarkers to be predictive for disability, but they failed to separate high-risk CIS from low-risk [41, 44]. One found a correlation between brain myo-inositol concentrations, a sensitive marker for normal appearing white matter abnormalities and glial cell proliferation, as measured by MR spectroscopy and patient disability after 14 years, but failed to find a significant correlation between cortical gray matter N-acetyl aspartate (NAA) and EDSS score after 14 years [44]. Another study correlated CSF N-acetyl aspartate (r=0.308, p<0.05), where decreases in this neuronal marker is indicative of neuronal loss or dysfunction, and CSF neurofilament heavy chain (r=0.304, p<0.05) to EDSS score within a year [41]. In summary, the lack of papers on biomarkers as predictors for disability prevent a conclusive judgement on the predictive value of biomarkers. Differences in follow-up time are especially pronounced in these studies.

4. Limitations and Future Studies The total number of patients was used as an index of strength. This approach did not statistically weigh the strength of statistics within each study, nor did it distinguish between independent and dependent risk factors. That said, we did pay attention qualitatively on the statistics within each paper, the authors‟ opinions therein, and other factors that contributed to the strengths of predictors and non-predictors of disability after CIS. The total number of participants including controls could alternatively be used in our tables, but doing so is unlikely to alter the overall conclusions of this study. EDSS was used as a measure of disability as it is mostly commonly used for clinical disability. Other scores such as the MS Composite Score or cognitive impairment scores may provide different and additional insights. For example, EDSS is influenced largely by mobility, which could bias to MRI changes in motor systems such as changes in macroscopic spinal cord and infratentorial lesions. This literature search involved keywords for titles and abstracts only, therefore studies that include CIS data without emphasizing it in the titles or abstracts may have been missed.

There are additional MRI methods such as diffusion-tensor imaging, resting-state functional MRI, susceptibility-weighted imaging, and quantitative susceptibility mapping could be used to provide valuable information with respective to disease monitoring and imaging biomarker of rapid disease progression, although they are not currently used in the clinics on CIS nor MS patients.

5. Conclusions This review paper identified imaging and other clinical features in populations with a majority of high-risk CIS patients that are associated with rapid disability worsening as measured by EDSS. By far lesion location (infratentorial and spinal cord), older age, and absence of DMT treatment were most predictive of future rapid disability, followed by T2 lesion volume and number of T2 lesions. Whether CNS atrophy, microstructural damage by diffusion-tensor MRI, T1 hypointensity, T1 contrast-enhanced lesions, and biomarkers are associated with rapid disability progression warrant further study. Although a consensus of neurologists in the United States support using contrast-enhanced lesions for DMT initiation as a measure to prevent rapid disability progression, this is not suggested by our current literature; thus, the practice may be misleading. White matter atrophy does not appear to be associated with rapid disability progression. While CHI3L1 and oligoclonal bands are important in the diagnosis of MS, their association with rapid disability progression in high-risk CIS patients warrants further investigation. Identifying imaging features associated with high likelihood of significant future or worsening disability could have important clinical applications. These findings may help guide future research studies to explore specific imaging features. Such knowledge may enable healthcare providers to monitor specific features more diligently, thereby providing patients with more informative or definitive prognoses. Doctors may be more likely to treat aggressively and closely follow CIS patients with a higher risk of future disability.

Funding Stony Brook School of Medicine (TRO-FUSION) pilot grant. We would like to acknowledge the use of the resources of the Biomedical Imaging Research Center (Radiology, Stony Brook Medicine). Conflict of Interest Statement None of the authors declare any conflicts of interest.

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