MRI – Prof G's MS Blog Archive

#ECTRIMS2021: Do you have inactive SPMS? How often are you having an MRI?

Barts-MS rose-tinted-odometer: ★★★★

Gray & White MRI Friday #808080

When we interrogated a large number of pwSPMS we discovered that what really determines if you have active vs. inactive SPMS is how frequently you have an MRI scan. The more frequently you get scanned the more likely your team are to find new MRI lesions. If you rely on having a clinical relapse you may wait a long time. For example, after 2 years of no relapse and no MRI activity, disease activity returned in >50% of previously inactive pwSPMS. However, in 4 out of 5 cases this was driven by MRI activity and not by having a relapse.

Based on the observation that many pwSPMS have reduced MRI monitoring this decreases the chances of detecting and potentially treating and preventing disease activity in pwSPMS.

For those of you who have been told you have inactive SPMS and are ineligible for treatment, you need to ask has my MS been looked at in enough detail?

Giovannoni et al. MRI activity versus relapses as markers of disease activity in SPMS: Data from real world and pivotal clinical studies. ECTRIMS2021 P001.

Introduction: Secondary progressive multiple sclerosis (SPMS) is often categorised as active (aSPMS) or non-active (naSPMS) based on the evidence of disease activity (relapses and/or magnetic resonance imaging [MRI] activity).

Objectives: To evaluate the contribution of MRI activity and relapses in defining disease activity in SPMS patients by analysing real-world data from Adelphi real-world MS Disease Specific Programme (Adelphi MS DSP) and to understand whether aSPMS and naSPMS are mutually exclusive groups based on data from the Phase 3 EXPAND study.

Methods: Adelphi MS DSP was a non-interventional, multinational real-world study consisting of 37,318 MS patients that includes 3580 patients with SPMS who were surveyed between 2011–2019. Patients were categorised into aSPMS (≥1 new lesion on the most recent MRI and/or ≥1 relapse in the last 12 months) and naSPMS groups. In the EXPAND study, disease activity (aSPMS) was defined as presence of relapses in the 2 years prior to screening and with/without ≥1 gadolinium-enhancing (Gd+) T1 lesion at baseline. Demographics, MRI and relapse status were analysed descriptively.

Results: Patients with SPMS from the Adelphi MS DSP were categorised as aSPMS (n=1889) and naSPMS (n=665). Disease activity (aSPMS) was defined on the basis of MRI lesions (59.1%), relapse status (12.6%), and both MRI and relapse (28.3%). In the past 12 months, aSPMS (vs naSPMS) patients had a lower mean Expanded Disability Status Scale score (4.6 vs 5.2), a higher proportion of patients undergoing MRI (87.7% vs 58.7%), and more MRIs per patient (1.24 vs 0.87). A greater proportion of naSPMS (vs aSPMS) patients were without treatment (45.1% vs 23.4%). In EXPAND, 52.6% of patients (n/N=866/1645) who had no relapse in the 2 years prior to screening and no Gd+ T1 lesions at baseline were categorised under naSPMS; of these naSPMS patients who were on placebo, 52.7% experienced on-study relapse and/or MRI activity: MRI (41.8%), relapses (4.6%), and both MRI and relapse (9.2%).

Conclusions: In both real-world and clinical studies, MRI activity appears to be a more sensitive measure of disease activity versus relapses. Even after 2 years of no relapse and no MRI activity at baseline, disease activity returned in >50% of previously ‘non-active’ patients on placebo in EXPAND. Further, reduced MRI monitoring in ‘naSPMS’ patients in the real world is a concern, which decreases the chance to detect and treat any new disease activity in these patients.

Some pointed out to me yesterday that they thought it was quite cool that I was P001; I think they were drawing an analogy to 007, but let’s not go there 😉

Conflicts of Interest

MS-Selfie Newsletter / MS-Selfie Microsite

Preventive Neurology

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General Disclaimer: Please note that the opinions expressed here are those of Professor Giovannoni and do not necessarily reflect the positions of the Barts and The London School of Medicine and Dentistry nor Barts Health NHS Trust and are not meant to be interpreted as personal clinical advice.

How demyelinated are my MS lesions?

Barts-MS rose-tinted-odometer: ★★★★★ (Vermillion Monday code #E34234)

There are very few what I call really deep-thinkers in MS research and Danny Reich is one of them. This paper from his group is so simple in its inception and execution; it is a fine example of seeing the woods for the trees. They use a relatively simple MRI technique to interrogate MS lesions to classify them as being remyelinated, demyelinated or mixed.

Using an MRI sequence they classify MS brains lesions as being “long-T1,” “short-T1,” and “mixed-T1”, which correspond to fully demyelinated, fully remyelinated, and mixed demyelinated/remyelinated lesions, respectively. Neat? You bet it is neat. Demyelination, rather than axon loss, dominantly contributed to initial T1 prolongation, which is a metric from the TI relaxation time* on imaging.

*T1 is the so-called longitudinal relaxation time and is the time constant that determines the rate at which excited protons return to equilibrium. It is a measure of the time taken for spinning protons to realign with the external magnetic field.

Short-T1 or remyelinated lesions were most common in the deep white matter, whereas long-T1/demyelinated and mixed-T1/demyelinated-remyelinated lesions were more common in lesions next to the cortex (juxtacortical) and ventricles (periventricular) and were much more likely to have paramagnetic or iron rims suggesting chronic inflammation. The latter are the so-called slowly expanding lesions that are one of the drivers of smouldering MS.

Please note older age at the time of lesion formation meant less remyelination, which is another reminder that as you get older your recovery mechanisms fail.

The question is whether or not this simple technique can be used as an outcome measure in trials and/or to profile pwMS for remyelination studies. There is little reason to load remyelination trials with patients who are not going to be able to respond to remyelination treatments. What about using this technique as a prognostic tool? Is there a biological reason, apart from age, why some pwMS remyelinate and others don’t?

Could this technique be used to supplement evoked potentials to assess whether or not a condition is demyelinating, i.e. as an aid to help make a diagnosis of MS?

You know a paper is good when it leaves you asking more questions than it answers.

Kolb et al. 7T MRI Differetiates Remyelinated from Demyelinated Multiple Sclerosis Lesions. Ann Neurol. 2021 Aug 14.

Objective: To noninvasively assess myelin status in chronic white matter lesions of multiple sclerosis (MS), we developed and evaluated a simple classification scheme based on T1 relaxation time maps derived from 7-tesla postmortem and in vivo MRI.

Methods: Using the MP2RAGE MRI sequence, we classified 36 lesions from 4 postmortem MS brains as “long-T1,” “short-T1,” and “mixed-T1” by visual comparison to neocortex. Within these groups, we compared T1 times to histologically derived measures of myelin and axons. We performed similar analysis of 235 chronic lesions with known date of onset in 25 MS cases in vivo and in a validation cohort of 222 lesions from 66 MS cases, investigating associations with clinical and radiological outcomes.

Results: Postmortem, lesions classified qualitatively as long-T1, short-T1, and mixed-T1 corresponded to fully demyelinated, fully remyelinated, and mixed demyelinated/remyelinated lesions, respectively (p ≤ 0.001). Demyelination (rather than axon loss) dominantly contributed to initial T1 prolongation. We observed lesions with similar characteristics in vivo, allowing manual classification with substantial interrater and excellent intrarater reliability. Short-T1 lesions were most common in the deep white matter, whereas long-T1 and mixed-T1 lesions were prevalent in the juxtacortical and periventricular white matter (p = 0.02) and were much more likely to have paramagnetic rims suggesting chronic inflammation (p < 0.001). Older age at the time of lesion formation portended less remyelination (p = 0.007).

Interpretation: 7-tesla T1 mapping with MP2RAGE, a clinically available MRI method, allows qualitative and quantitative classification of chronic MS lesions according to myelin content, rendering straightforward the tracking of lesional myelination changes over time.

Conflicts of Interest

MS-Selfie Newsletter / MS-Selfie Microsite

Preventive Neurology

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Knowing about damage or not

Barts-MS rose-tinted-odometer: ★ (seeing orange; halfway between red and yellow)

Do you want to know how badly damaged your MS brain is or would you prefer to put your head in the sand and ignore it? This is a dilemma facing a large number of you. Do you ask your neurologist if you have exaggerated or accelerated brain atrophy? Do you ask to have cognitive screening to see how good or bad your cognition is?

Another metric that is likely to enter clinical practice in the future is a metric to assess how well your brain’s functional network is working. The brain is like multiple computers working together in parallel. The brains’ computers or functional domains work together in harmony as a functional network. If you acquire enough lesions and damage the functional network the brain stops working as well and efficiently as it should. This manifests as cognitive fatigue and cognitive problems. It takes so much more mental effort to get the brain’s damaged functional network to perform well, which is why it causes fatigue.

The study below shows that in pwMS with damage to the brain measured using both structure (loss of volume) and function (loss of connectivity) do poorly; i.e. they were more likely to become secondary progressive over the next 6 years. Are you surprised by these results? It is amazing how accurate these MRI metrics were in being able to predict who would become progressive or not.

The message from this and other studies is simple, MS damage begets MS damage. This is why we have to diagnose and treat MS as early as possible and if necessary as effectively as possible. Once damage accumulates it is irreversible and when it is detected it represents a sick brain, which then continues to be shredded by the processes that drive smouldering MS.

Rocca et al. Network Damage Predicts Clinical Worsening in Multiple Sclerosis: A 6.4-Year Study. Neurol Neuroimmunol Neuroinflamm. 2021 May 21;8(4):e1006.

Objective: In multiple sclerosis (MS), clinical impairment is likely due to both structural damage and abnormal brain function. We assessed the added value of integrating structural and functional network MRI measures to predict 6.4-year MS clinical disability deterioration.

Methods: Baseline 3D T1-weighted and resting-state functional MRI scans were obtained from 233 patients with MS and 77 healthy controls. Patients underwent a neurologic evaluation at baseline and at 6.4-year median follow-up (interquartile range = 5.06-7.51 years). At follow-up, patients were classified as clinically stable/worsened according to disability changes. In relapsing-remitting (RR) MS, secondary progressive (SP) MS conversion was evaluated. Global brain volumetry was obtained. Furthermore, independent component analysis identified the main functional connectivity (FC) and gray matter (GM) network patterns.

Results: At follow-up, 105/233 (45%) patients were clinically worsened; 26/157 (16%) patients with RRMS evolved to SPMS. The treatment-adjusted random forest model identified normalized GM and brain volumes, decreased FC between default-mode networks, increased FC of the left precentral gyrus in the sensorimotor network (SMN), and GM atrophy in the fronto-parietal network (false discovery rate [FDR]-corrected p = range 0.01-0.09) as predictors of clinical worsening (out-of-bag [OOB] accuracy = 0.74). An expected contribution of baseline disability was also present (FDR-p = 0.01). Baseline disability, normalized GM volume, and GM atrophy in the SMN (FDR-p = range 0.01-0.09) were independently associated with SPMS conversion (OOB accuracy = 0.84). At receiver operating characteristic analysis, including network MRI variables improved disability worsening (p = 0.05) and SPMS conversion (p = 0.02) prediction.

Conclusions: Integration of MRI network measures helped determining the relative contributions of global/local GM damage and functional reorganization to clinical deterioration in MS.

Conflicts of Interest

Preventive Neurology

Twitter

Medium

What is happening to my cortex?

A very common analogy is the comparison of MS to an iceberg. Why?

Only one-eighth of an iceberg is visible above the water; to see what is below the water line requires specialised technology. The MS iceberg analogy refers to several observations:

1. For each clinical relapse, 10 or more MRI visible lesions are seen on MRI.
2. For each visible white matter lesions on MRI, there are at least an equivalent number or more grey matter lesions. In fact, it is now estimated that more than half the MS pathology is in the grey matter.
3. For every visible white matter lesion, either on MRI or with the naked eye, there are 20 or more microscopic lesions present in the white matter.
4. Despite only a relatively small amount of brain or spinal cord atrophy, there is almost three times as much neuronal loss underlying the atrophy.
5. Despite a relatively good recovery of function in a particular pathway, for example, after a relapse, there is a substantial loss of axons and hence reserve capacity in that pathway.
6. People with MS have many more hidden symptoms and disabilities than visible physical disabilities; early MS is often a hidden disease.

When you use newer technologies, for example, a 7 Tesla MRI to look at cortical or grey matter lesions in MS you begin to see how large the iceberg really is. Please remember the vast majority of cortical MS lesions (>90%) or not seen with conventional MRI. The bad news in the study below is that almost all the pwMS studied had cortical lesions and these, not surprisingly, correlated with disability and cognitive impairment. What is interesting is that the lesions on the surface of the brain (subpial), but not those on the grey-white matter interface (leukocortical), correlated better with cortical volume. However, the grey-white matter interface, or leukocortical, lesions correlated most strongly with cognitive impairment.

What is becoming increasingly important is to try and target the grey matter pathology and prevent cognitive impairment in pwMS. The problem is we don’t routinely monitor brain and in particular grey matter atrophy in routine clinical practice; in fact it is largely ignored. If we did we would probably find many more pwMS opting for the higher efficacy treatments that have the greatest impact on brain atrophy (alemtuzumab and HSCT).

It is important for you to realise that you can be NEDA-3, i.e. no clinical attacks and MRI activity, and still have progressive grey matter atrophy. Why this is happening is debatable. Some evidence points to immunoglobulins and complement activation, rather than cytotoxic T-cells, being the major driver of cortical pathology. This why Barts-MS is exploring add-on drugs that will hopefully target the B-cell follicles and plasma cells within the central nervous system to try and slow down this process. We plan to start recruiting for our add-on study later this year.

I have little doubt that slowing down and preventing progressive brain and grey matter atrophy will become one of the treatment targets for the next generation of MSologists. To make this a reality we need to have tools to measure these processes reliably in clinical practice.

Harrison et al. Association of Cortical Lesion Burden on 7-T Magnetic Resonance Imaging With Cognition and Disability in Multiple Sclerosis. JAMA Neurol. 2015 Jul 20. doi: 10.1001/jamaneurol.2015.1241.

IMPORTANCE: Cortical lesions (CLs) contribute to physical and cognitive disability in multiple sclerosis (MS). Accurate methods for visualization of CLs are necessary for future clinical studies and therapeutic trials in MS.

OBJECTIVE: To evaluate the clinical relevance of measures of CL burden derived from high-field magnetic resonance imaging (MRI) in MS.

DESIGN, SETTING, AND PARTICIPANTS: An observational clinical imaging study was conducted at an academic MS center. Participants included 36 individuals with MS (30 relapsing-remitting, 6 secondary or primary progressive) and 15 healthy individuals serving as controls. The study was conducted from March 10, 2010, to November 23, 2012, and analysis was performed from June 1, 2011, to September 30, 2014. Seven-Tesla MRI of the brain was performed with 0.5-mm isotropic resolution magnetization-prepared rapid acquisition gradient echo (MPRAGE) and whole-brain, 3-dimensional, 1.0-mm isotropic resolution magnetization-prepared, fluid-attenuated inversion recovery (MPFLAIR). Cortical lesions, seen as hypointensities on MPRAGE, were manually segmented. Lesions were classified as leukocortical, intracortical, or subpial. Images were segmented using the Lesion-TOADS (Topology-Preserving Anatomical Segmentation) algorithm, and brain structure volumes and white matter (WM) lesion volume were reported. Volumes were normalized to intracranial volume.

MAIN OUTCOMES AND MEASURES: Physical disability was measured by the Expanded Disability Status Scale (EDSS). Cognitive disability was measured with the Minimal Assessment of Cognitive Function in MS battery.

RESULTS: Cortical lesions were noted in 35 of 36 participants (97%), with a median of 16 lesions per participant (range, 0-99). Leukocortical lesion volume correlated with WM lesion volume (ρ = 0.50; P = .003) but not with cortical volume; subpial lesion volume inversely correlated with cortical volume (ρ = -0.36; P = .04) but not with WM lesion volume. Total CL count and volume, measured as median (range), were significantly increased in participants with EDSS scores of 5.0 or more vs those with scores less than 5.0 (count: 29 [11-99] vs 13 [0-51]; volume: 2.81 × 10-4 [1.30 × 10-4 to 7.90 × 10-4] vs 1.50 × 10-4 [0 to 1.01 × 10-3]) and in cognitively impaired vs unimpaired individuals (count: 21 [0-99] vs 13 [1-54]; volume: 3.51 × 10-4 [0 to 1.01 × 10-4] vs 1.19 × 10-4 [0 to 7.17 × 10-4]). Cortical lesion volume correlated with EDSS scores more robustly than did WM lesion volume (ρ = 0.59 vs 0.36). Increasing log[CL volume] conferred a 3-fold increase in the odds of cognitive impairment (odds ratio [OR], 3.36; 95% CI, 1.07-10.59; P = .04) after adjustment for age and sex and a 14-fold increase in odds after adjustment for WM lesion volume and atrophy (OR, 14.26; 95% CI, 1.06-192.37; P = .045). Leukocortical lesions had the greatest effect on cognition (OR for log [leukocortical lesion volume], 9.65; 95% CI, 1.70-54.59, P = .01).

CONCLUSIONS AND RELEVANCE: This study provides in vivo evidence that CLs are associated with cognitive and physical disability in MS and that leukocortical and subpial lesion subtypes have differing clinical relevance. Quantitative assessments of CL burden on high-field MRI may further our understanding of the development of disability and progression in MS and lead to more effective treatments.

CoI: multiple