Imaging grey matter atrophy to find the roots of disability

How do we measure nerve loss?

The imagers tell us it is grey matter loss that holds the key.

So what’s new here?

About ten years ago I was at a meeting where a very distinguished MRI expert was saying that ‘whole brain volume’ was not a good outcome measure to monitor progression and that grey matter volume was a much more responsive outcome measure.

However, we (the neuros should I say) have continued to use whole brain atrophy as an outcome measure, and trials have failed, over and over again. 

The white matter may swell due to the inflammatory activity and shrink when the immune response goes. 

This study suggests that grey matter loss best correlates with disability. So when will people start to listen?

High-dose biotin made the brain shrink and the EMA want more data.

Statins slowed the shrinkage, does it mean it is good?

People are using cord shrinkage as an outcome, but again it has problems as we have shown that it may miss a lot of the nerve loss.

Eshaghi A, Prados F, Brownlee W, Altmann DR, Tur C, Cardoso MJ, De Angelis F, van de Pavert SH, Cawley N, De Stefano N, Stromillo ML, Battaglini M, Ruggieri S, Gasperini C, Filippi M, Rocca MA, Rovira A, Sastre-Garriga J, Vrenken H, Leurs CE, Killestein J, Pirpamer L, Enzinger C, Ourselin S, Wheeler-Kingshott CAMG, Chard D, Thompson AJ, Alexander DC, Barkhof F, Ciccarelli O; MAGNIMS study group. Ann Neurol. 2018. doi: 10.1002/ana.25145. [Epub ahead of print]


Grey matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS.


We analysed 3,604 brain high-resolution T1-weighted MRI scans from 1,417 participants: 1,214 MS patients (253 clinically-isolated syndrome[CIS], 708 relapsing-remitting[RRMS], 128 secondary-progressive[SPMS], 125 primary-progressive[PPMS]), over an average follow-up of 2.41 years (standard deviation[SD]=1.97), and 203 healthy controls (HCs) [average follow-up=1.83 year, SD=1.77], attending 7 European centres. Disability was assessed with the Expanded-Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem and cerebral white matter. The annual percentag was assessed.


SPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time-to-EDSS progression (hazard ratio=0.73, 95% CIs 0.65, 0.82; p<0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow-up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (-1.45%), PPMS (-1.66%), and RRMS (-1.34%) than CIS (-0.88%) and HCs (-0.94%)[p<0.01]. The rate of temporal GM atrophy in SPMS (-1.21%) was significantly faster than RRMS (-0.76%), CIS (-0.75%), and HCs (-0.51%). Similarly, the rate of parietal GM atrophy in SPMS (-1.24-%) was faster than CIS (-0.63%) and HCs (-0.23%) (all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta=0.04, p<0.001). 


This large multi-centre and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions. 

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