Resting state networks change in clinically isolated syndrome Stefan Roosendaal Lucien Appel Prize of the ESNR Symposium Neuroradiologicum 4 October 2010, Bologna Nog doen: -Ruis-netwerk

Jury Lucien Appel Prize 2010 Co-authors In particular dr. Geurts Acknowledgments Jury Lucien Appel Prize 2010 Co-authors In particular dr. Geurts and prof. Barkhof Sabrina van der Kleij Funding Dutch MS Research Foundation #06-592 Department of Radiology VU University medical center I would like to start by thanking the Jury of the Lucien Appel Prize of the ESNR, for selecting my paper for such an honourable award; and also the organizers for allowing me to present my work. Secondly, I thank my co-authors, especially Jeroen Geurts and Frederik Barkhof, who have been most helpful. I thank my funding during my thesis research, as well as the department of Radiology.

Brain 133 (2010) 1612-1621 The paper that I submitted for the Prize is part of my thesis; People who are interested in the details of the paper can find it in a volume of Brain of this year, starting at page 1612.

Mainero et al. NeuroImage 2004 Introduction: task fMRI in MS FMRI has the ability to show us how the brain functionally reacts to damage FMRI during motor- and cognitive tasks  cortical reorganization in MS Rocca et al. NeuroImage 2003 Fingertapping Controls early MS Memory recall Controls MS patients FMRI is used in neurodegenerative disease for a couple of years now, because it provides us with a view of how the brain functionally reacts to damage. It does this because the strenght and spatial extent of activation in reaction to a task differs between patients and controls. These changes may or may not be beneficial, but are in themselves interesting already to document how the brain functionally reacts to the disease. In multiple sclerosis, much research has been performed using motor- and cognitive tasks, and reorganization of activity patterns has been shown, as you can see here for a fingertapping task and for a memory recall task. Mainero et al. NeuroImage 2004

Introduction: resting state fMRI In absence of a task, BOLD signals from functionally related brain regions show temporal correlation (synchronization) Biswal et al. MRM 1995 In 1995, a correlation in the temporal fluctuations of the blood-oxygen level dependent (or BOLD) signal was found between 2 spatially distant, but functionally related brain areas (the motor cortices), in absence of a task, by Biswal et al. When this correlation is statistically quantified, and the strenght of this statistic subsequently colour-coded for each voxel, a connectivity map in absence of a task of the motor network is created.

Fox & Raichle. Nature Rev Neurosci 2007 Introduction: resting state fMRI Synchronization during rest: Why is it of interest? Energy consumption in absence of task is large Several resting state networks in healthy controls  investigate whole brain at once Early Alzheimer (MCI): altered resting state network Damoiseaux et al. PNAS 2006 Fox & Raichle. Nature Rev Neurosci 2007 Sorg et al. PNAS 2007 In following years, it became clear that to study the brain at rest with FMRI, thus in absence of a task, has two major advantages: -a theoretical one: energy consumption of the brain is 10 times larger than one would expect on behalf of its weight, and only a small part of that consumption is devoted to increases associated with task performance. Thus to study the brain without looking at the ‘resting state’ situation would be to look at an iceberg without looking at the larger, underwater part. -secondly, it has an empirical advantage; in absence of a task, the whole brain can be studied, and not only that part of the brain that is involved in a task. As a matter of fact, in healthy controls it was shown that in rest several functionally related brain regions are communicating in multiple networks.

To investigate whether: Objectives To investigate whether: fMRI resting state networks are different in early MS patients (clinically isolated syndrome; CIS) these networks are still different in more advanced MS patients (relapsing remitting; RR) In this paper our aims were to investigate whether fMRI rs networks different in early MS patients as compared to controls, and whether that also accounts for more advanced MS patients.

Methods Subjects 41 healthy controls were included, as well as 14 patients with clinically isolated syndrome and 31 relapsing remitting patients. You will notice that the CIS patients are on average a bit younger, but that the gender ratio’s, handedness and IQ are more or less the same between the three groups.

FMRI in absence of task (200 volumes / 10 min.) Methods MRI (1.5T Siemens Sonata) FMRI in absence of task (200 volumes / 10 min.) TR 2.85 s, 3 mm isotropic voxels analyzed using independent component analysis1 voxel-wise analysis (GLM) using non-parametric permutation testing, controlling for multiple comparisons Structural damage: 3D-T1 (atrophy) DTI (white matter damage, voxel-wise) T2 & T1 lesion volumes 1 Beckmann et al. NeuroImage 2005 All subjects were imaged on a single MR system, namely a 1.5 T siemens sonata. Echo planar images were acquired for 10 minutes in absence of a task. These were then analyzed using mathematical software, which applies independent component analysis and find patterns in the data. Relevant patterns, or networks, were compared between the three groups. Additionally, we compared structural measures of damage: atrophy was automatically measured using software on 3D-T1 images; Fractional anisotropy differences of the white matter between groups were assessed voxel-wise; lastly T2 and T1 lesion volumes were measured.

In our subjects, 8 resting state networks of interest were identified Results In our subjects, 8 resting state networks of interest were identified In 6 of these 8 networks, increased synchronization in CIS patients was found Visual Audit & Lang DMN Motor & sens func >control >RR >control Executive func Ventr & dors attention >control We found 8 relevant networks in our subjects; these have all been consistently found in previous healthy controls studies. In six of these 8 networks CIS patients showed an increased communication within the network compared to the other 2 groups; 4 of which compared to controls, 3 of which compared to RR patients. We did not find significant differences in RR patients compared to controls. >RR Working mem R Working mem L >RR >RR

Synchronization value (Z-score) Example Z=10.0 Executive function CIS > Controls TFCE Z=3 p<0.01 Z=-3.0 Synchronization value (Z-score) Disease type Z=-10.0 For one network the results in detail; on the upper left the network. CIS patients showed higher communication or synchronization in the left medial prefrontal cortex shown on the right. p<0.05

Fractional Anisotropy in RR no sign. FA in CIS compared to controls Results No differences of synchronization were found between RR patients and controls Structural damage: Fractional Anisotropy in RR no sign. FA in CIS compared to controls atrophy in RR but not in CIS Controls CIS RR mean SD Norm. Brain Volume (L) 1.63 0.06 0.07 1.58 0.08 T2 lesion volume (mL) - 1.0 2.1 3.5 4.9 T1 black hole volume (mL) 0.5 1.2 1.5 2.8 We did find structural damage in RR patients, with decrease FA, and decreased normal brain volume. Beside focal lesions, no significant damage was measured in CIS patients.

Conclusion ↑ synchronization in several resting state networks in early MS patients (CIS) In more advanced patients (RR) with ↑ brain damage this increased synchronization dissappears Thus we conclude that there is increased synchronization in several resting state networks in early MS patients. It seems that in more advanced patients with increasing damage the increases in synchrozation disappear.

What factors are responsible for resting state differences? Discussion What factors are responsible for resting state differences? -between individual patients? -between disease types? Longitudinal studies are necessary Relation between functional MRI at rest and clinical function What is the effect of pharmacotherapy on reorganization of resting state networks? Rocca et al. Neurology 2010  Found reduced connectivity of the DMN in secondary progressive patients CIS Low structural damage No disability High functional reorganization Early RRMS Increasing structural damage Beginning disability Maximum functional reorganization Late RRMS / SPMS High structural damage Increasing disability Failing functional reorganization Schoonheim et al. Neurology 2010 The question remains what factors drive these differences between disease types, and also between individual patients. Recently, the Milan MS research group found a reduced connectivity in one of the rest networks, the default mode network. One could come up with a model, in which early patients have little damage, no disability. With increasing damage, disability may still be relatively limited because of increasing finctional reorganization. When damage accumulates, reorganization fails and clinical disability increases. More research into this area is necessary.

Thank you for your attention!