European Journal of Radiology 84 (2015) 703–708

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Altered thalamic functional connectivity in multiple sclerosis Yaou Liu a , Peipeng Liang a , Yunyun Duan a , Jing Huang a , Zhuoqiong Ren a , Xiuqin Jia a , Huiqing Dong b , Jing Ye b , Fu-Dong Shi c , Helmut Butzkueven d , Kuncheng Li a,∗ a

Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China Department of Neurology and Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin 300052, PR China d Department of Medicine, University of Melbourne, Parkville 3010, Australia b c

a r t i c l e

i n f o

Article history: Received 16 May 2014 Received in revised form 13 November 2014 Accepted 1 January 2015 Keywords: Multiple sclerosis Resting-state functional MRI Functional connectivity Thalamus Functional impairment Brain plasticity

a b s t r a c t Objective: To compare thalamic functional connectivity (FC) in patients with multiple sclerosis (MS) and healthy controls (HC), and correlate these connectivity measures with other MRI and clinical variables. Methods: We employed resting-state functional MRI (fMRI) to examine changes in thalamic connectivity by comparing thirty-five patients with MS and 35 age- and sex-matched HC. Thalamic FC was investigated by correlating low frequency fMRI signal fluctuations in thalamic voxels with voxels in all other brain regions. Additionally thalamic volume fraction (TF), T2 lesion volume (T2LV), EDSS and disease duration were recorded and correlated with the FC changes. Results: MS patients were found to have a significantly lower TF than HC in bilateral thalami. Compared to HC, the MS group showed significantly decreased FC between thalamus and several brain regions including right middle frontal and parahippocampal gyri, and the left inferior parietal lobule. Increased intra- and inter-thalamic FC was observed in the MS group compared to HC. These FC alterations were not correlated with T2LV, thalamic volume or lesions. In the MS group, however, there was a negative correlation between disease duration and inter-thalamic connectivity (r = −0.59, p < 0.001). Conclusion: We demonstrated decreased FC between thalamus and several cortical regions, while increased intra- and inter-thalamic connectivity in MS patients. These complex functional changes reflect impairments and/or adaptations that are independent of T2LV, thalamic volume or presence of thalamic lesions. The negative correlation between disease duration and inter-thalamic connectivity could indicate an adaptive role of thalamus that is gradually lost with increasing disease duration. © 2015 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Multiple sclerosis (MS) is an inflammatory demyelinating disorder of the central nervous system (CNS). It has been traditionally recognized as predominantly involving the white matter (WM). However, gray matter, including deep gray matter, damage is now known to be prevalent in MS. This gray matter injury, caused by widespread axonal and neuronal degeneration, is thought to contribute substantially to MS disability progression [1–3]. The thalamus, a key part of the deep gray matter, has extensive afferent and efferent connections with spinal afferents, the midbrain and the cerebral cortex. It is involved in motor planning, sensory information processing and many cognitive functions [4,5]. Numerous previous studies have demonstrated damage to

∗ Corresponding author. Tel.: +86 13911099059; fax: +86 10 83198376. E-mail address: [email protected] (K. Li). http://dx.doi.org/10.1016/j.ejrad.2015.01.001 0720-048X/© 2015 Elsevier Ireland Ltd. All rights reserved.

the thalamus in MS, such as decreased neuronal integrity, loss of neurons and macroscopic atrophy [6], and MRI abnormalities including T2 hypointensity [7], hypometabolism [8], decreased NAA [9] and increased diffusivity [10]. Furthermore, in several task-specific functional MRI studies, abnormal activation of the thalamus had been widely reported in patients with CIS and MS [11–15]. Resting-state fMRI, as a relatively new branch of functional imaging, reflects baseline neural network connectivity in the “unattended” state, and assesses between-voxel correlations in spontaneous blood oxygen level dependent (BOLD) fluctuations. Functional connectivity (FC) changes in MS have been observed by resting-state fMRI in brain network or regions such as brain default mode network (DMN), the motor network, the hippocampus and the thalamus [16–19]. For thalamic-cortical connectivity, discordant results were reported in different studies [18,19]. In this study, we investigated thalamic FC between thalamus and other brain regions by resting-state fMRI in patients with MS and healthy

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Y. Liu et al. / European Journal of Radiology 84 (2015) 703–708

Table 1 Descriptive data of the study groups.

Number of subjects Mean age (range) [years] Sex (M/F) Median EDSS (range) Median disease duration (range) [months] Median T2 lesion load (range) [mm3 ]

2.3. Thalamic and white matter lesion volume measurement RRMS

HC

35 38.1 (18–58) 11/24 2.5 (1.0–6.0) 43.7 (6–204)

35 35.6 (18–54) 11/24 – –

6225 (78–25481)



RRMS: relapsing–remitting multiple sclerosis; HC: healthy controls; EDSS: expanded disability status scale. See text for further details.

controls (HC), and correlated the FC changes with other MRI and clinical variables. 2. Materials and methods 2.1. Participants We studied thirty-five patients with relapsing-remitting multiple sclerosis [20,21] (11 males, 24 females; mean age 38.1, SD 11.9). All subjects were assessed clinically by a single experienced neurologist (J.Y), who was unaware of the MRI results. The main demographic and clinical characteristics of the patients studied are reported in Table 1. None of the participating patients had been treated with MS-specific medications (e.g., interferon-beta or immunosuppressive therapies) within three months of the MR images being obtained. We choose 35 age- and sex-matched HC (mean age 35.6, SD 10.5) with no previous history of neurological disease and with normal findings on neurological examination. The subjects were all right-handed as measured by the Edinburgh Inventory [22]. The institutional review board of Xuanwu Hospital approved the study, and written informed consent was obtained from each participant. 2.2. MRI acquisition Imaging was performed on a 1.5 T Siemens Sonata scanner in the Radiology Department, Xuanwu Hospital, Capital Medical University. A standard head coil with foam padding was used to restrict head motion. All the routine axial slices were positioned parallel to a line that joins the most inferoanterior and inferoposterior parts of the corpus callosum, with an identical field of view (240 mm × 210 mm), matrix size (256 × 224), number of sections (30), section thickness (4 mm), and intersection gap (0.4 mm): (a) T2-weighted turbo spin echo (repetition time [TR] = 5500 ms, echo time [TE] = 94 ms, number of signals acquired = 3, echo train length = 11), (b) T1-weighted spin echo (TR/TE = 650/6, number of signals acquired = 3), (c) fluid-attenuated inversion recovery (FLAIR) (TR/TE = 8500/150, inversion time [TI] = 2200 ms, number of signals acquired = 3, echo train length = 8). Sagittal three-dimensional (3D) Volumetric T1-weighted magnetization-prepared rapid acquisition gradient echo (MPRAGE) (TR/TE = 1970/3.9 ms, TI = 1100 ms, flip angle = 15◦ , FOV = 219 mm × 250 mm, matrix size = 256 × 256, slice thickness = 1.7 mm, voxel dimensions = 0.5 mm × 0.5 mm × 1.7 mm) images were also obtained. During resting-state fMRI, subjects were instructed to keep their eyes closed, to remain motionless, and to not to think of anything in particular. We used a gradient-echo echo-planar sequence sensitive to BOLD (Blood Oxygen Level Dependent) contrast to acquire functional images (TR = 2000 ms, TE = 60 ms, flip angle = 90◦ ). Twenty axial slices were collected with 5 mm thickness, and a 2 mm gap. Resolution was 1.875 mm × 1.875 mm in-plane.

All visible lesions were identified from FLAIR and T2 images and manually extracted from T2-weighted scans using MRIcro software (http://www.cabiatl.com/mricro) including lesions in the thalamus. Next, the T2 lesion volume of each patient was calculated (shown in Table 1). The whole thalamus was traced and saved as a mask from the coronal three-dimensional MPRAGE images by an experienced radiologist (Y.D, with 8 years experience), blinded to clinical information. The thalamic boundaries were determined manually using MRIcro, and left and right thalamus was saved as masks for further FC analyses. Raw thalamic volumes were normalized within each subject as a ratio to the intracranial volume. The resulting normalized thalamic volume was referred to as the thalamic fraction (TF). To test the reproducibility of our findings, twenty randomly chosen subjects (10 patients with MS and 10 HC) had thalamic segmentation repeated by the same observer (Y.D) one month later and by another experienced observer (Y.L, with 7 years experience in neuroradiology) to determine intra- and inter-rater reliability. 2.4. Resting-state functional MRI data analysis 2.4.1. Image preprocessing All analyses were conducted using a statistical parametric mapping software package (SPM5, http://www.fil.ion.ucl.ac.uk/spm). The first 10 volumes of the functional images were discarded to reach signal equilibrium and allow participants adaptation to the scanning noise. The remaining 229 fMRI images were first corrected for within-scan acquisition time differences between slices and then realigned to the first volume to correct for interscan head motions. No participant had head motion of more than 1.5 mm maximum displacement in any of the x, y, or z directions, or 1.5◦ of any angular motion throughout the course of scan. Next, we spatially normalized the realigned images to the standard echo-planar imaging template and resampled them to 3 mm × 3 mm × 3 mm. Subsequently, the functional images were spatially smoothed with a Gaussian kernel of 4 mm × 4 mm × 4 mm FWHW to decrease spatial noise. Following this, temporal filtering (0.01 Hz 0.11). 4. Discussion The thalamus is an area of great current interest in MS research [24], as both structural and functional thalamic alterations are reported by numerous pathological and imaging studies [6–11]. However to our knowledge, very few previous studies systematically examined thalamic FC in MS by resting-state fMRI together with thalamic volume measurement [18]. We confirmed MS associated thalamic atrophy and demonstrated decreased thalamic FC with several cortical regions. Furthermore, a marked increase in

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Fig. 3. Brain regions showing connectivity changes with the right thalamus in MS patients. (a) Decreased connectivity in right parahippocampal gyrus, left inferior parietal lobule; and (b) increased connectivity in bilateral thalami. The color scale represents t values.

both intra and inter-thalamic connectivity was identified in MS. These FC changes in thalamus were not associated with thalamic volume loss, presence of thalamic lesions, or cerebral T2 lesion volume. The IPL is a key hub among the default mode network (DMN), a network consisting of functionally linked PCC/precuneus, and medial frontal regions [25,26]. Connectivity of the DMN plays an important role in human cognition, including the integration of cognitive and emotional processing, and monitoring the world around us [27]. The parahippocampal gyrus is important for memory encoding and retrieval, an essential part of cognition, while the

Table 3 Regions showing decreased and increased connectivity to right thalamus in MS patients (p < 0.05 corrected). Brain regions

TAL Coordinates x

y

BA

Cluster size

T-score

35

33

40

28

3.55 2.92 1.83 3.02 2.84

z

HC vs. MS Rt. parahippocampal gyrus Lt. inferior parietal lobule

24 24 18 −59 −56

−21 −9 −6 −28 −21

−15 −19 −7 26 40

−12 −18 −9 12 3 6

−8 −17 −29 −32 −5 −11

6 4 10 7 9 3

MS vs. HC Lt. thalamus

Rt. thalamus

124

63

3.27 3.11 2.78 3.88 3.60 2.80

Y. Liu et al. / European Journal of Radiology 84 (2015) 703–708

Fig. 4. The negative correlation between disease duration and inter-thalamic functional connectivity (r = −0.59, p < 0.001).

middle frontal gyrus has been widely reported to be involved in the processing of higher information, mental set maintenance and response to task difficulty [28]. In the current study, the decreased connectivity between and the IPL, parahippocampal, middle frontal gyri and the thalamus in MS could be a substrate for early cognitive change in MS patients, and this hypothesis could warrant further examination with correlative and serial studies combining resting-state connectivity measures with formal cognitive testing. A previous study [18] demonstrated increased thalamic-cortical connectivity in hippocampal and dorsal–frontal components of the network and decreased connectivity in the cerebellum, cingulum and prefrontal cortex components in MS. The discordance of the findings with our current study may due to different clinical characteristics of the patients (such as EDSS and disease duration) or different analysis methods. A multi-center study with large sample and standardized MRI analysis method is warranted to confirm the results. The structural basis of the decreased FC between thalamus and several cortical regions is probably demyelination and neurodegeneration (structural disconnection) reported by a MRIpathology study [29]. Stein and colleagues [4] assessed FC of the thalamus in six healthy volunteers and found evidence of intra and inter-thalamic connectivity. In our study, evidence of intra- and inter-thalamic FC was also present in HC, and this was markedly increased in MS patients, which is consistent with a previous study using a resting-state functional homotopic method and showing increasing FC between bilateral thalami [19]. The thalamus, a central hub in the brain, functions as a relay of sensory and motor information to and from the cerebral cortex, and has documented key roles in general arousal states including the regulation of consciousness, sleep and attention. Increased activation of the thalamus had been widely reported in patients with CIS and MS in a whole range of task-specific functional MRI studies during simple motor tasks [30], visual tasks [31] attention and working memory tasks and planning tasks [13]. This increased activation in multiple task-related fMRI studies, the previously reported increase in overall thalamic resting-state activity [32] and our demonstration of enhanced resting-state intra- and inter-thalamic connectivity, could all reflect the same disease-associated functional change. One possibility is that this phenomenon reflects a role for the thalamus as a coordinator or circuit element for brain plasticity and functional remapping in MS, compensating for the relative loss of cortex and gradual loss of afferent and efferent cortical connections. An alternate explanation for our finding of increased resting-state thalamic connectivity is that this is a functionally irrelevant epiphenomenon, perhaps secondary to functional disconnection of the thalami from afferents or efferents (the latter also demonstrated in our study). The negative correlation we identified between disease duration and inter-thalamic connectivity would support an adaptive

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or compensatory function (itself gradually lost with increasing MS duration), as one would expect an epiphenomenon or directly pathologically driven change in MS to worsen and not reverse with increasing damage over time. A longitudinal study is warrant to corroborate these findings. The absence of correlation between thalamic volume loss and FC changes in the current study could be viewed as contradicting a recent study [33] showing that lower alpha2 band resting-state FC using magnetoencephalography (MEG) in the visual network was correlated with thalamic atrophy. However, MEG resting-state only acquires data from cortical regions, so that thalamic resting-state connectivity measures cannot be acquired. Our results indicate that the FC changes directly involving the thalami are independent of thalamic volume changes, thalamic lesion presence or cerebral T2LV, supporting the hypothesis that the connectivity alterations within the thalami are not markers of increasing disease burden, and more likely represent an active adaptive phenomenon. There are several limitations in our study. First, formal neuropsychological tests were not performed in this study, which prevented us from correlating cognitive test scores with our fMRI results. Most importantly, prospective studies would be required to understand the functional significance of altered thalamic connectivity in early relapsing–remitting MS. Secondly, the current study is a cross-sectional study based on 1.5 T MRI data, and 3 T restingstate fMRI acquisition would provide a higher signal-to-noise ratio, but would be unlikely to alter our significant results. A longitudinal study with 3 T MRI data is warranted to confirm the current findings and investigate the dynamic changes of the thalamic-cortical FC in MS. Thirdly, at the technical level, resting-state fMRI is prone to respiratory and cardiac cycle artifacts, enhanced by slow sampling rates. (e.g., TR = 2 s in this study). However, these effects would have to apply differentially to the MS patients and healthy controls to affect the results, which is unlikely [34].

5. Conclusion In patients with relapsing–remitting MS, we demonstrate decreased resting-state functional FC between the thalamus and several cortical regions, and increased intra- and inter-thalamic connectivity. This increased resting-state FC between thalami is independent of T2LV, thalamic volume or thalamic lesions, but is attenuated by increasing disease duration, suggesting an adaptive role of the thalamus that is gradually lost as disease progresses.

Conflict of interest None.

Author’s contribution Kuncheng Li, Yaou Liu: guarantor of integrity of the entire study Yaou Liu, Peipeng Liang: study concepts Yaou Liu, Peipeng Liang: study design Yaou Liu, Peipeng Liang;Yunyun Duan: definition of intellectual content Yaou Liu, Peipeng Liang: literature research Huiqing Dong, Jing Ye, Yunyun Duan: clinical studies Jing Ye, Yaou Liu, Yunyun Duan: experimental studies Yunyun Duan, Yaou Liu, Jing Huang, Zhuoqiong Ren: data acquisition Peipeng Liang, Xiuqin Jia, Yunyun Duan: data analysis Peipeng Liang, Yaou Liu: statistical analysis Yaou Liu, Peipeng Liang: manuscript preparation Yaou Liu, Helmut Butzkueven, Fu-dong Shi: manuscript editing

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Fu-dong Shi, Helmut Butzkueven, Kuncheng Li: manuscript review Disclosure Dr Yaou Liu, Dr Peipeng Liang, Dr Yunyun Duan, Dr Jing Huang, Dr Zhuoqiong Ren, Dr Huiqing Dong, Dr Jing Ye, Professor Fu-dong Shi, Dr Helmut Butzkueven, and Professor Kuncheng Li report no disclosures. Acknowledgements This work was supported by the National Natural Science Foundation of China (Nos. 81101038, 30930029), Beijing Natural Science Foundation (No. 7133244) and Beijing Nova Program (No. xx2013045). References [1] Pirko I, Lucchinetti CF, Sriram S, Bakshi R. Gray matter involvement in multiple sclerosis. Neurology 2007;68:634–42. [2] Geurts JJ, Barkhof F. Grey matter pathology in multiple sclerosis. Lancet Neurol 2008;7:841–51. [3] Zivadinov R, Minagar A. Evidence for gray matter pathology in multiple sclerosis: a neuroimaging approach. J Neurol Sci 2009;282:1–4. [4] Stein T, Moritz C, Quigley M, Cordes D, Haughton V, Meyerand E. Functional connectivity in the thalamus and hippocampus studied with functional MR imaging. AJNR Am J Neuroradiol 2000;21:1397–401. [5] Aggleton JP, Brown MW. Episodic memory, amnesia, and the hippocampalanterior thalamic axis. Behav Brain Sci 1999;22:425–44, discussion 44–89. [6] Cifelli A, Arridge M, Jezzard P, Esiri MM, Palace J, Matthews PM. Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 2002;52:650–3. [7] Bermel RA, Puli SR, Rudick RA, Weinstock-Guttman B, Fisher E, Munschauer 3rd FE, et al. Prediction of longitudinal brain atrophy in multiple sclerosis by gray matter magnetic resonance imaging T2 hypointensity. Arch Neurol 2005;62:1371–6. [8] Blinkenberg M, Rune K, Jensen CV, Ravnborg M, Kyllingsbaek S, Holm S, et al. Cortical cerebral metabolism correlates with MRI lesion load and cognitive dysfunction in MS. Neurology 2000;54:558–64. [9] Wylezinska M, Cifelli A, Jezzard P, Palace J, Alecci M, Matthews PM. Thalamic neurodegeneration in relapsing–remitting multiple sclerosis. Neurology 2003;60:1949–54. [10] Fabiano AJ, Sharma J, Weinstock-Guttman B, Munschauer 3rd FE, Benedict RH, Zivadinov R, et al. Thalamic involvement in multiple sclerosis: a diffusionweighted magnetic resonance imaging study. J Neuroimaging 2003;13: 307–14. [11] Rocca MA, Gavazzi C, Mezzapesa DM, Falini A, Colombo B, Mascalchi M, et al. A functional magnetic resonance imaging study of patients with secondary progressive multiple sclerosis. Neuroimage 2003;19:1770–7. [12] Rocca MA, Matthews PM, Caputo D, Ghezzi A, Falini A, Scotti G, et al. Evidence for widespread movement-associated functional MRI changes in patients with PPMS. Neurology 2002;58:866–72. [13] Wishart HA, Saykin AJ, McDonald BC, Mamourian AC, Flashman LA, Schuschu KR, et al. Brain activation patterns associated with working memory in relapsing–remitting MS. Neurology 2004;62:234–8.

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Altered thalamic functional connectivity in multiple sclerosis.

To compare thalamic functional connectivity (FC) in patients with multiple sclerosis (MS) and healthy controls (HC), and correlate these connectivity ...
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