Brain Iron Deficiency in Restless Legs Syndrome Measured by Quantitative Susceptibility and its Relation to Clinical Features
Xu Li1,2, Hongjun Liu1,2, Richard P Allen3, Christopher J Earley3, Richard A.E. Edden1,2, Peter B Barker1,2, Tiana Cruz3, and Peter C.M. van Zijl1,2

1F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 2Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 3Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States

Synopsis

Possible brain iron deficiency was assessed using quantitative susceptibility mapping at 7T in restless legs syndrome (RLS) and analyzed with clinical measurements including IRLS severity score, serum iron, serum ferritin and periodic limb movement during sleep (PLMS). Using magnetic susceptibility as a brain iron index and compared to control group, significantly decreased iron was found in RLS patients in dentate nuclei and thalamus, and in substantia nigra in a subset of RLS patients with severe clinical symptoms with PLMS larger than 100 times per hour. Significant correlation between PLMS and brain iron was only found in substantia nigra in RLS.

Introduction

Restless legs syndrome (RLS) is a neurological disorder with a prevalence of 5-10% of the population. It is characterized by unpleasant sensations mainly in the legs and an urge to move during sitting or resting in the later part of the day1. Previous studies have associated RLS to the abnormal dopaminergic function in the central nervous system (CNS) and dysfunction in iron metabolism2-5. In vivo measures of tissue iron using relaxometry or MR phase have suggested a general trend of iron decrease in the brain especially in the substantia nigra (SN), yet many inconsistencies still exist in the reported iron change of different brain regions in different RLS phenotypes5,6. The present study thus aims to assess possible brain iron deficiency in RLS using quantitative susceptibility mapping (QSM)7-10 and test possible correlations between tissue magnetic susceptibility and RLS clinical features.

Methods

Age matched subjects (30 controls with Mean ± SD ages of 57.9±8.5 years, 40 primary RLS patients off all RLS medications for at least 12 days with ages of 58.2±9.4 years and IRLS severity scores Mean ± SD 25.3 ± 7.1) were scanned at 7T (Philips Healthcare) using a 32-channel Nova medical receiver head coil using 3D GRE sequence, with either 1mm isotropic resolution, TR/TE1/ΔTE=45/2/2 ms, 9 echoes, flip angle of 9°, bandwidth 1530 Hz/px (n=2), or 0.8 mm isotropic resolution, with TR/TE= 20/12 ms, flip angle 10°, bandwidth 169 Hz/px (n=68). For all the scans, MR phase data at TE=12 ms were used to generate quantitative susceptibility maps. Phase data were unwrapped with Laplacian-based phase unwrapping and the background field was removed using the V-SHARP method11-12. QSM images were then generated using the LSQR method12. The QSM image was referenced with respect to the CSF in the lateral ventricle. Regions of interest (ROI) were selected automatically using a QSM based atlas10 and corrected by a neuroradiologist if necessary (HL). In addition, a fixed shape ROI (3x3 square) was selected in the center of the SN in order to test the influence of different ways of ROI selection6 (Fig. 1). Group differences between control and RLS groups were tested using ANOVA controlling either the ROI volume or subject age. Pearson partial correlations were obtained between tissue magnetic susceptibility and RLS clinical measurements including IRLS severity score, serum iron, serum ferritin and periodic limb movement during sleep (PLMS) on the 2nd of two-consecutive-nights sleep studies controlling for ROI volume (for full ROI) and age.

Results

RLS compared to controls showed significantly lower susceptibility in the dentate nucleus (DN) (p<0.01) and in the thalamus (p<0.05). There were no significant differences in the serum ferritin or serum iron in control versus RLS group. In most brain regions, no significant correlations were found between brain susceptibility and serum iron or serum ferritin except some weak correlations in caudate nucleus (CN) and putamen (PUT) (Table 1). Brain tissue magnetic susceptibility does not correlate with IRLS severity score, but a significant negative correlation was found between susceptibility in SN and PLMS measures. This finding persists with both automatically selected ROI and fixed-shape ROI (Fig. 2). In addition, for a subgroup of RLS patients (n=11) with severe clinical feature of PLMS/hr ≥ 100, a significant decrease of SN susceptibility was noticed as compared to control group (p<0.05 with automated ROI and p<0.01 with fixed shape ROI).

Discussion

As the iron homeostasis inside the CNS is regulated by multiple mechanisms, the lack of strong correlations between the measured tissue susceptibility and serum iron or serum ferritin is not fully unexpected. As compared to previous studies4-6, our current results suggest possible iron deficiency also in the DN and thalamus in RLS. While previous RLS studies have indicated that SN is the main region affected by iron deficiency in RLS4, the current study seems to suggest that the iron deficiency in SN happens mostly in those RLS patients with severe PLMS symptoms. The strong negative correlation between tissue susceptibility and PLMS may also indicate the important role of iron in the pathophysiology driving the PLMS motor sign of RLS.

Conclusion

The current study suggests lower brain iron in DN and thalamus in primary RLS and in SN in RLS patients with severe PLMS, though the serum iron and serum ferritin levels do not differ significantly. The iron status in SN as measured by magnetic susceptibility has been found to significantly correlate with PLMS, which is the motor sign of RLS.

Acknowledgements

Funding: R01 NS075184 and P41 EB015909

References

[1] Allen and Earley, J. Clin. Neurophysiol. 2001, 18(2):128-47.

[2] Earley et al. Neurology, 2000, 54(8):1698-700.

[3] Allen et al. Neurology, 2001; 56(2):263-5.

[4] Earley et al. Sleep Med. 2006, 7:458-61.

[5] Rizzo et al. Mov Disord. 2013, 28(13), 1886-90.

[6] Moon et al. Med Devices. 2015; 30(8):341-50.

[7] Wang and Liu, MRM, 2015, 73(1):82-101.

[8] Liu et al, JMRI, 2015, 42(1):23-41.

[9] Langkammer et al. NeuroImage, 2012, 62:1593-9.

[10] Lim et al. NeuroImage, 2013, 82:449-69.

[11] Wu et al. MRM, 2012, 67(1):137-47.

[12] Li et al. NeuroImage, 2011, 55(4):1645-56.

Figures

Fig. 1: Example slice of selected ROI in SN using (a) atlas based automated segmentation (b) manually fixed-shape tracing overlaid on QSM image of a normal control subject.

Fig. 2: Correlation between PLMS and magnetic susceptibility in SN in RLS patients. A fixed-shape ROI at the center of SN was used.

Table 1: Pearson correlation coefficient (r) between tissue magnetic susceptibility in different brain regions and serum iron, serum ferritin, IRLS severity scores and PLMS. a: tested in all subjects. b: tested in RLS patients. *: p<0.05, **: p<0.01, ***: p<0.001. SN: substantia nigra, RN: red nucleus, DN: dentate nucleus, CN: caudate nucleus, PUT: putamen, GP: globus pallidus, Thal: thalamus, Pul: pulvinar, STN: subthalamic nuclei, SN(fs): substantia nigra with fixed-shape ROI



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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