Elsevier

NeuroImage

Volume 59, Issue 1, 2 January 2012, Pages 331-339
NeuroImage

Abnormal subcortical deep-gray matter susceptibility-weighted imaging filtered phase measurements in patients with multiple sclerosis: A case-control study

https://doi.org/10.1016/j.neuroimage.2011.07.045Get rights and content

Abstract

Objective

To investigate abnormal phase on susceptibility-weighted imaging (SWI)-filtered phase images indicative of iron content, in subcortical deep-gray matter (SDGM) of multiple sclerosis (MS) patients and healthy controls (HC), and to explore its relationship with MRI outcomes.

Methods

169 relapsing–remitting (RR) and 64 secondary-progressive (SP) MS patients, and 126 age- and sex-matched HC were imaged on a 3 T scanner. Mean phase of the abnormal phase tissue (MP-APT), normal phase tissue volume (NPTV) and normalized volume were determined for total SDGM, caudate, putamen, globus pallidus, thalamus, pulvinar nucleus of thalamus (PVN), hippocampus, amygdala, nucleus accumbens, red nucleus and substantia nigra. 63 HC were used for establishment of normal reference phase values, while additional 63 HC were used for blinded comparisons with MS patients.

Results

Increased MP-APT, decreased normalized volume and decreased NPTV were detected in total SDGM, caudate, putamen, globus pallidus, thalamus and PVN in MS patients compared to HC (p < .0004). MS patients also showed decreased volume in hippocampus (< .0001) and decreased NPTV in the hippocampus, amygdala and accumbens (< .0004). SPMS patients had increased MP-APT, decreased volume and decreased NPTV in total SDGM, caudate and amygdala compared to RRMS (p < .005), while individual measure differences were also detected in putamen, thalamus, hippocampus and accumbens (p < .006). RRMS patients showed a significant relationship between increased MP-APT and increased lesion burden and more advanced brain atrophy (p < .004).

Conclusions

Abnormal phase, indicative of higher iron content was significantly increased in MS patients compared to HC, and was related to more severe lesion burden and brain atrophy.

Highlights

► We investigate iron content on SWI in 233 MS patients and 126 controls. ► Increased iron content is detected in MS patients compared to controls. ► Increased iron content is related to lesion burden and brain atrophy in MS. ► SWI is a powerful tool for evaluating the degree of iron deposition in MS.

Introduction

Increased iron deposition has been described previously in multiple sclerosis (MS) (Adams, 1988, Bakshi et al., 2000, Craelius et al., 1982, LeVine and Chakrabarty, 2004, LeVine et al., 1999, Mehindate et al., 2001, Valberg et al., 1989). However, the precise role of increased iron is not clear (Grimaud et al., 1995). Previous imaging approaches designed to study the presence of abnormal iron deposits in brain parenchyma have focused on T2- and T2*-weighted imaging (WI). Using these techniques, investigators have shown correlations of increases in putative iron content with clinical progression (Neema et al., 2009a, Tjoa et al., 2005), cognitive impairment (Brass et al., 2006) and brain atrophy (Bakshi et al., 2001, Bakshi et al., 2002, Bermel et al., 2005, Khalil et al., 2009). Nonetheless, direct interpretation of these results has suffered from the non-specificity of T2-based approaches, which are highly sensitive to a range of tissue changes other than iron (Haacke et al., 2004, Neema et al., 2007).

More recently, greater attention has been paid to the phase component of MRI acquisition (Haacke et al., 2009b). The phase values of individual voxels can in fact provide more information about the presence of substances with different magnetic properties than normal tissue (Haacke et al., 2007). It is known that paramagnetic substances such as deoxyhemoglobin and ferritin change the local magnetic field and thus influence the frequency or “phase” of proton spin isochromats. Tissues differ in their susceptibility to phase effects, making possible a form of contrast enhancement called susceptibility-weighted imaging (SWI). As the constituents of iron markedly influence magnetic fields, SWI provides a metric of the density of iron in vertebral tissue (Hopp et al., 2010).

Despite this advantage, a number of difficulties are encountered when working with phase-based imaging techniques. Blood flow can cause extensive artifacts and phase changes that are not due to true tissue susceptibility differences. In addition, patient position and orientation in the scanner can affect observed phase values by changing the relative dipole orientation. Finally, and perhaps most importantly, the presence of large non-uniformities throughout the imaging volume can dwarf the more biologically interesting local phase changes both in extent and in scale. The SWI-filtered approach (Haacke et al., 2004, Haacke et al., 2009b) combats this problem by employing a complex-space high-pass filter in order to retain only localized phase shifts — the type caused by iron deposition (Hopp et al., 2010).

The SWI-filtered/phase imaging approaches have been recently used in MS research to understand more specifically the characteristics of iron deposition (Eissa et al., 2009, Ge et al., 2009, Haacke et al., 2009a, Haacke et al., 2010a, Hammond et al., 2008b, Zivadinov et al., 2010). However, the use of those for iron content measurement is still in its infancy, and more studies need to be conducted to understand the relationship between SWI-filtered/phase images and other conventional and non-conventional MRI and clinical outcomes in patients with MS. Furthermore, current approaches to SWI-filtered/phase image-based tissue quantification are still relatively time-consuming and labor-intensive, and their scan–rescan reproducibility is not well understood on a structure-by-structure basis.

Therefore, our goal in this study was twofold. First, we sought to create a reliable, reproducible, and highly-automated framework for structure-specific analysis of SWI-filtered phase images (and, therefore, indirectly of iron content). Second, we aimed to apply this technique to a large group of MS patients and healthy controls to better understand subcortical DGM (SDGM) abnormal phase changes, indicative of increased iron in MS, as well as to investigate their relationship with other MRI techniques.

Section snippets

Participants

We studied 233 consecutively enrolled MS patients [169 relapsing–remitting (RR), 64 secondary-progressive (SP)], and 126 age- and sex-matched healthy controls. The study was planned on 2:1 randomization basis (2 MS patients enrolled for 1 healthy control). The first 63 enrolled healthy control subjects were used for standardization of the normal reference phase values (healthy control group 1) and the other 63 healthy controls were used for comparisons with MS patients (healthy control group

Demographic and clinical characteristics

Table 1 shows demographic, clinical and MRI characteristics of MS patients and healthy control 1 and 2 groups. The mean age of the MS patients was 46.6 years (SD 10.6), mean disease duration 14.1 years (SD 9.8) and median EDSS 3.0. One hundred sixty-seven (71.7%) MS patients were females. Healthy controls were age- and sex-matched to MS patients. There were no age, sex or MRI differences between subjects used for establishing reference phase values (healthy control group 1) and those used for

Discussion

MS patients showed increased abnormal phase values, decreased normalized and normal phase SDGM volumes compared to healthy controls. These results suggest that iron content measured on SWI-filtered phase images is significantly increased in MS patients compared to healthy controls in the majority of the SDGM regions that we studied. Increased abnormal phase values were associated with more advanced MRI lesion and brain atrophy outcomes in RR but not in the SPMS patients. These results suggest

Acknowledgments

We thank all study subjects for their participation. In particular, we thank Prof. Rohit Bakshi and Prof. E. Mark Haacke for critical review of the manuscript and thoughtful discussion. We thank Eve Salczynski for technical assistance in the preparation of the manuscript.

References (61)

  • X. Xu et al.

    Age, gender, and hemispheric differences in iron deposition in the human brain: an in vivo MRI study

    Neuroimage

    (2008)
  • C.W. Adams

    Perivascular iron deposition and other vascular damage in multiple sclerosis

    Br. Med. J.

    (1988)
  • D. Aquino et al.

    Age-related iron deposition in the basal ganglia: quantitative analysis in healthy subjects

    Radiology

    (2009)
  • B. Audoin et al.

    Atrophy mainly affects the limbic system and the deep grey matter at the first stage of multiple sclerosis

    J. Neurol. Neurosurg. Psychiatry

    (2010)
  • R. Bakshi et al.

    MRI T2 shortening (‘black T2’) in multiple sclerosis: frequency, location, and clinical correlation

    Neuroreport

    (2000)
  • R. Bakshi et al.

    T2 hypointensity in the deep gray matter of patients with multiple sclerosis: a quantitative magnetic resonance imaging study

    Arch. Neurol.

    (2002)
  • R.A. Bermel et al.

    Prediction of longitudinal brain atrophy in multiple sclerosis by gray matter magnetic resonance imaging T2 hypointensity

    Arch. Neurol.

    (2005)
  • S.D. Brass et al.

    Cognitive impairment is associated with subcortical magnetic resonance imaging grey matter T2 hypointensity in multiple sclerosis

    Mult. Scler.

    (2006)
  • A. Burgetova et al.

    Multiple sclerosis and the accumulation of iron in the basal ganglia: quantitative assessment of brain iron using MRI t(2) relaxometry

    Eur. Neurol.

    (2010)
  • A. Ceccarelli et al.

    T2 hypointensity in the deep gray matter of patients with benign multiple sclerosis

    Mult. Scler.

    (2009)
  • A. Ceccarelli et al.

    Deep gray matter T2 hypointensity is present in patients with clinically isolated syndromes suggestive of multiple sclerosis

    Mult. Scler.

    (2010)
  • A. Ceccarelli et al.

    Deep grey matter T2 hypo-intensity in patients with paediatric multiple sclerosis

    Mult. Scler.

    (2011)
  • A. Cifelli et al.

    Thalamic neurodegeneration in multiple sclerosis

    Ann. Neurol.

    (2002)
  • W. Craelius et al.

    Iron deposits surrounding multiple sclerosis plaques

    Arch. Pathol. Lab. Med.

    (1982)
  • L. de Rochefort et al.

    Quantitative MR susceptibility mapping using piece-wise constant regularized inversion of the magnetic field

    Magn. Reson. Med.

    (2008)
  • A. Deistung et al.

    Calculation of the magnetic susceptibility from susceptibility weighted phase images

  • A. Eissa et al.

    Detecting lesions in multiple sclerosis at 4.7 Tesla using phase susceptibility-weighting and T2-weighting

    J. Magn. Reson. Imaging

    (2009)
  • A.J. Fabiano et al.

    Thalamic involvement in multiple sclerosis: a diffusion-weighted magnetic resonance imaging study

    J. Neuroimaging

    (2003)
  • Y. Ge et al.

    Quantitative assessment of iron accumulation in the deep gray matter of multiple sclerosis by magnetic field correlation imaging

    Am. J. Neuroradiol.

    (2007)
  • Y. Ge et al.

    Diminished visibility of cerebral venous vasculature in multiple sclerosis by susceptibility-weighted imaging at 3.0 Tesla

    J. Magn. Reson. Imaging

    (2009)
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