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ORIGINAL ARTICLE
Year : 2014  |  Volume : 62  |  Issue : 4  |  Page : 362-366

Characterizing brain mineral deposition in patients with Wilson disease using susceptibility-weighted imaging


1 Department of Neurology, The East Area of the First Affiliated Hospital, Guangzhou, China
2 Department of Radiology, The East Area of the First Affiliated Hospital, Guangzhou, China
3 Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
4 Department of Reproductive Medical Sciences and Urology, Guangdong General Hospital, Guangdong Academy of Medical Science, Guangzhou, China

Date of Submission28-May-2014
Date of Decision01-Jun-2014
Date of Acceptance10-Aug-2014
Date of Web Publication19-Sep-2014

Correspondence Address:
Xiang-Xue Zhou
Department of Neurology, Sun Yat Sen University Number 183, East Road of Huangpu, Guangzhou, Guangdong
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0028-3886.141221

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 » Abstract 

Aims: The aim of this study was to evaluate the feasibility of characterizing the brain-mineral deposition in patients with Wilson disease (WD) using susceptibility-weighted imaging (SWI). Materials and Methods: The study enrolled 30 WD patients and 20 age-matched healthy controls. Neurological symptoms were scored using the modified Young Scale. The hepatic function indices, serum and urinary copper content, and serum iron content were determined. All study objects received the magnetic resonance imaging (MRI) and SWI test of the brain. The values of corrected phase (CP) were calculated on SWI. The relationship between CP values and the clinical status were evaluated. Results: The serum iron content of WD patients was higher than the normal. The CP values of substantia nigra, caudate nucleus, and globus pallidus of WD were lower than the normal values, while the CP value of substantia nigra was the lowest. No correlations were determined between the CP values and the iron and copper parameters. There was negative correlation between the scores of dysarthria and the CP values of the globus pallidus. There was negative correlation between the scores of tremor and the CP values of caudate nucleus. Some regions, which had high signals on T2-weighted image, had low signals on SWI. Conclusions: There might be abnormal iron metabolism in patients with WD. The decreased CP values might reflect a deposition of both copper and iron. SWI may be more sensitive than the ordinary MRI. The mineral deposition may contribute to the neural symptoms.


Keywords: Copper, iron susceptibility-weighted imaging, Wilson disease


How to cite this article:
Zhou XX, Qin HL, Li XH, Huang HW, Liang YY, Liang XL, Pu XY. Characterizing brain mineral deposition in patients with Wilson disease using susceptibility-weighted imaging. Neurol India 2014;62:362-6

How to cite this URL:
Zhou XX, Qin HL, Li XH, Huang HW, Liang YY, Liang XL, Pu XY. Characterizing brain mineral deposition in patients with Wilson disease using susceptibility-weighted imaging. Neurol India [serial online] 2014 [cited 2019 Aug 24];62:362-6. Available from: http://www.neurologyindia.com/text.asp?2014/62/4/362/141221



 » Introduction Top


Wilson disease (WD) is an autosomal recessive inherited disorder of copper metabolism and it is characterized by excessive copper deposition, especially in the liver and brain. The lesions generally appear as hyperintense signals on T2-weighted images and hypointense on T1-weighted images on brain MRI. [1],[2] Ceruloplasmin levels are usually low in patients with WD. Ceruloplasmin is a copper-containing plasma ferroxidase that plays an essential role in iron metabolism. [3] Therefore, low ceruloplasmin levels and reduced ferroxidase activity can lead to the storage of iron in WD. Iron in the brain has been proposed to play an important role in the pathophysiology of the neurodegenerative disease. Iron overload was also observed in patients with WD. [4] Recent studies showed that WD might be complicated by high iron concentrations in the basal ganglia of the brain. [5] However, there is still no effective way to assess the location and the concentration of iron and copper in the brain.

Susceptibility weighted imaging (SWI) is superior in its ability to demonstrate paramagnetic signals than conventional MRI. [6] SWI is an in vivo assessment of brain metal concentration. It is sensitive to detect metals especially iron and copper. Iron is a paramagnetic element that will strengthen the local magnetic field. SWI can help to improve understanding of the pathophysiology of mineral depositions in patients with WD. However, there are few results regarding use of SWI in diagnosis WD patients. The characteristic of metal deposition in SWI and the correlation between metal concentration and clinical status of patients with WD were also need to be further determined. The purpose of this study is to estimate brain metal deposition using SWI, and to investigate the correlations between brain metal concentration and clinical status of WD.


 » Materials and Methods Top


Thirty WD patients (18 males and 12 females; mean age, 23 ± 9 years) from the First Affiliated Hospital, Sun Yat-Sen University between July 2007 and October 2013 were enrolled in this study. The diagnosis in each patient was decided by a combination of clinical symptoms and laboratory tests. The clinical diagnosis included a decreased serum ceruloplasmin concentration, low serum copper concentration, an elevated 24-h urinary copper excretion, the presence of Kayser-Fleischer (K-F) ring. Twenty age-matched healthy controls were also recruited from the hospital. Informed consent was obtained from all participants prior to enrollment.

Patients were categorized as hepatic type when presenting with signs of liver disease without any neural symptoms or cerebral type when presenting mainly with psychiatric and/or neural symptoms. The severity of neural symptoms was assessed using the modified Young Scale. [7] The scale consisted of dysarthria, throat dysmyotonia, dyskinesia, ataxia, tremor, choreic movement, gait abnormality, and psychogenia. The hepatic function indices were detected. The Child Grade used to assess hepatic functional grades was done according to hepatic function indices. The serum copper content, 24-h urinary copper content, and copper content in cerebral spinal fluid (CSF) were also determined. Iron concentrations in serum, total iron-binding capacity, and serum iron saturation were measured. All patients accepted treatment using copper chelators. The treatment lasted for 1 month using sodium dimercaptopropane sulfonate (DMPS) with a dose of 2.5-5 mg -1 Kg -1 day. All patients were followed up by using assessment of laboratory measurements of liver function tests and copper and iron indices after treatment.

MRI protocol

All participants underwent conventional MRI and SWI of the brain before treatment. All MRI data were obtained using a 1.5 T scanner (Philips Achieva Nova Dual Plus) equipped with eight-channel, phase-array head coils. All participants were subjected to T1-weighted sequence, T2-weighted sequence, and SWI. SWI images were obtained parallel to the anteroposterior commissural line by using a high-resolution, gradient-echo sequence with following parameters: TR/TE, 60/40 ms; flip angle, 18°; slices, 48; field of view, 230/184 mm; matrix, 240 × 240.

Image processing

The region of interests (ROIs) were drawn according to the anatomical structures, including globus pallidus (GP), head of caudate nucleus (CA), putamen (PU), thalamus (TH), substantia nigra (SN), and red nucleus (RN). The values of corrected phase (CP) were checked. According to the methods of Sinha S et al. [8] we scored the high signals and low signals on T2-weighted image separately.

Statistical analysis

Results were presented as mean ± SEM. Statistical analyses were performed using SPSS 13.0. (SPSS Inc., Chicago, Illinois, USA). A paired-sample t-test was used to compare the CP values between each two different ROIs. One-way ANOVA was also used to compare the CP values among different ROIs. A paired-sample t-test was used to compare the CP values in patients with WD and the healthy controls. Pearson's correlation analysis was applied to assess the correlation between CP values and copper, iron parameters, the modified Young Scale scores, respectively. Significance criterion of P < 0.05 was used for all inferences.


 » Results Top


The demographic and clinical characteristics of the subject groups are shown in [Table 1]. No significant differences in gender or age were observed between the patients and the healthy controls. The 30 WD patients included 20 cerebral type patients and 10 hepatic type patients.
Table 1: Clinical and demographic characteristics of patients with WD and controls

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Results of CP value

Low signals could be seen mostly in GP, CA, PU, TH, RN, and SN on SWI. The CP values in GP, CA, PU, TH, RN, and SN in WD patients and the healthy controls are shown in [Table 2]. There were significant differences of the CP values between the patients and the controls in the SN (t = 9.88, P = 0.017), right CA (t = -1.21, P = 0.037), and right GP (t = 4.42, P = 0.032).
Table 2: CP values in patients with WD and the healthy controls

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In WD patients, a significant difference in CP values between the two hemisphere was observed in the TH (P = 0.048), whereas no significant difference was found in the other regions. The CP value of SN was lower than that of RN (P = 0.022), TH (P = 0.031), CA (P = 0.019), GP (P = 0.025), and PU (P = 0.047). No obvious difference was found among other regions.

The CP values of the left RN and right CA were lower in the cerebral type WD than that in the hepatic type (P = 0.045, 0.020).

The correlations between CP values and the clinical parameters of patients with WD

The results of metal parameters of WD patients and healthy controls are shown in [Table 3]. The CSF copper content and urinary copper content of WD patients was significantly higher than normal, while the serum copper content was lower than that in the control. No obvious correlation was found between CP values and copper parameters.
Table 3: Scores of modifi ed Young scale and metal parameters of WD patients and healthy controls

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The serum iron content of the hepatic type WD patients was significantly higher than the control. There was no significant correlation between CP values and the serum iron content, total iron-binding capacity, and serum iron saturation independently.

In the 10 hepatic type WD patients, there were 7 of Child Grade A, 2 of Child Grade B, and 1 of Child Grade C. No obvious correlation was found between CP values and the Child Grades. No relationship was found between CP values and disease duration.

The correlations between CP values and modified Young Scale scores

Pearson's correlation analysis showed that there was negative correlation between the scores of dysarthria and the CP values of the right GP in WD patients (r = -0.620, P = 0.042). We found negative correlation between the scores of tremor and the CP values of the left CA in WD patients (r = -0.649, P = 0.042). No correlation was found between the CP values and scores of rigidity, choreic movement, ataxia, psychiatric symptom, and gait instability.

The correlation between CP values and T2 parameters in conventional MRI

Negative correlation between the CP values and scores of the low signal in TH was observed (r = -0.866, P = 0.048). The CP values were negatively correlated with the scores of low signal in the GP (r = -0.691, P = 0.048). Negative correlation was also observed between CP values and the scores of high signal in the right PU (r = -0. 758, P = 0.018). The low signal imaging on SWI was not coincident with that on T2WI completely. Some regions that had high signals on T2-weighted image had low signals on SWI [Figure 1].
Figure 1: The MRI and SWI images of a WD patient who is 18 years old. T1-weighted image reveals bilateral symmetric low signal intensity in the globus pallidus, putamen and caudate nucleus. (a) T2-weighted image shows high signal intensity in the putamen and caudate nucleus, and both low signal and high signal in the globus pallidus. (b) SWI shows markedly dark paramagnetic signals in globus pallidus, putamen and caudate nucleus. (c) Some regions which had high signals on T2-weighted image had low signals on SWI (arrows)

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 » Discussion Top


WD is an autosomal recessive defect of cellular copper export. The neural manifestations result from copper accumulation in the brain. However, there is no effective way to evaluate the copper content in the brain. Moreover, whether iron deposition attributes to the damage of brain in WD remains unknown.

The hypointense signals in SWI can reflect mineral deposition. [1],[9],[10] The negative correlation between SWI signal change and mineral accumulation was confirmed. [11],[12] In this study, the mineral deposition in the brain of patients with WD was evaluated by SWI technique. The exact nature of hypointense signals in WD patients remains unclear. Since copper is paramagnetic, the observed abnormalities may indicate copper deposition. [13] These signal abnormalities can be also correlated with the paramagnetic effect of iron. [1] However, no correlations were observed between the copper content and CP values in our series. The possible reason may be that serum and CSF copper content cannot reflect the exact copper level in the brain. No correlation between serum iron content and CP values was determined. The serum iron may not reflect the level of iron content in brain. It is believed that the hyperintense lesions on T2-weighted images in the brain indicate secondary edema, giosis, or demyelinization, while the hypointense signals reflect copper deposition. [1] We found that the CP values of TH and GP were negatively correlated with the hypointense signal scores independently, indicating that CP value might reflect copper content in the brain. The hypointense signals on SWI in WD patients may have resulted from the combination of copper and iron deposition. Further pathological study is needed to confirm the issue.

The CP values in SN, CN, and GP in WD patients were decreased, suggesting that mineral concentration increased in these regions. We found the CP value in SN was the lowest in these regions, suggesting that the content of mineral in SN might be the highest. Meanwhile, the CP values in hepatic type WD were decreased, which indicated the mineral deposition in the brain of the hepatic type patients with WD. CP values in RN and CA showed significant difference between the hepatic and cerebral type WD, suggesting more mineral deposition in the brain of cerebral type patients with WD.

Abnormal iron deposition in brain has been observed in many chronic diseases. [14] Elevated iron level in the SN of PD patients has been confirmed. [1] In our series, abnormal iron metabolism was also observed in WD patients. The elevated serum iron level in WD patients was detected. Ceruloplasmin is a potent ferroxidase that catalyzes the conversion of ferrous to ferric iron, which is essential for iron transport across cell membrane. [1] Ceruloplasmin deficiency may result in brain iron overload. [1] The iron deposition may also attribute to a secondary neuronal degeneration. [6],[13],[15]

There are contradictions as to whether MRI correlates with symptoms. [6] The correlations between the phase shift values of the SN and UPDRS motor scores indicate that the amount of iron deposition in the SN might reflect the severity of PD. [14],[15] The phase shift values of the GP, PU, and RN have been shown to be associated with the extent of tremor. [6] The correlation between the extent of abnormal posture and the anterior GP has been found. [6] In this series, we also observed the correlations between the CP values and the modified Young scale scores in WD patients. The tremor scores were negatively correlated with the CP values of the CA, indicating that the mineral deposition in CA might be important in the pathogenesis of tremor. Our results also indicated that the mineral deposition in the GP might induce dysarthria in WD patients.

During the treatment of WD, there is no effective way to assess the change of mineral content of brain. Therefore, it is difficult to plan the treatment strategy. Our study showed that the hypointense signals on SWI did not completely correspond to the hypointense signals on T2-weighted images. Some regions that had hyperintense signal on T2-weighted images showed hypointense signals on SWI, indicating that there are mineral depositions in these regions. SWI may be more sensitive than ordinary MRI in determining the mineral deposition. If there are hypointense signals on SWI, the mineral deposition may exist in the brain of WD patients. In that case, copper-chelating treatment should be employed. If there are only hyperintense signals on T2-weighted images but no hypointense signals on SWI, there may be only neural damages in the brain. In that case, the copper-chelating treatment may be useless. SWI may be used as a maker of pathological changes in WD patients. The treatment can be decided according to the SWI results.

There are some limitations in this study. First, SWI is not a true quantitative method to measure brain mineral. Further studies evaluating correlations between SWI and pathology with larger samples are needed. Second, we did not check SWI after treatment; therefore, the change of the mineral deposition in the brain of WD patients after treatment was not known. More researches to evaluate the outcome of treatment using SWI should be performed in the future.

In summary, there are paramagnetic signal abnormalities on SWI in the brain of WD patients, reflecting the mineral deposition in the brain. The mineral deposition may be obvious in SN, GP, and CA of WD patients, while the mineral content in SN may be the highest. The mineral deposition may contribute to the neural symptoms. SWI can function as an in vivo technique to identify pathological changes in brain of patients with WD, and it can help to make the treatment strategy.

 
 » References Top

1.Lee JH, Yang TI, Cho M, Yoon KT, Baik SK, Han YH. Widespread cerebral cortical mineralization in Wilson′s disease detected by susceptibility-weighted imaging. J Neurol Sci 2012;313:54-6.  Back to cited text no. 1
    
2.Barbosa ER, Silveira-Moriyama L, Machado AC, Bacheschi LA, Rosemberg S, Scaff M. Wilson′s disease with myoclonus and white matter lesions. Parkinsonism Relat Disord 2007;13:185-8.  Back to cited text no. 2
    
3.Hellman NE, Gitlin JD. Ceruloplasmin metabolism and function. Annu Rev Nutr 2002;22:439-58.  Back to cited text no. 3
    
4.Sorbello O, Sini M, Civolani A, Demelia L. HFE gene mutations andWilson′s disease in Sardinia. Dig Liver Dis 2010;42:216-9.  Back to cited text no. 4
    
5.Kim JM, Ko SB, Kwon SJ, Kim HJ, Han MK, Kim DW, et al. Ferrous and ferric iron accumulates in the brain of aged Long-Evans Cinnamon rats, an animalmodel ofWilson′s disease. Neurosci Lett 2005;382:143-7.  Back to cited text no. 5
    
6.Rossi M, Ruottinen H, Soimakallio S, Elovaara I, Dastidar P. Clinical MRI for iron detection in Parkinson′s disease. Clin Imaging 2013;37:631-6.  Back to cited text no. 6
    
7.Zhou XX, Li XH, Huang HW, Liu B, Liang YY, Zhu RL, et al. Improved Young Scale -a scale for the neural syndrome of Wilson disease. Chin J Nerv Ment Dis 2011;37:171-2.  Back to cited text no. 7
    
8.Sinha S, Taly AB, Ravishankar S, Prashanth LK, Venugopal KS, Arunodaya GR, et al. Wilson′ s disease: Cranial MRI observations and clinical correlation. Neuroradiology 2006;48:613-21.  Back to cited text no. 8
    
9.Haack EM, Cheng NY, Xu Y, Reichenbach JR. Susceptibility weighted imaging (SWI). Magn Reson Med 2004;52;612-8.  Back to cited text no. 9
    
10.Mittal S, Wu Z, Neelavalli J, Haacke EM. Susceptibility-weighted imaging: Technical aspects and clinical applications, part 2. AJNR Am J Neuroradiol 2009;30:232-52.  Back to cited text no. 10
    
11.Zhang W, Sun SG, Jiang YH, Qiao X, Sun X, Wu Y. Determination of brain iron contentin patients with Parkinson′s disease using magnetic susceptibility imaging. Neurosci Bull 2009;25:353-60.  Back to cited text no. 11
    
12.Haacke EM, Cheng NY, House MJ, Liu Q, Neelavalli J, Ogg RJ, et al. Imaging iron stores in the brain using magnetic resonance imaging [J]. Magn Reson Imaging 2005;23:1-25.  Back to cited text no. 12
    
13.Hingwala DR, Kesavadas C, Thomas B, Kapilamoorthy TR. Susceptibility weighted imaging in the evaluation of movement disorders. Clin Radiol 2013;68:e338-48.  Back to cited text no. 13
    
14.Han YH, Lee JH, Kang BM, Mun CW, Baik SK, Shin YI, et al. Topographical differences of brain iron deposition between progressive supranuclear palsy and parkinsonian variant multiple system atrophy. J Neurol Sci 2013;325:29-35.  Back to cited text no. 14
    
15.Zhang J, Zhang Y, Wang J, Cai P, Luo C, Qian Z, et al. Characterizing iron deposition in Parkinson′s disease using susceptibility-weighted imaging: An in vivo MR study. Brain Res 2010;1330:124-30.  Back to cited text no. 15
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]

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