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Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*
Magnetic Resonance Imaging xxx (2015) xxx–xxx
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Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*☆ Jeam Haroldo Oliveira Barbosa a,⁎, Antonio Carlos Santos b, Vitor Tumas b, Manju Liu c, Weili Zheng c, E. Mark Haacke c, d, Carlos Ernesto Garrido Salmon a a
Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil MRI Institute for Biomedical Research, Detroit, MI, United States d Wayne State University, Detroit, MI, United States b c
a r t i c l e
i n f o
Article history: Received 31 March 2014 Revised 19 August 2014 Accepted 16 February 2015 Available online xxxx Keywords: QSM Susceptibility magnetic Iron Brain Parkinson
a b s t r a c t Purpose: To evaluate the sensitivity and specificity of quantitative magnetic resonance (MR) iron mapping including R2, R2* and magnetic susceptibility to differentiate patients with Parkinson's disease (PD) from healthy controls. Materials and Methods: Thirty (30) healthy controls (HC) (64 ± 7 years old) and 20 patients with idiopathic PD (66 ± 8 years old) were studied using a 3 T MR imaging scanner. R2 maps were generated from GRASE sequence while R2*, and quantitative susceptibility mapping (QSM) were obtained from a conventional multi-echo gradient-echo sequence. R2, R2* and relative susceptibility (Δχ) values of structures in the basal ganglia were measured for each patient and control. An analysis of sensitivity and specificity and unpaired t-test was applied to the two groups. Results: A significant difference (p b 0.05) was found for R2 and Δχ values in the substantia nigra as a whole and in the pars compacta for PD patients. The R2* values were different significantly (p b 0.05) only on the substantia nigra pars compacta. QSM presented the highest sensitivity and specificity to differentiate the two populations. Conclusion: The QSM map was the most sensitive quantitative technique for detecting a significant increase of iron for PD. The highest significant difference between controls and patients was found in the substantia nigra pars compacta using QSM. © 2015 Elsevier Inc. All rights reserved.
1. Introduction The ability of iron to accept and donate electrons makes it essential for cellular homeostasis and various biological reactions. However, excess iron deposition in the brain may lead to deleterious effects by generating reactive oxygen species that cause oxidative stress [1]. Some cadaver brain studies have found higher iron concentration in the basal ganglia in Parkinson's disease (PD) patients [2–5] than in healthy controls (HC). Several in vivo magnetic resonance (MR) imaging studies have used transverse relaxation rates (R2 and R2*) to distinguish patients with PD from healthy controls [6–14]. However, other studies were not able to find significant differences between the groups using the same approach [15,16]. These contradictory results could
☆ Contract grant sponsor: CNPq: 136062/2011-3, FAPESP: 2005/56447-7, CAPES. ⁎ Corresponding author at: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo (USP). Av. Bandeirantes 3900, 14040-901, Ribeirão Preto, São Paulo, Brazil. E-mail address: [email protected] (J.H.O. Barbosa).
be explained by the different methodologies used in these studies (segmentation of the structures and image acquisition parameters (echo time, numbers of echo time and inter-echo spacing) [17]. The relaxometry rates are influenced by changes in water content, local water diffusion rates in inhomogeneous field [18] and macroscopic magnetic field inhomogeneities. Recently, quantitative susceptibility mapping (QSM) has been proposed to investigate iron concentration in the brain [19–24], because it is, in principle, more accurate than transverse relaxation rates in terms of iron quantification. QSM has shown superior sensitivity over R2* mapping in differentiating controls and multiple sclerosis patients in regions with iron accumulation in the brain [25]. Another study showed that QSM improved contrast of the subthalamic nucleus in patients with PD better than T2-weighted, T2*-weighted, R2* mapping, susceptibility-weighted and phase images [26]. The subthalamic nucleus appeared to have higher iron content than the surrounding tissues [27]. A recent study reported elevated magnetic susceptibility values in the substantia nigra (SN) of patients with PD [28]. However, this study only analyzed the SN and did not compare iron in other
http://dx.doi.org/10.1016/j.mri.2015.02.021 0730-725X/© 2015 Elsevier Inc. All rights reserved.
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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structures. The comparative study of the MR techniques for iron quantification in the basal ganglia for patients with Parkinson's disease may define the most sensitive quantitative technique to estimate the metal and possible marker of PD. In our study, we propose the use of different quantitative MR techniques including R2 mapping, R2* mapping and QSM to quantify putative iron in multiple regions in the basal ganglia. 2. Materials and methods 2.1. Subjects The local ethics committee approved this study, and all participants signed the consent form. Twenty [20] patients (66 ± 8 years old, 12 males and 8 females) with idiopathic PD and 30 HC (64 ± 7 years old, 9 males and 21 females) were recruited from the university hospital and from the local university. The PD patients were selected by two experienced neurologists with expertise in extrapyramidal diseases (more than 10 years clinical experience each). The inclusion criteria for PD patients included: subjects above 50 years of age and diagnosis of Parkinson's disease according to the criteria of the United Kingdom Brain Bank. The exclusion criteria were: history of other neurological and psychiatric disorders, patients with PD as secondary disease and with atypical disease progression. All patients were receiving levodopa therapy. The inclusion criteria for controls included: subjects above 50 years of age, without history of neurological disease, hypertension or diabetes and normal diagnostic exam on the MRI. The disease duration, H&Y score (Hoehn and Yahr stage of Parkinson's disease) and affected side for the PD patients are summarized in Table 1. 2.2. MR imaging All subjects underwent MR imaging scans on a 3 T MR scanner (Achieva, Philips, Best, The Netherlands) with an 8 channel radio frequency head coil. We used a GRASE sequence for quantification of R2, as used by other study with brain iron quantification in multiple sclerosis [29]. This sequence uses successive 180° radio frequency pulses that cancel some of the field inhomogeneity errors and interspersed gradient echoes to save time and allow for high resolution imaging [30]. Phase errors and chemical shift effects are avoided by use of discontinuous phase encode order during the echo
Table 1 Information about the patients with PD. Patients
Disease years
H&Y ⁎
Side most affected
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
6 9 5 16 5 3 10 9 10 12 5 16 8 5 8 5 16 3 5 6
2 2 2 2 3 2 2 2 4 2 2 3 2 2 2 3 2 2 2 2
Right Left Right Right Right Right Right Both Left Right Right Left Right Right Left Left Right Both Left Right
⁎ Scale Hoehn and Yahr [41].
train. The imaging parameters were: EPI factor 3 with 12 equally spaced echoes, echo spacing = 12 ms, TE1 = 12 ms, TR = 3000 ms, FOV = 230 × 230 mm2, in-plane resolution = 0.479 × 0.479 mm2, slices number = 20, slice thickness = 2 mm and acquisition time = 6 min. Quantitative R2* mapping and QSM images were obtained from the same conventional multi-echo gradient-echo data with 4 equally spaced echoes. The imaging parameters were: TR = 100 ms, TE1 = 7.7 ms, echo spacing = 12 ms, FA = 15°, FOV = 230 × 230 mm2, in-plane resolution = 0.479 × 0.479 mm2, slices number = 20, slice thickness = 2 mm and acquisition time = 6 min10 s. We used an automatic first order shimming over the whole volume as done in [31]. After shimming, the full width at half maximum of the water signal in the adjusted volume was smaller than 45 Hz (0.35 ppm in 3 T) in all the subjects. The phase images of the second echo (TE2 = 19.7 ms) were used to create the QSM maps. T1-weighted images were acquired using a three-dimensional gradient echo sequence to provide more structural information for the segmentation procedure. The imaging parameters were: TR = 7 ms, TE = 3.2 ms, FA = 8°, FOV = 240 × 240 mm2; in-plane resolution = 0.9 × 0.9 mm2; slice number = 170, slice thickness = 1 mm, and acquisition time = 4 min27 s.
2.3. Data processing and analysis The following steps were performed to generate the QSM images: 1) phase unwrapping using prelude in FSL [32]; 2) brain extraction based on magnitude images using BET2 in FSL [33]; 3) background phase removal using TSVD-SHARP [21] with a kernel size of 6 mm and regularization parameter of 0.05; 4) truncated k-space division (TKD) with a threshold of 0.1 to create the susceptibility maps [34]. The QSM processing steps are summarized in Fig. 2. QSM by its nature does not generate an absolute susceptibility since no information is available at k = 0 but rather a relative susceptibility (Δχ) between tissues. In our study, the occipital white matter was used as reference region for each subject. In general, the occipital white matter has reasonably homogeneous distribution on the QSM map and in a recent study has been shown to have the least inter-subject variation [35]. Nine regions of interest (ROIs) were drawn manually on the QSM images for each case: substantia nigra (SN), substantia nigra pars compacta (SNc), red nucleus (RN), globus pallidus (GP), putamen (PUT), caudate nucleus (CN), thalamus (THA), white matter (WM) and gray matter (GM). We segmented the substantia nigra pars compacta as Ref. [28], because this region showed higher iron concentration in patients with PD [5]. Each region was segmented only on the more representative slice (Fig. 1). Data processing was performed by three researchers with more than 3 years of experience in image processing. T1w images were used for better definition of the boundaries of the caudate nucleus and thalamus. It is currently assumed that contrast in the QSM maps was dominated by tissue iron [26]. The R2 and R2* values were calculated using a mono-exponential decay fitting of averaged signal intensities in the ROI for each echo time, but disregarding the first and the last echo in R2 and R2*, respectively. The first echo in the T2w image showed less intensity than the second echo and exponential behavior different than other echoes. The last set of gradient echo images were eliminated from fitting because of severe signal loss around the nasal sinus region caused by long echo time. The average signal intensity of the ROIs from the first three gradient echoes never fell below 3 times the noise level, even in high iron content regions. The brain iron concentration was estimated based on a pathology study by Hallgren and Sourander [36]. For CN, GP and PUT of a given subject and its age, the iron concentration was calculated according to the equations involving accumulated iron and age, reported by Hallgren & Sourander. For the other structures, we used the same
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
J.H.O. Barbosa et al. / Magnetic Resonance Imaging xxx (2015) xxx–xxx
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Fig. 1. Structures of interest in the basal ganglia on the QSM map for a 68 year old male healthy control. The ROIs were drawn manually for substantia nigra (SN), substantia nigra pars compacta (SNc), red nucleus (RN), globus pallidus (GP), putamen (PUT), caudate nucleus (CN), thalamus (THA), white matter (WM) and gray matter (GM).
average iron concentration that Hallgren & Sourander found for all individuals. The lateral asymmetry seen for the R2, R2* and Δχ values for each ROI was evaluated in controls and PD patients. The asymmetry coefficient for controls was defined as: Asym ¼
Valueleft ‐Valueright = Valueleft þ Valueright 100%
ð1Þ
The asymmetry coefficient for PD patients was defined as: Asym ¼ ðValuedisease ‐Valuenon‐disease Þ=ðValuedisease þ Valuenon‐disease Þ 100%
ð2Þ Valuedisease represents the measurement from the most affected disease side. 2.4. Statistical analysis The interobserver variability of segmentation was tested by using the intraclass correlation coefficient (ICC) for the three observers. The Kolmogorov–Smirnov test was used to analyze the normality of the samples. A student t-test was used to compare the iron concentration between the two populations represented by different
MR parameters. A value of p b 0.05 was considered statistically significant, and these calculations were performed in the software OriginPro8. The sensitivity and specificity of R2, R2* and magnetic susceptibility to separate PD patients from normal controls were analyzed by ROC curves (receiver operating characteristic) [37]. 3. Results The normal and patient groups were age matched, and therefore there was no significant difference with age (p = b0.5). All R2, R2* and Δχ maps for structures in the basal ganglia showed a high contrast to the surrounding tissue (Figs. 3–4). From a qualitative point of view, in general, it is hard to differentiate the age matched PD patients and controls from the information in Figs. 3–4. By means of the segmentations performed by the three observers (ICC values of 0.97), R2, R2* and Δχ values were recorded. A linear correlation was found between the R2, R2* and Δχ values and the estimated iron in the basal ganglia (left and right) for the control subjects (n = 30) (Fig. 5). These correlations were performed in healthy people because the iron data reported by Hallgren and Sourander are related to normal controls [36]. The mean values and standard deviations of the R2, R2* and Δχ maps for the ROIs defined in Fig. 1 are summarized in Table 2. A significant difference was found for R2 and Δχ values in the
Fig. 2. QSM map processing with mask of brain (Bet), unwrapping phase (Prelude), background filter (filter SHARP), and QSM threshold (TKD).
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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Fig. 3. R2 maps (A) and R2* maps (B) of a 66 years old male healthy control (top row) and of a 66 years old male patient with Parkinson's disease (bottom row). The unit of the maps is s−1.
substantia nigra and pars compacta. The R2* values was different significantly only on the substantia nigra pars compacta. No correlation was found between R2, R2* and Δχ values with disease
duration (R 2 b 0.12). The asymmetry coefficients, mean (± standard deviation), in the substantia nigra compacta of controls were: −2.3% (±4.5%), 1.0% (±10.8%) and − 3.9% (±12.6%) for R2, R2* and Δχ,
Fig. 4. QSM of a 66 years old male healthy control (top row) and of a 66 years old male patient with Parkinson's disease (bottom row). The unit of the maps is expressed in ppb.
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
J.H.O. Barbosa et al. / Magnetic Resonance Imaging xxx (2015) xxx–xxx
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Fig. 5. Linear correlations among R2, R2* and Δχ values with estimated iron considering the age effect for healthy controls [36]. The fitted linear equation and r2 value are presented inside each graph.
respectively. In patients considering the most affected side they were: 0.2% (±3.3%), 2.6% (±8.3%) and 0.8% (± 9.4%) for R2, R2* and Δχ, respectively. This lack of statistical significance presumed that there was no asymmetry in iron deposition between the hemispheres in both groups. The ability of each technique (R2, R2*, QSM) to classify healthy individuals and patients with PD were analyzed using the ROC curve in the substantia nigra and substantia nigra pars compacta (Fig. 6). The QSM map had higher sensitivity to classify patients with Parkinson's disease than the R2 or R2* map for both the SN and SNc. The area under the curve and respective standard deviations are given in the Fig. 6. 4. Discussion According to a review article by Grog and Berg (2012), the studies on R2 and R2* differentiating controls from patients with Parkinson's disease are controversial. Only 4 of 8 studies [6–9] with R2 values and 6 of 8 studies [8,10–14] with R2* values, found significant differences between groups in the region of the substantia nigra. The inconsistency of the iron quantification results in the literature
Table 2 Mean values and standard deviation of R2, R2* and QSM maps. Maps
Region
Controls
PD patients
p value
R2
SN** SNc*** RN GP PUT CN THA SN SNc* RN GP PUT CN THA SN*** SNc**** RN GP PUT CN THA
20.7 (1.7) 21.2 (2.2) 20.8 (2.7) 22.6 (2.0) 19.3 (1.5) 16.9 (1.4) 15.9 (1.0) 45.7 (6.5) 47.7 (8.4) 41.5 (7.7) 50.0 (6.5) 41.5 (6.4) 31.5 (5.9) 25.9 (4.6) 114.7 (32.5) 140.1 (38.5) 115.2 (39.7) 122.5 (25.5) 63.2 (22.7) 40.83 (20.7) 19.8 (17.6)
21.7 23.3 21.6 22.5 19.2 17.3 16.2 47.7 52.8 42.4 48.1 39.3 32.9 25.9 150.9 186.7 106.2 132.9 57.6 41.2 20.7
b0.01** b0.001*** 0.10 0.74 0.61 0.12 0.14 0.20 0.013* 0.57 0.14 0.07 0.26 0.97 b0.001*** b0.00001**** 0.23 0.13 0.20 0.92 0.80
R2*
Δχ
(1.7) (2.8) (1.8) (1.7) (1.1) (1.1) (1.1) (8.5) (11.7) (7.5) (5.8) (5.0) (7.1) (3.6) (41.5) (53.2) (32.2) (43.2) (18.5) (22.7) (16.3)
R2 and R2* values are in sec−1. Δχ values are in ppb. Values in parentheses are standard deviation. Symbols of “*” indicate significant difference: * pb0.05; **pb0.01; ***pb0.001; ****pb0.00001.
may be explained by the use of different imaging measures. In this work, we found a significant increase of R2* (p b 0.05), R2 (p b 0.01 and p b 0.001) and Δχ (p b 0.001 and p b 0.00001) values in the entire substantia nigra and in the pars compacta, respectively, for the PD patients (except R2* values for substantia nigra as a whole). These results are in agreement with other in vivo studies that found significant differences separately: on the SN R2 [8]; on the SNc R2 [6,7,9], R2* [14] and Δχ [28]. The R2* values of the basal ganglia, except for SNc, did not show significant differences between controls and patients (Table 2) as reported by Braffman et al., (1989) and Ordidge et al., (1994) [16,38] which disagree with other studies [8,10–13]. The controversy of the previous results may be due the R2* map to be influenced by the inhomogeneity of the magnetic field unrelated to iron accumulation [17] and by the effect of water diffusion in this inhomogeneous field [18] which has been well studied by many researchers [13,14,38]. Martin and colleagues [14] divided the substantia nigra into four regions: SN pars compacta medial, SN pars compacta lateral, SN pars reticulata medial and SN pars reticulata lateral. These authors reported significant variations in R2* (p b 0.005) just in the substantia nigra pars compacta lateral as we found on the SNc. Sofic and colleagues [5] demonstrated a selective increase of total iron content in Parkinsonian substantia nigra pars compacta but not in the substantia nigra pars reticulata. Therefore, our results confirm the in vivo results of Sofic et al., and we suggest the SNc as the specific region to study iron deposition in the PD. To validate our parameter estimations, linear regressions between R2, R2* and susceptibility values and the estimated iron for basal ganglia of healthy controls were performed and compared with other studies. Our results were close to the reported values in the literature [14,22,39,40] (Table 3). We also highlight that a change in the R2 values can be attributed to a change in the concentration or distribution of free water molecules. Moreover, changes in values of R2, R2* and QSM can be influenced by the accumulation of other paramagnetic ions (Cu+2), paramagnetic ion oxidation states and the coupling between them [28]. However the strong correlation of this parameter with the iron concentration suggests that iron is the dominant factor. The area under the ROC curve can be interpreted as the probability that the patient is diagnosed as PD compared to a healthy person. The test is classified as unable to determine patients and controls when it has an area equal to 0.5 and is perfect when equal to 1.0. In our analyses in the SN and SNc region, the QSM map had higher sensitivity to classify patients with Parkinson's disease (area = 0.77 ± 0.05 for both regions) than the R2 map (area = 0.67 ± 0.06 and area = 0.77 ± 0.05, respectively) and R2* map (area = 0.54 ± 0.06 and area = 0.65 ± 0.06, respectively) (Fig. 6).
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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Fig. 6. ROC curve for R2, R2* and QSM maps of SN (left) and SNc (right).
As expected, the lateral asymmetries in healthy people were close to zero in all the calculated parameters in the basal ganglia. Although patients in the initial stage of Parkinson's disease have unilateral involvement with minimal disability, we did not find significant asymmetry in the R2, R2* and Δχ values. This is expected because the patients studied had more than 1 on the H&Y scale, and it is well-known that patients with more than 1 on the H&Y scale have bilateral involvement [41]. Moreover, there was no correlation between disease duration and R2, R2* and susceptibility values that suggests no change in the iron concentration in patients with 2 or more score on the H&Y scale. We used conventional sequences close to clinical practice to acquire the R2 and R2* mapping. The GRASE sequence was selected to acquire multi spin echo with multi-gradient echoes because of its rapid high resolution acquisition capabilities. Even though absolute R2 values may not be correct with this approach, relative values between patients and controls are expected to be unaffected by a possible error in R2 measurements. Other authors using spin echo approaches also found a significant increase of R2 values on the SN for patients with PD [6,8]. The multi-echo gradient-echo sequence was acquired to process R2* map. Similarly, Peran et al. (2010) acquired gradient echo sequence, and Du et al. (2011) did multigradient echo 3D with flow compensation on three directions. Gorrell et al. (1995), Martin and Weiler (2008) and Baudrexel et al. (2010) acquired gradient echo sequence added to the specific radio frequency pulse or gradient refocusing pulse to mitigate the signal loss caused by background macroscopic susceptibility gradients. Although these last three papers used the acquisition sequence with
specific artifacts removed, all authors found significant increases of R2* values in the SN or SNc for patients with PD. The main limitation of this study is the small number of patients studied. Patients were recruited with predominantly intermediate Hoehn and Yahr Scores [2–4]. Patients in the advanced stage of the disease (Hoehn and Yahr Score 5) have many tremors, body rigidity and physical debilitation, and would have been difficult to scan. One possible inaccuracy of our R2 values is related to the imperfections in the slice profile of the refocusing pulses and gradient echo acquisitions, even using a low EPI factor. Another limitation is the fact that only the most representative slice of the region of interest was evaluated and not the full 3D anatomical region. We preferred to select the slice of center position to avoid partial volume on the regions from extreme slices. Although the literature has shown strong linear correlation between the QSM values and local iron content on the basal ganglia [20,24], several factors can influence this relationship suggesting a non-linear relation, mainly, for regions with very low iron concentrations (e.g., myelin content (34)). In this study, it also used the more simplistic relationship; however the dispersion of the quantitative values measured in each region (Fig. 5) suggests a multifactorial relationship. 5. Conclusion Susceptibility measurements represent the most sensitive quantitative technique to detect a significant increase of iron in PD patients. The highest significant difference between controls and patients was found for the substantia nigra pars compacta.
Table 3 Linear regression coefficients among R2, R2* and Δχ values with estimated iron for controls. Map
Regions
R2
SN, RN, GP, PUT, CN, GM
R2*
SN, RN, GP, PUT, CN, WM
R2*
GP, PUT, CN, THA
Δχ
SN, RN, GP, PUT, CN, THA, GM
Linear regression Slope
Intercept
R2
0.61 0.42 1.0a 1.2 1.2 1.4 7.5 6.5
12.7 13.0 17.5a 21.3 14.2 19.2 – –
0.92 0.60 0.81 0.50 0.87 0.71 0.96 0.70
Image sequence
References
GESFIDE GRASE MGE GRASE GRE MGE GE MGE
GELMAN et al., 1999 Our results MARTIN et al., 2008 a Our results YAO et al., 2009 Our results Wharton and Bowtell (2010) Our results
All references were acquired in 3 T magnetic field, except Whartom and Bowtell (2010) that used 7 T. All the references estimated iron by Hallgren and Sourander (1956). In our results, we selected different regions for the same technique to compare with other reported results. The unit of the slope of both R2 and R2* is s−1/mgFe/100 g, and for Δχ it is ppb/mgFe/100 g. a Estimated values from the plot of Martin et al. (2008).
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*☆ Jeam Haroldo Oliveira Barbosa a,⁎, Antonio Carlos Santos b, Vitor Tumas b, Manju Liu c, Weili Zheng c, E. Mark Haacke c, d, Carlos Ernesto Garrido Salmon a a
Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil MRI Institute for Biomedical Research, Detroit, MI, United States d Wayne State University, Detroit, MI, United States b c
a r t i c l e
i n f o
Article history: Received 31 March 2014 Revised 19 August 2014 Accepted 16 February 2015 Available online xxxx Keywords: QSM Susceptibility magnetic Iron Brain Parkinson
a b s t r a c t Purpose: To evaluate the sensitivity and specificity of quantitative magnetic resonance (MR) iron mapping including R2, R2* and magnetic susceptibility to differentiate patients with Parkinson's disease (PD) from healthy controls. Materials and Methods: Thirty (30) healthy controls (HC) (64 ± 7 years old) and 20 patients with idiopathic PD (66 ± 8 years old) were studied using a 3 T MR imaging scanner. R2 maps were generated from GRASE sequence while R2*, and quantitative susceptibility mapping (QSM) were obtained from a conventional multi-echo gradient-echo sequence. R2, R2* and relative susceptibility (Δχ) values of structures in the basal ganglia were measured for each patient and control. An analysis of sensitivity and specificity and unpaired t-test was applied to the two groups. Results: A significant difference (p b 0.05) was found for R2 and Δχ values in the substantia nigra as a whole and in the pars compacta for PD patients. The R2* values were different significantly (p b 0.05) only on the substantia nigra pars compacta. QSM presented the highest sensitivity and specificity to differentiate the two populations. Conclusion: The QSM map was the most sensitive quantitative technique for detecting a significant increase of iron for PD. The highest significant difference between controls and patients was found in the substantia nigra pars compacta using QSM. © 2015 Elsevier Inc. All rights reserved.
1. Introduction The ability of iron to accept and donate electrons makes it essential for cellular homeostasis and various biological reactions. However, excess iron deposition in the brain may lead to deleterious effects by generating reactive oxygen species that cause oxidative stress [1]. Some cadaver brain studies have found higher iron concentration in the basal ganglia in Parkinson's disease (PD) patients [2–5] than in healthy controls (HC). Several in vivo magnetic resonance (MR) imaging studies have used transverse relaxation rates (R2 and R2*) to distinguish patients with PD from healthy controls [6–14]. However, other studies were not able to find significant differences between the groups using the same approach [15,16]. These contradictory results could
☆ Contract grant sponsor: CNPq: 136062/2011-3, FAPESP: 2005/56447-7, CAPES. ⁎ Corresponding author at: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo (USP). Av. Bandeirantes 3900, 14040-901, Ribeirão Preto, São Paulo, Brazil. E-mail address: [email protected] (J.H.O. Barbosa).
be explained by the different methodologies used in these studies (segmentation of the structures and image acquisition parameters (echo time, numbers of echo time and inter-echo spacing) [17]. The relaxometry rates are influenced by changes in water content, local water diffusion rates in inhomogeneous field [18] and macroscopic magnetic field inhomogeneities. Recently, quantitative susceptibility mapping (QSM) has been proposed to investigate iron concentration in the brain [19–24], because it is, in principle, more accurate than transverse relaxation rates in terms of iron quantification. QSM has shown superior sensitivity over R2* mapping in differentiating controls and multiple sclerosis patients in regions with iron accumulation in the brain [25]. Another study showed that QSM improved contrast of the subthalamic nucleus in patients with PD better than T2-weighted, T2*-weighted, R2* mapping, susceptibility-weighted and phase images [26]. The subthalamic nucleus appeared to have higher iron content than the surrounding tissues [27]. A recent study reported elevated magnetic susceptibility values in the substantia nigra (SN) of patients with PD [28]. However, this study only analyzed the SN and did not compare iron in other
http://dx.doi.org/10.1016/j.mri.2015.02.021 0730-725X/© 2015 Elsevier Inc. All rights reserved.
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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J.H.O. Barbosa et al. / Magnetic Resonance Imaging xxx (2015) xxx–xxx
structures. The comparative study of the MR techniques for iron quantification in the basal ganglia for patients with Parkinson's disease may define the most sensitive quantitative technique to estimate the metal and possible marker of PD. In our study, we propose the use of different quantitative MR techniques including R2 mapping, R2* mapping and QSM to quantify putative iron in multiple regions in the basal ganglia. 2. Materials and methods 2.1. Subjects The local ethics committee approved this study, and all participants signed the consent form. Twenty [20] patients (66 ± 8 years old, 12 males and 8 females) with idiopathic PD and 30 HC (64 ± 7 years old, 9 males and 21 females) were recruited from the university hospital and from the local university. The PD patients were selected by two experienced neurologists with expertise in extrapyramidal diseases (more than 10 years clinical experience each). The inclusion criteria for PD patients included: subjects above 50 years of age and diagnosis of Parkinson's disease according to the criteria of the United Kingdom Brain Bank. The exclusion criteria were: history of other neurological and psychiatric disorders, patients with PD as secondary disease and with atypical disease progression. All patients were receiving levodopa therapy. The inclusion criteria for controls included: subjects above 50 years of age, without history of neurological disease, hypertension or diabetes and normal diagnostic exam on the MRI. The disease duration, H&Y score (Hoehn and Yahr stage of Parkinson's disease) and affected side for the PD patients are summarized in Table 1. 2.2. MR imaging All subjects underwent MR imaging scans on a 3 T MR scanner (Achieva, Philips, Best, The Netherlands) with an 8 channel radio frequency head coil. We used a GRASE sequence for quantification of R2, as used by other study with brain iron quantification in multiple sclerosis [29]. This sequence uses successive 180° radio frequency pulses that cancel some of the field inhomogeneity errors and interspersed gradient echoes to save time and allow for high resolution imaging [30]. Phase errors and chemical shift effects are avoided by use of discontinuous phase encode order during the echo
Table 1 Information about the patients with PD. Patients
Disease years
H&Y ⁎
Side most affected
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
6 9 5 16 5 3 10 9 10 12 5 16 8 5 8 5 16 3 5 6
2 2 2 2 3 2 2 2 4 2 2 3 2 2 2 3 2 2 2 2
Right Left Right Right Right Right Right Both Left Right Right Left Right Right Left Left Right Both Left Right
⁎ Scale Hoehn and Yahr [41].
train. The imaging parameters were: EPI factor 3 with 12 equally spaced echoes, echo spacing = 12 ms, TE1 = 12 ms, TR = 3000 ms, FOV = 230 × 230 mm2, in-plane resolution = 0.479 × 0.479 mm2, slices number = 20, slice thickness = 2 mm and acquisition time = 6 min. Quantitative R2* mapping and QSM images were obtained from the same conventional multi-echo gradient-echo data with 4 equally spaced echoes. The imaging parameters were: TR = 100 ms, TE1 = 7.7 ms, echo spacing = 12 ms, FA = 15°, FOV = 230 × 230 mm2, in-plane resolution = 0.479 × 0.479 mm2, slices number = 20, slice thickness = 2 mm and acquisition time = 6 min10 s. We used an automatic first order shimming over the whole volume as done in [31]. After shimming, the full width at half maximum of the water signal in the adjusted volume was smaller than 45 Hz (0.35 ppm in 3 T) in all the subjects. The phase images of the second echo (TE2 = 19.7 ms) were used to create the QSM maps. T1-weighted images were acquired using a three-dimensional gradient echo sequence to provide more structural information for the segmentation procedure. The imaging parameters were: TR = 7 ms, TE = 3.2 ms, FA = 8°, FOV = 240 × 240 mm2; in-plane resolution = 0.9 × 0.9 mm2; slice number = 170, slice thickness = 1 mm, and acquisition time = 4 min27 s.
2.3. Data processing and analysis The following steps were performed to generate the QSM images: 1) phase unwrapping using prelude in FSL [32]; 2) brain extraction based on magnitude images using BET2 in FSL [33]; 3) background phase removal using TSVD-SHARP [21] with a kernel size of 6 mm and regularization parameter of 0.05; 4) truncated k-space division (TKD) with a threshold of 0.1 to create the susceptibility maps [34]. The QSM processing steps are summarized in Fig. 2. QSM by its nature does not generate an absolute susceptibility since no information is available at k = 0 but rather a relative susceptibility (Δχ) between tissues. In our study, the occipital white matter was used as reference region for each subject. In general, the occipital white matter has reasonably homogeneous distribution on the QSM map and in a recent study has been shown to have the least inter-subject variation [35]. Nine regions of interest (ROIs) were drawn manually on the QSM images for each case: substantia nigra (SN), substantia nigra pars compacta (SNc), red nucleus (RN), globus pallidus (GP), putamen (PUT), caudate nucleus (CN), thalamus (THA), white matter (WM) and gray matter (GM). We segmented the substantia nigra pars compacta as Ref. [28], because this region showed higher iron concentration in patients with PD [5]. Each region was segmented only on the more representative slice (Fig. 1). Data processing was performed by three researchers with more than 3 years of experience in image processing. T1w images were used for better definition of the boundaries of the caudate nucleus and thalamus. It is currently assumed that contrast in the QSM maps was dominated by tissue iron [26]. The R2 and R2* values were calculated using a mono-exponential decay fitting of averaged signal intensities in the ROI for each echo time, but disregarding the first and the last echo in R2 and R2*, respectively. The first echo in the T2w image showed less intensity than the second echo and exponential behavior different than other echoes. The last set of gradient echo images were eliminated from fitting because of severe signal loss around the nasal sinus region caused by long echo time. The average signal intensity of the ROIs from the first three gradient echoes never fell below 3 times the noise level, even in high iron content regions. The brain iron concentration was estimated based on a pathology study by Hallgren and Sourander [36]. For CN, GP and PUT of a given subject and its age, the iron concentration was calculated according to the equations involving accumulated iron and age, reported by Hallgren & Sourander. For the other structures, we used the same
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
J.H.O. Barbosa et al. / Magnetic Resonance Imaging xxx (2015) xxx–xxx
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Fig. 1. Structures of interest in the basal ganglia on the QSM map for a 68 year old male healthy control. The ROIs were drawn manually for substantia nigra (SN), substantia nigra pars compacta (SNc), red nucleus (RN), globus pallidus (GP), putamen (PUT), caudate nucleus (CN), thalamus (THA), white matter (WM) and gray matter (GM).
average iron concentration that Hallgren & Sourander found for all individuals. The lateral asymmetry seen for the R2, R2* and Δχ values for each ROI was evaluated in controls and PD patients. The asymmetry coefficient for controls was defined as: Asym ¼
Valueleft ‐Valueright = Valueleft þ Valueright 100%
ð1Þ
The asymmetry coefficient for PD patients was defined as: Asym ¼ ðValuedisease ‐Valuenon‐disease Þ=ðValuedisease þ Valuenon‐disease Þ 100%
ð2Þ Valuedisease represents the measurement from the most affected disease side. 2.4. Statistical analysis The interobserver variability of segmentation was tested by using the intraclass correlation coefficient (ICC) for the three observers. The Kolmogorov–Smirnov test was used to analyze the normality of the samples. A student t-test was used to compare the iron concentration between the two populations represented by different
MR parameters. A value of p b 0.05 was considered statistically significant, and these calculations were performed in the software OriginPro8. The sensitivity and specificity of R2, R2* and magnetic susceptibility to separate PD patients from normal controls were analyzed by ROC curves (receiver operating characteristic) [37]. 3. Results The normal and patient groups were age matched, and therefore there was no significant difference with age (p = b0.5). All R2, R2* and Δχ maps for structures in the basal ganglia showed a high contrast to the surrounding tissue (Figs. 3–4). From a qualitative point of view, in general, it is hard to differentiate the age matched PD patients and controls from the information in Figs. 3–4. By means of the segmentations performed by the three observers (ICC values of 0.97), R2, R2* and Δχ values were recorded. A linear correlation was found between the R2, R2* and Δχ values and the estimated iron in the basal ganglia (left and right) for the control subjects (n = 30) (Fig. 5). These correlations were performed in healthy people because the iron data reported by Hallgren and Sourander are related to normal controls [36]. The mean values and standard deviations of the R2, R2* and Δχ maps for the ROIs defined in Fig. 1 are summarized in Table 2. A significant difference was found for R2 and Δχ values in the
Fig. 2. QSM map processing with mask of brain (Bet), unwrapping phase (Prelude), background filter (filter SHARP), and QSM threshold (TKD).
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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Fig. 3. R2 maps (A) and R2* maps (B) of a 66 years old male healthy control (top row) and of a 66 years old male patient with Parkinson's disease (bottom row). The unit of the maps is s−1.
substantia nigra and pars compacta. The R2* values was different significantly only on the substantia nigra pars compacta. No correlation was found between R2, R2* and Δχ values with disease
duration (R 2 b 0.12). The asymmetry coefficients, mean (± standard deviation), in the substantia nigra compacta of controls were: −2.3% (±4.5%), 1.0% (±10.8%) and − 3.9% (±12.6%) for R2, R2* and Δχ,
Fig. 4. QSM of a 66 years old male healthy control (top row) and of a 66 years old male patient with Parkinson's disease (bottom row). The unit of the maps is expressed in ppb.
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
J.H.O. Barbosa et al. / Magnetic Resonance Imaging xxx (2015) xxx–xxx
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Fig. 5. Linear correlations among R2, R2* and Δχ values with estimated iron considering the age effect for healthy controls [36]. The fitted linear equation and r2 value are presented inside each graph.
respectively. In patients considering the most affected side they were: 0.2% (±3.3%), 2.6% (±8.3%) and 0.8% (± 9.4%) for R2, R2* and Δχ, respectively. This lack of statistical significance presumed that there was no asymmetry in iron deposition between the hemispheres in both groups. The ability of each technique (R2, R2*, QSM) to classify healthy individuals and patients with PD were analyzed using the ROC curve in the substantia nigra and substantia nigra pars compacta (Fig. 6). The QSM map had higher sensitivity to classify patients with Parkinson's disease than the R2 or R2* map for both the SN and SNc. The area under the curve and respective standard deviations are given in the Fig. 6. 4. Discussion According to a review article by Grog and Berg (2012), the studies on R2 and R2* differentiating controls from patients with Parkinson's disease are controversial. Only 4 of 8 studies [6–9] with R2 values and 6 of 8 studies [8,10–14] with R2* values, found significant differences between groups in the region of the substantia nigra. The inconsistency of the iron quantification results in the literature
Table 2 Mean values and standard deviation of R2, R2* and QSM maps. Maps
Region
Controls
PD patients
p value
R2
SN** SNc*** RN GP PUT CN THA SN SNc* RN GP PUT CN THA SN*** SNc**** RN GP PUT CN THA
20.7 (1.7) 21.2 (2.2) 20.8 (2.7) 22.6 (2.0) 19.3 (1.5) 16.9 (1.4) 15.9 (1.0) 45.7 (6.5) 47.7 (8.4) 41.5 (7.7) 50.0 (6.5) 41.5 (6.4) 31.5 (5.9) 25.9 (4.6) 114.7 (32.5) 140.1 (38.5) 115.2 (39.7) 122.5 (25.5) 63.2 (22.7) 40.83 (20.7) 19.8 (17.6)
21.7 23.3 21.6 22.5 19.2 17.3 16.2 47.7 52.8 42.4 48.1 39.3 32.9 25.9 150.9 186.7 106.2 132.9 57.6 41.2 20.7
b0.01** b0.001*** 0.10 0.74 0.61 0.12 0.14 0.20 0.013* 0.57 0.14 0.07 0.26 0.97 b0.001*** b0.00001**** 0.23 0.13 0.20 0.92 0.80
R2*
Δχ
(1.7) (2.8) (1.8) (1.7) (1.1) (1.1) (1.1) (8.5) (11.7) (7.5) (5.8) (5.0) (7.1) (3.6) (41.5) (53.2) (32.2) (43.2) (18.5) (22.7) (16.3)
R2 and R2* values are in sec−1. Δχ values are in ppb. Values in parentheses are standard deviation. Symbols of “*” indicate significant difference: * pb0.05; **pb0.01; ***pb0.001; ****pb0.00001.
may be explained by the use of different imaging measures. In this work, we found a significant increase of R2* (p b 0.05), R2 (p b 0.01 and p b 0.001) and Δχ (p b 0.001 and p b 0.00001) values in the entire substantia nigra and in the pars compacta, respectively, for the PD patients (except R2* values for substantia nigra as a whole). These results are in agreement with other in vivo studies that found significant differences separately: on the SN R2 [8]; on the SNc R2 [6,7,9], R2* [14] and Δχ [28]. The R2* values of the basal ganglia, except for SNc, did not show significant differences between controls and patients (Table 2) as reported by Braffman et al., (1989) and Ordidge et al., (1994) [16,38] which disagree with other studies [8,10–13]. The controversy of the previous results may be due the R2* map to be influenced by the inhomogeneity of the magnetic field unrelated to iron accumulation [17] and by the effect of water diffusion in this inhomogeneous field [18] which has been well studied by many researchers [13,14,38]. Martin and colleagues [14] divided the substantia nigra into four regions: SN pars compacta medial, SN pars compacta lateral, SN pars reticulata medial and SN pars reticulata lateral. These authors reported significant variations in R2* (p b 0.005) just in the substantia nigra pars compacta lateral as we found on the SNc. Sofic and colleagues [5] demonstrated a selective increase of total iron content in Parkinsonian substantia nigra pars compacta but not in the substantia nigra pars reticulata. Therefore, our results confirm the in vivo results of Sofic et al., and we suggest the SNc as the specific region to study iron deposition in the PD. To validate our parameter estimations, linear regressions between R2, R2* and susceptibility values and the estimated iron for basal ganglia of healthy controls were performed and compared with other studies. Our results were close to the reported values in the literature [14,22,39,40] (Table 3). We also highlight that a change in the R2 values can be attributed to a change in the concentration or distribution of free water molecules. Moreover, changes in values of R2, R2* and QSM can be influenced by the accumulation of other paramagnetic ions (Cu+2), paramagnetic ion oxidation states and the coupling between them [28]. However the strong correlation of this parameter with the iron concentration suggests that iron is the dominant factor. The area under the ROC curve can be interpreted as the probability that the patient is diagnosed as PD compared to a healthy person. The test is classified as unable to determine patients and controls when it has an area equal to 0.5 and is perfect when equal to 1.0. In our analyses in the SN and SNc region, the QSM map had higher sensitivity to classify patients with Parkinson's disease (area = 0.77 ± 0.05 for both regions) than the R2 map (area = 0.67 ± 0.06 and area = 0.77 ± 0.05, respectively) and R2* map (area = 0.54 ± 0.06 and area = 0.65 ± 0.06, respectively) (Fig. 6).
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
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Fig. 6. ROC curve for R2, R2* and QSM maps of SN (left) and SNc (right).
As expected, the lateral asymmetries in healthy people were close to zero in all the calculated parameters in the basal ganglia. Although patients in the initial stage of Parkinson's disease have unilateral involvement with minimal disability, we did not find significant asymmetry in the R2, R2* and Δχ values. This is expected because the patients studied had more than 1 on the H&Y scale, and it is well-known that patients with more than 1 on the H&Y scale have bilateral involvement [41]. Moreover, there was no correlation between disease duration and R2, R2* and susceptibility values that suggests no change in the iron concentration in patients with 2 or more score on the H&Y scale. We used conventional sequences close to clinical practice to acquire the R2 and R2* mapping. The GRASE sequence was selected to acquire multi spin echo with multi-gradient echoes because of its rapid high resolution acquisition capabilities. Even though absolute R2 values may not be correct with this approach, relative values between patients and controls are expected to be unaffected by a possible error in R2 measurements. Other authors using spin echo approaches also found a significant increase of R2 values on the SN for patients with PD [6,8]. The multi-echo gradient-echo sequence was acquired to process R2* map. Similarly, Peran et al. (2010) acquired gradient echo sequence, and Du et al. (2011) did multigradient echo 3D with flow compensation on three directions. Gorrell et al. (1995), Martin and Weiler (2008) and Baudrexel et al. (2010) acquired gradient echo sequence added to the specific radio frequency pulse or gradient refocusing pulse to mitigate the signal loss caused by background macroscopic susceptibility gradients. Although these last three papers used the acquisition sequence with
specific artifacts removed, all authors found significant increases of R2* values in the SN or SNc for patients with PD. The main limitation of this study is the small number of patients studied. Patients were recruited with predominantly intermediate Hoehn and Yahr Scores [2–4]. Patients in the advanced stage of the disease (Hoehn and Yahr Score 5) have many tremors, body rigidity and physical debilitation, and would have been difficult to scan. One possible inaccuracy of our R2 values is related to the imperfections in the slice profile of the refocusing pulses and gradient echo acquisitions, even using a low EPI factor. Another limitation is the fact that only the most representative slice of the region of interest was evaluated and not the full 3D anatomical region. We preferred to select the slice of center position to avoid partial volume on the regions from extreme slices. Although the literature has shown strong linear correlation between the QSM values and local iron content on the basal ganglia [20,24], several factors can influence this relationship suggesting a non-linear relation, mainly, for regions with very low iron concentrations (e.g., myelin content (34)). In this study, it also used the more simplistic relationship; however the dispersion of the quantitative values measured in each region (Fig. 5) suggests a multifactorial relationship. 5. Conclusion Susceptibility measurements represent the most sensitive quantitative technique to detect a significant increase of iron in PD patients. The highest significant difference between controls and patients was found for the substantia nigra pars compacta.
Table 3 Linear regression coefficients among R2, R2* and Δχ values with estimated iron for controls. Map
Regions
R2
SN, RN, GP, PUT, CN, GM
R2*
SN, RN, GP, PUT, CN, WM
R2*
GP, PUT, CN, THA
Δχ
SN, RN, GP, PUT, CN, THA, GM
Linear regression Slope
Intercept
R2
0.61 0.42 1.0a 1.2 1.2 1.4 7.5 6.5
12.7 13.0 17.5a 21.3 14.2 19.2 – –
0.92 0.60 0.81 0.50 0.87 0.71 0.96 0.70
Image sequence
References
GESFIDE GRASE MGE GRASE GRE MGE GE MGE
GELMAN et al., 1999 Our results MARTIN et al., 2008 a Our results YAO et al., 2009 Our results Wharton and Bowtell (2010) Our results
All references were acquired in 3 T magnetic field, except Whartom and Bowtell (2010) that used 7 T. All the references estimated iron by Hallgren and Sourander (1956). In our results, we selected different regions for the same technique to compare with other reported results. The unit of the slope of both R2 and R2* is s−1/mgFe/100 g, and for Δχ it is ppb/mgFe/100 g. a Estimated values from the plot of Martin et al. (2008).
Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021
J.H.O. Barbosa et al. / Magnetic Resonance Imaging xxx (2015) xxx–xxx
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Please cite this article as: Barbosa JHO, et al, Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2*, Magn Reson Imaging (2015), http://dx.doi.org/10.1016/j.mri.2015.02.021