Introduction
Gait issues in Parkinson’s disease (PD) are widespread and diverse in nature. These include decreased gait speed and step length, increased gait variability, and freezing of gait (FOG). Reference Mirelman, Bonato and Camicioli1 FOG manifests as hesitation when initiating walking, trying to turn, or navigating tight spaces. Reference Fahn2,Reference Schaafsma, Balash, Gurevich, Bartels, Hausdorff and Giladi3 Gait impairment in PD portends a poor prognosis Reference Choi, Jung, Yoon and Kim4 and increases risk of falls and cognitive impairment. Reference Morris, Lord and Lawson5
Susceptibility-based MRI methods including susceptibility weighted imaging (SWI), relaxometry (R2, R2*), and quantitative susceptibility mapping (QSM) have shown elevated iron content in the brains of PD patients in the subcortical structures. Reference Chen, Chen and Zhang6,Reference Wang, Zhuang and Zhu7 However, there is a paucity of literature relating iron detected with susceptibility-based MRI methods with gait in PD.
Studies that have used susceptibility-based MRI methods in relation to gait have compared estimates of iron content in deep gray matter structures to measures of gait impairment (namely FOG) and PD with postural instability-gait disorder (PIGD). Two studies demonstrated increased R2* in the substantia nigra pars compacta in PD patients with FOG relative to PD patients without FOG. Reference Naduthota, Honnedevasthana and Lenka8,Reference Wieler, Gee, Camicioli and Martin9 Another study using SWI found significantly decreased signal intensity in the putamen and globus pallidus in PIGD patients compared to non-PIGD PD patients, with signal intensities of the putamen being positively correlated with the Tinetti balance score. Reference Schneider, Ng and Yeoh10 Increased susceptibility has also been seen in PIGD versus healthy controls in the substantia nigra pars reticulata and pars compacta using QSM. Reference Chen, Cai and Li11 In addition, SWI has been used to quantify the number of cerebral microbleeds in PD patients, where those with PIGD had significantly more cerebral microbleeds than other subtypes of PD. Reference Chiu, Chan, Wu, Ko, Chen and Hong12 More studies are needed to determine the validity of QSM as an imaging tool to predict PD gait impairment, and more aspects of gait need to be compared to QSM outside of looking solely at FOG.
The objectives of this study were to compare QSM in various brain region of interests (ROIs) in PD patients without dementia versus cognitively unimpaired (CU) participants and to ascertain if there was a relationship between iron content in specific ROIs and both qualitative and quantitative measures of gait which has not been investigated by other studies to date. We hypothesized that basal ganglia structures would show altered iron signal in relation to gait impairment. Specifically, we hypothesized that gait would be related to basal ganglia structures with direct dopamine projections (i.e., caudate and putamen), while FOG would be related to the final common basal ganglia output (i.e., globus pallidus).
Materials and Methods
Participants
Participants were included from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND). Reference Chertkow, Borrie and Whitehead13 COMPASS-ND is a Canadian national study investigating those with dementia or other cognitive concerns that is observational in nature. Reference Chertkow, Borrie and Whitehead13 This sub-study of COMPASS-ND (Pro00061456) was approved by the University of Alberta Research Ethics Board (Pro00099707). All participants provided written informed consent for the study. CU participants were from the COMPASS-ND study and CBBRAIN, a neuroimaging study of healthy controls. Reference Treit, Naji and Seres14 For the CBRAIN study, participants underwent cognitive screening using the National Institutes of Health Toolbox Cognitive Battery Reference Denboer, Nicholls, Corte and Chestnut15 which encompasses testing for verbal recall, working memory, processing speed, and episodic memory where participants needed to score within two standard deviations of the mean; participants also could not have a self-reported history of brain injury, neurologic or psychiatric conditions. Reference Solar, Treit and Beaulieu16 Inclusion and exclusion criteria for the PD participants were the same as for COMPASS-ND in general (outlined below, also see Reference Chertkow, Borrie and Whitehead13,Reference Pieruccini-Faria, Black and Masellis17 for additional information). Consecutive patients with PD or PD with mild cognitive impairment (MCI) at the University of Alberta were included. Participants with PD (with or without MCI but without dementia; n = 29, referred to as the PD group) and age-matched CU (n = 27) were included. PD participants were not selected per se but, rather, were subjects that were willing to undergo additional neuroimaging at the University of Alberta that included QSM. This included patients who were on treatment and not on treatment. Patients who had undergone deep brain stimulation prior to study initiation were not included.
Functional impairment on the basis of cognition was necessary for the diagnosis of dementia. A Montreal Cognitive Assessment (MoCA) score <25 in a participant who otherwise met criteria for PD (based on the MDS criteria for MD) Reference Postuma, Poewe and Litvan18 defined PD-MCI, consistent with published criteria. Reference Litvan, Goldman and Troster19 PD participants could be taking PD medications: levodopa equivalent daily dose was calculated. Reference Tomlinson, Stowe, Patel, Rick, Gray and Clarke20 Exclusion criteria have been published and included significant known chronic brain disease, developmental disorders, malignant tumors, current alcohol or drug abuse, lack of a study partner, insufficient proficiency in English or French, total MoCA score of less than 13, inability to comprehend test instructions, and incapable of walking more than 10 m independently. Reference Chertkow, Borrie and Whitehead13,Reference Pieruccini-Faria, Black and Masellis17
Participant Assessments
Patient assessments include the Movement Disorders Society United Parkinson’s Disease Rating Scale (MDS-UPDRS). Items from Part II (patient’s view of motor aspects of experiences of daily living) and Part III of the MDS-UPDRS (motor examination completed by the clinician) addressing gait difficulties and FOG were used. Reference Goetz, Tilley and Shaftman21 The items included were 2.12 (difficulties with walking and balance), 2.13 (freezing), 3.10 (general gait impairment), and 3.11 (FOG specifically). Hoehn and Yahr scores provide an estimation of overall impairment in an individual with PD. Reference Goetz, Poewe and Rascol22
Image Acquisition
Whole brain QSM images were acquired on a 3T (Siemens Prisma) scanner using a 20-channel head coil. Acquisition parameters were as follows: axial multi-gradient echo sequence with seven echoes (first echo at 3.82 ms and subsequent echoes spaced at 5.49 ms), TR = 45.0 ms, flip angle = 17°, 80 slices, 2.0 mm slice thickness for a total coverage of 160 mm, 240 × 218 mm FOV, voxel dimensions 0.9 mm × 0.9 mm × 2.0 mm = 1.62 mm3 without interpolation, parallel imaging (generalized autocalibrating partially parallel acquisitions (GRAPPA) with an acceleration factor of 2), and a scan time of 5.65 minutes. Whole brain sagittal T1-weighted images were acquired using 3D magnetization-prepared rapid gradient echo (MPRAGE) with the following parameters: 192 slices, 1.0 mm slice thickness; 256 mm FOV; image matrix 256 × 256; voxel size of 1.0 mm × 1.0 mm × 1.0 mm = 1.0 mm3 with no subsequent interpolation; TR = 2300 ms; TE = 2.98 ms; TI = 900 ms; flip angle 9°; parallel imaging (GRAPPA with acceleration factor of 2); scan time of 5.35 minutes.
Processing of Susceptibility Maps
After saving raw phase images, QSM was reconstructed using a series of steps including phase unwrapping, background field removal, and then susceptibility inversion. Reference Sun, Walsh and Lebel23 Briefly, brain tissue was extracted using brain extraction tool Reference Smith24 on the magnitude image of the first echo; coil-combined phase was unwrapped using phase region expanding labeler for unwrapping discrete estimates (PRELUDE), Reference Jenkinson25 background field was removed with the regularization enabled sophisticated harmonic artifact reduction on phase data (RESHARP) method, Reference Sun and Wilman26 and dipole inversion via total variation. Reference Bilgic, Pfefferbaum, Rohlfing, Sullivan and Adalsteinsson27
ROI Analysis
ROIs investigated in our study included the caudate nucleus, globus pallidus, putamen, pulvinar nucleus of the thalamus, substantia nigra, red nucleus, and dentate nucleus. These were selected based on previous studies that have looked at and shown susceptibility changes in PD patients. Reference Chen, Cai and Li11,Reference Cheng, Huang and Liang28
Using ImageJ (https://imagej.nih.gov/ij/, 1997–2021), ROIs were drawn manually on the susceptibility maps by a single rater (NN) who was blinded to participant group using three separate axial slices. The slice with the largest cross section of the globus pallidus that also enabled visualization of each of the caudate nucleus, putamen, and pulvinar nucleus of the thalamus was selected as the first slice for looking at the aforementioned ROIs. ROIs were drawn bilaterally on the most central part of each area of interest (caudate nucleus, putamen, globus pallidus, pulvinar nucleus of the thalamus) with attention being given to avoid encompassing the edges of a given ROI to avoid inclusion of noise in the susceptibility measurement as much as possible. ROIs were placed bilaterally on a more caudal single slice in axial orientation (second slice) that best delineated the substantia nigra and red nucleus. ROIs for the dentate nucleus were placed bilaterally on an even more caudal single slice (third slice) that delineated this structure best.
The posterior limb of the internal capsule was examined as a reference region for which the ROI was drawn bilaterally on the same slice as the one that was used to outline the caudate, putamen, globus pallidus, and pulvinar nucleus of the thalamus (Figure 1). For each ROI tracing aside from the substantia nigra which was drawn individually for each subject, the size of each individual ROI was kept consistent across all subjects to enable for more consistent susceptibility measurements. Tracing was repeated on data from 10 randomly selected participants after an interval of 1 week to determine intra-rater reliability.
Sample quantitative susceptibility map outlining the regions of interest selected for analysis.
Volumetric Analysis
To determine the presence or absence of atrophy of structures included as ROIs, volumetric analysis was undertaken using T1-weighted images. Automated segmentation of subcortical brain regions and ventricles was performed using the "recon-all" pipeline in FreeSurfer (v6.0). Reference Fischl29 Processing was done on the Canadian Brain Imaging Research Platform, Reference Sherif, Rioux and Rousseau30 a web-based software for distributed computing for neuroimaging research. Volumes of the caudate, putamen, globus pallidus, thalamus, and intracranial volume were estimated. The left and right volumes were summed and reported as a % of intracranial volume (summed volume/intracranial volume × 100%).
Clinical Gait Assessment
The original FOG questionnaire (FOGQ) developed by Giladi and colleagues was used. Reference Giladi, Shabtai, Simon, Biran, Tal and Korczyn31 This is a self-reported questionnaire with items addressing different aspects of gait which include the following: need for assistance during the individual’s worst state of gait; if gait difficulties are affecting activities of daily living; if feet feel glued to the floor while walking or turning (freezing); the duration of the freezing episode; the duration of the typical start hesitation (freezing at time of gait initiation); and the duration of turning hesitation (freezing when turning). Reference Giladi, Shabtai, Simon, Biran, Tal and Korczyn31
The PD group was classified into two different ways with respect to gait. First, participants were categorized as gait impaired if FOGQ total score ≥ 1 (n = 23) or not have gait impairment (n = 6). Second, participants were divided into those with FOG (FOG+, n = 12) and those without (FOG−, n = 17) where the FOG+ group consisted of the participants who scored ≥1 on items 3–6 inclusive. This approach was chosen as other studies have used only item 3 from the FOGQ Reference Naduthota, Honnedevasthana and Lenka8,Reference Canu, Agosta and Sarasso32 ; however, items 4−6 also encompass other pertinent measures of freezing (i.e., duration of freezing episode, start hesitation, turning hesitation) which would help reflect the degree of FOG.
Quantitative Gait Assessment
Quantitative gait measures were determined as previously described in the ON state (on medication). Reference Pieruccini-Faria, Black and Masellis17,Reference Cullen, Montero-Odasso and Bherer33 In brief, participants were instructed to walk on a 6 m electronic walkway (Zeno®- Protokinetics™) at their self-selected pace, starting 1 m from the walkway and ending 1 m beyond the walkway to minimize recording of accelerations and decelerations. Three trials were performed, and gait parameters were derived using Zeno®- Protokinetics™ software (stride velocity, cadence, stride length, step time, stride time variability, and double support time).
Statistical Analyses
GraphPad Prism (version 9.0.2; GraphPad Software, LLC) was used for statistical analyses. To compare groups with respect to participant demographics, all continuous variables were compared using two-sided t-tests and all categorical variables were compared using Fisher’s exact test, with the exception of Hoehn Yahr score distribution between the groups, which was compared with Chi-squared test.
Intra-class correlation coefficient was used for 10 participants who had repeat ROI tracing (test, re-test, blinded to participant group in all instances, conducted by NN) to determine intra-rater reliability. To compare QSM values for each ROI between the left and right sides in CU and PD, unpaired t-tests were used. As there was no significant difference between left and right sides for any ROIs in CU and PD (p > 0.05), the average of left and right-side values was used for the remainder of analysis.
To test for whether the data followed a normal distribution or not, the D’Agostino and Pearson test was used. To compare QSM values for each ROI between CU and PD, unpaired t-tests were used for data that was normally distributed; in cases where data were not normally distributed, the Mann–Whitney nonparametric test was used instead. Pearson correlation coefficient was used to look for correlation between age and QSM values for each ROI in CU and PD; to look for correlation between sex and QSM values for each ROI in CU and PD; and to look for correlation between UPDRS-III total score and QSM values for each ROI in PD. In cases where data were not normally distributed, the Spearman correlation nonparametric test was used instead.
Unpaired t-tests were used to compare QSM values for each ROI between gait impaired and non-gait impaired PD participants. Unpaired t-tests were used to compare each of the quantitative gait measures between gait impaired and non-gait impaired PD participants. As above, in cases where data were not normally distributed, the Mann–Whitney nonparametric test was used instead. Unpaired t-tests were used to compare ROI volumes between gait impaired and non-gait impaired, and FOG+ versus FOG−. A p-value of 0.05 (two-tailed) was deemed statistically significant.
Results
Description of Participant Population
Participants in the CU group and PD group were age matched but not sex matched. The CU group had 12 males and 15 females, while the PD group had 20 males and 9 females. The average age of CU participants was 64.4 ± 6.2 years (mean ± standard deviation). Demographics of the PD participants are shown (Table 1). No patients were on cholinergic medications.
Demographics of 29 PD participants. All values reported as mean ± standard deviation or count (%)
PD = Parkinson’s disease; MoCA = Montreal Cognitive Assessment; LEDD = levodopa equivalent daily dose; UPDRS = United Parkinson’s Disease Rating Scale; FOGQ = freezing of gait questionnaire.
Reliability of the Analysis Method
Intra-class correlation coefficients were >0.90 (p < 0.001) except for the right globus pallidus which was 0.70 (p = 0.04). No differences were found between right and left sides for each ROI studied in CU or PD (p > 0.05) and so were combined for subsequent analyses.
Relationship between Susceptibility and Sex, Age, MoCA in CIE and PD participants
The mean susceptibility of ROIs in relation to sex in CU and PD showed a significant difference for the globus pallidus in CU (r = 0.39, p = 0.05, Spearman correlation), but otherwise no significant differences were seen for any other ROIs in CU or PD (p > 0.05 for all). In CU, there was a significant correlation between age and susceptibility in caudate nucleus (r = −0.45, p = 0.02, Pearson correlation coefficient) and dentate nucleus (r = −0.53, p = 0.01, Pearson correlation coefficient). In PD participants, there was no correlation between age and susceptibility in any of the ROIs (p > 0.05 for all). With respect to cognitive function, there was only a significant negative correlation between susceptibility of the dentate nucleus and MoCA scores in PD (r = −0.47, p = 0.01) but not for the rest of the ROIs, even with a MoCA score of <25 as a cut-off (all p > 0.05). As there few significant differences with no real consistent pattern when comparing susceptibility for the ROIs and sex, age, or cognitive status, these variables were not analyzed as co-variates for subsequent analyses.
Comparison of Susceptibilities of ROIs Between CU and PD
Susceptibility for each ROI in the 27 CU participants and the 29 PD participants is shown (Table 2). There was no significant difference between CU and PD for any ROI (all p > 0.05). Re-analyzing the data using the posterior limb of the internal capsule as a reference region did not change the significance for any ROI (all p > 0.05).
Susceptibility values (ppm) in CIE (n = 27) and PD (n = 29)
CU = cognitively unimpaired; PD=Parkinson’s disease.
Relationship Between Susceptibilities and Qualitative Measures of Gait Impairment in PD
Comparing PD participants with gait impairment (n = 23) versus those without gait impairment (n = 6), there was a significant difference in susceptibility for the putamen (p = 0.008, Mann–Whitney test; Figure 2a), red nucleus (p = 0.01, unpaired t-test; Figure 2b), and caudate nucleus (p = 0.03, unpaired t-test; Figure 2c) but not for the pulvinar, posterior limb of the internal capsule, substantia nigra, or dentate nucleus (all p > 0.05; Table 3). When separating FOG+ (n = 12) versus FOG− (n = 17), there was a significant difference in susceptibility for the globus pallidus only (p = 0.03, Mann–Whitney test) but not for the other ROIs (all p > 0.05; Table 3).
Susceptibility values in those Parkinson’s disease patients with gait impairment compared to those without gait impairment in the (a) putamen, (b) red nucleus, and (c) caudate nucleus.
Susceptibility values (ppm) in gait-impaired (n = 23), non-gait-impaired (n = 6), FOG+ (n = 12), and FOG− (n = 17) PD participants
FOG = freezing of gait.
Relationship Between Susceptibilities and Quantitative Measures of Gait Impairment in PD
There was no significant difference between gait-impaired versus not-gait-impaired PD participants in any quantitative gait measures (all p > 0.05, Supplemental Table 1). For FOG+ versus FOG−, there was a significant difference between groups only for stride time variability (p = 0.04, Supplemental Table 1).
Relationship Between Volumes of ROIs and Gait Impairment or FOG in PD
Volumes did not differ for any ROIs measured (caudate, putamen, globus pallidus, thalamus) between gait impaired versus not-gait impaired (all p > 0.05) or FOG+ versus FOG− (all p > 0.05) in PD participants.
Discussion
In this study, PD participants with gait impairment had increased susceptibility in basal ganglia (caudate, putamen) and extra-basal ganglia structures (red nucleus) compared to PD participants without gait impairment. For FOG specifically, susceptibility was increased in FOG+ PD participants in the globus pallidus versus FOG− PD participants. This suggests that gait impairment in general can lead to susceptibility changes across multiple structures, whereas FOG has a more focused localization in the globus pallidus, aligning with our hypothesis.
Aside from stride time variability in FOG+ versus FOG−, there was no between-group difference in any other quantitative gait measures. A recent study showed that microstructural changes in the thalamus and caudate detected with DTI correlated with quantitative gait parameters in PD patients, with different correlations in the ON (on medication) versus OFF state (off medication). Reference Surkont, Joza, Camicioli, Martin, Wieler and Ba34
The most likely substrate for the susceptibility changes seen is iron, though calcium and altered myelination could also contribute. Though we only used QSM, a meta-analysis looking at the different types of susceptibility MRI for iron deposition in PD found that QSM was the most reproducible of the susceptibility MRI methods. Reference Pyatigorskaya, Sanz-Morere and Gaurav35 Furthermore, the differences in susceptibility were not due to atrophy of these structures leading to more concentrated iron, as volumes of the ROIs studied were not significantly different between groups. The susceptibility obtained with QSM for the ROIs studied was similar to what has been measured by others. Reference Bilgic, Pfefferbaum, Rohlfing, Sullivan and Adalsteinsson27,Reference Acosta-Cabronero, Betts, Cardenas-Blanco, Yang and Nestor36 Presuming that the susceptibility changes are primarily due to iron, the question that follows is what does the increase in iron deposition indicate? Some proposed mechanisms include buildup of iron in dopaminergic neurons with subsequent production of reactive oxygen species, altered iron trafficking, and increased expression of α-synuclein which can lead to both increased levels and redistribution of iron in neurons. Reference Ma, Gholam Azad and Dharmasivam37,Reference Ortega, Carmona and Roudeau38
Degeneration in dopamine rich structures would be postulated to lead to impaired response to dopamine treatment. Gait disorders are particularly implicated. The association between increased susceptibility in the caudate and putamen is consistent with this hypothesis. In contrast, the globus pallidus is the main outflow from the basal ganglia. Recent studies have showed that diffusion changes in the globus pallidus are associated with FOG. Reference Kou, Wang and Zheng39,Reference Lench, Keith and Wilson40
Within the landscape of susceptibility MRI studies in PD investigating the relationship between susceptibility and gait, our study aligns with another study demonstrating susceptibility changes in the putamen and globus pallidus. Reference Schneider, Ng and Yeoh10 Our study complements these susceptibility and diffusion MRI studies by showing that susceptibility changes in the globus pallidus are also implicated in FOG. Others have shown changes in the substantia nigra Reference Naduthota, Honnedevasthana and Lenka8,Reference Wieler, Gee, Camicioli and Martin9,Reference Chen, Cai and Li11 which we did not see, perhaps due to differences in methodologic details and patient selection.
One strength of this study was that the method used for evaluating the ROIs was simple and demonstrated good intra-rater reliability and thus can be replicated by others rather than relying on automatic segmentation that may lead to variable results depending on the assumptions inherent to the software used. The use of a broader definition of gait impaired, encompassing use of specific items from the FOGQ rather than just using item 3 as others have, Reference Naduthota, Honnedevasthana and Lenka8,Reference Canu, Agosta and Sarasso32 was also a strength as we were able to identify ROIs with significant differences that would have otherwise been missed. As such, this is the first study to our knowledge that demonstrates distinct elevated iron content in the basal ganglia and extra-basal ganglia structures that relate to gait impairment and FOG in PD.
The simplicity of our method was a strength but could conversely be viewed as a weakness as we did not encompass the entire ROI. Nonetheless, our values were similar to those reported by others, suggesting that this method could be used reliably. Reference Bilgic, Pfefferbaum, Rohlfing, Sullivan and Adalsteinsson27,Reference Acosta-Cabronero, Betts, Cardenas-Blanco, Yang and Nestor36 Another weakness was using single time points for gait and MRI, while patients were in the ON state. Hence, we were only examining features not responsive to medications. Furthermore, how the relationships between susceptibility values in these ROIs and gait evolve over time is unknown. Future studies would be enhanced with longitudinal imaging and multimodal imaging to see how susceptibility changes over time and to help clarify the relationship between different markers of neuronal damage and plasticity, respectively. Lastly, our study had imbalances in sex distribution with CU not being matched for sex. Consecutive PD patients and CU participants were used for analyses and balanced as well as possible given the available sample.
Conclusions
Susceptibility in basal ganglia and extra-basal ganglia structures is differentially related to gait impairment and FOG in PD patients. This warrants further investigation to ascertain the link between altered susceptibility suggestive of iron deposition and gait impairment.
Supplementary Material
To view supplementary material for this article, please visit https://doi.org/10.1017/cjn.2022.316.
Acknowledgments
This work was funded by the Canadian Consortium in Neurodegeneration in Aging (CCNA), the Canadian Institutes of Health Research (CIHR), Alberta Innovates, and the Canada Research Chairs. The study was performed on behalf of Team 8 (Lewy bodies, Aging and Dementia; Richard Camicioli, team lead) of CCNA which is supported by a grant from CIHR and with funding from several partners.
Conflict of Interest
None to declare.
Statement of Authorship
All authors participated in study conception and design, and interpretation of results. All the co-authors contributed to the project implementation and data collection. The first author analyzed data and drafted the first version of manuscript. The last author supervised the whole process. All authors revised and approved the manuscript before submission and take responsibility for contents of the article.
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