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. Author manuscript; available in PMC: 2024 Dec 1.
Published in final edited form as: Mov Disord. 2023 Sep 29;38(12):2282–2290. doi: 10.1002/mds.29613

Magnetic susceptibility in progressive supranuclear palsy variants, PD and corticobasal syndrome

Ryota Satoh 1, Stephen D Weigand 2, Thu Pham 3, Farwa Ali 1, Arvin Arani 3, Matthew L Senjem 3,4, Clifford R Jack Jr 3, Jennifer L Whitwell 3, Keith A Josephs 1
PMCID: PMC10840892  NIHMSID: NIHMS1931070  PMID: 37772771

Abstract

Background:

Previous studies have shown that magnetic susceptibility is increased in several subcortical regions in progressive supranuclear palsy (PSP). However, it is still unclear how subcortical and cortical susceptibilities vary across different PSP variants, Parkinson’s disease (PD) and corticobasal syndrome (CBS).

Objective:

This study aims to clarify the susceptibility profiles in the subcortical and cortical regions in different PSP variants, PD and CBS.

Methods:

Sixty-four patients, 20 PSP-Richardson syndrome (PSP-RS), nine PSP-parkinsonism (PSP-P), seven PSP-progressive gait freezing (PSP-PGF), four PSP-postural instability (PSP-PI), 11 PD and 13 CBS, and 20 cognitively normal controls underwent a 3 Tesla MRI scan to reconstruct quantitative susceptibility maps. Region-of-interest analysis was performed to obtain susceptibility in several subcortical and cortical regions. Bayesian linear mixed effect models were used to estimate susceptibility within group and differences between groups.

Results:

In the subcortical regions, PSP-RS and PSP-P showed greater susceptibility than controls in the pallidum, substantia nigra, red nucleus, and cerebellar dentate (p<0.05). PSP-RS also showed greater susceptibility than PSP-PGF, PD, and CBS in the red nucleus and cerebellar dentate, and PSP-P showed greater susceptibility than PD in the red nucleus. PSP-PI and CBS showed greater susceptibility than controls in the pallidum and substantia nigra. No significant differences were observed in any cortical region.

Conclusions:

The PSP variants and CBS had different patterns of magnetic susceptibility in the subcortical regions. The findings will contribute to our understanding about iron profiles and pathophysiology of PSP and may provide a potential biomarker to differentiate PSP variants, PD, and CBS.

Keywords: PSP, CBS, Quantitative susceptibility mapping, Iron, PSP-P

Introduction

Progressive supranuclear palsy (PSP) is a four-repeat (4R) tauopathy typically characterized by oculomotor dysfunction, posterior instability, akinesia, and cognitive dysfunction1, 2. The brainstem, midbrain, basal ganglia, thalamus, cerebellum, and cortex are affected in PSP3, although the pattern of impairment varies from case to case. PSP has a broad clinical spectrum in its initial presentation. The most typical subtype is PSP-Richardson syndrome (PSP-RS), as originally described by Steele, Richardson and Olszewski4, but many other clinical variants have gradually been recognized such as PSP-Parkinsonism (PSP-P)5, PSP-progressive gait freezing (PSP-PGF)6, and PSP-posture instability (PSP-PI)7. The International Parkinson and Movement Disorder Society (MDS)-endorsed PSP Study Group has recently developed guidelines for diagnosing the different clinical variants of PSP8. However, improvements are still needed to accurately diagnose these clinical variants and differentiate them from other related disorders such as Parkinson's disease (PD) and corticobasal syndrome (CBS) in their early stages. In fact, it is almost impossible to distinguish PSP-P early in the disease course from PD.

Neuroimaging studies are important for understanding the pathophysiology in different PSP clinical variants3. Quantification of atrophy in the midbrain and superior cerebellar peduncle (known as the Magnetic Resonance Parkinsonism Index, MRPI) is a useful biomarker to differentiate PSP from other parkinsonisms9 and also a potential marker to differentiate PSP clinical variants10-12. Atrophy in the frontal cortex may help differentiate PSP subcortical (e.g., PSP-P and PSP-PGF) and cortical (e.g., PSP-CBS and PSP-frontal) subtypes13. Our group also found that the subcortical and cortical spatial patterns of flortaucipir uptake varied in different PSP clinical variants13. Abnormal iron deposition is also a prominent feature of PSP14. One study investigated iron-sensitive MR relaxometry (R2*) in PSP-RS, PSP-P, and other parkinsonisms15, but to our knowledge, no studies have investigated iron profiles of other clinical variants such as PSP-PGF and PSP-PI.

Quantitative susceptibility mapping (QSM) is an advanced MRI technique that provides contrasts of the estimated magnetic susceptibility distribution16. QSM has been used in many neurodegenerative studies17 because of its sensitivity to paramagnetic iron deposition18 and diamagnetic myelin loss19. The QSM studies in PD have suggested that estimated susceptibility in the substantia nigra is more robust than relaxometry in differentiating PD from controls20 and that white-matter susceptibility may detect a reduction in myelin content21. The QSM studies in PSP also have shown that these patients have increased susceptibility in several subcortical regions such as pallidum and red nucleus, suggesting abnormal iron deposition in these regions22-24. However, to our knowledge, no studies have investigated magnetic susceptibility differences across different PSP clinical variants, PD and CBS. In addition, the above studies mainly focused on subcortical susceptibilities and did not investigate cortical susceptibility changes including the frontal lobe in PSP.

The aim of this study is to assess differences in magnetic susceptibility across PSP clinical variants, PD and CBS in disease-related subcortical and cortical regions. We hypothesized that these disorders have different magnetic susceptibility patterns in subcortical and cortical regions.

Materials and methods

Subjects

Fifty-one PSP, 11 PD, and 13 CBS patients were prospectively recruited by the Mayo Clinic, Neurodegenerative Research Group (NRG), between October 2018 and September 2022. All underwent detailed neurological tests including the Montreal cognitive assessment (MoCA)25, the frontal assessment battery (FAB)26, the Movement Disorders Society sponsored revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III)27, the PSP rating scale28, and the PSP Saccadic Impairment Scale (PSIS)29 as well as a 3 Tesla MRI scan with a multi-echo gradient echo sequence. Of the 51 PSP patients, 24 patients were PSP-RS, ten were PSP-P, seven were PSP-PGF, four were PSP-PI, two were PSP-CBS, two were PSP-corticospinal, one was PSP-frontal, and one was PSP-speech/language. The subtypes with one or two patients (PSP-CBS, PSP-corticospinal, PSP-frontal, and PSP-speech/language) were excluded due to insufficient sample sizes. Two PSP-RS cases and one PSP-P case were excluded due to poor gradient-echo image quality. Two PSP-RS cases were also excluded because they had intracerebral hemorrhage on QSM images. In total, 64 patients with 40 PSP (20 PSP-RS, nine PSP-P, seven PSP-PGF, and four PSP-PI), 11 PD and 13 CBS were included in the study. We did not include CBS-AD patients in the CBS cohort. All CBS patients underwent Pittsburgh compound B (PiB) amyloid PET, [18F] flortaucipir tau PET, and fluorodeoxyglucose (FDG) PET and none had evidence for underling AD. Twenty cognitively and motorically normal subjects who did not have any complaints of cognitive, motor, or behavioral abnormalities and had a score of ≥23 on the MoCA test30 and a score of 0 on the Hoehn and Yahr scale31 were also included. These controls were recruited by NRG over the same time period, and all underwent the same MRI scans.

This study was approved by the Mayo Clinic Institutional Review Board, and informed consent was obtained from all participants.

MRI analysis

All subjects underwent a standardized MRI protocol on a 3 Tesla scanner (Magnetom Prisma, Siemens AG, Healthineers, Erlangen, Germany), including a 3D magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence and a 3D multi-echo gradient-echo sequence. The imaging protocol and sequence parameters were the same as in previous studies32, 33. The gradient-echo sequence parameters were TR of 28.0 ms, TE of 6.7 ms, 10.6 ms, 14.5 ms, 18.4 ms, and 22.4 ms, flip angle of 15°, a 20-cm FOV, in-plane acquisition matrix of 384×269, slice number of 88, slice thickness of 1.8 mm, and GRAPPA acceleration factor of 2.0.

MRI images were processed using the same methods as previously reported33. Briefly, T1-weighted images from the MPRAGE scan were segmented into gray and white matter using templates and settings from the Mayo Clinic Adult Lifespan Template (MCALT). Brain atlases for regions of interest (ROI) analysis were nonlinearly registered from the MCALT space to each subject space using Advanced Normalization Tools (ANTs). The multi-echo images from the gradient-echo scan were processed to create brain masks and then reconstruct QSM images by using MATLAB and STI suite34-36. The reconstructed QSM images were then rigidly registered to the T1-weighted images by using statistical parametric mapping (SPM12) to apply the atlases to QSM images. MRPI9 was also measured by using T1-weighted images from the MPRAGE scan with ITK-SNAP software as previously described11.

ROI analysis

Magnetic susceptibility values were obtained in eight subcortical and 12 cortical regions of interest (ROIs) using brain atlases as described below. The regions were selected based on previous neuroimaging studies that reported abnormalities in PSP and CBS13, 37, 38. The eight subcortical ROIs included the caudate, putamen, pallidum, subthalamic nucleus, thalamus, substantia nigra, red nucleus, and cerebellar dentate. The 12 cortical ROIs were defined in the frontal and parietal lobes, including precentral gyrus, superior frontal gyrus (dorsolateral), middle frontal gyrus, inferior frontal gyrus, orbital frontal gyrus, rolandic operculum, supplementary motor area, superior frontal gyrus (medial), superior frontal gyrus (medial orbital), postcentral gyrus, superior parietal gyrus, and paracentral lobule. Susceptibility in the inferior frontal gyrus was defined as the average in the opercular and triangular parts of the inferior frontal gyrus. Susceptibility in the orbital frontal gyrus was defined as the average in the orbital part of the superior, middle, and inferior frontal gyri.

For each ROI, the mean susceptibility was calculated in the left and right hemisphere, respectively. Susceptibilities in each subcortical ROI were averaged as the sum of the gray and white matter masks. Susceptibilities in each cortical ROI were averaged separately in gray and white matter masks, respectively33, because gray and white matter have different compositions of magnetic susceptibility sources in the cortex39. The MCALT atlas40 (originally from the automated anatomical labeling atlas41) was used for four subcortical (caudate, putamen, pallidum, and thalamus) and all cortical ROIs; the Deep Brain Stimulation Intrinsic Template atlas42 was used for three subcortical ROIs (subthalamic nucleus, substantia nigra, and red nucleus); and an in-house developed atlas43 was used for the cerebellar dentate ROI.

Statistical analysis

Demographics and clinical scores were compared between clinical groups using a chi-squared test for categorical values and a Kruskal-Wallis test for continuous values using the MATLAB Statistics and Machine Learning Toolbox (The MathWorks Inc., Natick, Massachusetts, USA).

We used linear mixed effects models to estimate mean susceptibility by clinical groups, fitting one model per ROI44. Each model was adjusted for age, sex, and hemisphere with these terms modelled as fixed effects. The diagnosis was modelled as a random effect in order to obtain more stable and generalizable estimated mean values for each group and to reduce false positives45, 46. Treating diagnosis as a random effect can also be understood as a way to account for multiple comparisons, because this statistical approach addresses multiplicity by modeling the groups as a so-called random effect which uses statistical shrinkage or penalization to shrink the group-wise means closer to the overall average47. Subgroups with fewer participants tend to be affected more than subgroups with more participants. The data for each model included susceptibility in the participant's left and right hemispheres, and therefore participant number was included in the model as a random effect as well to account for intra-individual correlation and inter-individual heterogeneity. As a sensitivity analysis, we also examined potential confounding due to differences in disease duration, defined as time from symptom onset to MRI, by fitting the linear mixed model described above but adding disease duration as a random slope. This model can be interpreted as allowing for group-specific duration effects but allowing us to make group-wise comparisons holding disease duration fixed at a specific level (e.g., four years). These analyses were performed using R version 4.1.3, and models were fit using the brms package48 with default priors and 5000 iterations for each of four chains.

The discriminative ability for susceptibility (left and right side averaged) and MRPI was evaluated using the area under the receiver operating characteristic curve (AUC).

Results

The characteristics of the participants are shown in Table 1. The proportion of females varied across the groups while education levels were generally similar. There was a significant difference in age at MRI scan, with the oldest age observed in PSP-PGF. Disease duration (time from first symptom onset to time of MRI scan) also differed, with the longest duration observed in PSP-P. There were no significant differences on the FAB and MDS-UPDRS III. The MoCA score differed with the lowest score occurring in PSP-RS. The PSP rating scale also differed with the highest total scores occurring in PSP-RS and PSP-P and with the lowest score in PD. The PSIS scores also differed across groups with the greatest ocular motor impairment occurring in PSP-RS.

Table 1.

Demographics and clinical findings across PSP variants, CBS, PD, and control groups.

PSP-RS
(n = 20)		 PSP-P
(n = 9)		 PSP-PGF
(n = 7)		 PSP-PI
(n = 4)		 CBS
(n = 13)		 PD
(n = 11)		 Control
(n = 20)		 p
Female, n (%) 11 (55%) 4 (44%) 7 (100%) 0 (0%) 6 (46%) 4 (36%) 10 (50%) 0.06
Education, y 14 (12,18) 14 (14,16) 16 (12,18) 13 (12,16) 14 (13,16) 16 (12,16) 16 (16,18) 0.37
Age at scan, y 70 (66, 76) 69 (63, 72) 77 (72, 79) 64 (57, 72) 67 (63, 71) 70 (67, 78) 69 (63, 74) 0.04
Age at onset, y 66 (62, 71) 60 (56, 63) 75 (66, 78) 58 (52, 69) 64 (60, 66) 63 (59, 67) <0.01
Disease duration, y 3.7 (2.7, 4. 5) 10.0 (4.6, 10.9) 2.3 (1.9, 6.1) 4.6 (3.1, 6.9) 3.3 (2.3, 4.5) 6.7 (4.2, 11.1) <0.01
MoCA (/30) 19 (18, 25) 24 (19, 26) 25 (23, 27) 24 (22, 26) 24 (19, 25) *1 24 (23, 25) 26 (26, 28) <0.001
FAB (/18) 14 (10, 17) 15 (11, 16) *1 17 (15, 18) *1 17 (13, 18) 16 (11, 18) *1 16 (13, 17) *2 0.47
MDS-UPDRS III (/132) 41 (30, 60) 42 (36, 52) 40 (26, 53) 31 (18, 38) 30 (18, 52) 32 (23, 48) *1 0.21
PSP rating scale (/100) 40 (34, 47) 39 (37, 44) 26 (19, 32) 27 (17, 30) 28 (19, 40) *1 15 (11, 21) *1 <0.001
PSIS (/5) 3 (2, 4) 2 (2, 3) 1 (0, 1) 1 (0, 1) 1 (0, 1) *2 0 (0, 1) *1 <0.001
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Results are presented as median (first and third quartiles) for all continuous values. Only one*1 or two*2 participants had missing data in some cells. Abbreviations: MoCA = Montreal Cognitive Assessment; FAB = Frontal Assessment Battery; MDS-UPDRS III = Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Parts III; PSP = Progressive supranuclear palsy; PSIS = PSP Saccadic Impairment Scale.

Fig. 1 shows the mean susceptibility with 95% CIs in the eight subcortical regions. Asterisks indicate disease groups with greater susceptibility than controls at p<0.05. Several disease groups had greater susceptibility than controls in five subcortical regions including pallidum, subthalamic nucleus, substantia nigra, red nucleus, and cerebellar dentate. In particular, PSP-RS showed greater susceptibility than controls in the four regions (pallidum, substantia nigra, red nucleus, and cerebellar dentate) and PSP-P showed greater susceptibility in these five regions. PSP-PI showed greater susceptibility in the pallidum and substantia nigra. CBS showed greater susceptibility in the pallidum, substantia nigra, and red nucleus. PSP-PGF and PD did not show significant differences compared to controls. There were significant differences in susceptibility among the disease groups in the red nucleus and cerebellar dentate (p<0.05). Fig. 2 shows pairwise differences in mean susceptibility between disease groups for these two regions. In the red nucleus, PSP-RS had greater susceptibility than PSP-PGF, PSP-PI, CBS, and PD. PSP-P also had greater susceptibility than PD. In the cerebellar dentate, PSP-RS had greater susceptibility than PSP-PGF, CBS, and PD. The results were generally unchanged after correction for disease duration. The AUC value for discriminating PSP-P from PD in the red nucleus was 0.79, which was comparable to MRPI (AUC = 0.80, p = 0.94). All AUC values for comparison of each pair are shown in Table S1.

Fig. 1. Estimated susceptibility in the subcortical regions.

Fig. 1.

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Mean susceptibility in the eight subcortical regions. Asterisks indicate disease groups with greater susceptibility than controls (p<0.05).

Fig. 2. Differences in mean susceptibility in the red nucleus and cerebellar dentate between disease groups.

Fig. 2.

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Asterisks indicate significant differences (p<0.05). Bars show 95% CIs.

Fig. 3 shows the averaged susceptibility maps in each group at the basal ganglia, midbrain, and cerebellum levels. The same trends as in the ROI analysis were also observed visually in these maps. As shown by the arrows in Fig. 3, in the pallidum, the PSP variants and CBS had greater susceptibility compared to the control group. In the red nucleus and cerebellar dentate, the PSP-RS and PSP-P groups had greater susceptibility than the other disease groups and controls. In the substantia nigra, all disease groups had greater susceptibility than the control group. Susceptibility-weighted images for the same slices were also shown in Fig. S1.

Fig. 3. Averaged QSM images in each group.

Fig. 3.

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Arrows indicate the regions where greater susceptibility was visually observed compared to controls. These images were generated by performing spatial normalization into the template space (MCALT space), subtle smoothing with the small 3D Gaussian kernel (σ = 0.5 pixels), and voxel-wise averaging within each group.

Fig. S2 shows the mean susceptibility in the frontal (Fig. S2a) and parietal (Fig. S2b) gray-matter regions. In the cortical gray-matter regions there was little inter-group variability, and no significant differences were observed across groups in any ROI. Fig. S3 shows mean susceptibility in frontal (Fig. S3a) and parietal (Fig. S3b) white-matter regions. In the cortical white-matter regions, no significant differences were observed among the groups in any ROI.

Discussion

In this study, we investigated magnetic susceptibility changes in PSP clinical variants, PD and CBS in disease-related cortical and subcortical regions. In the cortical regions, there were no significant differences in susceptibility across groups. However, in the subcortical regions, PSP and CBS patients had greater susceptibility compared to controls in the pallidum and substantia nigra, with PSP also showing greater susceptibility in the red nucleus and cerebellar dentate. These regions are qualitatively consistent with the previous PSP studies using iron-sensitive MRI methods such as QSM22-24, MR phase images49, and relaxometry15. We also found that the patterns of increased susceptibility differed among several PSP variants and CBS and specifically between PSP-P and PD. The previous histological studies showed that the estimated magnetic susceptibility is strongly associated with the iron in the subcortical regions18, 50. Therefore, our results suggest that the amount of abnormal iron deposition in the subcortical regions is different among PSP clinical variants, PD and CBS. These findings of the differences in iron levels may be related to different tau levels between the different PSP clinical subtypes and CBS. This hypothesis is supported by many researchers who have argued that excessive iron is involved in adverse biological processes such as oxidative stress and tau aggregation14, 51, 52.

PSP-RS and PSP-P showed greater susceptibility in the pallidum, substantia nigra, red nucleus, and cerebellar dentate compared to controls. In addition, PSP-RS also had greater susceptibility in the red nucleus and cerebellar dentate compared to PSP-PGF, PSP-PI, CBS, and PD. The greater involvement of both the red nucleus and cerebellar dentate is reasonable since these two nuclei are connected via the dentatorubrothalamic tract. Our group recently found that the dentatorubrothalamic tract is severely degenerated in autopsy-confirmed PSP-RS53. Other studies have also found more midbrain atrophy in PSP-RS patients compared to other PSP subtypes such as PSP-PGF10, 11. Our findings in PSP-RS are consistent with these MRI studies, and susceptibility in these two regions could be a potential biomarker to differentiate PSP-RS from PSP-PGF and PSP-PI, as well as from PD and CBS.

One of the most important findings of this study was that PSP-P had greater susceptibility in the red nucleus compared with PD. This result concurs with the study using relaxometry15 in which the R2* values in PSP-P were significantly greater than those in PD. In the previous QSM studies24, 54, 55, red nucleus susceptibility prominently increases in PSP compared with other parkinsonian disorders and controls. Although the discriminative ability of QSM was comparable to MRPI in this study, we expect QSM to provide complementary information in the early disease course given that these two biomarkers address different aspects of the pathophysiology: QSM for iron deposition and MRPI for atrophy. In other words, our results offer hope that red nucleus susceptibility could be a potential useful biomarker to distinguish PSP-P from PD in the earlier disease course when clinical symptoms are indistinguishable. Further studies are needed that include PSP patients in earlier stages of the disease, longitudinal follow-up, and autopsy confirmation.

PSP-PGF did not show significant differences from controls in any subcortical region, suggesting relatively less iron deposition in this subtype. These results are consistent with the previous MRI studies that found relatively preserved local brain volumes in PSP-PGF compared to PSP-RS11, 12.

PSP-PI showed greater susceptibility than controls in the pallidum and substantia nigra. Although there is a lack of neuroimaging studies in PSP-PI, our results suggest abnormal iron deposition in these two regions. The finding in the pallidum is consistent with the previous findings that the basal ganglia are deeply involved in a postural control56.

CBS had greater susceptibility than controls in the same regions as PSP-RS (pallidum, substantia nigra, and red nucleus), but had smaller mean values than PSP-RS in these regions. CBS-AD was not included in our cohort, and therefore most of our CBS patients are likely to have a 4R tauopathy such as CBD (CBS-CBD) or PSP (CBS-PSP) pathologies. There are two possible reasons why CBS was less prominent than PSP-RS in some subcortical regions. First, pathological studies have shown that CBD generally have severe involvement in the pallidum and substantia nigra, but less involvement in some other subcortical nuclei such as the cerebellar dentate compared with PSP57. This may explain why the susceptibilities in cerebellar dentate and red nucleus were significantly smaller in CBS than in PSP-RS, while there were no significant differences between CBS and PSP-RS in pallidum and substantia nigra, in our study. Second, based on the midbrain/pons ratio from recent studies11, 58, we speculate that PSP pathologies in CBS-PSP patients have less subcortical involvement compared with typical PSP-RS patients, which may have also resulted in less subcortical susceptibility in CBS than in PSP-RS in our study. Further validation including pathologically confirmed CBS-CBD and CBS-PSP patients will be needed in the future to confirm these hypotheses in more detail.

No susceptibility differences were observed in the cortex, although we expected some cortical changes, especially in CBS, since it predominantly affects the cortex. Our results may indicate that susceptibility changes in the cortex are relatively small compared to the subcortical regions in PSP and CBS. Alternatively, these results may be related to the relatively small dynamic range of the estimated cortical susceptibility on QSM images36. Indeed, the susceptibility differences in the cortex were relatively small compared to those in the subcortical regions and should therefore be more vulnerable to disturbances like noise and artifacts. Since our study was limited to the inclusion of subcortical variants of PSP, further investigation of cortical susceptibilities is needed on the cortical variants of PSP including PSP-CBS, PSP-frontal, and PSP-speech/language. We hypothesize that some cortical variants may show changes in cortical susceptibility because our group recently found that patients with progressive apraxia of speech, which is strongly associated with PSP-speech/language59, had greater susceptibility than controls in the white-matter precentral gyrus33.

The strength of this study is the novelty of applying QSM to the different PSP variants because, to our knowledge, no studies have addressed the susceptibility differences between different PSP clinical variants, PD, and CBS by using QSM. One of the limitations is that the number of patients is unbalanced between groups and some groups had relatively small numbers of patients (e.g., n = 4 in PSP-PI). Still, our statistical approach of modeling clinical group as random effect accounts for these limitations and enables us to make robust inferences about group-wise differences. Another limitation is that the PSP and CBS patients are not confirmed by autopsy, which should be addressed in the future. In addition, all patients were clinically diagnosable, i.e., they were not all in early stages, where improvements in diagnostic accuracy are more needed. Further longitudinal studies are now needed to evaluate its utility as an early biomarker by assessing patients in earlier stages of the disease. Lastly, it should be noted that disease duration from first reported symptoms to MRI scan is different among groups, with the longest duration in PSP-P. And while this is unavoidable at present given that a diagnosis of PSP-P cannot be made until later in time when classic features of PSP develop, we confirmed that the results were generally unchanged before and after correction for disease duration. Therefore, the longest disease duration in PSP-P does not appear to be an important factor in their greater susceptibilities.

In conclusion, we have investigated magnetic susceptibility differences across several PSP clinical variants, PD, and CBS patients. The results showed that most of these variants and CBS had different patterns of greater susceptibility compared to controls in subcortical regions. There were also susceptibility differences among disease groups in the red nucleus and cerebellar dentate. These findings contribute to our understanding of iron profiles and pathophysiology of PSP neurodegeneration and may provide a potential biomarker to differentiate PSP clinical variants, PD and CBS.

Supplementary Material

Supinfo

Acknowledgements

The authors would like to thank the patients and their families for participation in our research studies. We would also like to thank Mrs. Sarah Boland and Ms Megan Broeren for contacting scheduling the clinical and MRI examinations.

Funding Sources for study:

This study was funded by NIH grant R01-NS89757 (MPIs: Whitwell and Josephs)

Footnotes

Financial Disclosure/Conflict of Interest concerning the research related to the manuscript: Nothing to report.

Financial disclosure for the previous 12 months

R.S., S.D.W., and M.L.S have no financial disclosure to report. F.A., A.A., C.R.J.J., J.L.W., and K.A.J. receive research funding from National Institutes of Health. K.A.J. is an Associate Editor of the Annals of Clinical and Translational Neurology and an editorial board member of Acta Neuropathologica and Neuropathology and Applied Neurobiology.

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