Poster No:
217
Submission Type:
Abstract Submission
Authors:
Jinxin Chen1, Gaurav Rathi1, Alan Gardner1, Jason Longhurst2, Zoltan Mari3, Virendra Mishra1
Institutions:
1University of Alabama at Birmingham, Birmingham, AL, 2Saint Louis University, St. Louis, MO, 3Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV
First Author:
Jinxin Chen
University of Alabama at Birmingham
Birmingham, AL
Co-Author(s):
Gaurav Rathi
University of Alabama at Birmingham
Birmingham, AL
Alan Gardner
University of Alabama at Birmingham
Birmingham, AL
Zoltan Mari
Cleveland Clinic Lou Ruvo Center for Brain Health
Las Vegas, NV
Introduction:
Freezing of gait (FOG) is a debilitating motor symptom affecting a subset of individuals with Parkinson's Disease (PD). Morphological metrics such as cortical thickness (CT) and surface area (SA) from conventional T1-weighted MRI may provide valuable insights into the neuroanatomical correlates of PD-FOG. We hypothesize that PD-FOG will exhibit distinctive cortical morphological differences when compared to PD patients without FOG (PD-nFOG) and healthy controls (HC). More specifically, we expect to observe differences in CT and SA in cortical regions involved across the three groups, providing further insights into the structural variations associated with PD-FOG. Moreover, we expect to see a significant correlation between the decreased CT and SA with clinical measures such as Part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and freezing of gait questionnaire (FOGQ) in the PD-FOG cohort, indicative of altered morphological changes associated with PD-FOG.
Methods:
A total of 45 individuals were recruited at Cleveland Clinic Lou Ruvo Center for Brain Health. Among these, 15 participants were categorized as PD-FOG, 15 were PD-nFOG, and 15 were HC. The diagnosis of PD-FOG was determined by a movement disorders specialist and a physical therapist (PT) using direct observation of the participant while performing FOG-inducing PT tasks. All participants utilized in this study underwent a comprehensive MRI examination and were scanned with the following T1-weighted MRI acquisition parameters on a 3T Siemens Skyra MRI scanner: resolution=1mm...3, TR/TE=2300/2.96ms. Following the guidelines outlined by Freesurfer developers, the acquired MRI data underwent the FreeSurfer 7.0 processing pipeline. To verify quality and reliability, the data underwent a dual quality check process that encompassed both manual and automatic methods. The manual method consisted of viewing the reconstructed T1 images of all patients and checking for any errors in their segmentation. If there were any segmentation errors, the errors were corrected manually. The automatic quality check method involved the utilization of the Computational Anatomy Toolbox (CAT). We computed vertexwise CT and SA of each participant and performed the statistical comparison and correlational analyses using the Permutation Analysis of Linear Models (PALM) toolbox integrated within FSL. To account for potential confounding variables, we regressed for sex, handedness, levodopa equivalent daily dose, and intracranial volume. Threshold-Free Cluster Enhancement (TFCE) was employed to detect spatially significant clusters without relying on predefined thresholds. Family-wise error Rate P-values (FWEP) were applied to correct for multiple comparisons, with statistical significance set at FWEP < 0.05.
Results:
Our analysis revealed significant reductions in CT and SA in PD-FOG compared to PD-nFOG and HC. Key affected regions included the superior frontal gyrus, cingulate cortex, and precentral gyrus, with TFCE analysis confirming robust differences. CT was significantly reduced in PD-FOG, with mean reductions of 657 µm (p...corr< 0.05). SA differences were most pronounced in the cingulate cortex, where mean reductions reached 9055 mm² (p...corr< 0.05). These structural changes correlated strongly with clinical measures, including UPDRS-III scores and FOG-Questionnaire scores, particularly in regions involved in motor planning and execution.
Conclusions:
PD-FOG is associated with significant reductions in CT and SA in motor-related and cognitive regions. These findings suggest that cortical structural metrics may serve as reliable neuroimaging biomarkers for understanding and tracking FOG in PD. Further research is needed to explore how these changes relate to therapeutic outcomes and disease progression.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Motor Behavior:
Motor Planning and Execution 2
Keywords:
Data analysis
Morphometrics
Movement Disorder
STRUCTURAL MRI
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
Yes
Are you Internal Review Board (IRB) certified?
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Please indicate which methods were used in your research:
Structural MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
FSL
Free Surfer
Provide references using APA citation style.
Dadar, M., Gee, M., Shuaib, A., Duchesne, S., & Camicioli, R. (2020). Cognitive and motor correlates of grey and white matter pathology in Parkinson's disease. Neuroimage-Clinical, 27. https://doi.org/ARTN 102353
10.1016/j.nicl.2020.102353
Longhurst, J. K., Cummings, J. L., John, S. E., Poston, B., Rider, J. V., Salazar, A. M., Mishra, V. R., Ritter, A., Caldwell, J. Z., Miller, J. B., Kinney, J. W., & Landers, M. R. (2022). Dual Task Performance Is Associated with Amyloidosis in Cognitively Healthy Adults. J Prev Alzheimers Dis, 9(2), 297-305. https://doi.org/10.14283/jpad.2022.1
Moore, O., Peretz, C., & Giladi, N. (2007). Freezing of gait affects quality of life of peoples with Parkinson's disease beyond its relationships with mobility and gait. Mov Disord, 22(15), 2192-2195. https://doi.org/10.1002/mds.21659
Nutt, J. G., Bloem, B. R., Giladi, N., Hallett, M., Horak, F. B., & Nieuwboer, A. (2011). Freezing of gait: moving forward on a mysterious clinical phenomenon. Lancet Neurol, 10(8), 734-744. https://doi.org/10.1016/s1474-4422(11)70143-0
https://doi.org/10.1016/j.jns.2018.05.005
Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014). Permutation inference for the general linear model. Neuroimage, 92(100), 381-397. https://doi.org/10.1016/j.neuroimage.2014.01.060
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