Motor skill fitness associated with volumetric and microstructural changes in the cerebellum in PD
Poster No:
242
Submission Type:
Abstract Submission
Authors:
Benjamin Newman1, Ryan Foreman2, Erin Donahue2, Michael Jakowec2, Andrew Petkus2, Daniel Holschneider2, Joseph O'Neil3, Dawn Schiehser4, Giselle Petzinger2, John Van Horn1
Institutions:
1University of Virginia, Charlottesville, VA, 2University of Southern California, Los Angeles, CA, 3University of California, Los Angeles, Los Angeles, CA, 4University of California, San Diego, San Diego, CA
First Author:
Co-Author(s):
Introduction:
Parkinson's disease (PD) is characterized by a progressive loss of motor coordination and function. The cerebellum is a key structure in the control and coordination of movements1, however, the connection between the cerebellum and PD symptoms has not been well defined. A recent large-scale analysis of several thousand PD patients and age-matched controls found limited associations with volumetric measurements2. In this study, we replicate this analysis in a smaller, but more richly studied sample with more detailed evaluations of cognitive, behavior, and motor skill fitness. We also further explore age-induced changes in the cerebellum using diffusion MRI cellular microstructure techniques.
Methods:
22 subjects (12 female) diagnosed with PD from a longitudinal observational study with mean age at baseline was 63.83 years ± 9.70 SD and average 3.72 years ± 2.65 SD after diagnosis at baseline. Participants were re-evaluated at ~24 months. All measurements were obtained in the 'ON' medication state. Full evaluations are described in detail for this cohort in previously published work3. A latent factor approach allowed for the assessment of motor functions, balance, agility, and endurance, combining well established, objective, and standardized measures into a standardized z-score.
Diffusion, T1-weighted, and T2-weighted images were acquired from each subject at baseline and follow-up. Images were preprocessed and used to calculate 3-tissue constrained spherical deconvolution (3T-CSD) measures of cellular microstructure4, which include an extracellular isotropic (ECI), intracellular isotropic (ICI), and intracellular anisotropic (ICA) compartments. T1-weighted images were processed using ACAPULCO, a U-Net pipeline for detailed structural segmentation of the cerebellum5. The ACAPULCO derived cerebellar parcellation was applied to the 3T-CSD microstructural maps to measure mean signal fraction from each of the 3 tissue compartments. General linear models were used to predict cerebellar ROI volume or 3T-CSD signal fraction from follow-up latent fitness controlled for baseline latent fitness, sex, age, years after PD diagnosis, days between baseline and follow up scans, and total brain volume.
Diffusion, T1-weighted, and T2-weighted images were acquired from each subject at baseline and follow-up. Images were preprocessed and used to calculate 3-tissue constrained spherical deconvolution (3T-CSD) measures of cellular microstructure4, which include an extracellular isotropic (ECI), intracellular isotropic (ICI), and intracellular anisotropic (ICA) compartments. T1-weighted images were processed using ACAPULCO, a U-Net pipeline for detailed structural segmentation of the cerebellum5. The ACAPULCO derived cerebellar parcellation was applied to the 3T-CSD microstructural maps to measure mean signal fraction from each of the 3 tissue compartments. General linear models were used to predict cerebellar ROI volume or 3T-CSD signal fraction from follow-up latent fitness controlled for baseline latent fitness, sex, age, years after PD diagnosis, days between baseline and follow up scans, and total brain volume.
Results:
The volume of cerebellar lobes was not significantly different between baseline and follow-up in any ROI (Fig. 1), but multiple lobes were positively associated with motor skill fitness at follow-up including lobe IV (left, p<0.01), lobe VI (right, p<0.05), lobe VII (right, p<0.05), lobe VIII (right, p<0.01). There was also a number of significant positive associations with baseline motor skill fitness and volume of lobe 4 (left, p<0.01), right Crus I (p<0.05), lobe VI (right, p<0.05), lobe VII (right, p<0.05), and lobe VIII (right, p<0.01). Further, the volume of the corpus medullare was significantly associated with MOCA (p<0.05), and memory & visuospatial cognitive performance (p<0.05).
3T-CSD was also associated with motor skill fitness across a wide number of cerebellar ROIs (Fig. 2). The ICA signal fraction was positively associated with both baseline and follow-up motor skill fitness in the Vermis X (p<0.05) and lobe IV (right, p<0.05). The ICI signal fraction was associated with both baseline and follow-up motor skill fitness in the Vermis X (p<0.05), lobe I & III (right, p<0.05), lobe IV (right, p<0.05), lobe V (right, p<0.05), and lobe VIII (right, p<0.05). The ECI signal fraction was associated with both baseline and follow-up motor skill fitness in the Vermis VIII (p<0.01) and lobe IX (right, p<0.05).
3T-CSD was also associated with motor skill fitness across a wide number of cerebellar ROIs (Fig. 2). The ICA signal fraction was positively associated with both baseline and follow-up motor skill fitness in the Vermis X (p<0.05) and lobe IV (right, p<0.05). The ICI signal fraction was associated with both baseline and follow-up motor skill fitness in the Vermis X (p<0.05), lobe I & III (right, p<0.05), lobe IV (right, p<0.05), lobe V (right, p<0.05), and lobe VIII (right, p<0.05). The ECI signal fraction was associated with both baseline and follow-up motor skill fitness in the Vermis VIII (p<0.01) and lobe IX (right, p<0.05).
·Figure 1: Volumetric data from all ROIs examined in this study at baseline and the 2-year follow-up. No significant changes in volume were observed in any ROI between baseline and follow-up.
·Figure 2: ROIs significantly associated with either baseline or follow-up motor fitness scores either volumetrically or in 3T-CSD measurement.
Conclusions:
We demonstrate that significant associations can be found in PD in the cerebellum, especially with highly detailed metrics. Further, the strong associations between motor skill fitness and cerebellar structure suggest that the cerebellum may be involved in compensation for deficits elsewhere in the brain during PD. Further research should explore the ability of the cerebellum-related skill training to increase patient function in PD.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Learning and Memory:
Skill Learning 2
Lifespan Development:
Aging
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Keywords:
Aging
Learning
Motor
Movement Disorder
Neurological
STRUCTURAL MRI
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Are you Internal Review Board (IRB) certified? Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
2. Kerestes R, Laansma MA, Owens‐Walton C, et al. Cerebellar Volume and Disease Staging in Parkinson’s Disease: An ENIGMA‐PD Study. Movement Disorders. 2023;38(12):2269-2281. doi:10.1002/mds.29611
3. Newman BT, Forman R, Donahue E, et al. Diffusion Signals of Glial Activation Correlate with Fitness Scores in Parkinson’s Subcortical Gray Matter. medRxiv. Published online 2024:2024-11.
4. Newman BT, Dhollander T, Reynier KA, Panzer MB, Druzgal TJ. Test–retest reliability and long‐term stability of three‐tissue constrained spherical deconvolution methods for analyzing diffusion MRI data. Magn Reson Med. 2020;84(4):2161-2173. doi:10.1002/mrm.28242
5. Han S, Carass A, He Y, Prince JL. Automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization. Neuroimage. 2020;218:116819.