Socioeconomic and Health Disparities Among Individuals Undergoing Amyloid PET without Structural MRI
Poster No:
209
Submission Type:
Abstract Submission
Authors:
Shaney Flores1, Jalen Scott1, Brian Gordon1, Yi Su2, Sarah Keefe1, Hunter Smith1, Russ Hornbeck1, Nicole McKay1, Ashlee Simmons1, Kaitlyn Dombrowski1, Jacqueline Rizzo11, Hope Shimony1, Susan Landau3, Randall Batmeman1, David Wolk4, James Lah5, Carey Gleason6, Erik Roberson7, John Morris1, Chengjie Xiong1, Tammie Benzinger1
Institutions:
1Washington University in St. Louis School of Medicine, St. Louis, MO, 2Banner Alzheimer's Institute, Phoenix, AZ, 3University of California, Berkeley, Berkeley, CA, 4University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 5Emory University School of Medicine, Atlanta, GA, 6University of Wisconsin-Madison, Madison, WI, 7University of Alabama-Birmingham School of Medicine, Birmingham, AL
First Author:
Co-Author(s):
Introduction:
The abnormal aggregation of β-amyloid (Aβ) plaques in Alzheimer disease (AD) can be measured in vivo using positron emission tomography (PET) imaging. Quantifying Aβ accrual typically requires obtaining a companion structural magnetic resonance imaging (MRI) scan to identify regions of interest (ROIs) for subsequent analyses. However, MRI contraindicators such as cardiac pacemakers may exclude a research participant from receiving MRI, and artefacts associated with excessive head movement can render an acquired MRI unsuitable for defining ROIs. Here, using a validated MR-free PET quantification pipeline (Landau et al., 2023), we investigated the characteristics of individuals typically excluded from MR-dependent PET analyses. We also extended the MR-free PET pipeline available for the 18F-florbetapir (FBP) and 18F-florbetaben (FBB) radiotracers by developing and validating a MR-free Centiloid (CL) equation for 11C-Pittsburgh Compound B (PiB).
Methods:
Aβ PET, structural MRI, clinical, cognitive, and demographic data for 2,712 participants were aggregated from the Study to Evaluate Amyloid in Blood and Imaging Related to Dementia (SEABIRD) and the Cross-Sectional and Longitudinal Racial Disparity in Molecular Biomarkers of AD study. All participants completed Aβ PET scans with FBP, FBB, or PiB. PET data were processed using both the MR-free pipeline and the MR-dependent FreeSurfer-based PET Unified Pipeline. Participants were classified into two groups: those with successfully processed MR-dependent results (usable MRI) and those with either no structural MRI scan or whose structural MRI failed quality control checks. Global cortical CLs were derived from previously published equations for the MR-dependent method (Su et al., 2018, 2019) and from a Level-2 CL calibration (Klunk et al., 2015) of our implemented MR-free method. Lin's concordance correlations and bias correction factors evaluated the agreement between the MR-free and MR-dependent CLs for 860 cross-sectional and 320 longitudinal participants with PiB PET and usable MRI. For our entire cohort, clinical, demographic and cognitive data were assessed using Fisher's exact tests and Welch t-tests for categorical and continuous variables, respectively.
Results:
Lin's concordance correlations for the PiB subset were 0.97 and 0.84 for the cross-sectional and longitudinal data, respectively. Bias correction factors were 0.98 for the cross-sectional data and 0.99 for longitudinal data, indicating minimal deviation from the identity line (see Figure 1). These results suggest the MR-free PiB CL equation produces comparable values to those derived from MR-dependent methods. Of the entire cohort, 369 participants (~13.6%) were classified with missing/unusable MRI for PET quantification (see Table 1). To understand if these excluded individuals represent specific subsets of the population, we compared demographic characteristics between these individuals and individuals with successfully acquired MRI scans. Broadly, excluded participants tended to be older and have lower levels of education. Significantly larger proportions of racial minority groups had missing/unusable MRI (23% of Black/African American compared to 12% White). Participants with missing/unusable MRI also tended to be more clinically symptomatic, cognitively impaired, and had significantly higher rates of comorbid diabetes and depression. Interestingly, cardiovascular measures, such as blood pressure, diagnosed hypertension, and diagnosed hypercholesterolemia, and body mass index were not significantly different from those with usable MRI.
Conclusions:
Participants excluded from neurologic PET studies due to missing/unusable MRI scans come from populations typically underrepresented in AD research. Excluding such participants may limit the generalizability of results from AD studies and clinical trials. MR-free PET quantification methods offer an alternative approach that may enhance the generalizability of results from imaging studies.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
PET Modeling and Analysis 2
Keywords:
Aging
Data analysis
Positron Emission Tomography (PET)
Other - Neurodegenerative disorders
1|2Indicates the priority used for review
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Was this research conducted in the United States?
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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.
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Provide references using APA citation style.
Landau, S. M., Ward, T. J., Murphy, A., Iaccarino, L., Harrison, T. M., La Joie, R., Baker, S., Koeppe, R. A., Jagust, W. J., & for the Alzheimer’s Disease Neuroimaging Initiative. (2023). Quantification of amyloid beta and tau PET without a structural MRI. Alzheimer’s & Dementia, 19(2), 444–455. https://doi.org/10.1002/alz.12668
Su, Y., Flores, S., Hornbeck, R. C., Speidel, B., Vlassenko, A. G., Gordon, B. A., Koeppe, R. A., Klunk, W. E., Xiong, C., Morris, J. C., & Benzinger, T. L. S. (2018). Utilizing the Centiloid scale in cross-sectional and longitudinal PiB PET studies. NeuroImage: Clinical, 19, 406–416. https://doi.org/10.1016/j.nicl.2018.04.022
Su, Y., Flores, S., Wang, G., Hornbeck, R. C., Speidel, B., Joseph‐Mathurin, N., Vlassenko, A. G., Gordon, B. A., Koeppe, R. A., Klunk, W. E., Jack, C. R., Farlow, M. R., Salloway, S., Snider, B. J., Berman, S. B., Roberson, E. D., Brosch, J., Jimenez‐Velazques, I., Dyck, C. H., … Benzinger, T. L. S. (2019). Comparison of Pittsburgh compound B and florbetapir in cross‐sectional and longitudinal studies. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 11(1), 180–190. https://doi.org/10.1016/j.dadm.2018.12.008