Evaluation of <scp>ComBat</scp> Harmonization for Reducing Across‐Tracer Differences in Regional Amyloid <scp>PET</scp> Analyses

Differences in amyloid positron emission tomography (PET) radiotracer pharmacokinetics and binding properties lead to discrepancies in amyloid-β uptake estimates. Harmonization of tracer-specific biases is crucial for optimal performance of downstream tasks. Here, we investigated the efficacy of ComBat, a data-driven harmonization model, for reducing tracer-specific biases in regional amyloid PET measurements from [<sup>18</sup>F]-florbetapir (FBP) and [<sup>11</sup>C]-Pittsburgh compound-B (PiB). One hundred thirteen head-to-head FBP-PiB scan pairs, scanned from the same subject within 90 days, were selected from the Open Access Series of Imaging Studies 3 (OASIS-3) dataset. The Centiloid scale, ComBat with no covariates, ComBat with biological covariates, and GAM-ComBat with biological covariates were used to harmonize both global and regional amyloid standardized uptake value ratios (SUVR). Variants of ComBat, including longitudinal ComBat and PEACE, were also tested. Intraclass correlation coefficient (ICC) and mean absolute error (MAE) were computed to measure the absolute agreement between tracers. Additionally, longitudinal amyloid SUVRs from an anti-amyloid drug trial were simulated using linear mixed effects modeling. Differences in rates-of-change between simulated treatment and placebo groups were tested, and change in statistical power/Type-I error after harmonization was quantified. In the head-to-head tracer comparison, ComBat with no covariates was the best at increasing ICC and decreasing MAE of both global summary and regional amyloid PET SUVRs between scan pairs of the same group of subjects. In the clinical trial simulation, harmonization with both Centiloid and ComBat increased statistical power of detecting true rate-of-change differences between groups and decreased false discovery rate in the absence of a treatment effect. The greatest benefit of harmonization was observed when groups exhibited differing FBP-to-PiB proportions. ComBat outperformed the Centiloid scale in harmonizing both global and regional amyloid estimates. Additionally, ComBat improved the detection of rate-of-change differences between clinical trial groups. Our findings suggest that ComBat is a viable alternative to Centiloid for harmonizing regional amyloid PET analyses.

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Publication Details

Journal
Human Brain Mapping
Published
2024-11-01
DOI
https://doi.org/10.1002/hbm.70068
Citations
6
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
2.31

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article

Evaluation of ComBat Harmonization for Reducing Across‐Tracer Differences in Regional Amyloid PET Analyses

Tammie L.S. Benzinger, Aristeidis Sotiras, Tom Earnest, Deydeep Kothapalli et al.
6 citations
Human Brain Mapping
Dementia and Cognitive Impairment Research
2.31
article

Evaluation of ComBat Harmonization for Reducing Across‐Tracer Differences in Regional Amyloid PET Analyses

Tammie L.S. Benzinger, Aristeidis Sotiras, Tom Earnest, Deydeep Kothapalli, Braden Yang, Brian A. Gordon, Sayantan Kumar
article en
6 citations

Abstract

Differences in amyloid positron emission tomography (PET) radiotracer pharmacokinetics and binding properties lead to discrepancies in amyloid-β uptake estimates. Harmonization of tracer-specific biases is crucial for optimal performance of downstream tasks. Here, we investigated the efficacy of ComBat, a data-driven harmonization model, for reducing tracer-specific biases in regional amyloid PET measurements from [<sup>18</sup>F]-florbetapir (FBP) and [<sup>11</sup>C]-Pittsburgh compound-B (PiB). One hundred thirteen head-to-head FBP-PiB scan pairs, scanned from the same subject within 90 days, were selected from the Open Access Series of Imaging Studies 3 (OASIS-3) dataset. The Centiloid scale, ComBat with no covariates, ComBat with biological covariates, and GAM-ComBat with biological covariates were used to harmonize both global and regional amyloid standardized uptake value ratios (SUVR). Variants of ComBat, including longitudinal ComBat and PEACE, were also tested. Intraclass correlation coefficient (ICC) and mean absolute error (MAE) were computed to measure the absolute agreement between tracers. Additionally, longitudinal amyloid SUVRs from an anti-amyloid drug trial were simulated using linear mixed effects modeling. Differences in rates-of-change between simulated treatment and placebo groups were tested, and change in statistical power/Type-I error after harmonization was quantified. In the head-to-head tracer comparison, ComBat with no covariates was the best at increasing ICC and decreasing MAE of both global summary and regional amyloid PET SUVRs between scan pairs of the same group of subjects. In the clinical trial simulation, harmonization with both Centiloid and ComBat increased statistical power of detecting true rate-of-change differences between groups and decreased false discovery rate in the absence of a treatment effect. The greatest benefit of harmonization was observed when groups exhibited differing FBP-to-PiB proportions. ComBat outperformed the Centiloid scale in harmonizing both global and regional amyloid estimates. Additionally, ComBat improved the detection of rate-of-change differences between clinical trial groups. Our findings suggest that ComBat is a viable alternative to Centiloid for harmonizing regional amyloid PET analyses.

Human Brain MappingVol. 45(16)
Washington University in St. Louis (US), Mallinckrodt (United States) (US)
Eli Lilly and Company, BrightFocus Foundation, National Institutes of Health, McDonnell Center for Systems Neuroscience, Avid Radiopharmaceuticals, National Institute on Aging, NIH Office of the Director, National Institute of Biomedical Imaging and Bioengineering
Openalex Percentile: Top 10%
Dementia and Cognitive Impairment Research
2.31
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