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Exploring Centiloid Robustness: Impact of Sample Size and Image Resolution on Centiloid Conversion Accuracy.
Jiaxiuxiu Zhang1, David N Soleimani-Meigooni1, Robert Koeppe2
1Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California.
Centiloid quantification of amyloid-β PET is crucial for Alzheimer disease trials. Study shows increasing participants in calibration datasets and maintaining high PET image resolution minimizes Centiloid measurement errors.
Area of Science:
- Nuclear Medicine
- Neuroimaging
- Alzheimer Disease Research
Background:
- Centiloids are widely used for quantifying amyloid-β (Aβ) positron emission tomography (PET) in clinical trials and settings.
- Accurate measurement error characterization is essential for reliable Aβ PET quantification.
- Potential sources of error include calibration dataset sampling and PET image resolution.
Purpose of the Study:
- To examine the impact of calibration dataset size and PET image resolution on Centiloid measurement accuracy.
- To evaluate the SUV ratio-to-Centiloid conversion equation's reliability under varying conditions.
- To identify optimal parameters for minimizing Centiloid quantification errors in Aβ PET analysis.
Main Methods:
- Analyzed [11C]PiB PET scans from 200 participants with clinically diagnosed Alzheimer disease (cAD) and 114 Aβ-negative individuals.
- Compared Centiloid conversion equations derived from subsamples (10-30 Aβ-negative, 15-50 cAD participants) and assessed PET image resolution effects (high, medium, low) on [11C]PiB, [18F]florbetaben, and [18F]florbetapir scans.
- Utilized standard Centiloid and MRI-based pipelines, alongside rPOP and CapAIBL PET-only pipelines.
Main Results:
- In the smallest calibration sample (15 cAD, 10 Aβ-negative), conversion errors were 1.7 and 3.4 Centiloids at 25 and 100 Centiloids, respectively.
- Increasing calibration participants to 50 cAD and 30 Aβ-negative reduced errors to 1.0 and 2.0 Centiloids.
- Lower PET image resolution systematically decreased Centiloid values, particularly in highly positive scans (e.g., 100 Centiloids at high resolution became 84.9 Centiloids at low resolution).
Conclusions:
- Accurate SUV ratio-to-Centiloid conversion for Level 2 analyses is achievable with minimally required datasets.
- Increasing cAD participants in calibration datasets effectively reduces Centiloid error at higher values.
- PET image resolution significantly impacts Centiloid values in highly positive scans and requires careful consideration during data interpretation.
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