NeuroImageNeurosciencePeer-reviewed journal article
Open-access template and database approaches for pseudo-CT generation in brain PET/MRI attenuation correction
Christian MilziD, Matej MurgašiD, Inès MéridaiD, L. SilberbaueriD, Lukas NicsiD, Godber Mathis GodberseniD, Gregor GryglewskiiD, Marcus HackeriD, Nicolas CostesiD, Alexander HammersiD, Rupert R. LanzenbergeriD, Andreas HahniD, Murray Bruce ReediD
Abstract
Positron emission tomography (PET) provides high-sensitivity molecular information in neuroimaging. However, its quantitative accuracy critically depends on attenuation correction (AC). Unlike PET/CT, hybrid PET/MRI systems cannot directly measure photon attenuation, necessitating alternative AC strategies. While several MRI-based AC tools exist, they often raise concerns regarding data privacy, long-term accessibility and reproducibility. We present an open-access framework for PET AC using pseudo-CT (pCT) methods. A database of 60 paired MRI-CT scans was curated and normalized to stereotactic MNI space. Three established pCT approaches (Boston, MaxProb, UCL) were adapted to enable their use with the normalized database. Method performance was assessed by comparison with a CT-based AC reference in an independent validation sample of 28 subjects, using the Jaccard index and [11C]DASB PET-derived serotonin transporter quantification as evaluation metrics. Boston and MaxProb demonstrated consistent performance across database subsets, while the UCL achieved the closest agreement with CT-derived AC and yielded the lowest quantification error (mean relative error <0.5%). This work demonstrates the feasibility of different pCT approaches using a database in MNI space thereby introducing an openly available reference database to support fast, reproducible and continued integration of MRI-based AC into PET reconstruction pipelines.
- assay: imaging
- research focus: benchmarking
- research focus: database / resource
- approach: statistical model
- approach: benchmark study
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- top 31%
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