Simulation-based partial volume correction for dopaminergic PET imaging: Impact of segmentation accuracy

Ye Rong, Ingo Vernaleken, Oliver H. Winz, Andreas Goedicke, Felix M. Mottaghy*, Elena Rota Kops

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Aim: Partial volume correction (PVC) is an essential step for quantitative positron emission tomography (PET). In the present study, PVELab, a freely available software, is evaluated for PVC in F-18-FDOPA brain-PET with a special focus on the accuracy degradation introduced by various MR-based segmentation approaches. Methods: Four PVC algorithms (M-PVC; MG-PVC; mMG-PVC; and R-PVC) were analyzed on simulated F-18-FDOPA brain-PET images. MR image segmentation was carried out using FSL (FMRIB Software Library) and SPM (Statistical Parametric Mapping) packages, including additional adaptation for subcortical regions (SPML). Different PVC and segmentation combinations were compared with respect to deviations in regional activity values and time-activity curves (TACs) of the occipital cortex (OCC), caudate nucleus (CN), and putamen (PUT). Additionally, the PVC impact on the determination of the influx constant (K-i) was assessed. Results: Main differences between tissue-maps returned by three segmentation algorithms were found in the subcortical region, especially at PUT Average misclassification errors in combination with volume reduction was found to be lowest for SPML, (PUT <30%) and highest for FSL (PUT > 70%). Accurate recovery of activity data at OCC is achieved by M-PVC (apparent recovery coefficient varies between 0.99 and 1.10). The other three evaluated PVC algorithms have demonstrated to be more suitable for subcortical regions with MG-PVC and mMG-PVC being less prone to the largest tissue misclassification error simulated in this study. Except for M-PVC, quantification accuracy of K-i for CN and PUT was clearly improved by PVC. Conclusions: The regional activity value of PUT was appreciably overcorrected by most of the PVC approaches employing FSL or SPM segmentation, revealing the importance of accurate MR image segmentation for the presented PVC framework. The selection of a PVC approach should be adapted to the anatomical structure of interest. Caution is recommended in subsequent interpretation of Ki values. The possible different change of activity concentrations due to PVC in both target and reference regions tends to alter the corresponding TACs, introducing bias to Ki determination. The accuracy of quantitative analysis was improved by PVC but at the expense of precision reduction, indicating the potential impropriety of applying the presented framework for group comparison studies.
Original languageEnglish
Pages (from-to)230-242
JournalZeitschrift für Medizinische Physik
Volume25
Issue number3
DOIs
Publication statusPublished - 2015

Keywords

  • Partial volume correction
  • F-18-FDOPA
  • PET
  • Striatum
  • MR segmentation (FSL, SPM)

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