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Published in: EJNMMI Research 1/2018

Open Access 01-12-2018 | Original research

[11C]SCH23390 binding to the D1-dopamine receptor in the human brain—a comparison of manual and automated methods for image analysis

Authors: Per Stenkrona, Granville J. Matheson, Simon Cervenka, Pontus Plavén Sigray, Christer Halldin, Lars Farde

Published in: EJNMMI Research | Issue 1/2018

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Abstract

Background

The D1-dopamine receptor radioligand [11C]SCH23390 has been frequently used in PET studies. In drug-naïve patients with schizophrenia, the findings have been inconsistent, with decreases, increases, and no change in the frontal cortex D1-dopamine receptors. While these discrepancies are likely primarily due to a lack of statistical power in these studies, we speculated that an additional explanation may be the differences due to methods of image analysis between studies, affecting reliability as well as bias between groups.

Methods

Fifteen healthy subjects underwent two PET measurements with [11C]SCH23390 on the same day. The binding potential (BPND) was compared using a 95% confidence interval following manual and automated delineation of a region of interest (ROI) as well as with and without frame-by-frame realignment.

Results

Automated target region delineation produced lower BPND values, while automated delineation of the reference region yielded higher BPND values. However, no significant differences were observed for repeatability using automated and manual delineation methods. Frame-by-frame realignment generated higher BPND values and improved repeatability.

Conclusions

The results suggest that the choice of ROI delineation method is not an important factor for reliability, whereas the improved results following movement correction confirm its importance in PET image analysis. Realignment is therefore especially important for measurements in patient populations such as schizophrenia or Parkinson’s disease, where motion artifacts may be more prevalent.
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Metadata
Title
[11C]SCH23390 binding to the D1-dopamine receptor in the human brain—a comparison of manual and automated methods for image analysis
Authors
Per Stenkrona
Granville J. Matheson
Simon Cervenka
Pontus Plavén Sigray
Christer Halldin
Lars Farde
Publication date
01-12-2018
Publisher
Springer Berlin Heidelberg
Published in
EJNMMI Research / Issue 1/2018
Electronic ISSN: 2191-219X
DOI
https://doi.org/10.1186/s13550-018-0416-2

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