DOI: 10.1186/s13550-018-0416-2Pages: 1-12

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

1. Karolinska Institutet, Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska University Hospital

2. Stockholm County Council

3. Karolinska Institutet, PET Science Centre, Precision Medicine and Genomics, IMED Biotech Unit, AstraZeneca

Correspondence to:
Per Stenkrona
Tel: +46 8 51772902




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.


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.


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.


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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  • Accepted: Jun 27, 2018
  • Online: Aug 2, 2018

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