Impact of PET/CT image reconstruction methods and liver uptake normalization strategies on quantitative image analysis.
BACKGROUND
In oncological imaging using PET/CT, the standardized uptake value has become the most common parameter used to measure tracer accumulation. The aim of this analysis was to evaluate ultra high definition (UHD) and ordered subset expectation maximization (OSEM) PET/CT reconstructions for their potential impact on quantification.


METHODS
We analyzed 40 PET/CT scans of lung cancer patients who had undergone PET/CT. Standardized uptake values corrected for body weight (SUV) and lean body mass (SUL) were determined in the single hottest lesion in the lung and normalized to the liver for UHD and OSEM reconstruction. Quantitative uptake values and their normalized ratios for the two reconstruction settings were compared using the Wilcoxon test. The distribution of quantitative uptake values and their ratios in relation to the reconstruction method used were demonstrated in the form of frequency distribution curves, box-plots and scatter plots. The agreement between OSEM and UHD reconstructions was assessed through Bland-Altman analysis.


RESULTS
A significant difference was observed after OSEM and UHD reconstruction for SUV and SUL data tested (p < 0.0005 in all cases). The mean values of the ratios after OSEM and UHD reconstruction showed equally significant differences (p < 0.0005 in all cases). Bland-Altman analysis showed that the SUV and SUL and their normalized values were, on average, up to 60 % higher after UHD reconstruction as compared to OSEM reconstruction.


CONCLUSIONS
OSEM and HD reconstruction brought a significant difference for SUV and SUL, which remained constantly high after normalization to the liver, indicating that standardization of reconstruction and the use of comparable SUV measurements are crucial when using PET/CT.
Department of Nuclear Medicine, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Georg
G
Kuhnert
Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands.
Ronald
R
Boellaard
Department of Nuclear Medicine, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Sergej
S
Sterzer
Department of Nuclear Medicine, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Deniz
D
Kahraman
Lung Cancer Group Cologne, Department I of Internal Medicine, Center for Integrated Oncology Cologne Bonn, University Hospital of Cologne, Cologne, Germany.
Matthias
M
Scheffler
Lung Cancer Group Cologne, Department I of Internal Medicine, Center for Integrated Oncology Cologne Bonn, University Hospital of Cologne, Cologne, Germany.
Jürgen
J
Wolf
Department of Nuclear Medicine, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Markus
M
Dietlein
Department of Nuclear Medicine, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Alexander
A
Drzezga
Department of Nuclear Medicine, University Hospital of Cologne, Kerpener Str. 62, 50937, Cologne, Germany. carsten.kobe@uk-koeln.de.
Carsten
C
Kobe
D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000592:standards; D008099:Liver / Q000000981:diagnostic imaging* / Q000378:metabolism; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D064847:Multimodal Imaging; D049268:Positron-Emission Tomography; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics*; D012016:Reference Values; D014057:Tomography, X-Ray Computed
D019275:Radiopharmaceuticals
Lung cancer; PET; Quantification; SUV