Objective: PET using semiconductor detectors provides high-quality images of the human brain because of its high spatial resolution. To quantitatively evaluate the delineation of image details in clinical PET images, we used normalized mutual information (NMI) to quantify the similarity with images obtained through MRI. NMI is used to evaluate image quality by determining similarity with a reference image. The aim of this study was to evaluate quantitatively the delineation of image details provided by semiconductor PET.
Materials and methods: To quantitatively evaluate anatomical delineation in clinical PET images, MRI scans of patients were used as T1-weighted images. [18F]-fluorodeoxyglucose (18F-FDG) PET brain images were obtained from six patients using (a) a Hitachi semiconductor PET scanner and (b) a ECAT HR+ scintillator PET scanner. The NMI calculated from the semiconductor PET and MRI was denoted by NMIsemic, whereas the NMI calculated from conventional scintillator PET and MRI was denoted by NMIconve. The higher the value of NMI, the greater the similarity to MRI.
Results: NMIsemic ranged from 1.22 to 1.29, whereas NMIconve ranged from 1.13 to 1.18 (P<0.05). Furthermore, all the NMI values of the semiconductor PET were higher than those of the conventional scintillator PET.
Conclusion: Utilizing NMI, we quantitatively evaluated the delineation of image details in clinical PET images. The results reveal that semiconductor PET has superior anatomical delineation and physical performance compared with conventional scintillator PET. This improved delineation of image details makes semiconductor PET promising for clinical applications.
aCentral Institute of Isotope Science
bDepartment of Nuclear Medicine, Hokkaido University, Sapporo
cCentral Research Laboratory, Hitachi Ltd, Tokyo, Japan
Correspondence to Tohru Shiga, MD, PhD, Department of Nuclear Medicine, Graduate School of Medicine, Hokkaido University, Kita 15 Nishi 7, Kita-ku, Sapporo 060-8638, Japan Tel: +81 11 706 5152; fax: +81 11 706 7155; e-mail: email@example.com
Received July 1, 2013
Accepted January 5, 2014