Original ArticleMotion frozen 18F-FDG cardiac PET
Introduction
The cardiac PET image quality can be limited by several factors including the intrinsic performance of the PET scanner. The distortions in the photon detection process due to the circular geometry of PET scanners and consequent increased tilting of the crystals off the center of the field of view (FOV) have a negative impact on the spatial resolution and on the noise in the reconstructed images. The recently introduced High-Definition Positron Emission Tomography (HD·PET) technology (Siemens Healthcare Molecular Imaging, Knoxville, TN), reconstruction, significantly improves image spatial resolution and signal-to-noise ratio in the images using spatially variant detector spatial response with 3D-specific Point Spread Function (PSF) during the reconstruction step.1,2 This type of resolution recovery reconstruction was introduced by other vendors as well and is termed in this manuscript as PSF reconstruction.
However, even with the improvements of PSF-based reconstruction in terms of spatial resolution and noise control, high-resolution myocardial imaging still faces the challenges of cardiac and respiratory motions, which degrade the static image quality by blurring the image. To address cardiac motion, the “Cardiac Motion Frozen” (CMF) technique has been developed previously by Slomka et al3 for myocardial perfusion single-photon emission computed tomography (SPECT) images. This algorithm tracks the motion of the left ventricle (LV) in cardiac gated images, and then adjusts all cardiac phases to one phase (typically end diastolic) resulting in an image free of cardiac motion.
To our knowledge, CMF has never been evaluated in PET cardiac images. We hypothesized that CMF technique can further improve image quality of cardiac PET above that offered by resolution recovery as recently described.2 In this study, the authors tested this hypothesis in cardiac PET with Fluorine-18 fluorodeoxyglucose (18F-FDG).4 We describe the technique, and evaluate the improvement of CMF processing on image contrast, noise, myocardial wall thickness, and detectability of myocardial defects.
Section snippets
PET Acquisition and Reconstruction
All images were acquired on a Siemens Biograph-64 TruePoint PET/CT with the TrueV option. This 3D system consists of a 64-slice CT and a PET scanner with 4 rings of Lutetium Oxyorthosilicate (LSO) detectors with a detector element dimensions of 4 × 4 × 20 mm3.5 The image plane spacing is 2 mm. The PET axial and transaxial FOV are 216 and 605 mm respectively. The coincidence time window and the energy window are respectively 4.5 ns and 425-650 keV. The data was acquired in list mode format. A
Myocardial Wall Thickness
The measured wall thickness was significantly smaller with CMF-PSF reconstruction as compared to 2D-AWOSEM and PSF reconstruction alone. We found that on average in 20 patients and over the 6 measured profiles, the wall thickness was 18.9 ± 5.2 mm for 2D-AWOSEM, 16.6 ± 4.5 mm for PSF, and 13.8 ± 3.9 mm for CMF-PSF (all P < .05). The CMF-PSF wall thickness was comparable to the thickness of the ED phase in the gated dataset reconstructed with PSF (13.3 ± 3.3 mm, P = NS). The results are
Discussion
“CMF” image processing technique compensates for the cardiac motion blur in the static images and has been shown to improve myocardial perfusion SPECT.3,10 In this study, we have demonstrated that it further improves the technical cardiac image quality obtained with PSF reconstruction.
The measured myocardial wall thickness was significantly decreased with CMF-PSF (−27.0% compared to 2D-AWOSEM and −16.9% compared to PSF reconstruction alone). The average wall thickness (13.8 ± 3.9 mm) for the
Conclusions
Our study on 18F-FDG viability studies showed that CMF processing increased myocardial-to-blood contrast and maximum LV counts to defect contrast while maintaining equivalent noise when compared to static summed images reconstructed with standard and modern reconstruction techniques incorporating resolution recovery. The significantly decreased myocardial wall thickness with CMF-PSF led to a better image quality in general.
Acknowledgments
The authors want to thank Jimmy Fermin and Brandi N. Huber from Cedars-Sinai Medical Center for their help with the PET acquisition, and Heidi Gransar for her help with the statistical analysis.
References (13)
- et al.
Enhanced definition PET for cardiac imaging
J Nucl Cardiol
(2010) - et al.
BMS-747158-02: A novel PET myocardial perfusion imaging agent
J Nucl Cardiol
(2007) - et al.
Fully 3-D PET reconstruction with system matrix derived from point source measurements
IEEE Trans Med Imaging
(2006) - et al.
“Motion-frozen” display and quantification of myocardial perfusion
J Nucl Med
(2004) Metabolic imaging using PET
Eur J Nucl Med Mol Imaging
(2007)- et al.
A comparison of the imaging properties of a 3-and 4-ring biograph PET scanner using a novel extended NEMA phantom
IEEE Nucl Sci Symp Conf Rec
(2007)