The authors aimed to develop an image-based registration scheme to detect and correct patient motion in stress and rest cardiacpositron emission tomography (PET)/CT images. The patient motion correction was of primary interest and the effects of patient motion with the use of flurpiridaz F 18 and82Rb were demonstrated.Methods:
The authors evaluated stress/rest PET myocardial perfusion imaging datasets in 30 patients (60 datasets in total, 21 male and 9 female) using a new perfusion agent (flurpiridaz F 18) (n = 16) and 82Rb (n = 14), acquired on a Siemens Biograph-64 scanner in list mode. Stress and rest images were reconstructed into 4 (82Rb) or 10 (flurpiridaz F 18) dynamic frames (60 s each) using standard reconstruction (2D attenuation weighted ordered subsets expectation maximization). Patient motion correction was achieved by an image-based registration scheme optimizing a cost function using modified normalized cross-correlation that combined global and local features. For comparison, visual scoring of motion was performed on the scale of 0 to 2 (no motion, moderate motion, and large motion) by two experienced observers.Results:
The proposed registration technique had a 93% success rate in removing left ventricular motion, as visually assessed. The maximum detected motion extent for stress and rest were 5.2 mm and 4.9 mm for flurpiridaz F 18 perfusion and 3.0 mm and 4.3 mm for82Rb perfusion studies, respectively. Motion extent (maximum frame-to-frame displacement) obtained for stress and rest were (2.2 ± 1.1, 1.4 ± 0.7, 1.9 ± 1.3) mm and (2.0 ± 1.1, 1.2 ±0 .9, 1.9 ± 0.9) mm for flurpiridaz F 18 perfusion studies and (1.9 ± 0.7, 0.7 ± 0.6, 1.3 ± 0.6) mm and (2.0 ± 0.9, 0.6 ± 0.4, 1.2 ± 1.2) mm for 82Rb perfusion studies, respectively. A visually detectable patient motion threshold was established to be ≥2.2 mm, corresponding to visual user scores of 1 and 2. After motion correction, the average increases in contrast-to-noise ratio(CNR) from all frames for larger than the motion threshold were 16.2% in stress flurpiridaz F 18 and 12.2% in rest flurpiridaz F 18 studies. The average increases in CNR were 4.6% in stress 82Rb studies and 4.3% in rest 82Rb studies.Conclusions:
Fully automatic motion correction of dynamic PET frames can be performed accurately, potentially allowing improved image quantification of cardiacPET data.
This research was supported in part by grant R01HL089765-01 from the National Heart, Lung, and Blood Institute/National Institutes of Health (NHLBI/NIH) (PI: Piotr Slomka). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NHLBI. The authors would like to thank Mark Hyun for his assistance in manual visual scoring and Arpine Oganyan for editing and proof-reading the text.
II. MATERIALS AND METHODS
II.A. Description of algorithm
II.A.1. Modified normalized cross-correlation
II.A.2. Automatic target frame selection
II.A.3. Registration based on global and local mNCC
II.B.1. Patient data
II.B.2. Imaging protocols
II.B.3. PET acquisition and reconstruction
II.B.4. Evaluation of registration algorithm
III.A. Quantitative analysis of uncorrected and corrected images
III.B. Simulated motion
III.C. Qualitative visual assessment
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