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Quantitative Assessment of Motion Artifacts and Validation of a New Motion-Correction Program for Myocardial Perfusion SPECT

Division of Nuclear Medicine, Department of Imaging; Division of Cardiology, Department of Medicine; and Artificial Intelligence in Medicine Program, Cedars-Sinai Medical Center, University of California Los Angeles School of Medicine, Los Angeles, California

Patient motion during myocardial perfusion SPECT can produce images that show artifactual perfusion defects. The relationship between the degree of motion and the extent of artifactual perfusion defects is not clear for either single- or double-head detectors. Using both single- and double-head detectors and quantitative perfusion SPECT (QPS) software, we studied the pattern and extent of defects induced by simulated motion and validated a new automatic motion-correction program for myocardial perfusion SPECT. Methods: Vertical motion was simulated by upward shifting of the raw projection datasets in a returning pattern (bounce) and in a nonreturning pattern at 3 different phases of the SPECT acquisition (early, middle, and late), whereas upward creep was simulated by uniform shifting throughout the acquisition. Lateral motion was similarly simulated by left shifting of the raw projection datasets in a returning pattern and in a nonreturning pattern. Simulations were performed using single- and double-head detectors, and simulated motion was applied to projection images from 8 patients who had normal ^99mTc-sestamibi SPECT findings. Additionally, images from 130 patients with actual clinical motion were assessed before and after motion correction. The extent of perfusion defects was assessed by QPS, and a 20-segment, 5-point scoring system was used to assess the effect of motion on the presence and extent of perfusion defects. Results: Of 12 bounce simulations, the bouncing motion failed to produce significant (>3%) perfusion defects with either the single- or the double-head detector. With the single-head detector, early shifting created the largest defect, whereas with the double-head detector, shifting during the middle of the acquisition created the largest defect. With regard to upward creep, defects were of larger extent with the double- than the single-head detector. With the single-head detector, 8 of 20 simulated motion patterns yielded significant perfusion defects of the left ventricle, 7 (88%) of which were significantly improved after motion correction. With the double-head detector, 12 of 20 patterns yielded significant defects, all of which improved significantly after correction. Of 2,600 segments in the 130 patients with actual clinical motion, only 1.3% (30/2,259) of segments that were considered normal (score = 0 or 1) changed to abnormal (score = 2–4) after motion correction, whereas 27% (92/341) of abnormal segments were reclassified as normal after motion correction. Conclusion: Artifactual perfusion defects created by simulated motion are a function of the time, degree, and type of motion and the number of camera detectors. Application of an automatic motion-correction algorithm effectively decreases motion artifacts on myocardial perfusion SPECT images.

Key Words: myocardial perfusion SPECT • motion correction • artifacts

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