Shelley Redgate1,2, David C Barber3, John W Fenner3, Abdallah Al-Mohammad4, Jonathon C Taylor5, Michael B Hanney5, Wendy B Tindale5. 1. Nuclear Medicine Department, Sheffield Teaching Hospitals NHS Foundation Trust, I-Floor, Royal Hallamshire Hospital, Glossop Rd, Sheffield, S10 2JF, United Kingdom. shelley.redgate@sth.nhs.uk. 2. Medical Physics Group (Cardiovascular Science), University of Sheffield, Sheffield, United Kingdom. shelley.redgate@sth.nhs.uk. 3. Medical Physics Group (Cardiovascular Science), University of Sheffield, Sheffield, United Kingdom. 4. Cardiology Department, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom. 5. Nuclear Medicine Department, Sheffield Teaching Hospitals NHS Foundation Trust, I-Floor, Royal Hallamshire Hospital, Glossop Rd, Sheffield, S10 2JF, United Kingdom.
Abstract
BACKGROUND: Due to differences in the design and acquisition parameters on the solid-state CZT cardiac camera the effect of patient motion may vary compared to Anger cameras. This study evaluates the effect of motion, two new methods of three-dimensional (3D) motion detection and a method of motion correction. METHOD: Phantom acquisitions were offset in the X, Y, and Z directions and combined to simulate different types of motion. Motion artifacts were identified using the total perfusion defect and blinded visual interpretation. Motion was detected by registering planar and reconstructed 30 second images, and corrected by summing the aligned reconstructed images. Validation was performed on phantom data. These techniques were then applied to 40 patient studies. RESULTS: Motion ≥10 mm and ≥60 seconds in duration introduced significant artifacts. There was no significant difference (P = .258) between the two methods of motion detection. Motion correction removed artifacts from 9/10 phantom simulations. Superior-inferior motion ≥8 mm was measured on 10% of patient studies, and 5% were affected by motion. Motion in the lateral and anterior-posterior directions was <8 mm. CONCLUSION: Superior-inferior patient motion artifacts have been identified on myocardial perfusion images acquired on a CZT camera. Routine QC to identify studies with significant motion is recommended.
BACKGROUND: Due to differences in the design and acquisition parameters on the solid-state CZT cardiac camera the effect of patient motion may vary compared to Anger cameras. This study evaluates the effect of motion, two new methods of three-dimensional (3D) motion detection and a method of motion correction. METHOD: Phantom acquisitions were offset in the X, Y, and Z directions and combined to simulate different types of motion. Motion artifacts were identified using the total perfusion defect and blinded visual interpretation. Motion was detected by registering planar and reconstructed 30 second images, and corrected by summing the aligned reconstructed images. Validation was performed on phantom data. These techniques were then applied to 40 patient studies. RESULTS: Motion ≥10 mm and ≥60 seconds in duration introduced significant artifacts. There was no significant difference (P = .258) between the two methods of motion detection. Motion correction removed artifacts from 9/10 phantom simulations. Superior-inferior motion ≥8 mm was measured on 10% of patient studies, and 5% were affected by motion. Motion in the lateral and anterior-posterior directions was <8 mm. CONCLUSION: Superior-inferior patient motion artifacts have been identified on myocardial perfusion images acquired on a CZT camera. Routine QC to identify studies with significant motion is recommended.
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