A preliminary evaluation of a high temporal resolution data-driven motion correction algorithm for rubidium-82 on a SiPM PET-CT system
| Autor: | Ian S. Armstrong, Charles Hayden, Parthiban Arumugam, Matthew J Memmott |
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| Rok vydání: | 2020 |
| Předmět: |
PET-CT
business.industry Image quality Phantoms Imaging Myocardial Perfusion Imaging Iterative reconstruction Torso Imaging phantom Visualization Rubidium-82 Motion medicine.anatomical_structure Cardiac PET Positron Emission Tomography Computed Tomography Positron-Emission Tomography Image Processing Computer-Assisted Medicine Humans Radiology Nuclear Medicine and imaging Cardiology and Cardiovascular Medicine business Algorithm Rubidium Radioisotopes Algorithms |
| Zdroj: | Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology. 29(1) |
| ISSN: | 1532-6551 |
| Popis: | Background In myocardial perfusion PET, images are acquired during vasodilator stress, increasing the likelihood of intra-frame motion blurring of the heart in reconstructed static images to assess relative perfusion. This work evaluated a prototype data-driven motion correction (DDMC) algorithm designed specifically for cardiac PET. Methods A cardiac torso phantom, with a solid defect, was scanned stationary and being manually pulled to-and-fro in the axial direction with a random motion. Non-motion-corrected (NMC) and DDMC images were reconstructed. Total perfusion deficit was measured in the defect and profiles through the cardiac insert were defined. In addition, 46 static perfusion images from 36 rubidium-82 MPI patients were selected based upon a perception of motion blurring in the images. NMC and DDMC images were reconstructed, blinded, and scored on image quality and perceived motion. Results Phantom data demonstrated near-perfect recovery of myocardial wall visualization and defect quantification with DDMC compared with the stationary phantom. Quality of clinical images was NMC: 10 non-diagnostic, 31 adequate, and 5 good; DDMC images: 0 non-diagnostic, 6 adequate, and 40 good. Conclusion The DDMC algorithm shows great promise in rubidium MPI PET with substantial improvements in image quality and the potential to salvage images considered non-diagnostic due to significant motion blurring. |
| Databáze: | OpenAIRE |
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