ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2022
The prevalence of image degradation due to motion in rest-stress rubidium-82 imaging on a SiPM PET-CT system.
Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Detection and correction of patient motion in dynamicJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Data-driven motion correction rescues interpretation of rubidium PET scan with extreme breathing artifacts.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Moving forward with motion reduction, detection and correction in cardiac PET.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMotion of the heart is known to affect image quality in cardiac PET. The prevalence of motion blurring in routine cardiac PET is not fully appreciated due to challenges identifying subtle motion artefacts. This study utilizes a recent prototype Data-Driven Motion Correction (DDMC) algorithm to generate corrected images that are compared with non-corrected images to identify visual differences in relative rubidium-82 perfusion images due to motion.
methods300 stress and 300 rest static images were reconstructed with DDMC and without correction (NMC). The 600 DDMC/NMC image pairs were assigned Visual Difference Score (VDS). The number of non-diagnostic images were noted. A "Dwell Fraction" (DF) was derived from the data to quantify motion and predict image degradation.
resultsMotion degradation (VDS = 1 or 2) was evident in 58% of stress images and 33% of rest images. Seven NMC images were non-diagnostic-these originated from six studies giving a 2% rate of non-diagnostic studies due to motion. The DF metric was able to effectively predict image degradation. The DDMC heart identification and tracking was successful in all images.
conclusionMotion degradation is present in almost half of all relative perfusion images. The DDMC algorithm is a robust tool for predicting, assessing and correcting image degradation.
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