ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2022
A preliminary evaluation of a high temporal resolution data-driven motion correction algorithm for rubidium-82 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 8 papers.
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8 citing papers in PubMed, 23 citations in OpenAlex.
- The Role of Motion Correction Tools in Left Ventricular Functional Parameters Measured by Gated [Diagnostics (Basel, Switzerland) · 2026Article
- Data-Driven Motion Correction Algorithm: Validation in [Journal of clinical medicine · 2026Article
- Inter-Software Reproducibility of Quantitative Values of Myocardial Blood Flow and Coronary Flow Reserve Acquired by [Diagnostics (Basel, Switzerland) · 2025Article
- Hybrid cardiovascular imaging. A clinical consensus statement of the european association of nuclear medicine (EANM) and the european association of cardiovascular imaging (EACVI) of the ESC.European journal of nuclear medicine and molecular imaging · 2025Review
- Noise-aware dynamic image denoising and positron range correction for Rubidium-82 cardiac PET imaging via self-supervision.Medical image analysis · 2025Article
- Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2022: positron emission tomography, computed tomography, and magnetic resonance.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Review
- Advances in Digital PET Technology and Its Potential Impact on Myocardial Perfusion and Blood Flow Quantification.Current cardiology reports · 2023Review
- Dynamic cardiac PET motion correction using 3D normalized gradient fields in patients and phantom simulations.Medical physics · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 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.
methodsA 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.
resultsPhantom 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.
conclusionThe 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.
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