ArticlePloS one2020
Impact of respiratory motion correction on lesion visibility and quantification in thoracic PET/MR imaging.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Respiratory motion-corrected quiescent period gating magnetic resonance attenuation correction (Q.MRAC) for enhancing quantitative accuracy in hepatic [18F]FDG PET/MRI: a dual-domain motion compensation study.Quantitative imaging in medicine and surgery · 2026Article
- Impact of Deep-Learning-Based Respiratory Motion Correction on [Biomedicines · 2026Article
- Clinical validation of a unified data-driven respiratory motion correction technique inEJNMMI physics · 2026Article
- International EANM-SNMMI-ISMRM consensus recommendation for PET/MRI in oncology.European journal of nuclear medicine and molecular imaging · 2023Article
- MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.Magnetic resonance in medicine · 2022Article
- Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Review
- Experimental evaluation of four-dimensional Magnetic Resonance Imaging for radiotherapy planning of lung cancer.Physics and imaging in radiation oncology · 2021Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The impact of a method for MR-based respiratory motion correction of PET data on lesion visibility and quantification in patients with oncologic findings in the lung was evaluated. Twenty patients with one or more lesions in the lung were included. Hybrid imaging was performed on an integrated PET/MR system using 18F-FDG as radiotracer. The standard thoracic imaging protocol was extended by a free-breathing self-gated acquisition of MR data for motion modelling. PET data was acquired simultaneously in list-mode for 5-10 mins. One experienced radiologist and one experienced nuclear medicine specialist evaluated and compared the post-processed data in consensus regarding lesion visibility (scores 1-4, 4 being best), image noise levels (scores 1-3, 3 being lowest noise), SUVmean and SUVmax. Motion-corrected (MoCo) images were additionally compared with gated images. Non-motion-corrected free-breathing data served as standard of reference in this study. Motion correction generally improved lesion visibility (3.19 ± 0.63) and noise ratings (2.95 ± 0.22) compared to uncorrected (2.81 ± 0.66 and 2.95 ± 0.22, respectively) or gated PET data (2.47 ± 0.93 and 1.30 ± 0.47, respectively). Furthermore, SUVs (mean and max) were compared for all methods to estimate their respective impact on the quantification. Deviations of SUVmax were smallest between the uncorrected and the MoCo lesion data (average increase of 9.1% of MoCo SUVs), while SUVmean agreed best for gated and MoCo reconstructions (MoCo SUVs increased by 1.2%). The studied method for MR-based respiratory motion correction of PET data combines increased lesion sharpness and improved lesion activity quantification with high signal-to-noise ratio in a clinical setting. In particular, the detection of small lesions in moving organs such as the lung and liver may thus be facilitated. These advantages justify the extension of the PET/MR imaging protocol by 5-10 minutes for motion correction.
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