{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T08:33:57Z","timestamp":1787906037603,"version":"build-2784847793"},"reference-count":43,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T00:00:00Z","timestamp":1699401600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005925","name":"Buddhist Tzu Chi Medical Foundation","doi-asserted-by":"publisher","award":["TCMF\u2010A 107\u201001\u201002(111)"],"award-info":[{"award-number":["TCMF\u2010A 107\u201001\u201002(111)"]}],"id":[{"id":"10.13039\/501100005925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005925","name":"Buddhist Tzu Chi Medical Foundation","doi-asserted-by":"publisher","award":["TCMF\u2010A 107\u201001\u201002(112)"],"award-info":[{"award-number":["TCMF\u2010A 107\u201001\u201002(112)"]}],"id":[{"id":"10.13039\/501100005925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Applied Clin Med Phys"],"published-print":{"date-parts":[[2023,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Purpose<\/jats:title><jats:p><jats:sup>18<\/jats:sup>F\u2010FDG PET quantitative features are susceptible to respiratory motion. However, studies using clinical patient data to explore the impact of respiratory motion on <jats:sup>18<\/jats:sup>F\u2010FDG PET radiomic features are limited. In this study, we investigated the impact of respiratory motion on radiomics stability with clinical <jats:sup>18<\/jats:sup>F\u2010FDG PET images using a data\u2010driven gating (DDG) algorithm on the digital PET scanner.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>A total of 101 patients who underwent oncological <jats:sup>18<\/jats:sup>F\u2010FDG PET scans were retrospectively included. A DDG algorithm combined with a motion compensation technique was used to extract the PET images with respiratory motion correction. <jats:sup>18<\/jats:sup>F\u2010FDG\u2010avid lesions from the thorax to the upper abdomen were analyzed on the non\u2010DDG and DDG PET images. The lesions were segmented with a 40% threshold of the maximum standardized uptake. A total of 725 radiomic features were computed from the segmented lesions, including first\u2010order, shape, texture, and wavelet features. The intraclass correlation coefficient (ICC) and coefficient of variation (COV) were calculated to evaluate feature stability. An ICC above 0.9 and a COV below 5% were considered high stability.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In total, 168 lesions with and without respiratory motion correction were analyzed. Our results indicated that most <jats:sup>18<\/jats:sup>F\u2010FDG PET radiomic features are sensitive to respiratory motion. Overall, only 27 out of 725 (3.72%) radiomic features were identified as highly stable, including one from the first\u2010order features (entropy), one from the shape features (sphericity), four from the gray\u2010level co\u2010occurrence matrix features (normalized and unnormalized inverse difference moment, joint entropy, and sum entropy), one from the gray\u2010level run\u2010length matrix features (run entropy), and 20 from the wavelet filter\u2010based features.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Respiratory motion has a significant impact on <jats:sup>18<\/jats:sup>F\u2010FDG PET radiomics stability. The highly stable features identified in our study may serve as potential candidates for further applications, such as machine learning modeling.<\/jats:p><\/jats:sec>","DOI":"10.1002\/acm2.14200","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T12:03:03Z","timestamp":1699444983000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Impact of respiratory motion on <sup>18<\/sup>F\u2010FDG PET radiomics stability: Clinical evaluation with a digital PET scanner"],"prefix":"10.1002","volume":"24","author":[{"given":"Yu\u2010Hung","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation  Hualien Taiwan"},{"name":"School of Medicine College of Medicine Tzu Chi University  Hualien Taiwan"},{"name":"Department of Medical Imaging and Radiological Sciences Tzu Chi University of Science and 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