{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T15:39:57Z","timestamp":1770565197580,"version":"3.49.0"},"reference-count":0,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2017,8,9]],"date-time":"2017-08-09T00:00:00Z","timestamp":1502236800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2017,9]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>Myocardial perfusion (<jats:styled-content style=\"fixed-case\">MP<\/jats:styled-content>) <jats:styled-content style=\"fixed-case\">PET<\/jats:styled-content> imaging is a powerful tool in risk assessment and stratification of patients with coronary artery disease. Involuntary organ motion degrades cardiac <jats:styled-content style=\"fixed-case\">PET<\/jats:styled-content> image resolution, while respiratory and\/or cardiac gating to freeze the motion leads to noisier reconstructed images due to reduced counts in the gated frames. In this work, we propose an <jats:styled-content style=\"fixed-case\">MRI<\/jats:styled-content>\u2010assisted dual motion correction method to compensate for respiratory and cardiac motion in <jats:styled-content style=\"fixed-case\">MP PET<\/jats:styled-content> data and study the impact of dual motion correction on <jats:styled-content style=\"fixed-case\">MP<\/jats:styled-content> defect detection using systematically designed experiments.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The proposed dual motion correction method addresses the respiratory motion before correcting the cardiac motion among the respiratory motion corrected cardiac gates. The respiratory motion is estimated from the respiratory\u2010gated only <jats:styled-content style=\"fixed-case\">PET<\/jats:styled-content> images and compensated within a 4D motion\u2010incorporated image reconstruction algorithm. The cardiac motion is then corrected using the motion vector fields estimated from the corresponding cardiac\u2010gated <jats:styled-content style=\"fixed-case\">MR<\/jats:styled-content> images. To evaluate the proposed method, we performed experiments using the standard <jats:styled-content style=\"fixed-case\">XCAT<\/jats:styled-content> phantom and two individual\u2010specific volunteer <jats:styled-content style=\"fixed-case\">XCAT<\/jats:styled-content> phantoms. For each of the three phantoms, we simulated four dual\u2010gated Rb\u201082 <jats:styled-content style=\"fixed-case\">MP PET<\/jats:styled-content> imaging datasets, one with normal perfusion and the other three with 50% nontransmural, 75% nontransmural, and transmural regionally reduced perfusion. The corresponding cardiac\u2010gated <jats:styled-content style=\"fixed-case\">MR<\/jats:styled-content> images were simulated by the <jats:styled-content style=\"fixed-case\">SIMRI<\/jats:styled-content> simulator, with the sequence specified to be 3D T1\u2010weighted as used in a protocol of a clinical <jats:styled-content style=\"fixed-case\">PET<\/jats:styled-content>\/<jats:styled-content style=\"fixed-case\">MRI<\/jats:styled-content> scanner. We quantitatively evaluated the reconstructed images with no motion correction, only respiratory motion correction and dual motion correction, in terms of the myocardium to blood pool contrast and the trade\u2010off between the noise and the normal to defect contrast. Using the channelized Hotelling observer, we performed receiver operating characteristic analysis for the task of detecting perfusion abnormalities with various myocardial coverages.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Compared with no motion correction, the respiratory motion correction was demonstrated to improve the myocardium to blood pool contrast as well as the trade\u2010off between the noise and the normal to defect contrast, on top of which the cardiac motion correction furthered the improvement. In the task of detecting regional perfusion defects, transmural or different levels of nontransmural, the respiratory motion correction significantly increased the defect detectability compared with no motion correction. Additionally, the respiratory and cardiac motion correction significantly improved the defect detection compared with the respiratory motion correction alone. Furthermore, the separability of the transmural and nontransmural defects was also improved by the proposed <jats:styled-content style=\"fixed-case\">MRI<\/jats:styled-content> assisted dual motion correction method.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The proposed dual respiratory and cardiac motion correction technique improves the accuracy of <jats:styled-content style=\"fixed-case\">PET<\/jats:styled-content> quantification and <jats:styled-content style=\"fixed-case\">MP<\/jats:styled-content> defect detection and classification, which shows its promise for clinical applications especially in cardiac <jats:styled-content style=\"fixed-case\">PET<\/jats:styled-content>\/<jats:styled-content style=\"fixed-case\">MR<\/jats:styled-content> imaging.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.12429","type":"journal-article","created":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T09:48:41Z","timestamp":1498297721000},"page":"4536-4547","source":"Crossref","is-referenced-by-count":12,"title":["MRI\u2010assisted dual motion correction for myocardial perfusion defect detection in PET imaging"],"prefix":"10.1002","volume":"44","author":[{"given":"Xinhui","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering Oakland University Rochester MI 48309 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arman","family":"Rahmim","sequence":"additional","affiliation":[{"name":"Department of Radiology Johns Hopkins University Baltimore MD 21287 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Oakland University Rochester MI 48309 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2017,8,9]]},"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fmp.12429","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.12429","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T03:35:19Z","timestamp":1696044919000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.12429"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,9]]},"references-count":0,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2017,9]]}},"alternative-id":["10.1002\/mp.12429"],"URL":"https:\/\/doi.org\/10.1002\/mp.12429","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,9]]}}}