Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107552
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dc.contributorDepartment of Health Technology and Informaticsen_US
dc.contributorDepartment of Rehabilitation Sciencesen_US
dc.creatorLi, Ten_US
dc.creatorCui, Den_US
dc.creatorRen, Gen_US
dc.creatorHui, ESen_US
dc.creatorCai, Jen_US
dc.date.accessioned2024-07-03T08:16:13Z-
dc.date.available2024-07-03T08:16:13Z-
dc.identifier.issn0031-9155en_US
dc.identifier.urihttp://hdl.handle.net/10397/107552-
dc.language.isoenen_US
dc.publisherInstitute of Physics Publishing Ltd.en_US
dc.rights© 2021 Institute of Physics and Engineering in Medicineen_US
dc.rightsThis is the Accepted Manuscript version of an article accepted for publication in Physics in Medicine & Biology. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/1361-6560/abf51f.en_US
dc.rightsThis manuscript version is made available under the CC-BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/)en_US
dc.subjectLivercanceren_US
dc.subjectMulti-parametric MRIen_US
dc.subjectRadiotherapyen_US
dc.titleInvestigation of the effect of acquisition schemes on time-resolved magnetic resonance fingerprintingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume66en_US
dc.identifier.issue9en_US
dc.identifier.doi10.1088/1361-6560/abf51fen_US
dcterms.abstractPurpose. This study aims to investigate the feasibility of different acquisition methods for time-resolved magnetic resonance fingerprinting (TR-MRF) in computer simulation. Methods. An extended cardiac-torso (XCAT) phantom is used to generate abdominal T1, T2, and proton density maps for MRF simulation. The simulated MRF technique consists of an IR-FISP MRF sequence with spiral trajectory acquisition. MRF maps were simulated with different numbers of repetitions from 1 to 15. Three different methods were used to generate TR-MRF maps: (1) continuous acquisition without delay between MRF repetitions; (2) continuous acquisition with 5 s delay between MRF repetitions; (3) triggered acquisition with variable delay between MRF repetitions to allow the next acquisition to start at different respiration phase. After the generation of TR-MRF maps, the image quality indexes including the absolute T1 and T2 values, signal-to-noise-ratio (SNR), tumor-to-liver contrast-to-noise ratio, error in the amplitude of diaphragm motion and tumor volume error were used to evaluate the reconstructed parameter maps. Three volunteers were recruited to test the feasibility of the selected acquisition method. Results. Dynamic MR parametric maps using three different acquisition methods were estimated. The overall and liver T1 value error, liver SNR in T1 and T2 maps, and tumor SNR from T1 maps from triggered method is statistically significantly better than the other two methods (p-value < 0.05). The other image quality indexes have no significant difference between the triggered method and the other two continuous acquisition methods. All image quality indexes exhibit no significant difference between the acquisition methods with 0 s and 5 s delay. The triggered method was successfully performed in three healthy volunteers. Conclusion. TR-MRF technique was investigated using three different acquisition methods in computer simulation where the triggered method showed better performance than the other two methods. The triggered method has been tested successfully in healthy volunteers.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPhysics in medicine and biology, 7 May 2021, v. 66, no. 9, 095013en_US
dcterms.isPartOfPhysics in medicine and biologyen_US
dcterms.issued2021-05-
dc.identifier.eissn1361-6560en_US
dc.identifier.artn095013en_US
dc.description.validate202407 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera2930a-
dc.identifier.SubFormID48787-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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