Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96565
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dc.contributorDepartment of Health Technology and Informatics-
dc.creatorCheung, ALYen_US
dc.creatorZhang, Len_US
dc.creatorLiu, Cen_US
dc.creatorLi, Ten_US
dc.creatorCheung, AHYen_US
dc.creatorLeung, Cen_US
dc.creatorLeung, AKCen_US
dc.creatorLam, SKen_US
dc.creatorLee, VHFen_US
dc.creatorCai, Jen_US
dc.date.accessioned2022-12-07T02:55:27Z-
dc.date.available2022-12-07T02:55:27Z-
dc.identifier.urihttp://hdl.handle.net/10397/96565-
dc.language.isoenen_US
dc.publisherFrontiers Research Foundationen_US
dc.rights© 2022 Cheung, Zhang, Liu, Li, Cheung, Leung, Leung, Lam, Lee and Cai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US
dc.rightsThe following publication Cheung, A. L. Y., Zhang, L., Liu, C., Li, T., Cheung, A. H. Y., Leung, C., ... & Cai, J. (2022). Evaluation of multisource adaptive MRI fusion for gross tumor volume delineation of hepatocellular carcinoma. Frontiers in Oncology, 12, 816678 is available at https://doi.org/10.3389/fonc.2022.816678.en_US
dc.subjectGTV delineationen_US
dc.subjectHepatocellular carcinomaen_US
dc.subjectMR-guided radiotherapyen_US
dc.subjectMRI fusionen_US
dc.subjectTumor contrasten_US
dc.titleEvaluation of Multisource Adaptive MRI Fusion for gross tumor volume delineation of hepatocellular carcinomaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume12en_US
dc.identifier.doi10.3389/fonc.2022.816678en_US
dcterms.abstractPurpose: Tumor delineation plays a critical role in radiotherapy for hepatocellular carcinoma (HCC) patients. The incorporation of MRI might improve the ability to correctly identify tumor boundaries and delineation consistency. In this study, we evaluated a novel Multisource Adaptive MRI Fusion (MAMF) method in HCC patients for tumor delineation.-
dcterms.abstractMethods: Ten patients with HCC were included in this study retrospectively. Contrast-enhanced T1-weighted MRI at portal-venous phase (T1WPP), contrast-enhanced T1-weighted MRI at 19-min delayed phase (T1WDP), T2-weighted (T2W), and diffusion-weighted MRI (DWI) were acquired on a 3T MRI scanner and imported to in-house-developed MAMF software to generate synthetic MR fusion images. The original multi-contrast MR image sets were registered to planning CT by deformable image registration (DIR) using MIM. Four observers independently delineated gross tumor volumes (GTVs) on the planning CT, four original MR image sets, and the fused MRI for all patients. Tumor contrast-to-noise ratio (CNR) and Dice similarity coefficient (DSC) of the GTVs between each observer and a reference observer were measured on the six image sets. Inter-observer and inter-patient mean, SD, and coefficient of variation (CV) of the DSC were evaluated.-
dcterms.abstractResults: Fused MRI showed the highest tumor CNR compared to planning CT and original MR sets in the ten patients. The mean ± SD tumor CNR was 0.72 ± 0.73, 3.66 ± 2.96, 4.13 ± 3.98, 4.10 ± 3.17, 5.25 ± 2.44, and 9.82 ± 4.19 for CT, T1WPP, T2W, DWI, T1WDP, and fused MRI, respectively. Fused MRI has the minimum inter-observer and inter-patient variations as compared to original MR sets and planning CT sets. GTV delineation inter-observer mean DSC across the ten patients was 0.81 ± 0.09, 0.85 ± 0.08, 0.88 ± 0.04, 0.89 ± 0.08, 0.90 ± 0.04, and 0.95 ± 0.02 for planning CT, T1WPP, T2W, DWI, T1WDP, and fused MRI, respectively. The patient mean inter-observer CV of DSC was 3.3%, 3.2%, 1.7%, 2.6%, 1.5%, and 0.9% for planning CT, T1WPP, T2W, DWI, T1WDP, and fused MRI, respectively.-
dcterms.abstractConclusion: The results demonstrated that the fused MRI generated using the MAMF method can enhance tumor CNR and improve inter-observer consistency of GTV delineation in HCC as compared to planning CT and four commonly used MR image sets (T1WPP, T1WDP, T2W, and DWI). The MAMF method holds great promise in MRI applications in HCC radiotherapy treatment planning.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationFrontiers in oncology, Feb. 2022, v. 12, 816678en_US
dcterms.isPartOfFrontiers in oncologyen_US
dcterms.issued2022-02-
dc.identifier.scopus2-s2.0-85126185915-
dc.identifier.eissn2234-943Xen_US
dc.identifier.artn816678en_US
dc.description.validate202212 bckw-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.pubStatusPublisheden_US
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