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dc.contributor.authorKataoka, Masakoen
dc.contributor.authorHonda, Mayaen
dc.contributor.authorOhashi, Akaneen
dc.contributor.authorYamaguchi, Kenen
dc.contributor.authorMori, Naokoen
dc.contributor.authorGoto, Marikoen
dc.contributor.authorFujioka, Tomoyukien
dc.contributor.authorMori, Mioen
dc.contributor.authorKato, Yutakaen
dc.contributor.authorSatake, Hirokoen
dc.contributor.authorIima, Mamien
dc.contributor.authorKubota, Kazunorien
dc.contributor.alternative片岡, 正子ja
dc.contributor.alternative飯間, 麻美ja
dc.date.accessioned2023-02-02T07:29:32Z-
dc.date.available2023-02-02T07:29:32Z-
dc.date.issued2022-
dc.identifier.urihttp://hdl.handle.net/2433/279046-
dc.description.abstractUltrafast dynamic contrast-enhanced (UF-DCE) MRI is a new approach to capture kinetic information in the very early post-contrast period with high temporal resolution while keeping reasonable spatial resolution. The detailed timing and shape of the upslope in the time–intensity curve are analyzed. New kinetic parameters obtained from UF-DCE MRI are useful in differentiating malignant from benign lesions and in evaluating prognostic markers of the breast cancers. Clinically, UF-DCE MRI contributes in identifying hypervascular lesions when the background parenchymal enhancement (BPE) is marked on conventional dynamic MRI. This review starts with the technical aspect of accelerated acquisition. Practical aspects of UF-DCE MRI include identification of target hypervascular lesions from marked BPE and diagnosis of malignant and benign lesions based on new kinetic parameters derived from UF-DCE MRI: maximum slope (MS), time to enhance (TTE), bolus arrival time (BAT), time interval between arterial and venous visualization (AVI), and empirical mathematical model (EMM). The parameters derived from UF-DCE MRI are compared in terms of their diagnostic performance and association with prognostic markers. Pitfalls of UF-DCE MRI in the clinical situation are also covered. Since UF-DCE MRI is an evolving technique, future prospects of UF-DCE MRI are discussed in detail by citing recent evidence. The topic covers prediction of treatment response, multiparametric approach using DWI-derived parameters, evaluation of tumor-related vessels, and application of artificial intelligence for UF-DCE MRI. Along with comprehensive literature review, illustrative clinical cases are used to understand the value of UF-DCE MRI.en
dc.language.isoeng-
dc.publisherJapanese Society for Magnetic Resonance in Medicineen
dc.publisher.alternative日本磁気共鳴医学会ja
dc.rights© 2022 by Japanese Society for Magnetic Resonance in Medicineen
dc.rightsThis article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectbreasten
dc.subjectcompressed sensingen
dc.subjectdynamic contrast enhanceden
dc.subjectmagnetic resonance imagingen
dc.subjectultrafasten
dc.titleUltrafast Dynamic Contrast-enhanced MRI of the Breast: How Is It Used?en
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleMagnetic Resonance in Medical Sciencesen
dc.identifier.volume21-
dc.identifier.issue1-
dc.identifier.spage83-
dc.identifier.epage94-
dc.relation.doi10.2463/mrms.rev.2021-0157-
dc.textversionpublisher-
dc.identifier.pmid35228489-
dcterms.accessRightsopen access-
dc.identifier.pissn1347-3182-
dc.identifier.eissn1880-2206-
出現コレクション:学術雑誌掲載論文等

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