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タイトル: Ultrafast Dynamic Contrast-enhanced MRI of the Breast: How Is It Used?
著者: Kataoka, Masako  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-6212-3351 (unconfirmed)
Honda, Maya
Ohashi, Akane
Yamaguchi, Ken
Mori, Naoko
Goto, Mariko
Fujioka, Tomoyuki
Mori, Mio
Kato, Yutaka
Satake, Hiroko
Iima, Mami  KAKEN_id  orcid https://orcid.org/0000-0002-1991-2494 (unconfirmed)
Kubota, Kazunori
著者名の別形: 片岡, 正子
飯間, 麻美
キーワード: breast
compressed sensing
dynamic contrast enhanced
magnetic resonance imaging
ultrafast
発行日: 2022
出版者: Japanese Society for Magnetic Resonance in Medicine
誌名: Magnetic Resonance in Medical Sciences
巻: 21
号: 1
開始ページ: 83
終了ページ: 94
抄録: Ultrafast 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.
著作権等: © 2022 by Japanese Society for Magnetic Resonance in Medicine
This article is licensed under a Creative Commons [Attribution-NonCommercial-NoDerivatives 4.0 International] license.
URI: http://hdl.handle.net/2433/279046
DOI(出版社版): 10.2463/mrms.rev.2021-0157
PubMed ID: 35228489
出現コレクション:学術雑誌掲載論文等

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