Ultrafast Dynamic Contrast‐Enhanced MRI of the Breast: From Theory to Practice

乳房磁振造影 动态增强MRI 乳腺癌 动态对比度 血管性 磁共振成像 病变 医学 放射科 阶段(地层学) 计算机科学 癌症 病理 乳腺摄影术 内科学 古生物学 生物
作者
Masako Kataoka,Maya Honda,Hajime Sagawa,Akane Ohashi,Rena Sakaguchi,Hina Hashimoto,Mami Iima,Masahiro Takada,Yuji Nakamoto
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:60 (2): 401-416 被引量:18
标识
DOI:10.1002/jmri.29082
摘要

The development of ultrafast dynamic contrast‐enhanced (UF‐DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view‐sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF‐DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF‐DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time‐intensity curve. Because kinetic information from UF‐DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper‐vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF‐DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF‐DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF‐DCE MRI, which offers better lesion‐to‐noise contrast. The excellent contrast of early‐enhancing vessels provides a key to understanding the detailed pathological structure of tumor‐associated vessels. UF‐DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence‐based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF‐DCE MRI are summarized. Evidence Level 5 Technical Efficacy Stage 2
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