Suppr超能文献

基于去卷积的二次团注T1加权动态对比增强数据分析法对乳腺肿瘤灌注和通透性的定量分析

Quantification of perfusion and permeability in breast tumors with a deconvolution-based analysis of second-bolus T1-DCE data.

作者信息

Makkat S, Luypaert R, Sourbron S, Stadnik T, De Mey J

机构信息

Department of Radiology, Academisch Ziekenhuis Vrije Universiteit Brussel/Medische Beeldvorming en Fysische Wetenschappen (BEFY), Laarbeeklaan 101, 1090 Brussels, Belgium.

出版信息

J Magn Reson Imaging. 2007 Jun;25(6):1159-67. doi: 10.1002/jmri.20937.

Abstract

PURPOSE

To test the feasibility of using a second-bolus injection, added to a routine breast MRI examination, to measure regional perfusion and permeability in human breast tumors.

MATERIALS AND METHODS

In 30 patients with breast tumors, first a routine whole-breast T1-DCE sequence was applied, and the slice where the lesion enhanced maximally was located. At that slice position, T1-weighted MR images were acquired at 0.3-second resolution using a second-bolus dynamic inversion recovery (IR)-prepared turbo field echo (TFE) sequence. A pixel-by-pixel model-independent deconvolution of the relative signal enhancement was performed to estimate the tumor blood flow (TBF), tumor volume of distribution (TVD), mean transit time (MTT), extraction flow product (EF), and extraction fraction (E). In addition to this pilot study, a first appraisal of its sensitivity to tissue type was made on the basis of a small patient cohort.

RESULTS

In the malignant tumors, the parametric maps clearly delineated tumors from the breast tissue and enabled visualization of the heterogeneity. The deconvolution analysis provided objective parametric maps of tumor perfusion with a mean TBF (84 +/- 48 mL/100 mL/minute) in malignant tumors in the high range of literature values.

CONCLUSION

In terms of these perfusion values, our method appears promising to quantitatively characterize tumor pathophysiology. However, the number of patients was limited, and the separation between malignant and benign groups was not clear-cut. Additional parameters generated through compartment modeling may improve the tumor differentiation.

摘要

目的

测试在常规乳腺MRI检查中增加第二次团注注射以测量人类乳腺肿瘤区域灌注和通透性的可行性。

材料与方法

对30例乳腺肿瘤患者,首先应用常规全乳腺T1-DCE序列,定位病变强化最大的层面。在该层面位置,使用第二次团注动态反转恢复(IR)准备的快速场回波(TFE)序列,以0.3秒分辨率采集T1加权MR图像。对相对信号增强进行逐像素独立于模型的去卷积,以估计肿瘤血流量(TBF)、肿瘤分布容积(TVD)、平均通过时间(MTT)、提取流量积(EF)和提取分数(E)。除了这项初步研究外,还基于一小群患者对其对组织类型的敏感性进行了首次评估。

结果

在恶性肿瘤中,参数图清晰地将肿瘤与乳腺组织区分开来,并能够显示异质性。去卷积分析提供了肿瘤灌注的客观参数图,恶性肿瘤的平均TBF(84±48 mL/100 mL/分钟)处于文献值的较高范围。

结论

就这些灌注值而言,我们的方法似乎有望定量表征肿瘤病理生理学。然而,患者数量有限,恶性和良性组之间的区分并不明确。通过房室模型生成的其他参数可能会改善肿瘤的鉴别。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验