Suppr超能文献

多形性腺瘤磁共振成像中的瘤内和瘤间变异性:解读磁共振成像多样表现的尝试

Inter- and intratumoral variability in magnetic resonance imaging of pleomorphic adenoma: an attempt to interpret the variable magnetic resonance findings.

作者信息

Motoori Ken, Yamamoto Seiji, Ueda Takuya, Nakano Koichi, Muto Takayuki, Nagai Yuichiro, Ikeda Mitsuaki, Funatsu Hiroyuki, Ito Hisao

机构信息

Departments of Radiology and Otolaryngology, Chiba University Hospital, Chiba, Japan.

出版信息

J Comput Assist Tomogr. 2004 Mar-Apr;28(2):233-46. doi: 10.1097/00004728-200403000-00014.

Abstract

OBJECTIVES

The purpose of our study was to describe the various magnetic resonance (MR) findings of pleomorphic adenoma and to interpret these findings.

METHODS

MR studies of 33 pleomorphic adenomas and 13 malignant tumors in the major salivary glands were reviewed.

RESULTS

High signal intensity on short-inversion-time inversion recovery (STIR) and T2-weighted (T2W) images, progressive enhancement on dynamic MR images, and high apparent diffusion coefficient (ADC) values on diffusion-weighted (DW) images reflected myxoid-dominant components in pleomorphic adenomas. Hypercellularity with less-myxoid stroma showed reduced signal intensity on STIR and T2W images and also reduced ADC values on DW images, and the peak of time versus signal intensity curves (TICs) was reached earlier on dynamic MR images.

CONCLUSIONS

The MR images of hypercellularity components in pleomorphic adenoma overlap with those of malignant parotid tumors. Detecting myxoid components by STIR, T2W, DW, and dynamic MR images is useful for predicting whether salivary gland tumors are pleomorphic adenoma or not.

摘要

目的

本研究的目的是描述多形性腺瘤的各种磁共振(MR)表现并对这些表现进行解读。

方法

回顾了33例大唾液腺多形性腺瘤和13例恶性肿瘤的MR研究。

结果

短反转时间反转恢复(STIR)和T2加权(T2W)图像上的高信号强度、动态MR图像上的渐进性强化以及扩散加权(DW)图像上的高表观扩散系数(ADC)值反映了多形性腺瘤中以黏液样为主的成分。细胞增多且黏液样基质较少的区域在STIR和T2W图像上信号强度降低,在DW图像上ADC值也降低,并且在动态MR图像上时间-信号强度曲线(TIC)达到峰值的时间更早。

结论

多形性腺瘤中细胞增多成分的MR图像与腮腺恶性肿瘤的MR图像有重叠。通过STIR、T2W、DW和动态MR图像检测黏液样成分有助于预测唾液腺肿瘤是否为多形性腺瘤。

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