Suppr超能文献

1.5T场强下短TI反转恢复序列(STIR)与自旋回波磁共振成像对45例疑似肢体肿瘤的比较:病变的显示清晰度及范围

Comparison of STIR and spin-echo MR imaging at 1.5 T in 45 suspected extremity tumors: lesion conspicuity and extent.

作者信息

Shuman W P, Patten R M, Baron R L, Liddell R M, Conrad E U, Richardson M L

机构信息

Department of Radiology, University of Washington School of Medicine, Seattle.

出版信息

Radiology. 1991 Apr;179(1):247-52. doi: 10.1148/radiology.179.1.2006285.

Abstract

Short inversion time inversion recovery (STIR) imaging and a double-echo spin-echo (SE) sequence at 1.5 T in 45 sequential patients with suspected extremity tumors were compared to assess the number of lesions detected, subjective conspicuity of lesions, approximate volume of abnormality detected in each lesion, and identification of peritumoral brightening in tissues adjacent to each lesion. STIR sequences enabled detection of all 45 lesions; 44 were detected with the SE sequence. Tumor appeared most conspicuous on STIR images in 35 patients (78%) and was most conspicuous on SE images in 10 patients (22%). Peritumoral brightening, which indicated either peritumoral edema or microscopic tumor infiltration, was detected in 20 patients but was detected only with STIR sequences in nine patients. It is concluded that, although STIR and SE sequences are comparable for lesion detection in the extremities, most lesions appear more conspicuous with STIR. STIR may enable detection of a greater volume of abnormality than SE sequences and may therefore have important implications for local staging and surgical and radiation therapy planning.

摘要

对45例连续的疑似肢体肿瘤患者,在1.5T场强下采用短反转时间反转恢复(STIR)成像和双回波自旋回波(SE)序列进行检查,比较两者检测到的病变数量、病变的主观清晰度、每个病变中检测到的异常大致体积,以及每个病变相邻组织中瘤周强化的识别情况。STIR序列能够检测到所有45个病变;SE序列检测到44个病变。35例患者(78%)的肿瘤在STIR图像上最为清晰,10例患者(22%)的肿瘤在SE图像上最为清晰。20例患者检测到瘤周强化,提示瘤周水肿或微小肿瘤浸润,但其中9例患者仅在STIR序列中检测到。结论是,虽然STIR和SE序列在肢体病变检测方面具有可比性,但大多数病变在STIR图像上显得更清晰。与SE序列相比,STIR可能能够检测到更大体积的异常,因此可能对局部分期以及手术和放射治疗计划具有重要意义。

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