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颈部淋巴结外扩散:基于像素的时间信号强度曲线分析的 MRI 检测。

Extranodal spread in the neck: MRI detection on the basis of pixel-based time-signal intensity curve analysis.

机构信息

Department of Radiology and Cancer Biology, Nagasaki University School of Dentistry, Nagasaki, Japan.

出版信息

J Magn Reson Imaging. 2011 Apr;33(4):830-8. doi: 10.1002/jmri.22454.

Abstract

PURPOSE

We evaluated dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the preoperative detection of extranodal spread (ENS) in metastatic nodes in the neck.

MATERIALS AND METHODS

The time-signal intensity curve (TIC) profiles of 54 histologically proven metastatic nodes (26 ENS-positive and 28 ENS-negative) from 43 patients with head and neck squamous cell carcinoma (SCC) were retrospectively analyzed to determine the effective TIC criteria for ENS-positive nodes. The TICs were semiautomatically classified into four distinctive patterns (flat, slow uptake, rapid uptake with low washout ratio, and rapid uptake with high washout ratio) on a pixel-by-pixel basis.

RESULTS

A number of the MRI findings were significantly correlated with ENS. However, multivariate logistic regression analysis revealed that only a short-axis diameter and an area with slow uptake TIC patterns were significantly and independently indicative of the presence of ENS. The combined MRI criteria of nodal size (>25 mm) or TIC profile (>44% nodal areas with slow-uptake TIC patterns) yielded the best results for differentiation between ENS-positive and ENS-negative nodes, providing 96% sensitivity, 100% specificity, 98% accuracy, and 100% positive, and 97% negative predictive values.

CONCLUSION

When combined with size criteria, pixel-based MR factor analysis may be a promising tool for detecting ENS.

摘要

目的

我们评估了动态对比增强(DCE)磁共振成像(MRI)在术前检测颈部转移性淋巴结的结外扩散(ENS)中的作用。

材料与方法

回顾性分析了 43 例头颈部鳞癌(SCC)患者的 54 个经组织学证实的转移性淋巴结(26 个 ENS 阳性和 28 个 ENS 阴性)的时间信号强度曲线(TIC)曲线,以确定 ENS 阳性淋巴结的有效 TIC 标准。TIC 以像素为基础半自动地分为四种不同的模式(平的、缓慢摄取、快速摄取伴低洗脱率和快速摄取伴高洗脱率)。

结果

多项 MRI 发现与 ENS 显著相关。然而,多变量逻辑回归分析显示,只有短轴直径和缓慢摄取 TIC 模式的区域是 ENS 存在的显著且独立的预测指标。淋巴结大小(>25mm)或 TIC 曲线(>44%的淋巴结区域具有缓慢摄取 TIC 模式)的联合 MRI 标准在区分 ENS 阳性和 ENS 阴性淋巴结方面效果最佳,提供了 96%的敏感性、100%的特异性、98%的准确性和 100%的阳性预测值,以及 97%的阴性预测值。

结论

当与大小标准相结合时,基于像素的磁共振因子分析可能是一种有前途的检测 ENS 的工具。

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