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表观扩散系数(ADC)直方图分析:应用分段读出扩散加权成像对腮腺良恶性肿瘤进行鉴别诊断。

Apparent diffusion coefficient (ADC) histogram analysis: differentiation of benign from malignant parotid gland tumors using readout-segmented diffusion-weighted imaging.

机构信息

Department of Radiology, The first Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R. China.

MR Collaboration, Siemens Healthcare, Beijing, China.

出版信息

Dentomaxillofac Radiol. 2019 Oct;48(7):20190100. doi: 10.1259/dmfr.20190100. Epub 2019 Jul 9.

DOI:10.1259/dmfr.20190100
PMID:31265331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6775791/
Abstract

OBJECTIVES

To explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating parotid gland tumors following readout-segmented diffusion-weighted imaging (RESOLVE).

METHODS

80 patients (40 with pleomorphic adenomas, 14 with Warthin tumors, and 26 with malignant parotid gland tumors) who underwent routine head-and-neck MRI and RESOLVE examinations, were retrospectively evaluated. RESOLVE data were acquired from a MAGNETOM Skyra 3T MR system. Eleven whole-lesion histogram parameters derived from histogram analysis (ADC_mean, ADC_minimum, ADC_maximum, ADC_1th, ADC_10th, ADC_50th, ADC_90th, ADC_99th, skewness, variance and kurtosis) were calculated for each patient using MaZda. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of the ADC for distinguishing among the three groups.

RESULTS

In total, nine parameters (ADC_minimum, ADC_maximum, ADC_mean, ADC_10th, ADC_50th, ADC_90th, ADC_99th, variance, skewness) were statistically significant (all < 0.05) for all three groups, in the comparison of pleomorphic adenomas to Warthin tumors; the ADC_mean, ADC_50th, and skewness revealed high diagnostic efficiency with areas under the receiver operating characteristic curve of 0.976, 0.970, and 0.970, respectively. In the comparison of pleomorphic adenomas to malignant parotid gland tumors, these nine parameters were also found to be statistically different (all < 0.05); the ADC_mean, ADC_10th and ADC_50th revealed high diagnostic efficiency with area under the curve of 0.851, 0.866, and 0.841, respectively. However, in the comparison of Warthin tumors to malignant parotid gland tumors, only three parameters (ADC_mean, ADC_50th, skewness) were statistically significant (all < 0.05).

CONCLUSIONS

Whole-lesion ADC histograms are effective in differentiating common parotid gland tumors.

摘要

目的

探讨基于分段回波的弥散加权成像(RESOLVE)后全病变表观弥散系数(ADC)直方图分析在鉴别腮腺肿瘤中的应用价值。

方法

回顾性分析 80 例(多形性腺瘤 40 例、Warthin 瘤 14 例、恶性腮腺肿瘤 26 例)接受常规头颈部 MRI 和 RESOLVE 检查的患者。RESOLVE 数据来自 MAGNETOM Skyra 3T MR 系统。使用 MaZda 计算每位患者的 11 个全病变直方图参数(ADC_mean、ADC_minimum、ADC_maximum、ADC_1th、ADC_10th、ADC_50th、ADC_90th、ADC_99th、偏度、方差和峰度)。采用受试者工作特征(ROC)曲线分析评估 ADC 鉴别三组患者的诊断效能。

结果

在多形性腺瘤与 Warthin 瘤的比较中,9 个参数(ADC_minimum、ADC_maximum、ADC_mean、ADC_10th、ADC_50th、ADC_90th、ADC_99th、方差、偏度)均有统计学意义(均<0.05);ADC_mean、ADC_50th 和偏度的 ROC 曲线下面积分别为 0.976、0.970 和 0.970,诊断效能较高。在多形性腺瘤与恶性腮腺肿瘤的比较中,这 9 个参数也有统计学差异(均<0.05);ADC_mean、ADC_10th 和 ADC_50th 的 ROC 曲线下面积分别为 0.851、0.866 和 0.841,诊断效能较高。然而,在 Warthin 瘤与恶性腮腺肿瘤的比较中,仅有 3 个参数(ADC_mean、ADC_50th、偏度)有统计学意义(均<0.05)。

结论

全病变 ADC 直方图在鉴别常见腮腺肿瘤方面具有一定的应用价值。

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