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扩散加权回波平面磁共振成像:鉴别原发性腮腺肿瘤的有效工具?

Diffusion-weighted echo-planar MRI: a valuable tool for differentiating primary parotid gland tumors?

作者信息

Habermann C R, Gossrau P, Graessner J, Arndt C, Cramer M C, Reitmeier F, Jaehne M, Adam G

机构信息

Department of Diagnostic and Interventional Radiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

出版信息

Rofo. 2005 Jul;177(7):940-5. doi: 10.1055/s-2005-858297.


DOI:10.1055/s-2005-858297
PMID:15973595
Abstract

PURPOSE: To investigate the feasibility of using diffusion-weighted (DW) echo-planar imaging (EPI) for differentiating primary parotid gland tumors. MATERIAL AND METHODS: Fifty consecutive patients with a suspected primary tumor of the parotid gland were examined with a DW EPI sequence (TR 1,500 msec, TE 77 msec, field of view 250 x 250 mm, pixel size 2.10 x 1.95 mm, section thickness 5 mm). The b factors used were 0, 500, and 1,000 sec/mm (2). Apparent diffusion coefficient (ADC) maps were digitally transferred to MRIcro (Chris Rorden, University of Nottingham, Great Britain) and evaluated with a manually placed irregular region of interest (ROI) containing the entire tumor. Additionally, the contralateral, non affected parotid gland was measured and a circular ROI containing 100 - 200 pixels was placed in the cerebrospinal fluid (CSF) next to the spinal cord in every patient. For comparison of the results, the two-tailed Student's t test was used, based on the median ADC values for each patient, and a p-value <.05 was determined to indicate statistical significance. RESULTS: In 45 patients, a primary neoplasm of the parotid gland could be histologically verified. For the non-affected parotid glands of all 45 evaluated patients, the mean ADC value was 1.14 x 10 ( - 3) mm (2)/sec +/- 0.12 x 10 ( - 3) mm (2)/sec (mean +/- standard deviation). Seven different entities of parotid gland tumors were histologically discriminated. Pleomorphic adenomas (2.14 x 10 ( - 3) mm (2)/sec +/- 0.11 x 10 ( - 3) mm (2)/sec), Warthin tumors (0.85 x 10 ( - 3) mm (2)/sec +/- 0.1 x 10 ( - 3) mm (2)/sec), and mucoepidermoid carcinomas (1.04 x 10 ( - 3) mm (2)/sec +/- 0.3 x 10 ( - 3) mm (2)/sec) showed statistically significant different ADC values in comparison to all other evaluated tumors (p .001), and also among each other (p <.001). Additionally, ADC values presented by lipomas were statistically significant compared to all other entities (p <.001 to .015). Among all other [corrected] primary malignant parotid gland tumors, no statistically significant ADC values could be observed (p .18 to 1). CONCLUSION: Diffusion-weighted echo-planar MRI seems to be a valuable tool for differentiating benign from malignant primary parotid gland tumors.

摘要

目的:探讨使用扩散加权(DW)回波平面成像(EPI)鉴别腮腺原发性肿瘤的可行性。 材料与方法:连续50例疑似腮腺原发性肿瘤患者接受DW EPI序列检查(重复时间1500毫秒,回波时间77毫秒,视野250×250毫米,像素大小2.10×1.95毫米,层厚5毫米)。使用的b值为0、500和1000秒/毫米²。表观扩散系数(ADC)图被数字传输至MRIcro(英国诺丁汉大学的Chris Rorden),并通过手动放置包含整个肿瘤的不规则感兴趣区(ROI)进行评估。此外,测量对侧未受影响的腮腺,并在每位患者脊髓旁的脑脊液(CSF)中放置一个包含100 - 200像素的圆形ROI。为比较结果,基于每位患者的ADC中位数,使用双尾Student t检验,p值<.05被判定为具有统计学意义。 结果:45例患者的腮腺原发性肿瘤经组织学证实。在所有45例接受评估患者的未受影响腮腺中,平均ADC值为1.14×10⁻³毫米²/秒±0.12×10⁻³毫米²/秒(平均值±标准差)。组织学上鉴别出7种不同类型的腮腺肿瘤。多形性腺瘤(2.14×10⁻³毫米²/秒±0.11×10⁻³毫米²/秒)、沃辛瘤(0.85×10⁻³毫米²/秒±0.1×10⁻³毫米²/秒)和黏液表皮样癌(1.04×10⁻³毫米²/秒±0.3×10⁻³毫米²/秒)与所有其他评估肿瘤相比,ADC值具有统计学显著差异(p<.001),且彼此之间也有差异(p<.001)。此外,脂肪瘤的ADC值与所有其他类型相比具有统计学显著性(p<.001至.015)。在所有其他[校正后]腮腺原发性恶性肿瘤中,未观察到统计学显著的ADC值(p=.18至1)。 结论:扩散加权回波平面MRI似乎是鉴别腮腺原发性肿瘤良恶性的一种有价值的工具。

相似文献

[1]
Diffusion-weighted echo-planar MRI: a valuable tool for differentiating primary parotid gland tumors?

Rofo. 2005-7

[2]
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[3]
[Functional imaging of submandibular glands: diffusion-weighted echo-planar MRI before and after stimulation].

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[4]
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[5]
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J Magn Reson Imaging. 2009-9

[6]
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J Magn Reson Imaging. 2008-11

[7]
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Acta Radiol. 2008-4

[8]
Value of apparent diffusion coefficient calculation in the differential diagnosis of parotid gland tumors.

Acta Radiol. 2007-11

[9]
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[10]
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J Imaging. 2024-10-18

[2]
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Int J Mol Sci. 2023-6-12

[3]
Radiomic Analysis of Multi-parametric MR Images (MRI) for Classification of Parotid Tumors.

J Biomed Phys Eng. 2022-12-1

[4]
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World J Radiol. 2022-8-28

[5]
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Dentomaxillofac Radiol. 2021-5-1

[6]
Classification of parotid gland tumors by using multimodal MRI and deep learning.

NMR Biomed. 2021-1

[7]
Diffusion-Weighted Imaging in Oncology: An Update.

Cancers (Basel). 2020-6-8

[8]
Effects of region of interest sizes on apparent diffusion coefficient measurements of pleomorphic adenoma, Warthin tumor, and normal parotid parenchyma.

Quant Imaging Med Surg. 2019-4

[9]
Quantitative diffusion magnetic resonance imaging in head and neck tumors.

Quant Imaging Med Surg. 2018-11

[10]
Non-enhanced MRI in combination with color Doppler flow imaging for improving diagnostic accuracy of parotid gland lesions.

Eur Arch Otorhinolaryngol. 2018-4

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