4.5 Article

Body diffusion-weighted MR imaging of uterine endometrial cancer: Is it helpful in the detection of cancer in nonenhanced MR imaging?

期刊

EUROPEAN JOURNAL OF RADIOLOGY
卷 70, 期 1, 页码 122-127

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.ejrad.2007.11.042

关键词

Diffusion-weighted image; Magnetic resonance (MR) image; Uterine endometrial cancer; Apparent diffusion coefficient

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Objective: In this study, the authors discussed the feasibility and value of diffusion-weighted (DW) MR imaging in the detection of uterine endometrial cancer in addition to conventional nonenhanced MR images. Methods and materials: DW images of endometrial cancer in 23 patients were examined by using a 1.5-T MR scanner. This study investigated whether or not DW images offer additional incremental value to conventional nonenhanced MR imaging in comparison with histopathological results. Moreover, the apparent diffusion coefficient (ADC) values were measured in the regions of interest within the endometrial cancer and compared with those of normal endometrium and myometrium in 31 volunteers, leiomyoma in 14 patients and adenomyosis in 10 patients. The Wilcoxon rank sum test was used, with a p < 0.05 considered statistically significant. Results: In 19 of 23 patients, endometrial cancers were detected only on T2-weighted images. In the remaining 4 patients, of whom two had coexisting leiomyoma, no cancer was detected on T2-weighted images. This corresponds to an 83% detection sensitivity for the carcinomas. When DW images and fused DW images/T2-weighted images were used in addition to the T2-weighted images, cancers were identified in 3 of the remaining 4 patients in addition to the 19 patients (overall detection sensitivity of 96%). The mean ADC value of endometrial cancer (n = 22) was (0.97 +/- 0.19) x 10(-3) mm(2)/s, which was significantly lower than those of the normal endometrium, myometrium, leiomyoma and adenomyosis (p < 0.05). Conclusion: DW imaging can be helpful in the detection of uterine endometrial cancer in nonenhanced MR imaging. (C) 2007 Elsevier Ireland Ltd. All rights reserved.

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