Diffusion-weighted magnetic resonance imaging of endometrial cancer: differentiation from benign endometrial lesions and preoperative assessment of myometrial invasion

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Abstract

BACKGROUND: Uterine endometrial cancer is the most common gynecologic malignancy, and benign endometrial hyperplasia or polyps should be differentiated from endometrial cancer. In evaluating endometrial cancer on magnetic resonance imaging (MRI), the assessment of the depth of myometrial invasion is important because it closely correlates with the patient's prognosis. PURPOSE: To verify the feasibility of diffusion-weighted magnetic resonance imaging (DWI) to distinguish benign and malignant endometrial lesions, and to evaluate myometrial invasion of endometrial cancer. MATERIAL AND METHODS: Sixty-seven endometrial lesions including 45 cancers and 22 benign lesions (hyperplasia and polyps) were evaluated by DWI with apparent diffusion coefficient (ADC) measurement. The staging accuracies of DWI and gadolinium-enhanced T1-weighted images in the assessment of myometrial invasion were evaluated in 33 patients with endometrial cancer. RESULTS: The ADC values (x10(-3) mm(2)/s) in cancer and benign lesions were 0.84+/-0.19 and 1.58+/-0.36, respectively (P<0.01). The staging accuracy (superficial or deep myometrial invasion) was 94% for DWI and 88% for gadolinium-enhanced T1-weighted images. Coexisting adenomyosis and infiltrative myometrial invasion caused staging errors on gadolinium-enhanced T1-weighted images, whereas DWI could demonstrate the tumor extent correctly. CONCLUSION: DWI provides helpful information in evaluating benign and malignant endometrial lesions.

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Condition tags

adenomyosis

MeSH descriptors

Diffusion Magnetic Resonance Imaging Endometrial Neoplasms Adult Aged Aged, 80 and over Contrast Media Diagnosis, Differential Diffusion Magnetic Resonance Imaging Endometrial Neoplasms Endometrial Neoplasms Feasibility Studies Female Gadolinium Humans Middle Aged Neoplasm Invasiveness Predictive Value of Tests Retrospective Studies Sensitivity and Specificity Statistics, Nonparametric

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europepmc
last seen: 2026-08-07T06:07:27.085738+00:00
pubmed
last seen: 2026-05-13T22:13:59.677786+00:00
unpaywall
last seen: 2026-05-14T19:30:52.867331+00:00
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