Add like
Add dislike
Add to saved papers

Diagnostic value of diffusion-weighted magnetic resonance imaging in discriminating between metastatic and non-metastatic pelvic lymph nodes in endometrial cancer.

Acta Radiologica 2020 November
BACKGROUND: Researchers have recently focused on assessing the accuracy of diffusion-weighted magnetic resonance imaging (DW-MRI) in predicting pelvic lymph node metastases in gynecological malignancies.

PURPOSE: To evaluate the diagnostic value of DW-MRI in discriminating between metastatic and non-metastatic pelvic lymph nodes in endometrial cancer patients.

MATERIAL AND METHODS: This retrospective database study was conducted with 33 women aged 30-84 years with pathologically proven endometrial cancer that had been assessed by DW-MRI before their first treatment initiation at our referral hospital from March 2016 to April 2019. The diffusion technique (b = 50, 400, and 1000 mm2 /s) was used in the imaging, and continuous apparent diffusion coefficient (ADC) metrics (ADCmin , ADCmax , ADCmean , ADCSD , and rADC) were compared between the metastatic and non-metastatic lymph nodes.

RESULTS: In total, 48 lymph nodes from 33 patients were assessed. All metastatic lymph nodes were restricted, while among the non-metastatic lymph nodes, only 19.3% were restricted. Considering pathological reports of metastatic and non-metastatic lymph nodes as the gold standard, DWI-related restricted and non-restricted features had a sensitivity of 80.6%, a specificity of 100%, and an accuracy of 87.5% to discriminate between a metastatic and non-metastatic pattern. ADC metrics of ADCmin , ADCmax , ADCmean , ADCSD , and rADC showed high values enabling differentiation between metastatic and non-metastatic lymph nodes. The best cut-off values were 0.7 × 10-3 , 1.2 × 10-3 , 1.01 × 10-3 , 123, and 0.78, respectively.

CONCLUSION: DW-MRI is a useful quantitative tool for differentiating between metastatic and benign lymph nodes in endometrial cancer patients.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app