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DOI 10.1016/j.mri.2014.07.001

Медицинская библиотека · Magnetic resonance imaging · 2014

Diagnostic value of breast MRI for predicting metastatic axillary lymph nodes in breast cancer patients: diffusion-weighted MRI and conventional MRI.

Kim Eun Jeong, Kim Sung Hun, Kang Bong Joo, Choi Byung Gil, Song Byung Joo, Choi Jae Jeong

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Аннотация

PURPOSES: To evaluate the diagnostic value of diffusion-weighted MRI (DWI) and combination of conventional MRI and DWI to predict metastatic axillary lymph nodes in breast cancer.

MATERIALS AND

METHODS

Two hundred fifty-two breast cancer patients with 253 axillae were included. The morphological parameters on axial T2-weighted images without fat saturation and apparent diffusion coefficient (ADC) values were retrospectively analyzed. An independent t-test/chi-square test and receiver operating characteristics (ROC) curve analysis were used.

RESULTS

On conventional MRI, short and long axis length, maximal cortical thickness, relative T2 value, loss of fatty hilum (p<0.001 for each), and eccentric cortical thickening (p<0.003) were statistically significantly different between the metastatic and nonmetastatic groups. The short axis to long axis ratio was not a statistically significant parameter. The ADC value was significantly different between the 2 groups, with an AUC that was higher than that of conventional MR parameters (AUC, 0.815; threshold, ≤0.986×10-3 mm(2)/sec; sensitivity, 75.8%; specificity, 83.9%). Using the adopted thresholds for each parameter, a total number of findings suggesting malignancy of 4 or higher was determined as the threshold, with high specificity (90.1%).

CONCLUSION

Using conventional MRI and DWI, we can evaluate the axilla in breast cancer with high specificity.

Для цитирования: Kim Eun Jeong, Kim Sung Hun, Kang Bong Joo, Choi Byung Gil, Song Byung Joo, Choi Jae Jeong. Diagnostic value of breast MRI for predicting metastatic axillary lymph nodes in breast cancer patients: diffusion-weighted MRI and conventional MRI.. Magnetic resonance imaging. 2014. DOI: 10.1016/j.mri.2014.07.001.

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