• Title of article

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

  • Author/Authors

    Kim، نويسنده , , Eun Jeong and Kim، نويسنده , , Sung-Hun and Kang، نويسنده , , Bong Joo and Choi، نويسنده , , Byung Gil and Song، نويسنده , , Byung-Joo and Choi، نويسنده , , Jae Jeong، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    7
  • From page
    1230
  • To page
    1236
  • Abstract
    AbstractPurposes luate the diagnostic value of diffusion-weighted MRI (DWI) and combination of conventional MRI and DWI to predict metastatic axillary lymph nodes in breast cancer. als and methods ndred 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. s ventional 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 mm2/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%). sion conventional MRI and DWI, we can evaluate the axilla in breast cancer with high specificity.
  • Keywords
    breast neoplasms , Diffusion magnetic resonance imaging , Lymphatic metastasis , MAGNETIC RESONANCE IMAGING
  • Journal title
    Magnetic Resonance Imaging
  • Serial Year
    2014
  • Journal title
    Magnetic Resonance Imaging
  • Record number

    1834591