OBJECTIVE: Malignant axillary lymph nodes are an important predictor for breast cancer recurrence, but invasive dissection or biopsy is required for the diagnosis. We determined whether and how malignant nodes could be diagnosed preoperatively with magnetic resonance (MR) imaging. MATERIALS AND METHODS: We obtained MR images of all women evaluated for breast cancer at the Sun Yat-Sen University Cancer Center in 2010 and correlated the image characteristics of each axillary node with the pathologic diagnosis of the same node. RESULTS: We analyzed 251 nodes (117 benign; 134 malignant) from 136 women (mean age, 44 years; range, 20-67). Mean diameter of the nodes was 18 mm (range, 5-58 mm). With pathologic diagnosis as the reference standard, MRI-based interpretations were 66.4% sensitive, 94% specific, and 79% accurate. Diameter, pathologic type, apparent diffusion coefficient value (ADC, b=500 and 800), time-intensity curve (TIC) type of breast tumors correlated with node metastasis; ADC value (b=500 and 800), TIC type, early enhancement rate, long-axis, short-axis, shape, margin and the location of nodes correlated with node metastasis (P<0.001 for all). Tumor immunohistochemistry results for estrogen receptors, progesterone receptors, c-erbB-2, vascular endothelial growth factor, and Ki67 were not. An MRI-based lymph node scoring system based on these correlations had a specificity of 91%, a sensitivity of 93%, and an area under the ROC curve of 0.95 (P<0.001). CONCLUSION: Metastatic axillary lymph nodes can be accurately diagnosed by MR in women with early breast cancer preoperatively and non-invasively. The scoring system appears to be superior to current methods.
OBJECTIVE: Malignant axillary lymph nodes are an important predictor for breast cancer recurrence, but invasive dissection or biopsy is required for the diagnosis. We determined whether and how malignant nodes could be diagnosed preoperatively with magnetic resonance (MR) imaging. MATERIALS AND METHODS: We obtained MR images of all women evaluated for breast cancer at the Sun Yat-Sen University Cancer Center in 2010 and correlated the image characteristics of each axillary node with the pathologic diagnosis of the same node. RESULTS: We analyzed 251 nodes (117 benign; 134 malignant) from 136 women (mean age, 44 years; range, 20-67). Mean diameter of the nodes was 18 mm (range, 5-58 mm). With pathologic diagnosis as the reference standard, MRI-based interpretations were 66.4% sensitive, 94% specific, and 79% accurate. Diameter, pathologic type, apparent diffusion coefficient value (ADC, b=500 and 800), time-intensity curve (TIC) type of breast tumors correlated with node metastasis; ADC value (b=500 and 800), TIC type, early enhancement rate, long-axis, short-axis, shape, margin and the location of nodes correlated with node metastasis (P<0.001 for all). Tumor immunohistochemistry results for estrogen receptors, progesterone receptors, c-erbB-2, vascular endothelial growth factor, and Ki67 were not. An MRI-based lymph node scoring system based on these correlations had a specificity of 91%, a sensitivity of 93%, and an area under the ROC curve of 0.95 (P<0.001). CONCLUSION: Metastatic axillary lymph nodes can be accurately diagnosed by MR in women with early breast cancer preoperatively and non-invasively. The scoring system appears to be superior to current methods.
Authors: Christopher Loiselle; Peter R Eby; Janice N Kim; Kristine E Calhoun; Kimberly H Allison; Vijayakrishna K Gadi; Sue Peacock; Barry E Storer; David A Mankoff; Savannah C Partridge; Constance D Lehman Journal: Acad Radiol Date: 2014-01 Impact factor: 3.173
Authors: Habib Rahbar; Jane L Conlin; Sana Parsian; Wendy B DeMartini; Sue Peacock; Constance D Lehman; Savannah C Partridge Journal: Acad Radiol Date: 2014-12-06 Impact factor: 3.173
Authors: V J L Kuijs; M Moossdorff; R J Schipper; R G H Beets-Tan; E M Heuts; K B M I Keymeulen; M L Smidt; M B I Lobbes Journal: Insights Imaging Date: 2015-03-24
Authors: Suvi Rautiainen; Mervi Könönen; Reijo Sironen; Amro Masarwah; Mazen Sudah; Juhana Hakumäki; Ritva Vanninen; Anna Sutela Journal: PLoS One Date: 2015-03-30 Impact factor: 3.240