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Predictive Value of Preoperative Multidetector-Row Computed Tomography for Axillary Lymph Nodes Metastasis in Patients With Breast Cancer.
Chen, Chun-Fa; Zhang, Yu-Ling; Cai, Ze-Long; Sun, Shu-Ming; Lu, Xiao-Feng; Lin, Hao-Yu; Liang, Wei-Quan; Yuan, Ming-Heng; Zeng, De.
Afiliación
  • Chen CF; Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Zhang YL; Department of Information, Cancer Hospital of Shantou University Medical College, Shantou, China.
  • Cai ZL; Department of Medical Imaging, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Sun SM; Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Lu XF; Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Lin HY; Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Liang WQ; Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Yuan MH; Cancer Research Center, Shantou University Medical College, Shantou, China.
  • Zeng; Department of Medical Oncology, Cancer Hospital of Shantou University Medical College, Shantou, China.
Front Oncol ; 8: 666, 2018.
Article en En | MEDLINE | ID: mdl-30671386
Introduction: Axillary lymph nodes (ALN) status is an essential component in tumor staging and treatment planning for patients with breast cancer. The aim of present study was to evaluate the predictive value of preoperative multidetector-row computed tomography (MDCT) for ALN metastasis in breast cancer patients. Methods: A total of 148 cases underwent preoperative MDCT examination and ALN surgery were eligible for the study. Logistic regression analysis of MDCT variates was used to estimate independent predictive factors for ALN metastasis. The prediction of ALN metastasis was determined with MDCT variates through receiver operating characteristic (ROC) analysis. Results: Among the 148 cases, 61 (41.2%) cases had ALN metastasis. The cortical thickness in metastatic ALN was significantly thicker than that in non-metastatic ALN (7.5 ± 5.0 mm vs. 2.6 ± 2.8 mm, P < 0.001). Multi-logistic regression analysis indicated that cortical thickness of >3 mm (OR: 12.32, 95% CI: 4.50-33.75, P < 0.001) and non-fatty hilum (OR: 5.38, 95% CI: 1.51-19.19, P = 0.009) were independent predictors for ALN metastasis. The sensitivity, specificity and AUC of MDCT for ALN metastasis prediction based on combined-variated analysis were 85.3%, 87.4%, and 0.893 (95% CI: 0.832-0.938, P < 0.001), respectively. Conclusions: Cortical thickness (>3 mm) and non-fatty hilum of MDCT were independent predictors for ALN metastasis. MDCT is a potent imaging tool for predicting ALN metastasis in breast cancer. Future prospective study on the value of contrast enhanced MDCT in preoperative ALN evaluation is warranted.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2018 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
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Imprimir
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2018 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza