Christopher Loiselle1, Peter R Eby2, Janice N Kim3, Kristine E Calhoun4, Kimberly H Allison5, Vijayakrishna K Gadi6, Sue Peacock7, Barry E Storer8, David A Mankoff9, Savannah C Partridge10, Constance D Lehman7. 1. Department of Radiation Oncology, University of Washington Medical Center, Seattle, WA; Department of Radiation Oncology, Swedish Cancer Institute, Seattle, WA. 2. Department of Radiology, Virginia Mason Medical Center, Seattle, WA. 3. Department of Radiation Oncology, University of Washington Medical Center, Seattle, WA. 4. Department of Surgery, University of Washington Medical Center, Seattle, WA. 5. Department of Pathology, University of Washington Medical Center, Seattle, WA; Department of Pathology, Stanford University Medical Center, Stanford, CA. 6. Division of Medical Oncology, Department of Medicine, University of Washington Medical Center, Seattle, WA; Fred Hutchinson Cancer Research Center, Seattle, WA. 7. Department of Radiology, University of Washington Medical Center, Seattle, WA. 8. Fred Hutchinson Cancer Research Center, Seattle, WA. 9. Department of Radiology, University of Washington Medical Center, Seattle, WA; Department of Radiology, University of Pennsylvania, Philadelphia, PA. 10. Department of Radiology, University of Washington Medical Center, Seattle, WA. Electronic address: scp3@uw.edu.
Abstract
RATIONALE AND OBJECTIVES: To test the ability of quantitative measures from preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict, independently and/or with the Katz pathologic nomogram, which breast cancer patients with a positive sentinel lymph node biopsy will have four or more positive axillary lymph nodes on completion axillary dissection. MATERIALS AND METHODS: A retrospective review was conducted to identify clinically node-negative invasive breast cancer patients who underwent preoperative DCE-MRI, followed by sentinel node biopsy with positive findings and complete axillary dissection (June 2005-January 2010). Clinical/pathologic factors, primary lesion size, and quantitative DCE-MRI kinetics were collected from clinical records and prospective databases. DCE-MRI parameters with univariate significance (P < .05) to predict four or more positive axillary nodes were modeled with stepwise regression and compared to the Katz nomogram alone and to a combined MRI-Katz nomogram model. RESULTS: Ninety-eight patients with 99 positive sentinel biopsies met study criteria. Stepwise regression identified DCE-MRI total persistent enhancement and volume adjusted peak enhancement as significant predictors of four or more metastatic nodes. Receiver operating characteristic curves demonstrated an area under the curve of 0.78 for the Katz nomogram, 0.79 for the DCE-MRI multivariate model, and 0.87 for the combined MRI-Katz model. The combined model was significantly more predictive than the Katz nomogram alone (P = .003). CONCLUSIONS: Integration of DCE-MRI primary lesion kinetics significantly improved the Katz pathologic nomogram accuracy to predict the presence of metastases in four or more nodes. DCE-MRI may help identify sentinel node-positive patients requiring further local-regional therapy.
RATIONALE AND OBJECTIVES: To test the ability of quantitative measures from preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict, independently and/or with the Katz pathologic nomogram, which breast cancerpatients with a positive sentinel lymph node biopsy will have four or more positive axillary lymph nodes on completion axillary dissection. MATERIALS AND METHODS: A retrospective review was conducted to identify clinically node-negative invasive breast cancerpatients who underwent preoperative DCE-MRI, followed by sentinel node biopsy with positive findings and complete axillary dissection (June 2005-January 2010). Clinical/pathologic factors, primary lesion size, and quantitative DCE-MRI kinetics were collected from clinical records and prospective databases. DCE-MRI parameters with univariate significance (P < .05) to predict four or more positive axillary nodes were modeled with stepwise regression and compared to the Katz nomogram alone and to a combined MRI-Katz nomogram model. RESULTS: Ninety-eight patients with 99 positive sentinel biopsies met study criteria. Stepwise regression identified DCE-MRI total persistent enhancement and volume adjusted peak enhancement as significant predictors of four or more metastatic nodes. Receiver operating characteristic curves demonstrated an area under the curve of 0.78 for the Katz nomogram, 0.79 for the DCE-MRI multivariate model, and 0.87 for the combined MRI-Katz model. The combined model was significantly more predictive than the Katz nomogram alone (P = .003). CONCLUSIONS: Integration of DCE-MRI primary lesion kinetics significantly improved the Katz pathologic nomogram accuracy to predict the presence of metastases in four or more nodes. DCE-MRI may help identify sentinel node-positive patients requiring further local-regional therapy.
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