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JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Identification of Breast Cancer Using Integrated Information from MRI and Mammography.
PloS One 2015
OBJECTIVES: Integration of information from corresponding regions between the breast MRI and an X-ray mammogram could benefit the detection of breast cancer in clinical diagnosis. We aimed to provide a framework of registration from breast MRI to mammography and to evaluate the diagnosis using the combined information.
MATERIALS AND METHODS: 43 patients with 46 lesions underwent both MRI and mammography scans, and the interval between the two examinations was around one month. The distribution of malignant to benign lesions was 31/46 based on histological results. Maximum intensity projection and thin-plate spline methods were applied for image registration for MRI to mammography. The diagnosis using integrated information was evaluated using results of histology as the reference. The assessment of annotations and statistical analysis were performed by the two radiologists.
RESULTS: For the cranio-caudal view, the mean post-registration error between MRI and mammography was 2.2±1.9 mm. For the medio-lateral oblique view, the proposed approach performed even better with a mean error of 3.0±2.4 mm. In the diagnosis using MRI assessment with information of mammography, the sensitivity was 91.9±2.3% (29/31, 28/31), specificity 70.0±4.7% (11/15, 10/15), accuracy 84.8±3.1% (40/46, 38/46), positive predictive value 86.4±2.1% (29/33, 28/33) and negative predictive value 80.8±5.4% (11/13, 10/13).
CONCLUSION: MRI with the aid of mammography shows potential improvements of sensitivity, specificity, accuracy, PPV and NPV in clinical breast cancer diagnosis compared to the use of MRI alone.
MATERIALS AND METHODS: 43 patients with 46 lesions underwent both MRI and mammography scans, and the interval between the two examinations was around one month. The distribution of malignant to benign lesions was 31/46 based on histological results. Maximum intensity projection and thin-plate spline methods were applied for image registration for MRI to mammography. The diagnosis using integrated information was evaluated using results of histology as the reference. The assessment of annotations and statistical analysis were performed by the two radiologists.
RESULTS: For the cranio-caudal view, the mean post-registration error between MRI and mammography was 2.2±1.9 mm. For the medio-lateral oblique view, the proposed approach performed even better with a mean error of 3.0±2.4 mm. In the diagnosis using MRI assessment with information of mammography, the sensitivity was 91.9±2.3% (29/31, 28/31), specificity 70.0±4.7% (11/15, 10/15), accuracy 84.8±3.1% (40/46, 38/46), positive predictive value 86.4±2.1% (29/33, 28/33) and negative predictive value 80.8±5.4% (11/13, 10/13).
CONCLUSION: MRI with the aid of mammography shows potential improvements of sensitivity, specificity, accuracy, PPV and NPV in clinical breast cancer diagnosis compared to the use of MRI alone.
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