The purpose of this article is to report our practical utilization of dynamic contrast-enhanced magnetic resonance mammography [DCE-MRM] in the diagnosis of breast lesions. In many European centers, was preferred a high-temporal acquisition of both breasts simultaneously in a large FOV. We preferred to scan single breasts, with the aim to combine the analysis of the contrast intake and washout with the morphological evaluation of breast lesions. We followed an interpretation model, based upon a diagnostic algorithm, which combined contrast enhancement with morphological evaluation, in order to increase our confidence in diagnosis. DCE-MRM with our diagnostic algorithm has identified 179 malignant and 41 benign lesions; final outcome has identified 178 malignant and 42 benign lesions, 3 false positives and 2 false negatives. Sensitivity of CE-MRM was 98.3%; specificity, 95.1%; positive predictive value 98.9%; negative predictive,. value, 92.8% and accuracy, 97.7%. (C) 2008 Elsevier Ltd. All rights reserved
Practical application of contrast-enhanced magnetic resonance mammography [CE-MRM] by an algorithm combining morphological and enhancement patterns / Potente, Giuseppe; Messineo, Daniela; Maggi, Claudia; Savelli, Sara. - In: COMPUTERIZED MEDICAL IMAGING AND GRAPHICS. - ISSN 0895-6111. - STAMPA. - 33:2(2009), pp. 83-90. [10.1016/j.compmedimag.2008.10.004]
Practical application of contrast-enhanced magnetic resonance mammography [CE-MRM] by an algorithm combining morphological and enhancement patterns
POTENTE, Giuseppe;MESSINEO, Daniela;MAGGI, CLAUDIA;SAVELLI, SARA
2009
Abstract
The purpose of this article is to report our practical utilization of dynamic contrast-enhanced magnetic resonance mammography [DCE-MRM] in the diagnosis of breast lesions. In many European centers, was preferred a high-temporal acquisition of both breasts simultaneously in a large FOV. We preferred to scan single breasts, with the aim to combine the analysis of the contrast intake and washout with the morphological evaluation of breast lesions. We followed an interpretation model, based upon a diagnostic algorithm, which combined contrast enhancement with morphological evaluation, in order to increase our confidence in diagnosis. DCE-MRM with our diagnostic algorithm has identified 179 malignant and 41 benign lesions; final outcome has identified 178 malignant and 42 benign lesions, 3 false positives and 2 false negatives. Sensitivity of CE-MRM was 98.3%; specificity, 95.1%; positive predictive value 98.9%; negative predictive,. value, 92.8% and accuracy, 97.7%. (C) 2008 Elsevier Ltd. All rights reservedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.