PURPOSE: The goal of this prospective study was to evaluate the possible diagnostic benefits of contrast-enhanced digital mammography (CEDM) over conventional mammography. MATERIALS AND METHODS: Our analysis included data from 70 patients with a total of 80 lesions (30 malignant and 50 benign). A series of contrast-enhanced images was acquired from each patient using a modified imaging system (GE Senographe 2000D with copper filter) suitable for displaying iodine contrast medium. After the mask image had been taken, the contrast medium was administered using a dosage of 1ml/kg body weight at a rate of 4ml/s. Three contrast-enhanced images in the cranio-caudal projection plane were then captured at intervals of 60s. The mask image was logarithmically subtracted from the contrast-enhanced images. We performed a ROC analysis of diagnostic quality with three readers. RESULTS: On average, 5.66 more malignant lesions were detected with the addition of digital dynamic contrast mammography versus conventional mammography alone. The sensitivity was increased from an average of 0.43 in conventional mammography to an average of 0.62 with contrast mammography. Even in dense breast parenchyma, the sensitivity increased from an average of 0.35-0.59. In the multi-reader-ROC analyses of all readers, the differences in the AUC with p=0.02 (BI-RADS) proved statistically significant in all cases. The Wilcoxon test showed that Readers I and II primarily used the CEDM to upgrade enhancing lesions to a higher BI-RADS category or a higher probability of malignancy. These two readers benefited most from the CEDM in the ROC analysis. CONCLUSION: Overall, we conclude that the addition of dynamic digital subtraction mammography to conventional mammography can significantly improve diagnostic quality. The increased sensitivity is particularly pronounced in the case of dense breast tissue.
PURPOSE: The goal of this prospective study was to evaluate the possible diagnostic benefits of contrast-enhanced digital mammography (CEDM) over conventional mammography. MATERIALS AND METHODS: Our analysis included data from 70 patients with a total of 80 lesions (30 malignant and 50 benign). A series of contrast-enhanced images was acquired from each patient using a modified imaging system (GE Senographe 2000D with copper filter) suitable for displaying iodine contrast medium. After the mask image had been taken, the contrast medium was administered using a dosage of 1ml/kg body weight at a rate of 4ml/s. Three contrast-enhanced images in the cranio-caudal projection plane were then captured at intervals of 60s. The mask image was logarithmically subtracted from the contrast-enhanced images. We performed a ROC analysis of diagnostic quality with three readers. RESULTS: On average, 5.66 more malignant lesions were detected with the addition of digital dynamic contrast mammography versus conventional mammography alone. The sensitivity was increased from an average of 0.43 in conventional mammography to an average of 0.62 with contrast mammography. Even in dense breast parenchyma, the sensitivity increased from an average of 0.35-0.59. In the multi-reader-ROC analyses of all readers, the differences in the AUC with p=0.02 (BI-RADS) proved statistically significant in all cases. The Wilcoxon test showed that Readers I and II primarily used the CEDM to upgrade enhancing lesions to a higher BI-RADS category or a higher probability of malignancy. These two readers benefited most from the CEDM in the ROC analysis. CONCLUSION: Overall, we conclude that the addition of dynamic digital subtraction mammography to conventional mammography can significantly improve diagnostic quality. The increased sensitivity is particularly pronounced in the case of dense breast tissue.
Authors: Thomas Knogler; Peter Homolka; Mathias Hörnig; Robert Leithner; Georg Langs; Martin Waitzbauer; Katja Pinker-Domenig; Sabine Leitner; Thomas H Helbich Journal: Eur Radiol Date: 2015-09-15 Impact factor: 5.315
Authors: Karen Drukker; Maryellen L Giger; Bonnie N Joe; Karla Kerlikowske; Heather Greenwood; Jennifer S Drukteinis; Bethany Niell; Bo Fan; Serghei Malkov; Jesus Avila; Leila Kazemi; John Shepherd Journal: Radiology Date: 2018-12-11 Impact factor: 11.105
Authors: Julie Sogani; Elizabeth A Morris; Jennifer B Kaplan; Donna D'Alessio; Debra Goldman; Chaya S Moskowitz; Maxine S Jochelson Journal: Radiology Date: 2016-07-04 Impact factor: 11.105
Authors: E M Fallenberg; C Dromain; F Diekmann; F Engelken; M Krohn; J M Singh; B Ingold-Heppner; K J Winzer; U Bick; D M Renz Journal: Eur Radiol Date: 2013-09-19 Impact factor: 5.315