OBJECTIVE: The purpose of this article is to assess the accuracy of contrast-enhanced digital mammography in the detection of breast carcinoma and to correlate the findings on the images with those of histologic analysis using microvessel quantification. SUBJECTS AND METHODS: Twenty patients with a suspicious breast abnormality underwent contrast-enhanced digital mammography using a full-field digital mammography unit that was modified to detect iodinated enhancement. For each patient, a total of six contrast-enhanced craniocaudal views were acquired from 30 seconds to 7 minutes after the injection of a bolus of 100 mL of an iodinated contrast agent. Image processing included a logarithmic subtraction and the analysis of enhancement kinetic curves. Contrast-enhanced digital mammography findings were compared with histologic analysis of surgical specimens, including intratumoral microvessel density quantification evaluated on CD34-immunostained histologic sections obtained from all patients. RESULTS: An area of enhancement was depicted on contrast-enhanced digital mammograms in 16 of the 20 histologically proven breast carcinomas. Excellent correlation was seen between the size of enhancement and the histologic size of tumors, which ranged from 9 to 22 mm. Early enhancement with washout was observed in four cases, early enhancement followed by a plateau in four cases, gradual enhancement in seven cases, and unexpected decrease of enhancement in one case. Intratumoral microvessel density ranged from 11.7 to 216.6 microvessels per square millimeter. A poor correlation was found between data measured on contrast-enhanced digital mammography and intratumoral microvessel density measured on CD34-immunostained histologic sections. CONCLUSION: Contrast-enhanced digital mammography is able to depict angiogenesis in breast carcinoma. Breast compression and projective images acquisition alter the quantitative assessment of enhancement parameters.
OBJECTIVE: The purpose of this article is to assess the accuracy of contrast-enhanced digital mammography in the detection of breast carcinoma and to correlate the findings on the images with those of histologic analysis using microvessel quantification. SUBJECTS AND METHODS: Twenty patients with a suspicious breast abnormality underwent contrast-enhanced digital mammography using a full-field digital mammography unit that was modified to detect iodinated enhancement. For each patient, a total of six contrast-enhanced craniocaudal views were acquired from 30 seconds to 7 minutes after the injection of a bolus of 100 mL of an iodinated contrast agent. Image processing included a logarithmic subtraction and the analysis of enhancement kinetic curves. Contrast-enhanced digital mammography findings were compared with histologic analysis of surgical specimens, including intratumoral microvessel density quantification evaluated on CD34-immunostained histologic sections obtained from all patients. RESULTS: An area of enhancement was depicted on contrast-enhanced digital mammograms in 16 of the 20 histologically proven breast carcinomas. Excellent correlation was seen between the size of enhancement and the histologic size of tumors, which ranged from 9 to 22 mm. Early enhancement with washout was observed in four cases, early enhancement followed by a plateau in four cases, gradual enhancement in seven cases, and unexpected decrease of enhancement in one case. Intratumoral microvessel density ranged from 11.7 to 216.6 microvessels per square millimeter. A poor correlation was found between data measured on contrast-enhanced digital mammography and intratumoral microvessel density measured on CD34-immunostained histologic sections. CONCLUSION: Contrast-enhanced digital mammography is able to depict angiogenesis in breast carcinoma. Breast compression and projective images acquisition alter the quantitative assessment of enhancement parameters.
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: Maha H Helal; Sahar M Mansour; Mai Zaglol; Lamia A Salaleldin; Omniya M Nada; Marwa A Haggag Journal: Br J Radiol Date: 2017-02-22 Impact factor: 3.039
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
Authors: Maxine S Jochelson; D David Dershaw; Janice S Sung; Alexandra S Heerdt; Cynthia Thornton; Chaya S Moskowitz; Jessica Ferrara; Elizabeth A Morris Journal: Radiology Date: 2012-12-06 Impact factor: 11.105