WE-G-103-01: Dual-Energy Temporal Study of Contrast-Enhanced Digital Mammography in 20 Patients: The Use of a Pixel-By-Pixel Weighting Formalism for the Subtraction

Abstract

Purpose: To study the possible correlation between iodine uptake in contrast-enhanced digital mammography images and microvessel density (MVD) in breast lesions. Methods: 20 BIRADS 4–5 patients were included. Mask images were acquired with low-and high-energy spectra from a SenographeDS. Iodine-based contrast medium (CM) was mechanically injected and high-energy CM images acquired between 1 and 5 minutes after injection. A biopsy was obtained after the images and specific biomarkers for newly-formed blood and lymphatic microvessels were applied; MVD was later evaluated in microscope fields. The subtraction combined dual-energy and temporal modalities. LE masks were subtracted from weighted CM images, and weight factor was a matrix obtained from the masks, containing pixel-by-pixel anatomical and radiological information. Iodine uptake in subtracted temporal series was quantified by contrast between lesion and normal glandular tissue. Alternative metrics for contrast quantification were evaluated. Contrast was transformed into iodine mass-thickness using calibrated samples. Results: 12 cases were malignant and 8, benign. The matrix-based subtraction formalism severely reduced anatomic noise in resulting images, compared with alternative techniques based on mean pixel values within regions-of-interest. Five types of time-intensity curves were identified, qualitatively similar to MRI. If iodine uptake in the lesion was evaluated, most frequent curve was plateau type, for cancer and malignant cases. The normalized Weber contrast indicated a frequency distribution with zero-contrast cases for benign lesions and most-frequent curve type washout for cancer. No correlation was found between contrast indicators and MVD. Blood and lymphatic MVD were correlated (r=0.94, p<0.05) and mean blood MVD values in cancer were about twice those in benign cases. Conclusion: This subtraction formalism, previously validated in non-homogeneous phantom images, adds quantitative features to the resulting clinical images. The statistical distribution of contrast curves for cancer and benign cases seems to be the most relevant parameter with a possible diagnostic value. Funding: DGAPA-UNAM Grants 102610 and 105813; Conacyt Grant Salud 2009-01-112374. No conflict of interest.