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SU‐E‐I‐45: Feasibility for Using Iodine Quantification to Assist Diagnosis in Dual Energy Contrast‐Enhanced Digital Mammography
Author(s) -
Hwang Y,
Lin Y,
Cheung Y,
Tsai C
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4924042
Subject(s) - mammography , digital mammography , medical imaging , medical physics , dual energy , contrast (vision) , digital radiography , nuclear medicine , medicine , radiology , computer science , artificial intelligence , breast cancer , radiography , pathology , cancer , bone mineral , osteoporosis
Purpose: The objective of this study is to develop quantitative calibration between image quality indexes and iodine concentration with dual‐energy (DE) contrast‐enhanced digital mammography (CEDM) techniques and further serve as the assistance for diagnosis. Methods: Custom‐made acrylic phantom with dimensions of 24×30 cm 2 simulated breast thickness from 2 to 6 cm was used in the calibration. The phantom contained matrix of four times four holes of 3 mm deep with a diameter of 15 mm for filling contrast agent with area density ranged from 0.1 to 10 mg/cm 2 . All the image acquisitions were performed on a full‐field digital mammography system (Senographe Essential, GE) with dual energy acquisitions. Mean pixel value (MPV), and contrast‐to‐noise ratio (CNR) were used for evaluating the relationship between image quality indexes and iodine concentration. Iodine map and CNR map could further be constructed with these calibration curves applied pixel by pixel utilized MATLAB software. Minimum iodine concentration could also be calculated with the visibility threshold of CNR=5 according the Rose model. Results: When evaluating the DE subtraction images, MPV increased linearly as the iodine concentration increased with all the phantom thickness surveyed (R 2 between 0.989 and 0.992). Lesions with increased iodine uptake could thus be enhanced in the color‐encoded iodine maps, and the mean iodine concentration could be obtained through the ROI measurements. As for investigating CNR performance, linear relationships were also shown between the iodine concentration and CNR (R 2 between 0.983 and 0.990). Minimum iodine area density of 1.45, 1.73, 1.80, 1.73 and 1.72 mg/cm 2 for phantom thickness of 2, 3, 4, 5, 6 cm were calculated based on Rose's visualization criteria. Conclusion: Quantitative calibration between image quality indexes and iodine concentrations may further serving as the assistance for analyzing contrast enhancement for patient participating the dual energy CEDM procedures.