Application of a Dynamic 4D Anthropomorphic Breast Phantom in Contrast-Based Imaging System Optimization: Dual-Energy or Temporal Subtraction?

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• 作者：Nooshin Kiarashi (123)
  Sujata V. Ghate (3)
  Joseph Y. Lo (12345)
  Loren W. Nolte (2)
  Ehsan Samei (123456)
• 关键词：Virtual Breast Model – ; Anthropomorphic Breast Model – ; Tomosynthesis – ; Mammography – ; Dual ; energy Subtraction – ; Temporal Subtraction
• 刊名：Lecture Notes in Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：7361
• 期：1
• 页码：658-665
• 全文大小：5.2 MB
• 参考文献：1. Kiarashi, N., Lin, Y., Segars, W.P., Ghate, S.V., Ikejimba, L., Chen, B., Lo, J.Y., Dobbins III, J.T., Nolte, L.W., Samei, E.: Development of a Dynamic 4D Anthropomorphic Breast Phantom for Contrast-based Breast Imaging. In: Proc. SPIE, vol. 8313, pp. 0C1–0C7 (2012)
  2. Chen, B., Shorey, J., Saunders, R.S., Richard, S., Thompson, J., Nolte, L.W., Samei, E.: An anthropomorphic breast model for breast imaging simulation and optimization. Acad. Radiol. 18(5), 536–546 (2011)
  3. Li, C.M., Segars, W.P., Lo, J.Y., Dobbins III, J.T., Veress, A.I., Boone, J.M.: Three-dimensional computer generated breast phantom based on empirical data. In: Proc. SPIE, vol. 6913, pp. 14.1–14.8 (2008)
  4. Li, C.M., Segars, W.P., Dobbins III, J.T., Tourassi, G.D., Boone, J.M.: Methodology for generating a 3D computerized breast phantom from empirical data. Med. Phys. 36(7), 3122–3131 (2009)
• 作者单位：1. Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, NC, USA2. Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA3. Department of Radiology, Duke University Medical Center, Durham, NC, USA4. Medical Physics Graduate Program, Duke University, Durham, NC, USA5. Department of Biomedical Engineering, Duke University, Durham, NC, USA6. Department of Physics, Duke University, Durham, NC, USA
• ISSN：1611-3349

文摘

We previously developed a dynamic 4D anthropomorphic breast phantom, which can be used to optimize contrast-based breast imaging systems, accounting for patient variability and contrast kinetics [1]. In this study we aim to compare the performance of contrast-enhanced mammographic and tomosynthesis imaging protocols followed by temporal subtraction and dual-energy subtraction, qualitatively and quantitatively across a couple of patient models. Signal-difference-to-noise ratio (SDNR) is measured for the six paradigms of contrast enhanced, temporally subtracted, and dual-energy subtracted mammography and tomosynthesis and compared. The results show how the performance is more dependent on the breast model in mammography than in tomosynthesis. Also, it is observed that dual-energy subtraction can be beneficial in mammography, whereas it is not advantageous in tomosynthesis. Lastly, the results suggest that temporal subtraction in general outperforms dual-energy subtraction.