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In-vivo Diagnosis of Breast Cancer Using Gamma Stimulated Emission Computed Tomography

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Annual rept. 1 Apr 2010-31 Mar 2011

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This project focuses on the development of a novel method of breast cancer detection called Gamma Stimulated Spectroscopy GSS. This technique is highly sensitive to early stage metabolic changes in tumors and has the ability to quantify specific malignancy-related elements in a tumor through a quick and low dose scan. In this project, we aim to design, implement and optimize a prototype of the GSS imaging system and determine its accuracy and efficacy in breast cancer detection. In the first year of the project, we designed and assembled a preliminary prototype of the GSS system using the free-electron laser at Duke University and acquired experimental spectra from calibration phantoms of elements associated with breast cancer. In addition, we initiated the development of a Monte-Carlo simulation model of the GSS imaging system including the gamma source and detectors. In the second year of the project, we continued the development of the GEANT4 simulation to model and refine the physics interactions governing GSS and investigated advanced detector systems to improve system sensitivity. In addition, we investigated the GSS radiation dose using whole body and breast dosimetry models irradiated with gamma beams. Simulated populations of breast tumor patients were scanned virtually to generate images of six individual malignancyrelated trace elements per phantom. The images showed excellent correlation between the location of the tumor and the concentration of the cancer-marking element in the breast. This data will now be used to identify the best candidate elements for cancer detection. In addition, we also initiated the development of a classifier algorithm to identify an optimal signature of cancer based on a combination of elements. We will now begin to optimize the GSS acquisition system for cancer detection through a targeted element search using the computer classifier algorithm.

Subject Categories:

  • Medicine and Medical Research
  • Atomic and Molecular Physics and Spectroscopy

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