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A thin target approach for portal imaging in medical accelerators
A Tsechanski1, A F Bielajew, S Faermann
1Ben-Gurion University of the Negev, Nuclear Engineering Department, Be'er Sheva, Israel. alex@prism.bgu.ac.il
Physics in Medicine and Biology
|September 2, 1998
Summary
A novel thin-target method enhances portal imaging by reducing photon absorption in medical linear accelerators. This technique improves image sharpness and contrast using low-energy photons.
Area of Science:
- Medical Physics
- Radiological Imaging
Background:
- Low-energy photons used in portal imaging are often absorbed by thick targets (e.g., Copper, Tungsten) in medical linear accelerators.
- Photoelectric absorption in high-Z materials significantly attenuates low-energy photons, limiting image quality.
Purpose of the Study:
- To develop and evaluate a new thin-target method for improved portal imaging using low-energy photons.
- To optimize target thickness and material to maximize low-energy photon fluence for enhanced image detail.
Main Methods:
- Utilized EGS4 Monte Carlo simulations to determine optimal target thickness for maximum photon fluence.
- Experimental validation using a 1.5 mm Copper target and a 5 mm Aluminum target (Copper mass equivalent).
- Acquired portal images using a Rando anthropomorphic phantom and a mammographic film sensitive to low-energy photons.
Main Results:
- A 1.5 mm Copper target yielded maximum photon fluence for a 4 MeV electron beam, significantly thinner than standard targets.
- The new thin-target method demonstrated a marked improvement in sharpness and contrast of anatomical details in portal images.
- Using a low-Z target (e.g., Aluminum) showed comparable results to Copper, while further reduction to Carbon or Beryllium offered no significant benefit.
Conclusions:
- A thin-target approach is effective for enhancing low-energy photon portal imaging in medical linear accelerators.
- Optimizing target thickness and material reduces self-absorption, leading to superior image quality.
- This method offers a practical improvement for diagnostic accuracy in radiotherapy imaging.