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Dual energy imaging using a clinical on-board imaging system.

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Dual energy (DE) imaging, a technique using two X-ray energies, shows promise for improving soft tissue visualization in lung cancer radiotherapy. This study confirms its feasibility with commercial systems, potentially enhancing tumor detection during image-guided treatment.

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Area of Science:

  • Medical Imaging
  • Radiotherapy Physics
  • Radiological Sciences

Background:

  • Dual energy (DE) imaging uses two X-ray energies to create enhanced soft tissue contrast images.
  • While established in diagnostic radiology for lung malignancy detection, DE imaging is not yet clinically used in radiotherapy.
  • Image-guided radiotherapy (IGRT) requires precise tumor localization, where improved soft tissue visualization is beneficial.

Purpose of the Study:

  • To evaluate the feasibility of implementing DE imaging on a commercial on-board imaging system for radiotherapy applications.
  • To determine optimal imaging parameters for DE subtraction to maximize tumor detectability.
  • To assess the potential of DE imaging to improve soft tissue contrast for lung cancer patients undergoing IGRT.

Main Methods:

  • Construction of simple and anthropomorphic phantoms for DE imaging analysis.
  • Acquisition of planar kilovoltage (kV) X-ray images at varying energies and milliampere-seconds (mAs).
  • Development of software for DE image subtraction and quantitative assessment of tumor detectability using signal-difference-to-noise ratio (SDNR).

Main Results:

  • DE subtraction effectively suppressed high-density objects in both phantoms.
  • The optimal imaging parameters identified were 140 kVp (1.0 mAs) and 60 kVp (3.2 mAs).
  • This technique achieved a higher SDNR than the reference technique at a comparable or lower radiation dose.

Conclusions:

  • DE imaging is feasible using a commercial on-board imaging system for radiotherapy.
  • The developed DE subtraction technique can enhance soft tissue visualization.
  • This approach holds potential for improving tumor detection and visualization in image-guided lung cancer radiotherapy.