Reconstruction algorithms and arm positioning effects on abdominal CT image quality and radiation dose: a phantom...

Area of Science:

• Medical Imaging
• Radiology
• Computed Tomography

Background:

• Patient positioning is crucial for optimizing radiation dose and image quality in abdominal CT scans.
• Standard protocols often require arms raised (AU), which may not always be feasible for patients.

Purpose of the Study:

• To investigate the influence of different arm positions and reconstruction algorithms on radiation dose and image quality in abdominal CT.
• To assess the effectiveness of deep learning-based reconstruction (DLIR) in mitigating image quality degradation caused by suboptimal arm positioning.

Main Methods:

• Abdominal CT scans were performed on a phantom using various arm positions (arms up, arms down, arms on belly, with/without air cushions) and noise index settings.
• Images were reconstructed using filtered back projection (FBP), iterative reconstruction, and DLIR.
• Radiation dose and quantitative/qualitative image quality metrics were evaluated.

Main Results:

• Non-arms-up positions significantly increased radiation dose (up to 83%) compared to the arms-up position.
• Deep learning-based reconstruction (DLIR) substantially improved image quality in non-arms-up positions, approaching diagnostic quality.
• Air cushions offered modest, configuration-dependent benefits, more apparent in arms-on-belly positions.

Conclusions:

• Arm positioning is the primary factor affecting radiation dose and image quality in abdominal CT.
• DLIR is effective in preserving diagnostic image quality when patients cannot raise their arms.
• Air cushions provide limited benefits, and arms-on-belly positioning should be avoided if possible.