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Introducing advanced ClearIQ engine (AiCE) deep learning reconstruction algorithm into a clinical radiotherapy

Jonathan D Allred1, Jonathan C R Stoddart1, Gavin Alexander1

  • 1Radiotherapy Physics, Nottingham University Hospitals NHS Trust, Nottingham, Notts NG51PB, United Kingdom.

The British Journal of Radiology
|December 22, 2025
PubMed
Summary
This summary is machine-generated.

Advanced intelligence Clear-IQ Engine (AiCE) image reconstruction offers stable Hounsfield Unit values for radiotherapy planning. This novel technique optimizes breast CT protocols, reducing radiation dose by 12% without compromising image quality.

Keywords:
CTdeep learningdose optimizationreconstruction

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Area of Science:

  • Medical Imaging
  • Radiotherapy
  • Image Reconstruction Technologies

Background:

  • Current CT protocols in radiotherapy may involve higher radiation doses.
  • Optimizing image quality while reducing radiation exposure is crucial for patient safety and treatment efficacy.

Purpose of the Study:

  • To evaluate the clinical integration of Advanced intelligence Clear-IQ Engine (AiCE) for computed tomography (CT) image reconstruction.
  • To assess the impact of AiCE on image quality and radiotherapy treatment planning.
  • To explore the potential for dose optimization in CT scanning.

Main Methods:

  • Electron density phantom scans were performed using both AIDR3D and AiCE at varying mAs values.
  • Clinical CT scans were reconstructed with AiCE, and subsequent radiotherapy dose distributions were recalculated.
  • A breast radiotherapy patient protocol was optimized post-phantom testing.

Main Results:

  • AiCE demonstrated Hounsfield Number stability within acceptable tolerances (5-6 HU variation) compared to AIDR3D.
  • Radiotherapy dose calculations showed a maximum difference of 0.45 Gy, with a median difference of 0.02 Gy.
  • A 12% reduction in mean dose-length product (DLP) was achieved with clinically acceptable image quality.

Conclusions:

  • AiCE reconstruction provides stable Hounsfield Unit values, making it suitable for radiotherapy treatment planning.
  • The implementation of AiCE enabled optimization of breast CT protocols, leading to reduced radiation doses.
  • AiCE is a viable novel reconstruction technique for clinical treatment planning and CT dose optimization.