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Updated: Mar 27, 2026

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Towards optimized CT lung cancer screening scan protocols.

Gareth R Iball1, Charlotte A Porter2

  • 1Faculty of Health and Social Care, University of Bradford, Bradford, West Yorkshire, BD7 1DP, United Kingdom.

The British Journal of Radiology
|March 26, 2026
PubMed
Summary
This summary is machine-generated.

CT lung cancer screening protocols show wide dose variations and inconsistent image quality. Soft tissue reconstruction kernels are essential for accurate nodule volumetry, meeting Quantitative Imaging Biomarkers Alliance (QIBA) criteria.

Keywords:
computed tomographyimage qualitylung cancerlung nodulesradiation dosescan protocolsscreening

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Area of Science:

  • Radiology
  • Medical Imaging
  • Oncology

Background:

  • Lung cancer screening using computed tomography (CT) is crucial for early detection.
  • Standardized protocols are needed to ensure consistent image quality and accurate measurements.

Purpose of the Study:

  • To evaluate radiation dose and image quality of CT lung cancer screening protocols.
  • To determine optimal reconstruction kernels for accurate nodule volumetry.

Main Methods:

  • Utilized anthropomorphic chest and lung screening image quality phantoms scanned on 17 different CT scanner models.
  • Assessed radiation dose metrics against international recommendations.
  • Evaluated nodule volumetry accuracy based on Quantitative Imaging Biomarkers Alliance (QIBA) criteria.

Main Results:

  • Radiation doses varied significantly across scanner models (up to sevenfold).
  • Many protocols failed QIBA criteria with standard lung kernels due to image artifacts.
  • Alternative soft tissue kernels enabled QIBA criteria compliance on most scanners.

Conclusions:

  • Contemporary CT lung cancer screening protocols exhibit considerable variability in radiation dose and image quality.
  • Scanner-specific selection of reconstruction kernels, particularly soft tissue kernels, is necessary for accurate nodule volumetry.
  • Findings support the development of optimized CT protocols for lung cancer screening programs.