ArticleJournal of applied clinical medical physics2025
Quantitative CT reconstruction kernel harmonization for multi-site lung cancer screening.
Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Quantitative CT reconstruction kernel harmonization for multi-site lung cancer screening.Journal of applied clinical medical physics · 2025Article
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2 authors.
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Abstract
backgroundPublished reference CT protocols for lung cancer screening are not optimized to produce uniform image appearance across different scanner manufacturers and models or to conform to quantitative imaging profiles for robust small lung nodule size and volume measurements, which are important in clinical management of screen-detected nodules. PURPOSE: This study used widely available phantoms and software to identify lung cancer screening CT reconstructions that enable accurate and reproducible nodule size measurements and to match reconstructions across scanner manufacturers and models to provide a consistent image appearance to interpreting physicians.
methodsACR CT accreditation phantom scans were used to measure the modulation transfer function (MTF) and noise power spectrum (NPS) for various reconstruction kernels for six CT scanner models from three manufacturers. A reference kernel was chosen, and other kernels were matched based on agreement between MTF and NPS for each candidate kernel. Kernels were validated for conformance to the Quantitative Imaging Biomarkers Alliance (QIBA) Small Lung Nodule profile using a commercial phantom and conformance testing software.
resultsMedium sharp kernels with similar MTF and NPS curves and QIBA-compliant imaging performance were identified for the six scanner models. One medium smooth kernel with iterative reconstruction and one common lung kernel did not conform to the QIBA profile.
conclusionsMTF and NPS comparisons to a validated reference CT protocol can be used to identify candidate scanner-specific reconstructions appropriate for lung cancer screening that conform to the QIBA protocol, thus producing accurate and reproducible nodule size measurements, and that should provide uniform image appearance to the interpreting radiologist.
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