ArticleThe British journal of radiology2025
Reproducibility of lung density quantification across photon-counting and conventional energy-integrating CT: a comparative study.
Article in The British journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesTo evaluate how photon-counting CT (PCCT) reproducibly quantifies lung density compared to conventional CT (energy-integrating CT or EICT) and assess the relevance of image quality.
methodsIn this retrospective analysis of a prospective study, subjects underwent acquisitions using EICT and PCCT systems (August-December 2021) on the same day. PCCT projections were reconstructed with 4 kernels and 2 voxel sizes using 2024 reconstruction software (ReconCT, Siemens). PCCT and EICT data were compared using lung density measurements: percentage of low-attenuation areas <-950 Hounsfield unit (HU) (LAA-950), 15th percentile of lung density histogram (Perc15), and mean lung density (MLD). Measurement reproducibility and its relation to image quality parameters (modulation transfer function and noise) were analyzed.
resultsFifty-four subjects (mean age, 67.4 years ± 9.6, 30 female) were studied. PCCT images had the closest agreement to EICT under identical voxel size and similar kernels, yielding lower LAA-950 (-0.9% ± 2.7, P < 0.05), higher Perc15 (1.4 HU ± 7.9, P > 0.05), and higher MLD (2.4 HU ± 10.8, P > 0.05). At higher PCCT resolution (1024 × 1024 matrix, 0.2 mm slice thickness), the smoother quantitative kernel (Qr36) improved agreement, with differences of -0.5% ± 3.0, -0.1 HU ± 9.8, and 2.8 HU ± 11.1, for LAA-950, Perc15, and MLD (P > 0.05). Image quality parameters strongly correlated with density measurements (RPerc152=85.3%).
conclusionsPCCT yields reproducible lung density measurements comparable to EICT, with optimal reproducibility dependent on optimized reconstruction parameters and explainable by image quality parameters. ADVANCES IN KNOWLEDGE: Lung density reproducibility is critical for integrating PCCT into EICT-based workflows. In our study, PCCT aligned more closely with EICT using similar kernels at identical voxel sizes, or smoother kernels at smaller voxel sizes.
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